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Energies, Volume 9, Issue 12 (December 2016)

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Cover Story We show a criterion for rating both the usability and accuracy of simplified one-diode models. The [...] Read more.
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Open AccessArticle Comparison of Optimized Control Strategies of a High-Speed Traction Machine with Five Phases and Bi-Harmonic Electromotive Force
Energies 2016, 9(12), 952; doi:10.3390/en9120952
Received: 27 May 2016 / Revised: 25 October 2016 / Accepted: 1 November 2016 / Published: 25 November 2016
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Abstract
The purpose of the paper is to present the potentialities in terms of the control of a new kind of PM synchronous machine. With five phases and electromotive forces whose first (E1) and third (E3) harmonics are
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The purpose of the paper is to present the potentialities in terms of the control of a new kind of PM synchronous machine. With five phases and electromotive forces whose first ( E 1 ) and third ( E 3 ) harmonics are of similar amplitude, the studied machine, so-called bi-harmonic, has properties that are interesting for traction machine payload. With three-phase machines, supplied by a mono-harmonic sinusoidal current, the weak number of freedom degrees limits the strategy of control for traction machines especially when voltage saturation occurs at high speeds. As the torque is managed for three-phase machines by a current with only one harmonic, flux weakening is necessary to increase speed when the voltage limitation is reached. The studied five-phase machine, thanks to the increase in the number of freedom degrees for control, aims to alleviate this fact. In this paper, three optimized control strategies are compared in terms of efficiency and associated torque/speed characteristics. These strategies take into account numerous constraints either from the supply (with limited voltage) or from the machine (with limited current densities and maximum acceptable copper, iron and permanent magnet losses). The obtained results prove the wide potentialities of such a kind of five-phase bi-harmonic machine in terms of control under constraints. It is thus shown that the classical Maximum Torque Per Ampere (MTPA) strategy developed for the three-phase machine is clearly not satisfying on the whole range of speed because of the presence of iron losses whose values can no more be neglected at high speeds. Two other strategies have been then proposed to be able to manage the compromises, at high speeds, between the high values of torque and efficiency under the constraints of admissible total losses either in the rotor or in the stator. Full article
(This article belongs to the collection Electric and Hybrid Vehicles Collection)
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Open AccessArticle Sustainable Energy Transitions in China: Renewable Options and Impacts on the Electricity System
Energies 2016, 9(12), 980; doi:10.3390/en9120980
Received: 8 October 2016 / Revised: 1 November 2016 / Accepted: 16 November 2016 / Published: 25 November 2016
Cited by 5 | PDF Full-text (2543 KB) | HTML Full-text | XML Full-text
Abstract
Chinese energy consumption has been dominated by coal for decades, but this needs to change to protect the environment and mitigate anthropogenic climate change. Renewable energy development is needed to fulfil the Intended Nationally Determined Contribution (INDC) for the post-2020 period, as stated
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Chinese energy consumption has been dominated by coal for decades, but this needs to change to protect the environment and mitigate anthropogenic climate change. Renewable energy development is needed to fulfil the Intended Nationally Determined Contribution (INDC) for the post-2020 period, as stated on the 2015 United Nations Climate Change Conference in Paris. This paper reviews the potential of renewable energy in China and how it could be utilised to meet the INDC goals. A business-as-usual case and eight alternative scenarios with 40% renewable electricity are explored using the EnergyPLAN model to visualise out to the year 2030. Five criteria (total cost, total capacity, excess electricity, CO2 emissions, and direct job creation) are used to assess the sustainability of the scenarios. The results indicate that renewables can meet the goal of a 20% share of non-fossil energy in primary energy and 40%–50% share of non-fossil energy in electricity power. The low nuclear-hydro power scenario is the most optimal scenario based on the used evaluation criteria. The Chinese government should implement new policies aimed at promoting integrated development of wind power and solar PV. Full article
(This article belongs to the Special Issue Sustainable Energy Technologies)
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Open AccessArticle Local Alternative for Energy Supply: Performance Assessment of Integrated Community Energy Systems
Energies 2016, 9(12), 981; doi:10.3390/en9120981
Received: 17 August 2016 / Revised: 31 October 2016 / Accepted: 14 November 2016 / Published: 25 November 2016
Cited by 4 | PDF Full-text (5036 KB) | HTML Full-text | XML Full-text
Abstract
Integrated community energy systems (ICESs) are emerging as a modern development to re-organize local energy systems allowing simultaneous integration of distributed energy resources (DERs) and engagement of local communities. Although local energy initiatives, such as ICESs are rapidly emerging due to community objectives,
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Integrated community energy systems (ICESs) are emerging as a modern development to re-organize local energy systems allowing simultaneous integration of distributed energy resources (DERs) and engagement of local communities. Although local energy initiatives, such as ICESs are rapidly emerging due to community objectives, such as cost and emission reductions as well as resiliency, assessment and evaluation are still lacking on the value that these systems can provide both to the local communities as well as to the whole energy system. In this paper, we present a model-based framework to assess the value of ICESs for the local communities. The distributed energy resources-consumer adoption model (DER-CAM) based ICES model is used to assess the value of an ICES in the Netherlands. For the considered community size and local conditions, grid-connected ICESs are already beneficial to the alternative of solely being supplied from the grid both in terms of total energy costs and CO2 emissions, whereas grid-defected systems, although performing very well in terms of CO2 emission reduction, are still rather expensive. Full article
(This article belongs to the Special Issue Smart Microgrids: Developing the Intelligent Power Grid of Tomorrow)
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Open AccessArticle Advanced Pareto Front Non-Dominated Sorting Multi-Objective Particle Swarm Optimization for Optimal Placement and Sizing of Distributed Generation
Energies 2016, 9(12), 982; doi:10.3390/en9120982
Received: 29 June 2016 / Revised: 19 October 2016 / Accepted: 15 November 2016 / Published: 25 November 2016
Cited by 8 | PDF Full-text (9115 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes an advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization (Advanced-PFNDMOPSO) method for optimal configuration (placement and sizing) of distributed generation (DG) in the radial distribution system. The distributed generation consists of single and multiple numbers of active power DG, reactive
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This paper proposes an advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization (Advanced-PFNDMOPSO) method for optimal configuration (placement and sizing) of distributed generation (DG) in the radial distribution system. The distributed generation consists of single and multiple numbers of active power DG, reactive power DG and simultaneous placement of active-reactive power DG. The optimization problem considers two multi-objective functions, i.e., power loss reduction and voltage stability improvements with voltage profile and power balance as constraints. First, the numerical output results of objective functions are obtained in the Pareto-optimal set. Later, fuzzy decision model is engendered for final selection of the compromised solution. The proposed method is employed and tested on standard IEEE 33 bus systems. Moreover, the results of proposed method are validated with other optimization algorithms as reported by others in the literature. The overall outcome shows that the proposed method for optimal placement and sizing gives higher capability and effectiveness to the final solution. The study also reveals that simultaneous placement of active-reactive power DG reduces more power losses, increases voltage stability and voltage profile of the system. Full article
(This article belongs to the Special Issue Distributed Renewable Generation)
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Open AccessArticle Increasing the Benefit from Cost-Minimizing Loads via Centralized Adjustments
Energies 2016, 9(12), 983; doi:10.3390/en9120983
Received: 9 September 2016 / Revised: 1 November 2016 / Accepted: 17 November 2016 / Published: 25 November 2016
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Abstract
Several demand response (DR) strategies rely on real-time pricing and selfish local optimization, which may not result in optimal electricity consumption patterns from the viewpoint of an energy supplier or a power system. Thus, this paper proposes a strategy enabling centralized adjustments to
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Several demand response (DR) strategies rely on real-time pricing and selfish local optimization, which may not result in optimal electricity consumption patterns from the viewpoint of an energy supplier or a power system. Thus, this paper proposes a strategy enabling centralized adjustments to cost-minimize consumers’ load. By employing the strategy, an aggregator is able to alter electricity consumption in order to remove power imbalances and to participate in the balancing power market (BPM). In this paper, we focus on direct electric space heating (DESH) loads that aim to minimize their heating cost locally. The consumers and an aggregator agree about an indoor temperature band, within which the aggregator is allowed to alter the temperature, and thus the electricity consumption. Centrally, the aggregator procures its electricity demand from a day-ahead (DA) market by utilizing the allowed temperature band and employs the band later in real-time (RT) operation for the balancing of its own imbalances or regulating power in the BPM. Full article
(This article belongs to the Special Issue Decentralized Management of Energy Streams in Smart Grids)
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Open AccessArticle Smart Charging of EVs in Residential Distribution Systems Using the Extended Iterative Method
Energies 2016, 9(12), 985; doi:10.3390/en9120985
Received: 1 August 2016 / Revised: 11 November 2016 / Accepted: 14 November 2016 / Published: 25 November 2016
Cited by 1 | PDF Full-text (4661 KB) | HTML Full-text | XML Full-text
Abstract
Smart charging of electrical vehicles (EVs) is critical to provide the secure and cost-effective operation for distribution systems. Three model objective functions which are minimization of total supplied power, energy costs and maximization of profits are formulated. The conventional household load is modeled
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Smart charging of electrical vehicles (EVs) is critical to provide the secure and cost-effective operation for distribution systems. Three model objective functions which are minimization of total supplied power, energy costs and maximization of profits are formulated. The conventional household load is modeled as a ZIP load that consists of constant power, constant current and constant impedance components. The imbalance of distribution system, constraints on nodal voltages and thermal loadings of lines and transformers are all taken into account. Utilizing the radial operation structure of distribution system, an extended iterative method is proposed to greatly reduce the dimensions of optimization variables and thus improve calculation speed. Impacts of the conventional household load model on the simulation results are also investigated. Case studies on three distribution systems with 2, 14, and 141 buses are performed and analyzed. It is found that the linear constrained convex quadratic programming model is applicable at each iteration, when the conventional household load is composed of constant power and constant impedance load. However, it is not applicable when the conventional household load consists of constant current load. The accuracy and computational efficiency of the proposed method are also validated. Full article
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Open AccessArticle Global Maximum Power Point Tracking (MPPT) of a Photovoltaic Module Array Constructed through Improved Teaching-Learning-Based Optimization
Energies 2016, 9(12), 986; doi:10.3390/en9120986
Received: 10 September 2016 / Revised: 10 November 2016 / Accepted: 15 November 2016 / Published: 25 November 2016
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Abstract
The present study proposes a maximum power point tracking (MPPT) method in which improved teaching-learning-based optimization (I-TLBO) is applied to perform global MPPT of photovoltaic (PV) module arrays under dissimilar shading situations to ensure the maximum power output of the module arrays. The
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The present study proposes a maximum power point tracking (MPPT) method in which improved teaching-learning-based optimization (I-TLBO) is applied to perform global MPPT of photovoltaic (PV) module arrays under dissimilar shading situations to ensure the maximum power output of the module arrays. The proposed I-TLBO enables the automatic adjustment of teaching factors according to the self-learning ability of students. Incorporating smart-tracking and self-study strategies can effectively improve the tracking response speed and steady-state tracking performance. To evaluate the feasibility of the proposed I-TLBO, a HIP-2717 PV module array from Sanyo Electric was employed to compose various arrays with different serial and parallel configurations. The arrays were operated under different shading conditions to test the MPPT with double, triple, or quadruple peaks of power-voltage characteristic curves. Boost converters were employed with TMS320F2808 digital signal processors to test the proposed MPPT method. Empirical results confirm that the proposed method exhibits more favorable dynamic and static-state response tracking performance compared with that of conventional TLBO. Full article
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Open AccessArticle Short-Term Load Forecasting Using Adaptive Annealing Learning Algorithm Based Reinforcement Neural Network
Energies 2016, 9(12), 987; doi:10.3390/en9120987
Received: 28 September 2016 / Revised: 11 November 2016 / Accepted: 18 November 2016 / Published: 25 November 2016
Cited by 2 | PDF Full-text (1777 KB) | HTML Full-text | XML Full-text
Abstract
A reinforcement learning algorithm is proposed to improve the accuracy of short-term load forecasting (STLF) in this article. The proposed model integrates radial basis function neural network (RBFNN), support vector regression (SVR), and adaptive annealing learning algorithm (AALA). In the proposed methodology, firstly,
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A reinforcement learning algorithm is proposed to improve the accuracy of short-term load forecasting (STLF) in this article. The proposed model integrates radial basis function neural network (RBFNN), support vector regression (SVR), and adaptive annealing learning algorithm (AALA). In the proposed methodology, firstly, the initial structure of RBFNN is determined by using an SVR. Then, an AALA with time-varying learning rates is used to optimize the initial parameters of SVR-RBFNN (AALA-SVR-RBFNN). In order to overcome the stagnation for searching optimal RBFNN, a particle swarm optimization (PSO) is applied to simultaneously find promising learning rates in AALA. Finally, the short-term load demands are predicted by using the optimal RBFNN. The performance of the proposed methodology is verified on the actual load dataset from the Taiwan Power Company (TPC). Simulation results reveal that the proposed AALA-SVR-RBFNN can achieve a better load forecasting precision compared to various RBFNNs. Full article
(This article belongs to the Special Issue Forecasting Models of Electricity Prices) Printed Edition available
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Open AccessArticle Scenario Analysis of Carbon Emissions of China’s Electric Power Industry Up to 2030
Energies 2016, 9(12), 988; doi:10.3390/en9120988
Received: 28 October 2016 / Revised: 20 November 2016 / Accepted: 22 November 2016 / Published: 25 November 2016
Cited by 1 | PDF Full-text (1166 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, the Long-range Energy Alternatives Planning (LEAP) model is constructed to simulate six scenarios for forecasting national electricity demand in China. The results show that in 2020 the total electricity demand will reach 6407.9~7491.0 billion KWh, and will be 6779.9~10,313.5 billion
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In this paper, the Long-range Energy Alternatives Planning (LEAP) model is constructed to simulate six scenarios for forecasting national electricity demand in China. The results show that in 2020 the total electricity demand will reach 6407.9~7491.0 billion KWh, and will be 6779.9~10,313.5 billion KWh in 2030. Moreover, under the assumption of power production just meeting the social demand and considering the changes in the scale and technical structure of power industry, this paper simulates two scenarios to estimate carbon emissions and carbon intensity till 2030, with 2012 as the baseline year. The results indicate that the emissions intervals are 4074.16~4692.52 million tCO2 in 2020 and 3948.43~5812.28 million tCO2 in 2030, respectively. Carbon intensity is 0.63~0.64 kg CO2/KWh in 2020 and 0.56~0.58 kg CO2/KWh in 2030. In order to accelerate carbon reduction, the future work should focus on making a more stringent criterion on the intensity of industrial power consumption and expanding the proportion of power generation using clean energy, large capacity, and high efficiency units. Full article
(This article belongs to the Special Issue Electric Power Systems Research 2017)
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Open AccessArticle Hybrid Short Term Wind Speed Forecasting Using Variational Mode Decomposition and a Weighted Regularized Extreme Learning Machine
Energies 2016, 9(12), 989; doi:10.3390/en9120989
Received: 3 August 2016 / Revised: 20 November 2016 / Accepted: 22 November 2016 / Published: 25 November 2016
Cited by 2 | PDF Full-text (6347 KB) | HTML Full-text | XML Full-text
Abstract
Accurate wind speed forecasting is a fundamental element of wind power prediction. Thus, a new hybrid wind speed forecasting model, using variational mode decomposition (VMD), the partial autocorrelation function (PACF), and weighted regularized extreme learning machine (WRELM), is proposed to improve the accuracy
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Accurate wind speed forecasting is a fundamental element of wind power prediction. Thus, a new hybrid wind speed forecasting model, using variational mode decomposition (VMD), the partial autocorrelation function (PACF), and weighted regularized extreme learning machine (WRELM), is proposed to improve the accuracy of wind speed forecasting. First, the historic wind speed time series is decomposed into several intrinsic mode functions (IMFs). Second, the partial correlation of each IMF sequence is analyzed using PACF to select the optimal subfeature set for particular predictors of each IMF. Then, the predictors of each IMF are constructed in order to enhance its strength using WRELM. Finally, wind speed is obtained by adding up all the predictors. The experiment, using real wind speed data, verified the effectiveness and advancement of the new approach. Full article
(This article belongs to the Special Issue Electric Power Systems Research 2017)
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Open AccessArticle Financing Innovations for the Renewable Energy Transition in Europe
Energies 2016, 9(12), 990; doi:10.3390/en9120990
Received: 21 September 2016 / Revised: 8 November 2016 / Accepted: 16 November 2016 / Published: 25 November 2016
Cited by 1 | PDF Full-text (5982 KB) | HTML Full-text | XML Full-text
Abstract
Renewable energy sources are vital to achieving Europe’s 2030 energy transition goals. Technological innovation, driven by public expenditures on research and development, is a major driver for this change. Thus, an extensive dataset on these expenditures of the European Member States and the
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Renewable energy sources are vital to achieving Europe’s 2030 energy transition goals. Technological innovation, driven by public expenditures on research and development, is a major driver for this change. Thus, an extensive dataset on these expenditures of the European Member States and the European Commission, dating back to the early 1970s, was created. This paper creates predictive scenarios of public investment in renewable energy research and development in Europe based on this historical dataset and current trends. Funding from both, European Member States and the European Commission, between today and 2030 are used in the analysis. The impact on the cumulative knowledge stock is also estimated. Two projection scenarios are presented: (1) business as usual; and (2) an advanced scenario, based on the assumption that the Mission Innovation initiative causes public expenditures to increase in the coming years. Both scenarios are compared to the European 2030 climate and energy framework target sets. Results indicate that Member States in Europe currently tend to fund renewables more than the European Commission, but funding from both sources is expected to increase in the future. Furthermore, the European Commission distributes its funding more equally across the various renewable energy sources than Member States. Full article
(This article belongs to the Special Issue Energy Time Series Forecasting)
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Open AccessArticle Strategy Design of Hybrid Energy Storage System for Smoothing Wind Power Fluctuations
Energies 2016, 9(12), 991; doi:10.3390/en9120991
Received: 10 October 2016 / Revised: 16 November 2016 / Accepted: 21 November 2016 / Published: 25 November 2016
Cited by 8 | PDF Full-text (15412 KB) | HTML Full-text | XML Full-text
Abstract
With the increasing contribution of wind power plants, the reliability and security of modern power systems have become a huge challenge due to the uncertainty and intermittency of wind energy sources. In this paper, a hybrid energy storage system (HESS) consisting of battery
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With the increasing contribution of wind power plants, the reliability and security of modern power systems have become a huge challenge due to the uncertainty and intermittency of wind energy sources. In this paper, a hybrid energy storage system (HESS) consisting of battery and supercapacitor is built to smooth the power fluctuations of wind power. A power allocation strategy is proposed to give full play to the respective advantages of the two energy storage components. In the proposed strategy, the low-frequency and high-frequency components of wind power fluctuations are absorbed by battery groups and supercapacitor groups, respectively. By inhibiting the low-frequency components of supercapacitor current, the times of charging-discharging of battery groups can be significantly reduced. A DC/AC converter is applied to achieve the power exchange between the HESS and the grid. Adjustment rules for regulating state-of-charge (SOC) of energy storage elements are designed to avoid overcharge and deep discharge considering the safety and the high efficiency of the energy storage elements. Experimental results on the test platform verify the effectiveness of the proposed power allocation strategy in DC/AC converter and battery SOC adjustment rules for regulating SOC levels. Full article
(This article belongs to the Special Issue Wind Turbine 2017)
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Open AccessArticle A New Design Optimization Method for Permanent Magnet Synchronous Linear Motors
Energies 2016, 9(12), 992; doi:10.3390/en9120992
Received: 28 July 2016 / Revised: 23 October 2016 / Accepted: 18 November 2016 / Published: 25 November 2016
Cited by 1 | PDF Full-text (4686 KB) | HTML Full-text | XML Full-text
Abstract
This study focused on the design optimization of permanent magnet synchronous linear motors (PMSLM) that are applied in microsecond laser cutting machines. A new design optimization method was introduced to enhance PMSLM performances in terms of motor thrust, thrust ripple, and inductive electromotive
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This study focused on the design optimization of permanent magnet synchronous linear motors (PMSLM) that are applied in microsecond laser cutting machines. A new design optimization method was introduced to enhance PMSLM performances in terms of motor thrust, thrust ripple, and inductive electromotive force (EMF). Based on accurate 3D finite element analysis (3D-FEA), a multiple support vector machine (multi-SVM) was proposed to build a non-parametric quick calculation model by mapping the relation between multivariate structure parameters and multivariate operation performances. The gravity center neighborhood algorithm (GCNA) was also applied to search the global optimal combination of the structure parameters by locating the gravity center of the multi-SVM model. The superiority and validity of this method are verified by experiments. Full article
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Open AccessArticle Modeling and Controller Design of PV Micro Inverter without Using Electrolytic Capacitors and Input Current Sensors
Energies 2016, 9(12), 993; doi:10.3390/en9120993
Received: 11 August 2016 / Revised: 14 November 2016 / Accepted: 21 November 2016 / Published: 25 November 2016
Cited by 3 | PDF Full-text (6541 KB) | HTML Full-text | XML Full-text
Abstract
This paper outlines the modeling and controller design of a novel two-stage photovoltaic (PV) micro inverter (MI) that eliminates the need for an electrolytic capacitor (E-cap) and input current sensor. The proposed MI uses an active-clamped current-fed push-pull DC-DC converter, cascaded with a
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This paper outlines the modeling and controller design of a novel two-stage photovoltaic (PV) micro inverter (MI) that eliminates the need for an electrolytic capacitor (E-cap) and input current sensor. The proposed MI uses an active-clamped current-fed push-pull DC-DC converter, cascaded with a full-bridge inverter. Three strategies are proposed to cope with the inherent limitations of a two-stage PV MI: (i) high-speed DC bus voltage regulation using an integrator to deal with the 2nd harmonic voltage ripples found in single-phase systems; (ii) inclusion of a small film capacitor in the DC bus to achieve ripple-free PV voltage; (iii) improved incremental conductance (INC) maximum power point tracking (MPPT) without the need for current sensing by the PV module. Simulation and experimental results demonstrate the efficacy of the proposed system. Full article
(This article belongs to the Special Issue Power Electronics Optimal Design and Control)
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Open AccessArticle A Novel Hybrid Short Term Load Forecasting Model Considering the Error of Numerical Weather Prediction
Energies 2016, 9(12), 994; doi:10.3390/en9120994
Received: 10 August 2016 / Revised: 15 October 2016 / Accepted: 18 November 2016 / Published: 25 November 2016
Cited by 1 | PDF Full-text (1699 KB) | HTML Full-text | XML Full-text
Abstract
In order to reduce the effect of numerical weather prediction (NWP) error on short term load forecasting (STLF) and improve the forecasting accuracy, a new hybrid model based on support vector regression (SVR) optimized by an artificial bee colony (ABC) algorithm (ABC-SVR) and
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In order to reduce the effect of numerical weather prediction (NWP) error on short term load forecasting (STLF) and improve the forecasting accuracy, a new hybrid model based on support vector regression (SVR) optimized by an artificial bee colony (ABC) algorithm (ABC-SVR) and seasonal autoregressive integrated moving average (SARIMA) model is proposed. According to the different day types and effect of the NWP error on forecasting prediction, working days and weekends load forecasting models are selected and constructed, respectively. The ABC-SVR method is used to forecast weekends load with large fluctuation, in which the best parameters of SVR are determined by the ABC algorithm. The working days load forecasting model is constructed based on SARIMA modified by ABC-SVR (AS-SARIMA). In the AS-SARIMA model, the ability of SARIMA to respond to exogenous variables is improved and the effect of NWP error on prediction accuracy is reduced more than with ABC-SVR. Contrast experiments are constructed based on International Organization for Standardization (ISO) New England load data. The experimental results show that prediction accuracy of the proposed method is less affected by NWP error and has higher forecasting accuracy than contrasting approaches. Full article
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Open AccessArticle Two Dimensional Thermal-Hydraulic Analysis for a Packed Bed Regenerator Used in a Reheating Furnace
Energies 2016, 9(12), 995; doi:10.3390/en9120995
Received: 22 August 2016 / Revised: 31 October 2016 / Accepted: 23 November 2016 / Published: 25 November 2016
Cited by 1 | PDF Full-text (5357 KB) | HTML Full-text | XML Full-text
Abstract
Packed bed is widely used for different industries and technologies, such as heat exchangers, heat recovery, thermal energy storage and chemical reactors. In modern steel industry, packed bed regenerator is widely utilized in the reheating furnace to increase the furnace efficiency. This study
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Packed bed is widely used for different industries and technologies, such as heat exchangers, heat recovery, thermal energy storage and chemical reactors. In modern steel industry, packed bed regenerator is widely utilized in the reheating furnace to increase the furnace efficiency. This study established a two dimensional numerical model to simulate a packed bed used in regenerative furnaces. The physical properties of fluids and packed stuffing (such as density, thermal conductivity, and specific heat) are considered as functions of temperature to adapt the large temperature variation in operation. The transient temperature profiles of the flue gas, packed bed, and air during the heating and regeneration period are examined for various switching time (30, 60, 120, and 240 s). The results reveal that, during the heating period, the spanwise averaged heat transfer coefficient is decreased along the longitudinal downstream direction, while during the regeneration period, the opposite trend is true. Moreover, the regenerator thermal effectiveness is decreased by increasing the switching time. Full article
(This article belongs to the Special Issue Thermally Driven Systems)
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Open AccessArticle Leaching of Metal Ions from Blast Furnace Slag by Using Aqua Regia for CO2 Mineralization
Energies 2016, 9(12), 996; doi:10.3390/en9120996
Received: 5 September 2016 / Revised: 19 November 2016 / Accepted: 23 November 2016 / Published: 25 November 2016
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Abstract
Blast furnace slag (BFS) was selected as the source of Ca for CO2 mineralization purposes to store CO2 as CaCO3. BFS was dissolved using aqua regia (AR) for leaching metal ions for CO2 mineralization and rejecting metal ions
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Blast furnace slag (BFS) was selected as the source of Ca for CO2 mineralization purposes to store CO2 as CaCO3. BFS was dissolved using aqua regia (AR) for leaching metal ions for CO2 mineralization and rejecting metal ions that were not useful to obtain pure CaCO3 (as confirmed by XRD analysis). The AR concentration, as well as the weight of BFS in an AR solution, was varied. Increasing the AR concentration resulted in increased metal ion leaching efficiencies. An optimum concentration of 20% AR was required for completely leaching Ca and Mg for a chemical reaction with CO2 and for suppressing the leaching of impurities for the production of high-purity carbonate minerals. Increasing the liquid-to-solid ratio (L/S) resulted in the increased leaching of all metal ions. An optimum L/S of 0.3/0.03 (=10) was required for completely leaching alkaline-earth metal ions for CO2 mineralization and for retaining other metal ions in the filtered residue. Moreover, the filtrate obtained using 20% AR and an L/S of 0.3/0.03 was utilized as Ca sources for forming carbonate minerals by CO2 mineralization, affording CaCO3. The results obtained herein demonstrated the feasibility of the use of AR, as well as increasing pH, for the storage of CO2 as high-purity CaCO3. Full article
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Open AccessArticle Optimization of Key Parameters of Energy Management Strategy for Hybrid Electric Vehicle Using DIRECT Algorithm
Energies 2016, 9(12), 997; doi:10.3390/en9120997
Received: 22 August 2016 / Revised: 16 November 2016 / Accepted: 22 November 2016 / Published: 26 November 2016
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Abstract
The rule-based logic threshold control strategy has been frequently used in energy management strategies for hybrid electric vehicles (HEVs) owing to its convenience in adjusting parameters, real-time performance, stability, and robustness. However, the logic threshold control parameters cannot usually ensure the best vehicle
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The rule-based logic threshold control strategy has been frequently used in energy management strategies for hybrid electric vehicles (HEVs) owing to its convenience in adjusting parameters, real-time performance, stability, and robustness. However, the logic threshold control parameters cannot usually ensure the best vehicle performance at different driving cycles and conditions. For this reason, the optimization of key parameters is important to improve the fuel economy, dynamic performance, and drivability. In principle, this is a multiparameter nonlinear optimization problem. The logic threshold energy management strategy for an all-wheel-drive HEV is comprehensively analyzed and developed in this study. Seven key parameters to be optimized are extracted. The optimization model of key parameters is proposed from the perspective of fuel economy. The global optimization method, DIRECT algorithm, which has good real-time performance, low computational burden, rapid convergence, is selected to optimize the extracted key parameters globally. The results show that with the optimized parameters, the engine operates more at the high efficiency range resulting into a fuel savings of 7% compared with non-optimized parameters. The proposed method can provide guidance for calibrating the parameters of the vehicle energy management strategy from the perspective of fuel economy. Full article
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Open AccessArticle The Energy Audit Activity Focused on the Lighting Systems in Historical Buildings
Energies 2016, 9(12), 998; doi:10.3390/en9120998
Received: 28 September 2016 / Revised: 5 November 2016 / Accepted: 21 November 2016 / Published: 27 November 2016
Cited by 3 | PDF Full-text (2832 KB) | HTML Full-text | XML Full-text
Abstract
The energy audit for a building is a procedure designed mainly to obtain adequate knowledge of the energy consumption profile, identify, and quantify opportunities for energy savings by a cost-benefit analysis and report, clearly and comprehensively, about the obtained results. If the audit
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The energy audit for a building is a procedure designed mainly to obtain adequate knowledge of the energy consumption profile, identify, and quantify opportunities for energy savings by a cost-benefit analysis and report, clearly and comprehensively, about the obtained results. If the audit is referred to a building with a significant historical and artistic value, a compatibility evaluation of the energy saving interventions with the architectural features should also be developed. In this paper, analysing the case study of a historical building used as public offices in Pisa (Italy), the authors describe how it is possible to conduct an energy audit activity (especially dedicated to the lighting system) and they show how, for this type of buildings, it is possible to obtain significant energy savings with a refurbishment of the lighting system. A total number of seven interventions on indoor and outdoor lighting sub-systems were analysed in the paper. They are characterised by absolute compatibility with the historical and artistic value of the building and they show short payback times, variable between 4 and 34 months, allowing a reduction of the electrical energy consumption for the artificial indoor and outdoor lighting variable from 1.1 MWh/year to 39.0 MWh/year. The followed methodology and the evaluation results described in the paper, although based on a case study, can be extended to numerous historical buildings used as public offices, a recurring situation in the centres of Italian historical cities. Full article
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Open AccessArticle Wind Turbines’ End-of-Life: Quantification and Characterisation of Future Waste Materials on a National Level
Energies 2016, 9(12), 999; doi:10.3390/en9120999
Received: 29 September 2016 / Revised: 14 November 2016 / Accepted: 15 November 2016 / Published: 26 November 2016
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Abstract
Globally, wind power is growing fast and in Sweden alone more than 3000 turbines have been installed since the mid-1990s. Although the number of decommissioned turbines so far is few, the high installation rate suggests that a similarly high decommissioning rate can be
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Globally, wind power is growing fast and in Sweden alone more than 3000 turbines have been installed since the mid-1990s. Although the number of decommissioned turbines so far is few, the high installation rate suggests that a similarly high decommissioning rate can be expected at some point in the future. If the waste material from these turbines is not handled sustainably the whole concept of wind power as a clean energy alternative is challenged. This study presents a generally applicable method and quantification based on statistics of the waste amounts from wind turbines in Sweden. The expected annual mean growth is 12% until 2026, followed by a mean increase of 41% until 2034. By then, annual waste amounts are estimated to 240,000 tonnes steel and iron (16% of currently recycled materials), 2300 tonnes aluminium (4%), 3300 tonnes copper (5%), 340 tonnes electronics (<1%) and 28,000 tonnes blade materials (barely recycled today). Three studied scenarios suggest that a well-functioning market for re-use may postpone the effects of these waste amounts until improved recycling systems are in place. Full article
(This article belongs to the Special Issue Energy and Waste Management)
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Open AccessArticle American’s Energy Future: An Analysis of the Proposed Energy Policy Plans in Presidential Election
Energies 2016, 9(12), 1000; doi:10.3390/en9121000
Received: 26 August 2016 / Revised: 22 November 2016 / Accepted: 23 November 2016 / Published: 30 November 2016
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Abstract
As the leader of the largest economy, President of the United States has substantive influence on addressing climate change problems. However, a presidential election is often dominated by issues other than energy problems. This paper focuses on the 2016 presidential election, and examines
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As the leader of the largest economy, President of the United States has substantive influence on addressing climate change problems. However, a presidential election is often dominated by issues other than energy problems. This paper focuses on the 2016 presidential election, and examines the energy plans proposed by the leading Democrat and Republican candidates. Our data from the Iowa caucus survey in January 2016 suggests that voters were more concerned about terrorism and economic issues than environmental issues. We then compare the Democratic and Republican candidate’s view of America’s energy future, and evaluate their proposed renewable energy targets. We find that the view on renewable energy is polarized between Democratic and Republican candidates, while candidates from both parties agree on the need for energy efficiency. Results from our ordinal least squares regression models suggests that Democratic candidates have moderate to ambitious goals for developing solar and other renewables. The Republican candidates favor fossil fuels and they choose not to provide any specific target for developing renewable energy. In addition, this trend of party polarization has grown more significant when compared with the past three presidential elections. Our observation suggests that energy policies need to be discussed more often regarding the diversification and decarbonization of the nation’s energy system. Full article
(This article belongs to the Special Issue Energy Policy and Climate Change 2016)
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Open AccessArticle Experimental and Potential Analysis of a Single-Valve Expander for Waste Heat Recovery of a Gasoline Engine
Energies 2016, 9(12), 1001; doi:10.3390/en9121001
Received: 8 September 2016 / Revised: 20 November 2016 / Accepted: 26 November 2016 / Published: 30 November 2016
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Abstract
In this paper, a Rankine cycle test system is established to recover exhaust energy from a 2.0 L gasoline engine. Experiments on the system’s performance are carried out under various working conditions. The experimental results indicate that the recovery power of the expander
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In this paper, a Rankine cycle test system is established to recover exhaust energy from a 2.0 L gasoline engine. Experiments on the system’s performance are carried out under various working conditions. The experimental results indicate that the recovery power of the expander is strongly related to the load and speed of the gasoline engine. It is found that when the output power of the gasoline engine is 39.8–76.6 kW, the net power of the expander is 1.8–2.97 kW, which is equivalent to 3.9%–4.9% of the engine power. The performance simulation shows that the mass flow rate, power output, and isentropic efficiency of the piston expander are directly determined by the intake valve timing. Selecting a suitable intake valve timing can optimize the performance of the expander. The simulation results show that a 1 kW increment in power can be obtained only by selecting an optimum intake open timing. The experimental results further verify that the single-valve piston expander, because of its small dimensions, simple structure, and high speed, is appropriate, and has great potential for energy recovery of gasoline engine exhaust and has good prospects for engineering applications. Full article
(This article belongs to the Special Issue Waste Heat Recovery)
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Open AccessArticle Hydraulic Hybrid Excavator—Mathematical Model Validation and Energy Analysis
Energies 2016, 9(12), 1002; doi:10.3390/en9121002
Received: 27 September 2016 / Revised: 9 November 2016 / Accepted: 23 November 2016 / Published: 29 November 2016
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Abstract
Recent demands to reduce pollutant emissions and improve energy efficiency have driven the implementation of hybrid solutions in mobile machinery. This paper presents the results of a numerical and experimental analysis conducted on a hydraulic hybrid excavator (HHE). The machinery under study is
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Recent demands to reduce pollutant emissions and improve energy efficiency have driven the implementation of hybrid solutions in mobile machinery. This paper presents the results of a numerical and experimental analysis conducted on a hydraulic hybrid excavator (HHE). The machinery under study is a middle size excavator, whose standard version was modified with the introduction of an energy recovery system (ERS). The proposed ERS layout was designed to recover the potential energy of the boom, using a hydraulic accumulator as a storage device. The recovered energy is utilized through the pilot pump of the machinery which operates as a motor, thus reducing the torque required from the internal combustion engine (ICE). The analysis reported in this paper validates the HHE model by comparing numerical and experimental data in terms of hydraulic and mechanical variables and fuel consumption. The mathematical model shows its capability to reproduce the realistic operating conditions of the realized prototype, tested on the field. A detailed energy analysis comparison between the standard and the hybrid excavator models was carried out to evaluate the energy flows along the system, showing advantages, weaknesses and possibilities to further improve the machinery efficiency. Finally, the fuel consumption estimated by the model and that measured during the experiments are presented to highlight the fuel saving percentages. The HHE model is an important starting point for the development of other energy saving solutions. Full article
(This article belongs to the Special Issue Energy Efficiency and Controllability of Fluid Power Systems)
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Open AccessArticle Reorientation of Magnetic Graphene Oxide Nanosheets in Crosslinked Quaternized Polyvinyl Alcohol as Effective Solid Electrolyte
Energies 2016, 9(12), 1003; doi:10.3390/en9121003
Received: 11 August 2016 / Revised: 11 November 2016 / Accepted: 14 November 2016 / Published: 29 November 2016
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Abstract
This work aims to clarify the effect of magnetic graphene oxide (GO) reorientation in a polymer matrix on the ionic conduction and methanol barrier properties of nanocomposite membrane electrolytes. Magnetic iron oxide (Fe3O4) nanoparticles were prepared and dispersed on
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This work aims to clarify the effect of magnetic graphene oxide (GO) reorientation in a polymer matrix on the ionic conduction and methanol barrier properties of nanocomposite membrane electrolytes. Magnetic iron oxide (Fe3O4) nanoparticles were prepared and dispersed on GO nanosheets (GO-Fe3O4). The magnetic GO-Fe3O4 was imbedded into a quaternized polyvinyl alcohol (QPVA) matrix and crosslinked (CL-) with glutaraldehyde (GA) to obtain a polymeric nanocomposite. A magnetic field was applied in the through-plane direction during the drying and film formation steps. The CL-QPVA/GO-Fe3O4 nanocomposite membranes were doped with an alkali to obtain hydroxide-conducting electrolytes for direct methanol alkaline fuel cell (DMAFC) applications. The magnetic field-reoriented CL-QPVA/GO-Fe3O4 electrolyte demonstrated higher conductivity and lower methanol permeability than the unoriented CL-QPVA/GO-Fe3O4 membrane or the CL-QPVA film. The reoriented CL-QPVA/GO-Fe3O4 nanocomposite was used as the electrolyte in a DMAFC and resulted in a maximum power density of 55.4 mW·cm−2 at 60 °C, which is 73.7% higher than that of the composite without the magnetic field treatment (31.9 mW·cm−2). In contrast, the DMAFC using the CL-QPVA electrolyte generated only 22.4 mW·cm−2. This research proved the surprising benefits of magnetic-field-assisted orientation of GO-Fe3O4 in facilitating the ion conduction of a polymeric electrolyte. Full article
(This article belongs to the Special Issue Methanol and Alcohol Fuel Cells)
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Open AccessArticle A Novel Boil-Off Gas Re-Liquefaction Using a Spray Recondenser for Liquefied Natural-Gas Bunkering Operations
Energies 2016, 9(12), 1004; doi:10.3390/en9121004
Received: 19 September 2016 / Revised: 23 November 2016 / Accepted: 23 November 2016 / Published: 29 November 2016
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Abstract
This study presents the design of a novel boil-off gas (BOG) re-liquefaction technology using a BOG recondenser system. The BOG recondenser system targets the liquefied natural gas (LNG) bunkering operation, in which the BOG phase transition occurs in a pressure vessel instead of
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This study presents the design of a novel boil-off gas (BOG) re-liquefaction technology using a BOG recondenser system. The BOG recondenser system targets the liquefied natural gas (LNG) bunkering operation, in which the BOG phase transition occurs in a pressure vessel instead of a heat exchanger. The BOG that is generated during LNG bunkering operation is characterized as an intermittent flow with various peak loads. The system was designed to temporarily store the transient BOG inflow, condense it with subcooled LNG and store the condensed liquid. The superiority of the system was verified by comparing it with the most extensively employed conventional re-liquefaction system in terms of consumption energy and via an exergy analysis. Static simulations were conducted for three compositions; the results indicated that the proposed system provided 0 to 6.9% higher efficiencies. The exergy analysis indicates that the useful work of the conventional system is 24.9%, and the useful work of the proposed system is 26.0%. Process dynamic simulations of six cases were also performed to verify the behaviour of the BOG recondenser system. The results show that the pressure of the holdup in the recondenser vessel increased during the BOG inflow mode and decreased during the initialization mode. The maximum pressure of one of the bunkering cases was 3.45 bar. The system encountered a challenge during repetitive operations due to overpressurizing of the BOG recondenser vessel. Full article
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Open AccessArticle Augmented Nonlinear Controller for Maximum Power-Point Tracking with Artificial Neural Network in Grid-Connected Photovoltaic Systems
Energies 2016, 9(12), 1005; doi:10.3390/en9121005
Received: 20 October 2016 / Revised: 21 November 2016 / Accepted: 24 November 2016 / Published: 30 November 2016
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Abstract
Photovoltaic (PV) systems have non-linear characteristics that generate maximum power at one particular operating point. Environmental factors such as irradiance and temperature variations greatly affect the maximum power point (MPP). Diverse offline and online techniques have been introduced for tracking the MPP. Here,
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Photovoltaic (PV) systems have non-linear characteristics that generate maximum power at one particular operating point. Environmental factors such as irradiance and temperature variations greatly affect the maximum power point (MPP). Diverse offline and online techniques have been introduced for tracking the MPP. Here, to track the MPP, an augmented-state feedback linearized (AFL) non-linear controller combined with an artificial neural network (ANN) is proposed. This approach linearizes the non-linear characteristics in PV systems and DC/DC converters, for tracking and optimizing the PV system operation. It also reduces the dependency of the designed controller on linearized models, to provide global stability. A complete model of the PV system is simulated. The existing maximum power-point tracking (MPPT) and DC/DC boost-converter controller techniques are compared with the proposed ANN method. Two case studies, which simulate realistic circumstances, are presented to demonstrate the effectiveness and superiority of the proposed method. The AFL with ANN controller can provide good dynamic operation, faster convergence speed, and fewer operating-point oscillations around the MPP. It also tracks the global maxima under different conditions, especially irradiance-mutating situations, more effectively than the conventional methods. Detailed mathematical models and a control approach for a three-phase grid-connected intelligent hybrid system are proposed using MATLAB/Simulink. Full article
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Open AccessArticle Soiling and Cleaning of Polymer Film Solar Reflectors
Energies 2016, 9(12), 1006; doi:10.3390/en9121006
Received: 30 September 2016 / Revised: 21 November 2016 / Accepted: 24 November 2016 / Published: 29 November 2016
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Abstract
This paper describes the accelerated ageing of commercially available silvered polymer film by contact cleaning using brushes and water in the presence of soiling created by dust and sand particles. These conditions represent cleaning regimes in real concentrating solar power (CSP) solar fields
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This paper describes the accelerated ageing of commercially available silvered polymer film by contact cleaning using brushes and water in the presence of soiling created by dust and sand particles. These conditions represent cleaning regimes in real concentrating solar power (CSP) solar fields in arid environments, where contact cleaning using brushes and water is often required to clean the reflecting surfaces. Whilst suitable for glass reflectors, this paper discusses the effects of these established cleaning processes on the optical and visual characteristics of polymer film surfaces, and then describes the development of a more benign but effective contact cleaning process for cleaning polymer reflectors. The effects of a range of cleaning brushes are discussed, with and without the presence of water, in the presence of sand and dust particles from selected representative locations. The experiments were repeated using different experimental equipment at Plataforma Solar de Almería (PSA) in Spain and Cranfield University in the UK. The results highlight differences that are attributable to the experimental methods used. Reflectance measurements and visual inspection show that a soft cleaning brush with a small amount of water, used in a cleaning head with both linear and rotational motion, can clean polymer film reflecting surfaces without inflicting surface damage or reducing specular reflectance. Full article
(This article belongs to the Special Issue Urban Generation of Renewable Energy and Sustainable Cities)
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Open AccessArticle Study of Unwanted Emissions in the CENELEC-A Band Generated by Distributed Energy Resources and Their Influence over Narrow Band Power Line Communications
Energies 2016, 9(12), 1007; doi:10.3390/en9121007
Received: 27 September 2016 / Revised: 18 November 2016 / Accepted: 18 November 2016 / Published: 30 November 2016
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Abstract
Distributed Energy Resources might have a severe influence on Power Line Communications, as they can generate interfering signals and high frequency emissions or supraharmonics that may cause loss of metering and control data. In this paper, the influence of various energy resources on
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Distributed Energy Resources might have a severe influence on Power Line Communications, as they can generate interfering signals and high frequency emissions or supraharmonics that may cause loss of metering and control data. In this paper, the influence of various energy resources on Narrowband Power Line Communications is described and analyzed through several test measurements performed in a real microgrid. Accordingly, the paper describes the effects on smart metering communications through the Medium Access Control (MAC) layer analysis. Results show that the switching frequency of inverters and the presence of battery chargers are remarkable sources of disturbance in low voltage distribution networks. In this sense, the results presented can contribute to efforts towards standardization and normative of emissions at higher frequencies higher, such as CENELEC EN 50160 and IEC/TS 62749. Full article
(This article belongs to the Special Issue Microgrids 2016)
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Open AccessArticle Cost Analysis of Direct Methanol Fuel Cell Stacks for Mass Production
Energies 2016, 9(12), 1008; doi:10.3390/en9121008
Received: 22 July 2016 / Revised: 15 October 2016 / Accepted: 23 November 2016 / Published: 30 November 2016
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Abstract
Fuel cells are very promising technologies for efficient electrical energy generation. The development of enhanced system components and new engineering solutions is fundamental for the large-scale deployment of these devices. Besides automotive and stationary applications, fuel cells can be widely used as auxiliary
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Fuel cells are very promising technologies for efficient electrical energy generation. The development of enhanced system components and new engineering solutions is fundamental for the large-scale deployment of these devices. Besides automotive and stationary applications, fuel cells can be widely used as auxiliary power units (APUs). The concept of a direct methanol fuel cell (DMFC) is based on the direct feed of a methanol solution to the fuel cell anode, thus simplifying safety, delivery, and fuel distribution issues typical of conventional hydrogen-fed polymer electrolyte fuel cells (PEMFCs). In order to evaluate the feasibility of concrete application of DMFC devices, a cost analysis study was carried out in the present work. A 200 W-prototype developed in the framework of a European Project (DURAMET) was selected as the model system. The DMFC stack had a modular structure allowing for a detailed evaluation of cost characteristics related to the specific components. A scale-down approach, focusing on the model device and projected to a mass production, was used. The data used in this analysis were obtained both from research laboratories and industry suppliers specialising in the manufacturing/production of specific stack components. This study demonstrates that mass production can give a concrete perspective for the large-scale diffusion of DMFCs as APUs. The results show that the cost derived for the DMFC stack is relatively close to that of competing technologies and that the introduction of innovative approaches can result in further cost savings. Full article
(This article belongs to the Special Issue Direct Alcohol Fuel Cells)
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Open AccessArticle Development of Correlations for Windage Power Losses Modeling in an Axial Flux Permanent Magnet Synchronous Machine with Geometrical Features of the Magnets
Energies 2016, 9(12), 1009; doi:10.3390/en9121009
Received: 13 October 2016 / Revised: 10 November 2016 / Accepted: 25 November 2016 / Published: 30 November 2016
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Abstract
In this paper, a set of correlations for the windage power losses in a 4 kW axial flux permanent magnet synchronous machine (AFPMSM) is presented. In order to have an efficient machine, it is necessary to optimize the total electromagnetic and mechanical losses.
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In this paper, a set of correlations for the windage power losses in a 4 kW axial flux permanent magnet synchronous machine (AFPMSM) is presented. In order to have an efficient machine, it is necessary to optimize the total electromagnetic and mechanical losses. Therefore, fast equations are needed to estimate the windage power losses of the machine. The geometry consists of an open rotor–stator with sixteen magnets at the periphery of the rotor with an annular opening in the entire disk. Air can flow in a channel being formed between the magnets and in a small gap region between the magnets and the stator surface. To construct the correlations, computational fluid dynamics (CFD) simulations through the frozen rotor (FR) method are performed at the practical ranges of the geometrical parameters, namely the gap size distance, the rotational speed of the rotor, the magnet thickness and the magnet angle. Thereafter, two categories of formulations are defined to make the windage losses dimensionless based on whether the losses are mainly due to the viscous forces or the pressure forces. At the end, the correlations can be achieved via curve fittings from the numerical data. The results reveal that the pressure forces are responsible for the windage losses for the side surfaces in the air-channel, whereas for the surfaces facing the stator surface in the gap, the viscous forces mainly contribute to the windage losses. Additionally, the results of the parametric study demonstrate that the overall windage losses in the machine escalate with an increase in either the rotational Reynolds number or the magnet thickness ratio. By contrast, the windage losses decrease once the magnet angle ratio enlarges. Moreover, it can be concluded that the proposed correlations are very useful tools in the design and optimizations of this type of electrical machine. Full article
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Open AccessArticle Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation
Energies 2016, 9(12), 1010; doi:10.3390/en9121010
Received: 9 August 2016 / Revised: 6 November 2016 / Accepted: 22 November 2016 / Published: 30 November 2016
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Abstract
An energy storage system (ESS) in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve). This paper presents an
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An energy storage system (ESS) in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve). This paper presents an optimal scheduling algorithm for frequency regulation by an ESS. This algorithm determines the bidding capacity and base point of an ESS in each operational period to achieve the maximum profit within a stable state-of-charge (SOC) range. However, the charging/discharging efficiency of an ESS causes SOC errors whenever the ESS performs frequency regulation. With an increase in SOC errors, the ESS cannot respond to an automatic generation control (AGC) signal. This situation results in low ESS performance scores, and finally, the ESS is disqualified from performing frequency regulation. This paper also presents a real-time SOC management algorithm aimed at solving the SOC error problem in real-time operations. This algorithm compensates for SOC errors by changing the base point of the ESS. The optimal scheduling algorithm is implemented in MATLAB by using the particle swarm optimization (PSO) method. In addition, changes in the SOC when the ESS performs frequency regulation in a real-time operation are confirmed using the PSCAD/EMTDC tool. The simulation results show that the optimal scheduling algorithm manages the SOC more efficiently than a commonly employed planning method. In addition, the proposed real-time SOC management algorithm is confirmed to be capable of performing SOC recovery. Full article
(This article belongs to the Special Issue Control of Energy Storage) Printed Edition available
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Open AccessArticle Life Cycle Assessment of Horse Manure Treatment
Energies 2016, 9(12), 1011; doi:10.3390/en9121011
Received: 19 September 2016 / Revised: 16 November 2016 / Accepted: 21 November 2016 / Published: 30 November 2016
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Abstract
Horse manure consists of feces, urine, and varying amounts of various bedding materials. The management of horse manure causes environmental problems when emissions occur during the decomposition of organic material, in addition to nutrients not being recycled. The interest in horse manure undergoing
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Horse manure consists of feces, urine, and varying amounts of various bedding materials. The management of horse manure causes environmental problems when emissions occur during the decomposition of organic material, in addition to nutrients not being recycled. The interest in horse manure undergoing anaerobic digestion and thereby producing biogas has increased with an increasing interest in biogas as a renewable fuel. This study aims to highlight the environmental impact of different treatment options for horse manure from a system perspective. The treatment methods investigated are: (1) unmanaged composting; (2) managed composting; (3) large-scale incineration in a waste-fired combined heat and power (CHP) plant; (4) drying and small-scale combustion; and (5) liquid anaerobic digestion with thermal pre-treatment. Following significant data uncertainty in the survey, the results are only indicative. No clear conclusions can be drawn regarding any preference in treatment methods, with the exception of their climate impact, for which anaerobic digestion is preferred. The overall conclusion is that more research is needed to ensure the quality of future surveys, thus an overall research effort from horse management to waste management. Full article
(This article belongs to the Special Issue Energy and Waste Management)
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Open AccessArticle A Hybrid Modular Multilevel Converter with Partial Embedded Energy Storage
Energies 2016, 9(12), 1012; doi:10.3390/en9121012
Received: 31 August 2016 / Revised: 14 November 2016 / Accepted: 23 November 2016 / Published: 30 November 2016
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Abstract
Modular and cascaded multilevel converters provide a functional solution for the integration of energy storage systems (ESSs). This paper develops a hybrid multilevel converter based on the modular multilevel converter (MMC) that can be functionally extended with partial embedded ESS as a fraction
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Modular and cascaded multilevel converters provide a functional solution for the integration of energy storage systems (ESSs). This paper develops a hybrid multilevel converter based on the modular multilevel converter (MMC) that can be functionally extended with partial embedded ESS as a fraction of the overall converter power rating. The configuration, which can operate as a typical DC-AC converter, enables multi-directional power flow between the DC- and AC-side of the converter, as well as the embedded energy storage elements. The use of a three-phase flying-capacitor submodule eliminates the second-order harmonic oscillations present in modular cascaded multilevel converters. Current, voltage and power control are discussed in the paper while simulation results illustrate the operation of the hybrid MMC as a DC-AC converter in a typical inverter application and the additional functions and control of the embedded ESS. Full article
(This article belongs to the Special Issue Selected Papers from 2nd Energy Future Conference)
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Open AccessArticle Dynamic Simulation of a Trigeneration Scheme for Domestic Purposes Based on Hybrid Techniques
Energies 2016, 9(12), 1013; doi:10.3390/en9121013
Received: 9 August 2016 / Revised: 21 November 2016 / Accepted: 22 November 2016 / Published: 30 November 2016
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Abstract
In this paper, the design of a system providing electricity by coupling photovoltaic/thermal (PVT) collectors and a wind turbine (WT), sanitary hot water (SHW) coming from the PVT and evacuated tube collectors (ETCs) and fresh water (FW) produced in two seawater desalting facilities
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In this paper, the design of a system providing electricity by coupling photovoltaic/thermal (PVT) collectors and a wind turbine (WT), sanitary hot water (SHW) coming from the PVT and evacuated tube collectors (ETCs) and fresh water (FW) produced in two seawater desalting facilities (membrane distillation, MD, and reverse osmosis, RO), has been carefully analyzed by means of a dynamic model developed in TRNSYS®. This analysis is compulsory to operate a lab-scale pilot plant that is being erected at Zaragoza, Spain. A new model-type has been included in TRNSYS® in order to include the MD unit in the scheme. A sensitivity analysis of some free-design variables, such that the ETC surface, PVT and ETC tilt, water storage tank, batteries capacities, and mass flow rates delivered to the SHW service and/or feeding the MD unit has been performed in order to propose the definite design of the scheme. The proposed base case was able to produce up to 15,311 L per year in the MD system and cover an electric energy demand of 1890 kWh. Coverage of SHW, water (including RO and MD) and power is respectively 99.3%, 100% and 70%. However, daily and yearly assessment of FW, SHW and power produced with the optimized design gave a better coverage of water and energy demands for a typical single family home. The improved and definite design was able to increase its MD production in 35% and the electric energy in 7% compared with base case. Full article
(This article belongs to the Special Issue Solar Cooling and Heating)
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Open AccessArticle Forecasting Crude Oil Price Using EEMD and RVM with Adaptive PSO-Based Kernels
Energies 2016, 9(12), 1014; doi:10.3390/en9121014
Received: 30 October 2016 / Revised: 23 November 2016 / Accepted: 25 November 2016 / Published: 1 December 2016
Cited by 3 | PDF Full-text (1335 KB) | HTML Full-text | XML Full-text
Abstract
Crude oil, as one of the most important energy sources in the world, plays a crucial role in global economic events. An accurate prediction for crude oil price is an interesting and challenging task for enterprises, governments, investors, and researchers. To cope with
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Crude oil, as one of the most important energy sources in the world, plays a crucial role in global economic events. An accurate prediction for crude oil price is an interesting and challenging task for enterprises, governments, investors, and researchers. To cope with this issue, in this paper, we proposed a method integrating ensemble empirical mode decomposition (EEMD), adaptive particle swarm optimization (APSO), and relevance vector machine (RVM)—namely, EEMD-APSO-RVM—to predict crude oil price based on the “decomposition and ensemble” framework. Specifically, the raw time series of crude oil price were firstly decomposed into several intrinsic mode functions (IMFs) and one residue by EEMD. Then, RVM with combined kernels was applied to predict target value for the residue and each IMF individually. To improve the prediction performance of each component, an extended particle swarm optimization (PSO) was utilized to simultaneously optimize the weights and parameters of single kernels for the combined kernel of RVM. Finally, simple addition was used to aggregate all the predicted results of components into an ensemble result as the final result. Extensive experiments were conducted on the crude oil spot price of the West Texas Intermediate (WTI) to illustrate and evaluate the proposed method. The experimental results are superior to those by several state-of-the-art benchmark methods in terms of root mean squared error (RMSE), mean absolute percent error (MAPE), and directional statistic (Dstat), showing that the proposed EEMD-APSO-RVM is promising for forecasting crude oil price. Full article
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Open AccessArticle Numerical Study of the Dynamic Response of Heat and Mass Transfer to Operation Mode Switching of a Unitized Regenerative Fuel Cell
Energies 2016, 9(12), 1015; doi:10.3390/en9121015
Received: 29 September 2016 / Revised: 14 November 2016 / Accepted: 21 November 2016 / Published: 1 December 2016
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Abstract
Knowledge concerning the complicated changes of mass and heat transfer is desired to improve the performance and durability of unitized regenerative fuel cells (URFCs). In this study, a transient, non-isothermal, single-phase, and multi-physics mathematical model for a URFC based on the proton exchange
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Knowledge concerning the complicated changes of mass and heat transfer is desired to improve the performance and durability of unitized regenerative fuel cells (URFCs). In this study, a transient, non-isothermal, single-phase, and multi-physics mathematical model for a URFC based on the proton exchange membrane is generated to investigate transient responses in the process of operation mode switching from fuel cell (FC) to electrolysis cell (EC). Various heat generation mechanisms, including Joule heat, reaction heat, and the heat attributed to activation polarizations, have been considered in the transient model coupled with electrochemical reaction and mass transfer in porous electrodes. The polarization curves of the steady-state models are validated by experimental data in the literatures. Numerical results reveal that current density, gas mass fractions, and temperature suddenly change with the sudden change of operating voltage in the mode switching process. The response time of temperature is longer than that of current density and gas mass fractions. In both FC and EC modes, the cell temperature and gradient of gas mass fraction in the oxygen side are larger than that in the hydrogen side. The temperature difference of the entire cell is less than 1.5 K. The highest temperature appears at oxygen-side catalyst layer under the FC mode and at membrane under a more stable EC mode. The cell is exothermic all the time. These dynamic responses and phenomena have important implications for heat analysis and provide proven guidelines for the improvement of URFCs mode switching. Full article
(This article belongs to the Special Issue Hydrogen Production, Separation and Applications)
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Open AccessArticle Numerical Investigation on the Effect of Cementing Properties on the Thermal and Mechanical Stability of Geothermal Wells
Energies 2016, 9(12), 1016; doi:10.3390/en9121016
Received: 9 August 2016 / Revised: 22 November 2016 / Accepted: 22 November 2016 / Published: 2 December 2016
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Abstract
In this paper, a two-dimensional (2-D) Finite Element (FE) analysis of a geothermal well was performed with respect to five different cross-sections corresponding to the design specifications for the geothermal well that is currently constructed in Pohang, South Korea. Among the essential components
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In this paper, a two-dimensional (2-D) Finite Element (FE) analysis of a geothermal well was performed with respect to five different cross-sections corresponding to the design specifications for the geothermal well that is currently constructed in Pohang, South Korea. Among the essential components (such as ground formation, casing, and cementing) of a geothermal well, the thermal and mechanical stability of the cementing component was discussed based on a series of parametric studies with consideration of the thermal conductivity and Young’s modulus of the cementing component. With increasing number of casing layers, the cementing component experiences less stress concentration. In addition, the lower thermal conductivity of the cementing material is advantageous for effectively controlling radial displacement. Consequently, it should be noted in geothermal well cementing construction that long-term strength degradation of the cementing might cause the severe structural instability of an entire geothermal well. Full article
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Open AccessArticle Ensemble Learning Approach for Probabilistic Forecasting of Solar Power Generation
Energies 2016, 9(12), 1017; doi:10.3390/en9121017
Received: 18 July 2016 / Revised: 24 November 2016 / Accepted: 28 November 2016 / Published: 1 December 2016
Cited by 2 | PDF Full-text (704 KB) | HTML Full-text | XML Full-text
Abstract
Probabilistic forecasting accounts for the uncertainty in prediction that arises from inaccurate input data due to measurement errors, as well as the inherent inaccuracy of a prediction model. Because of the variable nature of renewable power generation depending on weather conditions, probabilistic forecasting
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Probabilistic forecasting accounts for the uncertainty in prediction that arises from inaccurate input data due to measurement errors, as well as the inherent inaccuracy of a prediction model. Because of the variable nature of renewable power generation depending on weather conditions, probabilistic forecasting is well suited to it. For a grid-tied solar farm, it is increasingly important to forecast the solar power generation several hours ahead. In this study, we propose three different methods for ensemble probabilistic forecasting, derived from seven individual machine learning models, to generate 24-h ahead solar power forecasts. We have shown that while all of the individual machine learning models are more accurate than the traditional benchmark models, like autoregressive integrated moving average (ARIMA), the ensemble models offer even more accurate results than any individual machine learning model alone does. Furthermore, it is observed that running separate models on the data belonging to the same hour of the day vastly improves the accuracy of the results. Getting more accurate forecasts will help the stakeholders come up with better decisions in resource planning and control when large-scale solar farms are integrated into the power grid. Full article
(This article belongs to the Special Issue Energy Time Series Forecasting)
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Open AccessArticle Experimental Investigation of Crack Extension Patterns in Hydraulic Fracturing with Shale, Sandstone and Granite Cores
Energies 2016, 9(12), 1018; doi:10.3390/en9121018
Received: 7 October 2016 / Revised: 17 November 2016 / Accepted: 23 November 2016 / Published: 1 December 2016
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Abstract
Hydraulic fracturing is an important method of reservoir stimulation in the exploitation of geothermal resources, and conventional and unconventional oil and gas resources. In this article, hydraulic fracturing experiments with shale, sandstone cores (from southern Sichuan Basin), and granite cores (from Inner Mongolia)
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Hydraulic fracturing is an important method of reservoir stimulation in the exploitation of geothermal resources, and conventional and unconventional oil and gas resources. In this article, hydraulic fracturing experiments with shale, sandstone cores (from southern Sichuan Basin), and granite cores (from Inner Mongolia) were conducted to investigate the different hydraulic fracture extension patterns in these three reservoir rocks. The different reactions between reservoir lithology and pump pressure can be reflected by the pump pressure monitoring curves of hydraulic fracture experiments. An X-ray computer tomography (CT) scanner was employed to obtain the spatial distribution of hydraulic fractures in fractured shale, sandstone, and granite cores. From the microscopic and macroscopic observation of hydraulic fractures, different extension patterns of the hydraulic fracture can be analyzed. In fractured sandstone, symmetrical hydraulic fracture morphology could be formed, while some micro cracks were also induced near the injection hole. Although the macroscopic cracks in fractured granite cores are barely observed by naked eye, the results of X-ray CT scanning obviously show the morphology of hydraulic fractures. It is indicated that the typical bedding planes well developed in shale formation play an important role in the propagation of hydraulic fractures in shale cores. The results also demonstrated that heterogeneity influenced the pathway of the hydraulic fracture in granite cores. Full article
(This article belongs to the Special Issue Oil and Gas Engineering)
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Open AccessArticle Assessment of the Usability and Accuracy of the Simplified One-Diode Models for Photovoltaic Modules
Energies 2016, 9(12), 1019; doi:10.3390/en9121019
Received: 17 October 2016 / Revised: 15 November 2016 / Accepted: 25 November 2016 / Published: 6 December 2016
Cited by 14 | PDF Full-text (3740 KB) | HTML Full-text | XML Full-text
Abstract
Models for photovoltaic (PV) cells and panels, based on the diode equivalent circuit, have been widely used because they are effective tools for system design. Many authors have presented simplified one-diode models whose three or four parameters are calculated using the data extracted
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Models for photovoltaic (PV) cells and panels, based on the diode equivalent circuit, have been widely used because they are effective tools for system design. Many authors have presented simplified one-diode models whose three or four parameters are calculated using the data extracted from the datasheets issued by PV panel manufactures and adopting some simplifying hypotheses and numerical solving techniques. Sometimes it may be difficult to make a choice among so many models. To help researchers and designers working in the area of photovoltaic systems in selecting the model that is fit for purpose, a criterion for rating both the usability and accuracy of simplified one-diode models is proposed in this paper. The paper minutely describes the adopted hypotheses, analytical procedures and operative steps to calculate the parameters of the most famous simplified one-diode equivalent circuits. To test the achievable accuracy of the models, a comparison between the characteristics of some commercial PV modules issued by PV panel manufacturers and the calculated current-voltage (I-V) curves, at constant solar irradiance and/or cell temperature, is carried out. The study shows that, even if different usability ratings and accuracies are observed, the simplified one-diode models can be considered very effective tools. Full article
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Open AccessArticle Energy Optimization and Fuel Economy Investigation of a Series Hybrid Electric Vehicle Integrated with Diesel/RCCI Engines
Energies 2016, 9(12), 1020; doi:10.3390/en9121020
Received: 26 September 2016 / Revised: 14 November 2016 / Accepted: 24 November 2016 / Published: 4 December 2016
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Abstract
Among different types of low temperature combustion (LTC) regimes, eactively controlled compression ignition (RCCI) has received a lot of attention as a promising advanced combustion engine technology with high indicated thermal efficiency and low nitrogen oxides (NOx) and particulate matter
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Among different types of low temperature combustion (LTC) regimes, eactively controlled compression ignition (RCCI) has received a lot of attention as a promising advanced combustion engine technology with high indicated thermal efficiency and low nitrogen oxides ( NO x ) and particulate matter (PM) emissions. In this study, an RCCI engine for the purpose of fuel economy investigation is incorporated in series hybrid electric vehicle (SHEV) architecture, which allows the engine to run completely in the narrow RCCI mode for common driving cycles. Three different types of energy management control (EMC) strategies are designed and implemented to achieve the best fuel economy. The EMC strategies encompass rule-based control (RBC), offline, and online optimal controllers, including dynamic programing (DP) and model predictive control (MPC), respectively. The simulation results show a 13.1% to 14.2% fuel economy saving by using an RCCI engine over a modern spark ignition (SI) engine in SHEV for different driving cycles. This fuel economy saving is reduced to 3% in comparison with a modern compression ignition (CI) engine, while NO x emissions are significantly lower. Simulation results show that the RCCI engine offers more fuel economy improvement in more aggressive driving cycles (e.g., US06), compared to less aggressive driving cycles (e.g., UDDS). In addition, the MPC results show that sub-optimal fuel economy is achieved by predicting the vehicle speed profile for a time horizon of 70 s. Full article
(This article belongs to the Special Issue Internal Combustion Engines)
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Open AccessArticle Gas Hydrate Growth Kinetics: A Parametric Study
Energies 2016, 9(12), 1021; doi:10.3390/en9121021
Received: 11 August 2016 / Revised: 28 October 2016 / Accepted: 28 November 2016 / Published: 5 December 2016
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Abstract
Gas hydrate growth kinetics was studied at a pressure of 90 bars to investigate the effect of temperature, initial water content, stirring rate, and reactor size in stirred semi-batch autoclave reactors. The mixing energy during hydrate growth was estimated by logging the power
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Gas hydrate growth kinetics was studied at a pressure of 90 bars to investigate the effect of temperature, initial water content, stirring rate, and reactor size in stirred semi-batch autoclave reactors. The mixing energy during hydrate growth was estimated by logging the power consumed. The theoretical model by Garcia-Ochoa and Gomez for estimation of the mass transfer parameters in stirred tanks has been used to evaluate the dispersion parameters of the system. The mean bubble size, impeller power input per unit volume, and impeller Reynold’s number/tip velocity were used for analyzing observed trends from the gas hydrate growth data. The growth behavior was analyzed based on the gas consumption and the growth rate per unit initial water content. The results showed that the growth rate strongly depended on the flow pattern in the cell, the gas-liquid mass transfer characteristics, and the mixing efficiency from stirring. Scale-up effects indicate that maintaining the growth rate per unit volume of reactants upon scale-up with geometric similarity does not depend only on gas dispersion in the liquid phase but may rather be a function of the specific thermal conductance, and heat and mass transfer limitations created by the limit to the degree of the liquid phase dispersion is batched and semi-batched stirred tank reactors. Full article
(This article belongs to the Special Issue Methane Hydrate Research and Development)
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Open AccessArticle A Comparison of Impedance-Based Fault Location Methods for Power Underground Distribution Systems
Energies 2016, 9(12), 1022; doi:10.3390/en9121022
Received: 14 October 2016 / Revised: 22 November 2016 / Accepted: 25 November 2016 / Published: 7 December 2016
Cited by 3 | PDF Full-text (2255 KB) | HTML Full-text | XML Full-text
Abstract
In the last few decades, the Smart Grid paradigm presence has increased within power systems. These new kinds of networks demand new Operations and Planning approaches, following improvements in the quality of service. In this sense, the role of the Distribution Management System,
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In the last few decades, the Smart Grid paradigm presence has increased within power systems. These new kinds of networks demand new Operations and Planning approaches, following improvements in the quality of service. In this sense, the role of the Distribution Management System, through its Outage Management System, is essential to guarantee the network reliability. This system is responsible for minimizing the consequences arising from a fault event (or network failure). Obviously, knowing where the fault appears is critical for a good reaction of this system. Therefore, several fault location techniques have been proposed. However, most of them provide individual results, associated with specific testbeds, which make the comparison between them difficult. Due to this, a review of fault location methods has been done in this paper, analyzing them for their use on underground distribution lines. Specifically, this study is focused on an impedance-based method because their requirements are in line with the typical instrumentation deployed in distribution networks. This work is completed with an exhaustive analysis of these methods over a PSCADTM X4 implementation of the standard IEEE Node Test Feeder, which truly allows us to consistently compare the results of these location methods and to determine the advantages and drawbacks of each of them. Full article
(This article belongs to the Special Issue Advances in Power System Operations and Planning)
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Open AccessArticle Inverse Aerodynamic Optimization Considering Impacts of Design Tip Speed Ratio for Variable-Speed Wind Turbines
Energies 2016, 9(12), 1023; doi:10.3390/en9121023
Received: 5 September 2016 / Revised: 23 November 2016 / Accepted: 28 November 2016 / Published: 3 December 2016
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Abstract
Because of the slow dynamic behavior of the large-inertia wind turbine rotor, variable-speed wind turbines (VSWTs) are actually unable to keep operating at the design tip speed ratio (TSR) during the maximum power point tracking (MPPT) process. Moreover, it has been pointed out
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Because of the slow dynamic behavior of the large-inertia wind turbine rotor, variable-speed wind turbines (VSWTs) are actually unable to keep operating at the design tip speed ratio (TSR) during the maximum power point tracking (MPPT) process. Moreover, it has been pointed out that although a larger design TSR can increase the maximum power coefficient, it also greatly prolongs the MPPT process of VSWTs. Consequently, turbines spend more time operating at the off-design TSRs and the wind energy capture efficiency is decreased. Therefore, in the inverse aerodynamic design of VSWTs, the static aerodynamic performance (i.e., the maximum power coefficient) and the dynamic process of MPPT should be comprehensively modeled for determining an appropriate design TSR. In this paper, based on the inverse design method, an aerodynamic optimization method for VSWTs, fully considering the impacts of the design TSR on the static and dynamic behavior of wind turbines is proposed. In this method, to achieve higher wind energy production, the design TSR, chord length and twist angle are jointly optimized, which is structurally different from the conventional separated design procedure. Finally, the effectiveness of the proposed method is validated by simulation results based on the Bladed software. Full article
(This article belongs to the collection Wind Turbines)
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Open AccessArticle Mitigation of the Impact of High Plug-in Electric Vehicle Penetration on Residential Distribution Grid Using Smart Charging Strategies
Energies 2016, 9(12), 1024; doi:10.3390/en9121024
Received: 25 July 2016 / Revised: 16 November 2016 / Accepted: 25 November 2016 / Published: 3 December 2016
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Abstract
Vehicle electrification presents a great opportunity to reduce transportation greenhouse gas emissions. The greater use of plug-in electric vehicles (PEVs), however, puts stress on local distribution networks. This paper presents an optimal PEV charging control method integrated with utility demand response (DR) signals
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Vehicle electrification presents a great opportunity to reduce transportation greenhouse gas emissions. The greater use of plug-in electric vehicles (PEVs), however, puts stress on local distribution networks. This paper presents an optimal PEV charging control method integrated with utility demand response (DR) signals to mitigate the impact of PEV charging to several aspects of a grid, including load surge, distribution accumulative voltage deviation, and transformer aging. To build a realistic PEV charging load model, the results of National Household Travel Survey (NHTS) have been analyzed and a stochastic PEV charging model has been defined based on survey results. The residential distribution grid contains 120 houses and is modeled in GridLAB-D. Co-simulation is performed using Matlab and GridLAB-D to enable the optimal control algorithm in Matlab to control PEV charging loads in the residential grid modeled in GridLAB-D. Simulation results demonstrate the effectiveness of the proposed optimal charging control method in mitigating the negative impacts of PEV charging on the residential grid. Full article
(This article belongs to the Special Issue Smart Microgrids: Developing the Intelligent Power Grid of Tomorrow)
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Open AccessArticle Forecasting the State of Health of Electric Vehicle Batteries to Evaluate the Viability of Car Sharing Practices
Energies 2016, 9(12), 1025; doi:10.3390/en9121025
Received: 14 July 2016 / Revised: 16 November 2016 / Accepted: 28 November 2016 / Published: 3 December 2016
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Abstract
Car-sharing practices are introducing electric vehicles (EVs) into their fleet. However, the literature suggests that at this point shared EV systems are failing to reach satisfactory commercial viability. A potential reason for this is the effect of higher vehicle usage, which is characteristic
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Car-sharing practices are introducing electric vehicles (EVs) into their fleet. However, the literature suggests that at this point shared EV systems are failing to reach satisfactory commercial viability. A potential reason for this is the effect of higher vehicle usage, which is characteristic of car sharing, and the implications on the battery’s state of health (SoH). In this paper, we forecast the SoH of two identical EVs being used in different car-sharing practices. For this purpose, we use real life transaction data from charging stations and different EV sensors. The results indicate that insight into users’ driving and charging behavior can provide a valuable point of reference for car-sharing system designers. In particular, the forecasting results show that the moment when an EV battery reaches its theoretical end of life can differ in as much as a quarter of the time when vehicles are shared under different conditions. Full article
(This article belongs to the Special Issue Energy Time Series Forecasting)
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Open AccessArticle Research on a Household Dual Heat Source Heat Pump Water Heater with Preheater Based on ASPEN PLUS
Energies 2016, 9(12), 1026; doi:10.3390/en9121026
Received: 6 October 2016 / Revised: 31 October 2016 / Accepted: 25 November 2016 / Published: 3 December 2016
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Abstract
This article proposes a dual heat source heat pump bathroom unit with preheater which is feasible for a single family. The system effectively integrates the air source heat pump (ASHP) and wastewater source heat pump (WSHP) technologies, and incorporates a preheater to recover
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This article proposes a dual heat source heat pump bathroom unit with preheater which is feasible for a single family. The system effectively integrates the air source heat pump (ASHP) and wastewater source heat pump (WSHP) technologies, and incorporates a preheater to recover shower wastewater heat and thus improve the total coefficient of performance (COP) of the system, and it has no electric auxiliary heating device, which is favorable to improve the security of the system operation. The process simulation software ASPEN PLUS, widely used in the design and optimization of thermodynamic systems, was used to simulate various cases of system use and to analyze the impact of the preheater on the system. The average COP value of a system with preheater is 6.588 and without preheater it is 4.677. Based on the optimization and analysis, under the standard conditions of air at 25 °C, relative humidity of 70%, wastewater at 35 °C, wastewater flow rate of 0.07 kg/s, tap water at 15 °C, and condenser outlet water temperature at 50 °C, the theoretical COP of the system can reach 9.784 at an evaporating temperature of 14.96 °C, condensing temperature of 48.74 °C, and preheated water temperature of 27.19 °C. Full article
(This article belongs to the Special Issue Advanced Heating and Cooling Techniques)
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Open AccessArticle Comparative Study of Shell and Helically-Coiled Tube Heat Exchangers with Various Dimple Arrangements in Condensers for Odor Control in a Pyrolysis System
Energies 2016, 9(12), 1027; doi:10.3390/en9121027
Received: 4 October 2016 / Revised: 18 November 2016 / Accepted: 30 November 2016 / Published: 5 December 2016
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Abstract
This study performed evaluations of the shell and helically-coiled tube heat exchangers with various dimple arrangements, that is, flat, inline, staggered, and bulged, at different Dean numbers (De) and inlet temperatures of a hot channel. Conjugated heat transfer was analyzed to
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This study performed evaluations of the shell and helically-coiled tube heat exchangers with various dimple arrangements, that is, flat, inline, staggered, and bulged, at different Dean numbers (De) and inlet temperatures of a hot channel. Conjugated heat transfer was analyzed to evaluate the heat transfer performance of the exchangers through temperature difference between the inlet and outlet, Nusselt number inside the coiled tube, and pressure drop of the coiled tube by using 3-D Reynolds-averaged Navier–Stokes (RANS) equations with shear stress transport turbulence closure. A grid dependency test was performed to determine the optimal number of the grid system. The numerical results were validated using the experimental data, and showed good agreement. The inline and staggered arrangements show the highest temperature differences through all De. The staggered arrangement shows the best heat transfer performance, whereas the inline arrangement shows the second highest performance with all ranges of De and the hot channel’s inlet temperature. The inline and staggered arrangements show the highest pressure drop among all inlet temperatures of the hot channel. Full article
(This article belongs to the Special Issue Engineering Fluid Dynamics)
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Open AccessArticle Predictive Modeling of a Buoyancy-Operated Cooling Tower under Unsaturated Conditions: Adjoint Sensitivity Model and Optimal Best-Estimate Results with Reduced Predicted Uncertainties
Energies 2016, 9(12), 1028; doi:10.3390/en9121028
Received: 18 October 2016 / Revised: 28 November 2016 / Accepted: 28 November 2016 / Published: 8 December 2016
PDF Full-text (7479 KB) | HTML Full-text | XML Full-text
Abstract
Nuclear and other large-scale energy-producing plants must include systems that guarantee the safe discharge of residual heat from the industrial process into the atmosphere. This function is usually performed by one or several cooling towers. The amount of heat released by a cooling
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Nuclear and other large-scale energy-producing plants must include systems that guarantee the safe discharge of residual heat from the industrial process into the atmosphere. This function is usually performed by one or several cooling towers. The amount of heat released by a cooling tower into the external environment can be quantified by using a numerical simulation model of the physical processes occurring in the respective tower, augmented by experimentally measured data that accounts for external conditions such as outlet air temperature, outlet water temperature, and outlet air relative humidity. The model’s responses of interest depend on many model parameters including correlations, boundary conditions, and material properties. Changes in these model parameters induce changes in the computed quantities of interest (called “model responses”), which are quantified by the sensitivities (i.e., functional derivatives) of the model responses with respect to the model parameters. These sensitivities are computed in this work by applying the general adjoint sensitivity analysis methodology (ASAM) for nonlinear systems. These sensitivities are subsequently used for: (i) Ranking the parameters in their importance to contributing to response uncertainties; (ii) Propagating the uncertainties (covariances) in these model parameters to quantify the uncertainties (covariances) in the model responses; (iii) Performing model validation and predictive modeling. The comprehensive predictive modeling methodology used in this work, which includes assimilation of experimental measurements and calibration of model parameters, is applied to the cooling tower model under unsaturated conditions. The predicted response uncertainties (standard deviations) thus obtained are smaller than both the computed and the measured standards deviations for the respective responses, even for responses where no experimental data were available. Full article
(This article belongs to the Special Issue Advances in Predictive Modeling of Nuclear Energy Systems)
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Open AccessArticle Effect of Wind Turbine Blade Rotation on Triggering Lightning: An Experimental Study
Energies 2016, 9(12), 1029; doi:10.3390/en9121029
Received: 2 October 2016 / Revised: 24 November 2016 / Accepted: 28 November 2016 / Published: 7 December 2016
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Abstract
Compared with other lightning targets on the ground, the most notable feature of a wind turbine is that the blades are usually in a rotating state when lightning strikes. To study the mechanism of blade rotation influencing wind turbine on triggering lightning, lightning
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Compared with other lightning targets on the ground, the most notable feature of a wind turbine is that the blades are usually in a rotating state when lightning strikes. To study the mechanism of blade rotation influencing wind turbine on triggering lightning, lightning discharge comparison tests based on a typical 2-MW 1:30-scaled wind turbine model with an arching high-voltage electrode were conducted under different modes of stationary and rotating blades. Negative polarity switching impulses of 250/2500 μs were applied to the arching electrode. The up-and-down method was adopted for 50% discharge voltage and the discharge process was observed. The experimental results showed that under the condition of a 4 m gap, the breakdown voltage decreases and the connection point of the leaders approaches the high-voltage electrode with increasing blade speed, indicating that the wind turbine’s blade rotation enhances the triggering of lightning. The analysis showed that the blade rotation could be altering the charge distribution on the blade tip, resulting in varied ascending leader development on the blade tip, which affected the discharge development process. Full article
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Open AccessArticle A Privacy-Preserving Distributed Optimal Scheduling for Interconnected Microgrids
Energies 2016, 9(12), 1031; doi:10.3390/en9121031
Received: 20 October 2016 / Revised: 21 November 2016 / Accepted: 29 November 2016 / Published: 7 December 2016
Cited by 1 | PDF Full-text (572 KB) | HTML Full-text | XML Full-text
Abstract
With the development of microgrids (MGs), interconnected operation of multiple MGs is becoming a promising strategy for the smart grid. In this paper, a privacy-preserving distributed optimal scheduling method is proposed for the interconnected microgrids (IMG) with a battery energy storage system (BESS)
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With the development of microgrids (MGs), interconnected operation of multiple MGs is becoming a promising strategy for the smart grid. In this paper, a privacy-preserving distributed optimal scheduling method is proposed for the interconnected microgrids (IMG) with a battery energy storage system (BESS) and renewable energy resources (RESs). The optimal scheduling problem is modeled to minimize the coalitional operation cost of the IMG, including the fuel cost of conventional distributed generators and the life loss cost of BESSs. By using the framework of the alternating direction method of multipliers (ADMM), a distributed optimal scheduling model and an iteration solution algorithm for the IMG is introduced; only the expected exchanging power (EEP) of each MG is required during the iterations. Furthermore, a privacy-preserving strategy for the sharing of the EEP among MGs is designed to work with the mechanism of the distributed algorithm. According to the security analysis, the EEP can be delivered in a cooperative and privacy-preserving way. A case study and numerical results are given in terms of the convergence of the algorithm, the comparison of the costs and the implementation efficiency. Full article
(This article belongs to the Special Issue Smart Microgrids: Developing the Intelligent Power Grid of Tomorrow)
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Open AccessArticle The Desalination Process Driven by Wave Energy: A Challenge for the Future
Energies 2016, 9(12), 1032; doi:10.3390/en9121032
Received: 24 September 2016 / Revised: 13 November 2016 / Accepted: 25 November 2016 / Published: 7 December 2016
Cited by 14 | PDF Full-text (4544 KB) | HTML Full-text | XML Full-text
Abstract
The correlation between water and energy is currently the focus of several investigations. In particular, desalination is a technological process characterized by high energy consumption; nevertheless, desalination represents the only practicable solution in several areas, where the availability of fresh water is limited
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The correlation between water and energy is currently the focus of several investigations. In particular, desalination is a technological process characterized by high energy consumption; nevertheless, desalination represents the only practicable solution in several areas, where the availability of fresh water is limited but brackish water or seawater are present. These natural resources (energy and water) are essential for each other; energy system conversion needs water, and electrical energy is necessary for water treatment or transport. Several interesting aspects include the study of saline desalination as an answer to freshwater needs and the application of renewable energy (RE) devices to satisfy electrical energy requirement for the desalination process. A merge between renewable energy and desalination is beneficial in that it is a sustainable and challenging option for the future. This work investigates the possibility of using renewable energy sources to supply the desalination process. In particular, as a case study, we analyze the application of wave energy sources in the Sicilian context. Full article
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Open AccessArticle Experimental and Simulation Studies of Strength and Fracture Behaviors of Wind Turbine Bearing Steel Processed by High Pressure Torsion
Energies 2016, 9(12), 1033; doi:10.3390/en9121033
Received: 3 November 2016 / Revised: 30 November 2016 / Accepted: 2 December 2016 / Published: 8 December 2016
PDF Full-text (5197 KB) | HTML Full-text | XML Full-text
Abstract
White structure flaking (WSF) has been found to be one of the failure modes in bearing steels under rolling contacts through the formation of cracks associated with a microstructural change called white etching area (WEA). In the present research, the effects of the
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White structure flaking (WSF) has been found to be one of the failure modes in bearing steels under rolling contacts through the formation of cracks associated with a microstructural change called white etching area (WEA). In the present research, the effects of the high-pressure torsion (HPT) process on the microstructure and mechanical properties of an AISI 52100 alloy are studied. An annealed AISI 52100 was subjected to high-pressure torsion at room temperature under a pressure of up to ~6 GPa for up to three turns. Finite-element modeling (FEM) was used to simulate the process under high-pressure torsion and quasi-constrained conditions to reveal the material property changes occurring in HPT. Scanning electron microscopy and microhardness testing after processing were used to investigate the microstructural and mechanical property evolution of the steel. Strain induced microstructural transformations occur and affect the mechanical properties in a similar way to the well-known white etching area (WEA) found beneath the surface of wind turbine bearings. Here, HPT is used to study the feasibility of creating microstructural changes that are similar to WEA. This paper presents the preliminary results of using HPT to produce WEAs. Full article
(This article belongs to the collection Wind Turbines)
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Open AccessArticle Assessment of Renewable Sources for the Energy Consumption in Malta in the Mediterranean Sea
Energies 2016, 9(12), 1034; doi:10.3390/en9121034
Received: 24 September 2016 / Revised: 18 November 2016 / Accepted: 28 November 2016 / Published: 8 December 2016
Cited by 17 | PDF Full-text (7696 KB) | HTML Full-text | XML Full-text
Abstract
The main purpose of this paper is to analyze the energy production in the Maltese islands, focusing on the employment of renewable energies in order to increase their energy independence. The main renewable source here proposed is wave energy: thanks to a strategic
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The main purpose of this paper is to analyze the energy production in the Maltese islands, focusing on the employment of renewable energies in order to increase their energy independence. The main renewable source here proposed is wave energy: thanks to a strategic position, Malta will be able to produce electrical energy using an innovative type of Wave Energy Converter (WEC) based on the prototype of a linear generator realized by University of Palermo. The use of this new technology will be able to cut down the electrical energy production from traditional power plants and, consequently, the greenhouse gas emissions (GHG). Wave energy source and off-shore photovoltaic (PV) technology are here proposed. Particularly, the installation of 12 wave farms, for a total installed capacity of 86 MW, will generate about 9.5% of Malta’s energy requirement in 2025, while the installation of 9.6 MW of off-shore PV will generate about 0.73%. Full article
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Open AccessArticle Design and Output Performance Model of Turbodrill Blade Used in a Slim Borehole
Energies 2016, 9(12), 1035; doi:10.3390/en9121035
Received: 1 September 2016 / Revised: 10 November 2016 / Accepted: 30 November 2016 / Published: 8 December 2016
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Abstract
Small-diameter turbodrills have great potential for use in slim boreholes because of their lower cost and higher efficiency when used in geothermal energy and other underground resource applications. Multistage hydraulic components consisting of stators and rotors are key aspects of turbodrills. This study
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Small-diameter turbodrills have great potential for use in slim boreholes because of their lower cost and higher efficiency when used in geothermal energy and other underground resource applications. Multistage hydraulic components consisting of stators and rotors are key aspects of turbodrills. This study aimed to develop a suitable blade that can be used under high temperature in granite formations. First, prediction models for single- and multi-stage blades were established based on Bernoulli’s Equation. The design requirement of the blade for high-temperature geothermal drilling in granite was proposed. A Φ89 blade was developed based on the dimensionless parameter method and Bezier curve; the parameters of the blade, including its radial size, symotric parameters, and blade profiles, were input into ANASYS and CFX to establish a calculation model of the single-stage blade. The optimization of the blade structure of the small-diameter turbodrill enabled a multistage turbodrill model to be established and the turbodrill’s overall output performance to be predicted. The results demonstrate that the design can meet the turbodrill’s performance requirements and that the multistage model can effectively improve the accuracy of the prediction. Full article
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Open AccessArticle Development of Seismic Demand for Chang-Bin Offshore Wind Farm in Taiwan Strait
Energies 2016, 9(12), 1036; doi:10.3390/en9121036
Received: 13 September 2016 / Revised: 31 October 2016 / Accepted: 28 November 2016 / Published: 9 December 2016
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Abstract
Taiwan is located on the Pacific seismic belt, and the soil conditions of Taiwan’s offshore wind farms are softer than those in Europe. To ensure safety and stability of the offshore wind turbine supporting structures, it is important to assess the offshore wind
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Taiwan is located on the Pacific seismic belt, and the soil conditions of Taiwan’s offshore wind farms are softer than those in Europe. To ensure safety and stability of the offshore wind turbine supporting structures, it is important to assess the offshore wind farms seismic forces reasonably. In this paper, the relevant seismic and geological data are obtained for Chang-Bin offshore wind farm in Taiwan Strait, the probabilistic seismic hazard analysis (PSHA) is carried out, and the first uniform hazard response spectrum for Chang-Bin offshore wind farm is achieved. Compared with existing design response spectrum in the local regulation, this site-specific seismic hazard analysis has influence on the seismic force considered in the design of supporting structures and therefore affects the cost of the supporting structures. The results show that a site-specific seismic hazard analysis is required for high seismic area. The paper highlights the importance of seismic hazard analysis to assess the offshore wind farms seismic forces. The follow-up recommendations and research directions are given for Taiwan’s offshore wind turbine supporting structures under seismic force considerations. Full article
(This article belongs to the Special Issue Wind Turbine 2017)
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Open AccessArticle Shear Resistance Properties of Modified Nano-SiO2/AA/AM Copolymer Oil Displacement Agent
Energies 2016, 9(12), 1037; doi:10.3390/en9121037
Received: 7 October 2016 / Revised: 7 October 2016 / Accepted: 22 November 2016 / Published: 9 December 2016
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Abstract
To address the problem regarding poor shear resistance of commonly employed polymers for oil displacement, modified nano-SiO2/AA/AM copolymer (HPMNS) oil displacement agents were synthesized using acrylic acid (AA), acrylamide (AM), and modified nano-SiO2 of different modification degrees as raw materials.
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To address the problem regarding poor shear resistance of commonly employed polymers for oil displacement, modified nano-SiO2/AA/AM copolymer (HPMNS) oil displacement agents were synthesized using acrylic acid (AA), acrylamide (AM), and modified nano-SiO2 of different modification degrees as raw materials. HPMNS was characterized by means of infrared spectroscopy (IR), nuclear magnetic resonance (1H-NMR, 13C-NMR), dynamic/static light scattering, and scanning electron microscope. A comparative study of the shear resistance properties for partially hydrolyzed polyacrylamide (HPAM) and HPMNS was conducted. Compared to HPAM, the introduced hyperbranched structure endowed HPMNS with good shear resistance, which was quantified from the viscosity retention ratio of the polymer solutions. From the perspective of rheological property, HPMNS also showed great shear stability after shearing by a Mixing Speed Governor and porous media shear model. Furthermore, with a higher degree of modification, HPMNS-2 had better shear stability in terms of viscosity and rheological property than HPMNS-1. The phenomena were due to its lower hydrodynamic radius, weight-average molecular weight, and better flexibility of its molecular chains. In addition, upon the indoor displacement test, the resistance factor and residual resistance factor values of HPMNS-2 were higher than those of HPAM. This behavior is beneficial for increasing oil recovery. Full article
(This article belongs to the Special Issue Oil and Gas Engineering)
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Open AccessArticle The Impact of Renewable Energy Policies on the Adoption of Anaerobic Digesters with Farm-Fed Wastes in Great Britain
Energies 2016, 9(12), 1038; doi:10.3390/en9121038
Received: 23 September 2016 / Revised: 11 November 2016 / Accepted: 29 November 2016 / Published: 9 December 2016
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Abstract
This paper explores the effects of the feed-in tariff (FiT) and renewable heat incentive (RHI) schemes on the adoption of anaerobic digesters (AD), and the potential energy generation from farm-fed wastes in Great Britain. This paper adopts a linear programming model, developed in
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This paper explores the effects of the feed-in tariff (FiT) and renewable heat incentive (RHI) schemes on the adoption of anaerobic digesters (AD), and the potential energy generation from farm-fed wastes in Great Britain. This paper adopts a linear programming model, developed in the International Energy Agency (IEA) TIMES platform, aiming to quantify the degree of adoption of AD and the type of energy generation technologies that can be driven by digester biogas to reduce farm energy costs. The results show that the adoption of AD is cost-beneficial for all farms, but different rates of the FiT and RHI schemes will influence the competitiveness between the implementation of combined heat and power (CHP) systems and the utilisation of biogas to only generate heat. The choice of technology is further dependent on the electricity/heat use ratio of the farms and the energy content of the feedstock. The results show that pig farms will more readily adopt CHP, because of its relatively higher electricity-to-heat use ratio, compared to other types of farms, which will favour biogas boilers. Full article
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Open AccessCommunication Exploring Stochastic Sampling in Nuclear Data Uncertainties Assessment for Reactor Physics Applications and Validation Studies
Energies 2016, 9(12), 1039; doi:10.3390/en9121039
Received: 25 September 2016 / Revised: 25 November 2016 / Accepted: 29 November 2016 / Published: 9 December 2016
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Abstract
The quantification of uncertainties of various calculation results, caused by the uncertainties associated with the input nuclear data, is a common task in nuclear reactor physics applications. Modern computation resources and improved knowledge on nuclear data allow nowadays to significantly advance the capabilities
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The quantification of uncertainties of various calculation results, caused by the uncertainties associated with the input nuclear data, is a common task in nuclear reactor physics applications. Modern computation resources and improved knowledge on nuclear data allow nowadays to significantly advance the capabilities for practical investigations. Stochastic sampling is the method which has received recently a high momentum for its use and exploration in the domain of reactor design and safety analysis. An application of a stochastic sampling based tool towards nuclear reactor dosimetry studies is considered in the given paper with certain exemplary test evaluations. The stochastic sampling not only allows the input nuclear data uncertainties propagation through the calculations, but also an associated correlation analysis performance with no additional computation costs and for any parameters of interest can be done. Thus, an example of assessment of the Pearson correlation coefficients for several models, used in practical validation studies, is shown here. As a next step, the analysis of the obtained information is proposed for discussion, with focus on the systems similarities assessment. The benefits of the employed method and tools with respect to practical reactor dosimetry studies are consequently outlined. Full article
(This article belongs to the Special Issue Advances in Predictive Modeling of Nuclear Energy Systems)
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Open AccessArticle A Flexible Ramping Capacity Model for Generation Scheduling with High Levels of Wind Energy Penetration
Energies 2016, 9(12), 1040; doi:10.3390/en9121040
Received: 10 October 2016 / Revised: 19 November 2016 / Accepted: 5 December 2016 / Published: 11 December 2016
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Abstract
The penetration level of renewable generation has increased significantly in recent years, which has led to operational concerns associated with the system ramping capability. Here, we propose the flexible ramping capacity (FRC) model, which considers the practical ramping capability of generation resources as
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The penetration level of renewable generation has increased significantly in recent years, which has led to operational concerns associated with the system ramping capability. Here, we propose the flexible ramping capacity (FRC) model, which considers the practical ramping capability of generation resources as well as the uncertainty in net load. The FRC model also incorporates the demand curve of the ramping capacity, which represents the hourly economic value of the ramping capacity. The model is formulated mathematically using ramp constraints, which are incorporated into unit commitment (UC) and economic dispatch (ED) processes. Simulations are carried out using a 10-unit system to compare the FRC model with conventional methods. We show that the FRC method can improve reliability and reduce expected operating costs. The simulation results also show that, by using the FRC model, system reliability can be satisfied at high wind power generation levels while achieving economic efficiency. Full article
(This article belongs to the Special Issue Wind Turbine 2017)
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Open AccessArticle A Parallel Probabilistic Load Flow Method Considering Nodal Correlations
Energies 2016, 9(12), 1041; doi:10.3390/en9121041
Received: 2 November 2016 / Revised: 24 November 2016 / Accepted: 26 November 2016 / Published: 10 December 2016
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Abstract
With the introduction of more and more random factors in power systems, probabilistic load flow (PLF) has become one of the most important tasks for power system planning and operation. Cumulants-based PLF is an effective algorithm to calculate PLF in an analytical way,
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With the introduction of more and more random factors in power systems, probabilistic load flow (PLF) has become one of the most important tasks for power system planning and operation. Cumulants-based PLF is an effective algorithm to calculate PLF in an analytical way, however, the correlations among the nodal injections to the system level have rarely been studied. A novel parallel cumulants-based PLF method considering nodal correlations is proposed in this paper, which is able to deal with the correlations among all system nodes, and avoid the Jacobian matrix inversion in the traditional cumulants-based PLF as well. In addition, parallel computing is introduced to improve the efficiency of the numerical calculations. The accuracy of the proposed method is validated by numerical tests on the standard IEEE-14 system, comparing with the results from Correlation Latin hypercube sampling Monte Carlo Simulation (CLMCS) method. And the efficiency and parallel performance is proven by the tests on the modified IEEE-300, C703, N1047 systems with distributed generation (DG). Numerical simulations show that the proposed parallel cumulants-based PLF method considering nodal correlations is able to get more accurate results using less computational time and physical memory, and have higher efficiency and better parallel performance than the traditional one. Full article
(This article belongs to the Special Issue Advances in Power System Operations and Planning)
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Open AccessArticle A Novel Approach for Microgrid Protection Based upon Combined ANFIS and Hilbert Space-Based Power Setting
Energies 2016, 9(12), 1042; doi:10.3390/en9121042
Received: 20 September 2016 / Revised: 10 November 2016 / Accepted: 30 November 2016 / Published: 10 December 2016
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Abstract
Nowadays, the use of distributed generation (DG) has increased because of benefits such as increased reliability, reduced losses, improvement in the line capacity, and less environmental pollution. The protection of microgrids, which consist of generation sources, is one of the most crucial concerns
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Nowadays, the use of distributed generation (DG) has increased because of benefits such as increased reliability, reduced losses, improvement in the line capacity, and less environmental pollution. The protection of microgrids, which consist of generation sources, is one of the most crucial concerns of basic distribution operators. One of the key issues in this field is the protection of microgrids against permanent and temporary failures by improving the safety and reliability of the network. The traditional method has a number of disadvantages. The reliability and stability of a power system in a microgrid depend to a great extent on the efficiency of the protection scheme. The application of Artificial Intelligence approaches was introduced recently in the protection of distribution networks. The fault detection method depends on differential relay based on Hilbert Space-Based Power (HSBP) theory to achieve fastest primary protection. It is backed up by a total harmonic distortion (THD) detection method that takes over in case of a failure in the primary method. The backup protection would be completely independent of the main protection. This is rarely attained in practice. This paper proposes a new algorithm to improve protection performance by adaptive network-based fuzzy inference system (ANFIS). The protection can be obtained in a novel way based on this theory. An advantage of this algorithm is that the protection system operates in fewer than two cycles after the occurrence of the fault. Another advantage is that the error detection is not dependent on the selection of threshold values, and all types of internal fault can identify and show that the algorithm operates correctly for all types of faults while preventing unwanted tripping, even if the data were distorted by current transformer (CT) saturation or by data mismatches. The simulation results show that the proposed circuit can identify the faulty phase in the microgrid quickly and correctly. Full article
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Open AccessArticle Cold Storage for a Single-Family House in Italy
Energies 2016, 9(12), 1043; doi:10.3390/en9121043
Received: 13 September 2016 / Revised: 14 November 2016 / Accepted: 6 December 2016 / Published: 12 December 2016
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Abstract
This work deals with the operation, modeling, simulation, and cost evaluation of two different cold storage systems for a single-family house in Italy, that differ from one another on the cold storage material. The two materials used to perform the numerical simulations of
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This work deals with the operation, modeling, simulation, and cost evaluation of two different cold storage systems for a single-family house in Italy, that differ from one another on the cold storage material. The two materials used to perform the numerical simulations of the cold storage systems are represented by cold water and a phase change material (PCM), and the numerical simulations have been realized by means of numerical codes written in Matlab environment. The main finding of the present work is represented by the fact that, for the considered user characteristics, and under the Italian electricity tariff policy, the use of a proper designed cold storage system characterized by an effective operation strategy could represent a viable solution from an economical point of view. Full article
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Open AccessArticle Modeling and Mitigation for High Frequency Switching Transients Due to Energization in Offshore Wind Farms
Energies 2016, 9(12), 1044; doi:10.3390/en9121044
Received: 7 October 2016 / Revised: 1 December 2016 / Accepted: 2 December 2016 / Published: 12 December 2016
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Abstract
This paper presents a comprehensive investigation on high frequency (HF) switching transients due to energization of vacuum circuit breakers (VCBs) in offshore wind farms (OWFs). This research not only concerns the modeling of main components in collector grids of an OWF for transient
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This paper presents a comprehensive investigation on high frequency (HF) switching transients due to energization of vacuum circuit breakers (VCBs) in offshore wind farms (OWFs). This research not only concerns the modeling of main components in collector grids of an OWF for transient analysis (including VCBs, wind turbine transformers (WTTs), submarine cables), but also compares the effectiveness between several mainstream switching overvoltage (SOV) protection methods and a new mitigation method called smart choke. In order to accurately reproduce such HF switching transients considering the current chopping, dielectric strength (DS) recovery capability and HF quenching capability of VCBs, three models are developed, i.e., a user–defined VCB model, a HF transformer terminal model and a three-core (TC) frequency dependent model of submarine cables, which are validated through simulations and compared with measurements. Based on the above models and a real OWF configuration, a simulation model is built and several typical switching transient cases are investigated to analyze the switching transient process and phenomena. Subsequently, according to the characteristics of overvoltages, appropriate parameters of SOV mitigation methods are determined to improve their effectiveness. Simulation results indicate that the user–defined VCB model can satisfactorily simulate prestrikes and the proposed component models display HF characteristics, which are consistent with onsite measurement behaviors. Moreover, the employed protection methods can suppress induced SOVs, which have a steep front, a high oscillation frequency and a high amplitude, among which the smart choke presents a preferable HF damping effect. Full article
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Open AccessArticle Modeling and Forecasting Electricity Demand in Azerbaijan Using Cointegration Techniques
Energies 2016, 9(12), 1045; doi:10.3390/en9121045
Received: 31 July 2016 / Revised: 15 November 2016 / Accepted: 21 November 2016 / Published: 13 December 2016
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Abstract
Policymakers in developing and transitional economies require sound models to: (i) understand the drivers of rapidly growing energy consumption and (ii) produce forecasts of future energy demand. This paper attempts to model electricity demand in Azerbaijan and provide future forecast scenarios—as far as
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Policymakers in developing and transitional economies require sound models to: (i) understand the drivers of rapidly growing energy consumption and (ii) produce forecasts of future energy demand. This paper attempts to model electricity demand in Azerbaijan and provide future forecast scenarios—as far as we are aware this is the first such attempt for Azerbaijan using a comprehensive modelling framework. Electricity consumption increased and decreased considerably in Azerbaijan from 1995 to 2013 (the period used for the empirical analysis)—it increased on average by about 4% per annum from 1995 to 2006 but decreased by about 4½% per annum from 2006 to 2010 and increased thereafter. It is therefore vital that Azerbaijani planners and policymakers understand what drives electricity demand and be able to forecast how it will grow in order to plan for future power production. However, modeling electricity demand for such a country has many challenges. Azerbaijan is rich in energy resources, consequently GDP is heavily influenced by oil prices; hence, real non-oil GDP is employed as the activity driver in this research (unlike almost all previous aggregate energy demand studies). Moreover, electricity prices are administered rather than market driven. Therefore, different cointegration and error correction techniques are employed to estimate a number of per capita electricity demand models for Azerbaijan, which are used to produce forecast scenarios for up to 2025. The resulting estimated models (in terms of coefficients, etc.) and forecasts of electricity demand for Azerbaijan in 2025 prove to be very similar; with the Business as Usual forecast ranging from about of 19½ to 21 TWh. Full article
(This article belongs to the Special Issue Energy Time Series Forecasting)
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Open AccessArticle Experimental Study of 6LoPLC for Home Energy Management Systems
Energies 2016, 9(12), 1046; doi:10.3390/en9121046
Received: 18 October 2016 / Revised: 27 November 2016 / Accepted: 2 December 2016 / Published: 12 December 2016
Cited by 6 | PDF Full-text (1368 KB) | HTML Full-text | XML Full-text
Abstract
Ubiquitous connectivity is already transforming residential dwellings into smart homes. As citizens continue to embrace the smart home paradigm, a new generation of low-rate and low-power communication systems is required to leverage the mass market presented by energy management in homes. Although Power
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Ubiquitous connectivity is already transforming residential dwellings into smart homes. As citizens continue to embrace the smart home paradigm, a new generation of low-rate and low-power communication systems is required to leverage the mass market presented by energy management in homes. Although Power Line Communication (PLC) technology has evolved in the last decade, the adaptation of PLC for constrained networks is not fully charted. By adapting some features of IEEE 802.15.4 and IPv6 over Low-power Wireless Personal Area Network (6LoWPAN) into power lines, this paper demonstrates a low-rate, low-power PLC system over the IPv6 network (referred to as 6LoPLC), for Home Energy Management System (HEMS) applications. The overall idea is to provide a framework for assessing various scenarios that cannot be easily investigated with the limited number of evaluation hardware available. In this respect, a network model is developed in NS-3 (Version 21) to measure several important characteristics of the designed system and then validated with experimental results obtained using the Hanadu evaluation kits. Following the good agreement between the two, the NS-3 model is utilised to investigate more complex scenarios and various use-cases, such as the effects of impulsive noise, the number of nodes and packet size on the latency and Bit Error Rate (BER) performances. We further demonstrate that for different network and application configurations, optimal data sizes exist. For instance, the results reveal that in order to guarantee 99% system reliability, the HEMS application data must not exceed 64 bytes. Finally, it is shown that with impulsive noise in a HEMS network comprising 50 appliances, provided the size of the payload does not exceed 64 bytes, monitoring and control applications incur a maximum latency of 238.117 ms and 248.959 ms, respectively; both of which are within acceptable limits. Full article
(This article belongs to the Special Issue Smart Home Energy Management)
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Open AccessArticle Structural Dynamic Analysis of Semi-Submersible Floating Vertical Axis Wind Turbines
Energies 2016, 9(12), 1047; doi:10.3390/en9121047
Received: 5 August 2016 / Revised: 3 October 2016 / Accepted: 5 December 2016 / Published: 13 December 2016
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Abstract
The strong and stable wind at offshore locations and the increasing demand for energy have made the application of wind turbines in deeper water surge. A novel concept of a 5 MW baseline Floating Vertical Axis Wind Turbine (FVAWT) and a 5 MW
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The strong and stable wind at offshore locations and the increasing demand for energy have made the application of wind turbines in deeper water surge. A novel concept of a 5 MW baseline Floating Vertical Axis Wind Turbine (FVAWT) and a 5 MW optimised FVAWT with the DeepWind Darrieus rotor and the optimised DeepWind Darrieus rotor, respectively, were studied extensively. The structural responses, fatigue damages, platform global motions and mooring line dynamics of the FVAWTs were investigated comprehensively during normal operating conditions under steady wind and turbulent wind conditions, using a coupled non-linear aero-hydro-servo-elastic code (the Simo-Riflex-DMS code) which was developed by Wang et al. for modeling FVAWTs. This coupled code incorporates the models for the turbulent wind field, aerodynamics, hydrodynamics, structural dynamics, and generator controller. The simulation is performed in a fully coupled manner in time domain. The comparison of responses under different wind conditions were used to demonstrate the effect of turbulence on both FVAWTs dynamic responses. The turbulent wind condition has the advantage of reducing the 2P effects. Furthermore, comparative studies of the FVAWTs responses were undertaken to explore the advantages of adopting the optimised 5 MW DeepWind Darrieus rotor over the baseline model. The results identified the 5 MW optimised FVAWT to having: lower Fore-Aft (FA) but higher lower Side-Side (SS) bending moments of structural components; lower motions amplitude; lower short-term fatigue equivalent loads and a further reduced 2P effects. Full article
(This article belongs to the Special Issue Modeling and Simulation for Wind Turbine Loads Analysis)
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