Energies, Volume 11, Issue 11 (November 2018) – 377 articles

To study Semi-Transparent photovoltaic (STPV) windows, experiments were conducted to test the energy potential of STPV window installed in buildings. Two identical rooms were built up as experimental units; one was fitted with amorphous silicon (a-silicon) photovoltaic (PV) windows, and another was fitted with a conventional window. The interactional influence was analyzed among air conditioning energy consumption, lighting energy consumption, and energy generation. It can be concluded that STPV windows could provide 0.26 kWh/per day and save 29% on comprehensive building load on a typical sunny day. In order to further investigate, buildings installed with STPV windows in four typical cities with different climate environments in southwest China were simulated and analyzed. The cooling load of the buildings were all decreased while the heating energy consumption and lighting energy consumption were lightly increased. The energy generation of STPV windows was highest in Lhasa at 402.1 kWh/year. The energy saving potential of STPV windows was predicted with good values; 54% in Kunming. Full article

Low frequency oscillation in an interconnected power system is becoming an increasingly serious problem. It is of great practical significance to make online evaluation of actual power grid’s stability. To evaluate the stability of the power system quickly and accurately, a low frequency oscillation stability evaluation method based on an improved XGboost algorithm and power system random response data is proposed in this paper. Firstly, the original input feature set describing the dynamic characteristics of the power system is established by analyzing the substance of low frequency oscillation. Taking the random response data of power system including the disturbance end time feature and the dynamic feature of power system as the input sample set, the wavelet threshold is applied to improve its effectiveness. Secondly, using the eigenvalue analysis method, different damping ratios are selected as threshold values to judge the stability of the system low-frequency oscillation. Then, the supervised training with improved XGboost algorithm is performed on the characteristics of stability. On this basis, the training model is obtained and applied to online low frequency oscillation stability evaluation of a power system. Finally, the simulation results of the eight-machine 36-node test system and Hebei southern power grid show that the proposed low frequency oscillation online evaluation method has the features of high evaluation accuracy, fast evaluation speed, low error rate of unstable sample evaluation, and strong anti-noise ability. Full article

Due to the complicated circuit topology and high switching frequency, field-programmable gate arrays (FPGA) can stand up to the challenges for the hardware in the loop (HIL) real-time simulation of power electronics converters. The Associated Discrete Circuit (ADC) modeling method, which has a fixed admittance matrix, greatly reduces the computation cost for FPGA. However, the oscillations introduced by the switch-equivalent model reduces the simulation accuracy. In this paper, firstly, a novel algorithm is proposed to determine the optimal discrete-time switch admittance parameter, Gs, which is obtained by minimizing the switching loss. Secondly, the FPGA resource optimization method, in which the simulation time step, bit-length, and model precision are taken into consideration, is presented when the power electronics converter is implemented in FPGA. Finally, the above method is validated on the topology of a three-phase inverter with LC filters. The HIL simulation and practicality experiments verify the effect of FPGA resource optimization and the validity of the ADC modeling method, respectively. Full article

The effective operation of machinery in agricultural processes is crucial in terms of energy efficiency, economic consequences, and environmental footprint. The agricultural sector provides many opportunities to bring biomass to the market. An interesting option is to collect the branches after a regular pruning of apple orchards in the winter-spring season. As the harvesting of pruning residues in apple orchards for energy purposes demands additional primary energy, any measures that increase the amount of collected biomass are desirable. In this study, the influence of pruning harvesting using a baler with and without windrowers on pruning biomass yield, energy input and output flow, energy balance, CO₂ emission reduction, and costs of that operation in apple orchards was investigated. The performed analysis, based on the results from two apple orchards, revealed that the energy balance was positive for both variants. However, in comparison with the harvesting process without windrowers, the use of windrowers in these two orchards caused an increase in pruning biomass yield by 0.45 tDM·ha⁻¹ per year (25%) and 0.54 tDM·ha⁻¹ per year (33%), respectively. The energy balance increased up by ca. 0.8–1.0 GJ·ha⁻¹, although the fuel consumption by the tractor was higher. The use of windrowers did not significantly increase the costs, but resulted in remarkably better income from biomass selling (ca. €30–40 ha⁻¹). Finally, the increase in the mass of harvested biomass led to a higher potential CO₂ emission reduction. As a result, pruning biomass is an attractive source of energy, especially for local markets. Full article

A numerical study of ferromagnetic-fluid flow and heat transfer in a square porous cavity under the effect of a magnetic field is presented. The water-magnetic particle suspension is treated as a miscible mixture and, thus, the magnetization, density and viscosity of the ferrofluid are obtained. The governing partial-differential equations were solved numerically using the cell-centered finite-difference method for the spatial discretization, while the multiscale time-splitting implicit method was developed to treat the temporal discretization. The Courant–Friedrichs–Lewy stability condition (CFL < 1) was used to make the scheme adaptive by dividing time steps as needed. Two cases corresponding to Dirichlet and Neumann boundary conditions were considered. The efficiency of the developed algorithm as well as some physical results such as temperature, concentration, and pressure; and the local Nusselt and Sherwood numbers at the cavity walls are presented and discussed. It was noticed that the particle concentration and local heat/mass transfer rate are related to the magnetic field strength, and both pressure and velocity increase as the strength of the magnetic was increased. Full article

The doubly-fed induction generator (DFIG) wind turbine system, which is composed of the wind turbine, generator, rotor-side converter, grid-side converter, and so on, is a typical multi-time scale system. The dynamic processes at different time scales do not exist in isolation. Furthermore, neglecting the coupling of parameters of different time scales to reduce the order of the model will lead to deviation between the simulation results and the actual results, which may not be suitable for power system transient analysis. This paper proposes an electromechanical transient model and an electromagnetic transient model of the DFIG wind turbine system that consider the interaction of multiple time-scale dynamic processes. Firstly, the paper applies the modal analysis method to explain the multi-time scale characteristics of the DFIG wind turbine system. Secondly, the variation in the eigenvalues of the DFIG wind turbine system before and after the order reduction and the coupling between variables and the system, as well as the coupling between variables of different time scales, are analyzed to obtain the preliminary 21-order simplified model. Thirdly, considering the weak coupling characteristics between the mechanical part and the electromagnetic part of the DFIG wind turbine system, the 21-order simplified model is decomposed into a 15-order electromagnetic transient model and a six-order electromechanical transient model on the basis of their time scales. Then, according to the balance between simulation time and simulation accuracy, the 14-order electromagnetic transient model and the 10 or 12-order electromechanical transient model are finally obtained. Finally, the rationality of the simplified models is verified by simulations under two large disturbance conditions, namely wind speed abrupt change and voltage sag. The obtained simplified models have reference significance for improving the simulation speed of a wind power grid-connected system and analyzing the internal mechanism of the DFIG wind turbine system’s stability. Full article

In this work, for the first time, the feasibility of obtaining carbonized refuse-derived fuel (CRDF) pelletization from municipal solid waste (MSW) was shown. Production of CRDF by torrefaction of MSW could be the future of recycling technology. The objective was to determine the applied pressure needed to produce CRDF pellets with compressive strength (CS) comparable to conventional biomass pellets. Also, the hypothesis that a binder (water glass (WG)) applied to CRDF as a coating can improve CS was tested. The pelletizing was based on the lab-scale production of CRDF pellets with pressure ranging from 8.5 MPa to 76.2 MPa. The resulting CS pellets increased from 0.06 MPa to 3.44 MPa with applied pelletizing pressure up to the threshold of 50.8 MPa, above which it did not significantly improve (p < 0.05). It was found that the addition of 10% WG to 50.8 MPa CRDF pellets or coating them with WG did not significantly improve the CS (p < 0.05). It was possible to produce durable pellets from CRDF. The CS was comparable to pine pellets. This research advances the concept of energy recovery from MSW, particularly by providing practical information on densification of CRDF originating from the torrefaction of the flammable fraction of MSW–refuse-derived fuel. Modification of CRDF through pelletization is proposed as preparation of lower volume fuel with projected lower costs of its storage and transportation and for a wider adoption of this technology. Full article

Climate change is one of the great challenges of our times. In the search for renewable energy sources, wastewater has received increasing attention in recent years. This is due to the fact that it can serve as a source of electricity and heat supply, as well as a substitute for natural gas. The current literature frequently addresses more technical aspects from a mostly sanitary engineering-orientated perspective. Social aspects related to the energetic use of wastewater still appear to be underrepresented. To support the closure of existing knowledge gaps and to contribute to the development in this field, this article addresses two issues: it defines and characterises key stakeholder groups required to catalyse broader energetic usage of wastewater, and it proposes a participatory approach to support successfully establishing wastewater as a commonly accepted source of renewable energy to best support the ongoing energy transition. Full article

The abundance of solar energy is a blessing in the Arabian Peninsula, where more than 2000 kWh/m² density has been recorded annually. This has resulted in sincere consideration of PV harvesting in the energy matrix and smart grid. However, artefacts such as degradation of PV efficiency due to the high temperature effect have to be addressed. This paper presents a novel design of a PV cooling system using water to mitigate the effect of high temperature. Several experiments have been conducted, and the results have been analyzed. It has been found that the collected water from the panel after 40 min of cooling gained a temperature of 10 °C approximately, during December 2016. Eventually, the efficiency was improved by 10.35% (without using MPPT) using water at ambient temperature (24 °C) compared to the non-cooled panel. Moreover, the temperature of the panel during solar peak hours dropped from 64.3 °C to 32 °C and from 59 °C to 27 °C in 3 min for the back and front surface, respectively. These results, which are the first of their kind in Qatar, constitute good incentives and pave the way for further investigation to enhance PV efficiency in harsh environments. This would be of paramount significance, especially for scaling up PV deployment, as is planned in Qatar and GCC countries in their 2030 vision. Full article

A two-step structural optimization method was proposed to select the transition section of a composite bucket foundation (CBF). In the first step, based on the variable density method, a solid isotropic microstructures with penalization (SIMP) interpolation model was established under specific load conditions and boundary conditions. The solution of force transmission path and the topology of the transition section in six forms (e.g., linear, arc-shaped, linear thin-walled, and arc-shaped thin-walled) were optimized. Afterwards, finite element software ABAQUS was used to verify this model. Results show that the utilization rate of the arc-shaped thin-walled structure was the largest, and its basic transmission force was more straightforward together with smaller cross-section size at the same height and smaller influence on spoiler flow. In the second step, the detailed optimization of CBF was carried out using mathematical programming. Under the premise of minimum total construction cost, the body shape parameters of each part were set as design variables satisfying the corresponding strength, stiffness, and stability conditions; meanwhile, the minimum total structure weight was set as the objective function. MATLAB was used to solve the sequence quadratic programming (SQP) algorithm and hybrid genetic algorithm, and the optimal body parameters were obtained. Full article

Pillars play a critical role in an underground mine, as an inadequate pillar design could lead to pillar failure, which may result in catastrophic damage, while an over-designed pillar would lead to ore loss, causing economic loss. Pillar design is dictated by the inclination of the ore body. Depending on the orientation of the pillars, loading can be axial (compression) in horizontal pillars and oblique (compression as well as shear loading) in inclined pillars. Empirical and numerical approaches are the two most commonly used methods for pillar design. Current empirical approaches are mostly based on horizontal pillars, and the inclination of the pillars in the dataset is not taken into consideration. Laboratory and numerical studies were conducted with different width-to-height ratios and at different inclinations to understand the reduction in strength due to inclined loading and to observe the failure mechanisms. The specimens’ strength reduced consistently over all the width-to-height ratios at a given inclination. The strength reduction factors for gypsum were found to be 0.78 and 0.56, and for sandstone were 0.71 and 0.43 at 10° and 20° inclinations, respectively. The strength reduction factors from numerical models were found to be 0.94 for 10° inclination, 0.87 for 20° inclination, 0.78 for 30° inclination, and 0.67 for 40° inclination, and a fitting equation was proposed for the strength reduction factor with respect to inclination. The achieved results could be used at preliminary design stages and can be verified during real mining practice. Full article

Steady-state, transient, as well as dynamic analyses of self-excited induction generators (SEIGs) are generally well-documented. However, in most of the documented studies, core losses have been neglected or inaccurately modeled. This paper is concerned with the accurate modeling of core losses in SEIG analysis. The core loss is presented as a function related to the level of saturation. This relation is determined experimentally and integrated into a nonlinear model of the SEIG. The nonlinear model is solved using a mathematical optimization scheme to obtain the performance parameters of the SEIG. A new set of curves describing accurate behavior of the SEIG parameters is produced and presented in this paper. The computed parameters of the model are validated experimentally, and the agreement attained demonstrates the functionality and accuracy of the proposed core-loss model. Full article

A more accurate hourly prediction of day-ahead wind power can effectively reduce the uncertainty of wind power integration and improve the competitiveness of wind power in power auction markets. However, due to the inherent stochastic and intermittent nature of wind energy, it is very difficult to sharply improve the multi-step wind power forecasting (WPF) accuracy. According to theory of direct and recursive multi-step prediction, this study firstly proposes the models of R (recursive)-VMD (variational model decomposition)-LSTM (long short-term memory) and D (direct)-VMD-LSTM for the hourly forecast of day-ahead wind power by using a combination of a novel and in-depth neural network forecasting model called LSTM and the variational model decomposition (VMD) technique. The data from these model tests were obtained from two real-world wind power series from a wind farm located in Henan, China. The experimental results show that LSTM can achieve more precise predictions than traditional neural networks, and that VMD has a good self-adaptive ability to remove the stochastic volatility and retain more adequate data information than empirical mode decomposition (EMD). Secondly, the R-VMD-LSTM and D-VMD-LSTM are comparatively studied to analyze the accuracy of each step. The results verify the effectiveness of the combination of the two models: The R-VMD-LSTM model provides a more accurate prediction at the beginning of a day, while the D-VMD-LSTM model provides a more accurate prediction at the end of a day. Full article

Hydrochar is a very interesting product from agricultural and food production residues. Unfortunately, severe conditions for complete conversion of lignocellulosic biomass is necessary, especially compared to the conversion of sugar compounds. The goal of this work is to improve the conversion of internal carbohydrates by application of a two-steps process, by acid addition and slightly higher water content. A set of experiments at different temperatures (180, 200, and 220 °C), reaction times (2 and 4 h), and moisture contents (80% and 90%) was performed to characterize the solid (high heating value (HHV), elemental) and liquid product phase. Afterwards, acid addition for a catalyzed hydrolysis reaction during hydrothermal carbonization (HTC) and a two-steps reaction (180 and 220 °C) were tested. As expected, a higher temperature leads to higher C content of the hydrochar and a higher fixed carbon (FC) content. The same effect was found with the addition of acids at lower temperatures. In the two-steps reaction, a primary hydrolysis step increases the conversion of internal carbohydrates. Higher water content has no significant effect, except for increasing the solubility of ash components. Full article

The goal of this work is to understand the gasification process for Miscanthus briquettes in a double-stage downdraft gasifier, and the impact of different Equivalence Ratios (ER) on syngas, biochar, and tar characteristics. The optimal ER was found to be 0.35, which yielded a syngas maximum heating value of 5.5 MJ/Nm³ with a syngas composition of 20.29% CO, 18.68% H₂, and 0.86% CH₄. To better understand the observed behavior, an equilibrium reaction model was created and validated using the experimental data. The model showed that the heating value decreased with increasing ER, and that hydrogen production peaked at ER = 0.37, while methane (CH₄) became negligible above ER = 0.42. Tar and particle content in the gas produced at a certain temperature can now be predicted. To assess the biochar characteristics, surface structure image analysis and a surface area porosity analysis were carried out. Employing images from a scanning electron microscope (SEM), the biochar cell bonds and pore structures were examined and analyzed. By using the Brunauer-Emmett-Teller (BET) analysis of the surface porosity, the surface area to be 186.06 m²/g and the micro pore volume was calculated to be 0.07 m³/g. The final aspect of the analysis involved an evaluation of tar production. Combining current and prior data showed a logarithmic relationship between the amount of tar produced and the gasifier bed temperature, where the amount of tar produced decreased with increasing bed temperature. This results in very low tar levels, which is one of the known advantages for a double-stage downdraft gasifier over a single-stage system. Full article

This editorial summarizes the performance of the special issue entitled Data Science and Big Data in Energy Forecasting, which was published at MDPI’s Energies journal. The special issue took place in 2017 and accepted a total of 13 papers from 7 different countries. Electrical, solar and wind energy forecasting were the most analyzed topics, introducing new methods with applications of utmost relevance. Full article

In this paper the effect of saturation on torque production of a reluctance synchronous motor (RSM), which was originally built as an induction motor (IM), is investigated. The rotor was replaced with new one, designed as synchronous reluctance cageless rotor with barriers, the shape and number of which were optimized to maximize the reluctance ratio. The torque measurement was done while the RSM was fed by frequency converter controlled by a microcontroller with closed loop field oriented control strategy to find out how saturation effects the developed torque at various values of the currents and speeds. It is shown how the load angle at which the maximum torque was achieved is changed. It was found out that the load angle was shifted to higher values depending on the speed of operation. Full article

This article analyses the influence of supporting scheme variants on the profitability of a projected investment of residential photovoltaic systems. The focus of the paper lies in evaluating the feasibility for the power system of solar power generation technologies to achieve a balance between energy generation and support costs in a more efficient way. The case study is based on a year-long time series of examples with an hourly resolution of electricity prices from the Nord Pool power market, in addition to the power demand and solar generation of Latvian prosumers. Electric energy generation and the consumption of big data from more than 100 clients were collected. Based on these data, we predict the processes for the next 25 years, and we estimate economic indicators using a detailed description of the net metering billing system and the Monte-Carlo method. A recommendation to change the current net system to a superior one, taking into account the market cost of energy, concludes the paper. Full article

The interaction between the gird and wind farms has significant impact on the power grid, therefore prediction of the interaction between gird and wind farms is of great significance. In this paper, a wind turbine-gird interaction prediction model based on long short term memory (LSTM) network under the TensorFlow framework is presented. First, the multivariate time series was screened by principal component analysis (PCA) to reduce the data dimensionality. Secondly, the LSTM network is used to model the nonlinear relationship between the selected sequence of wind turbine network interactions and the actual output sequence of the wind farms, it is proved that it has higher accuracy and applicability by comparison with single LSTM model, Autoregressive Integrated Moving Average (ARIMA) model and Back Propagation Neural Network (BPNN) model, the Mean Absolute Percentage Error (MAPE) is 0.617%, 0.703%, 1.397% and 3.127%, respectively. Finally, the Prony algorithm was used to analyze the predicted data of the wind turbine-grid interactions. Based on the actual data, it is found that the oscillation frequencies of the predicted data from PCA-LSTM model are basically the same as the oscillation frequencies of the actual data, thus the feasibility of the model proposed for analyzing interaction between grid and wind turbines is verified. Full article

This study designs an active equilibrium control strategy based on model predictive control (MPC) for series battery packs. To shorten equalisation time and reduce unnecessary energy consumption, bidirectional active equalisation is modelled and analysed, and the model predictive control algorithm is then applied to the established state space equation. The optimisation problem that minimises the equilibrium time is transformed to a linear programming form in each cycle. By solving the linear programming problem online, a group of control optimal solutions is found and the series equalisation problem is decoupled. The equalisation time is shortened by dynamically adjusting the equalisation current. Simulation results show that the MPC algorithm can avoid unnecessary energy transfer and shorten equalisation time. The bench experimental result shows that the equilibrium time is reduced by 31%, verifying the rationality of the MPC strategy. Full article

Cogging torque is a pulsating, parasitic, and undesired torque ripple intrinsic of the design of a permanent magnet synchronous generator (PMSG), which should be minimized due to its adverse effects: vibration and noise. In addition, as aerodynamic power is low during start-up at low wind speeds in small wind energy systems, the cogging torque must be as low as possible to achieve a low cut-in speed. A novel mitigation technique using compound pre-slotting, based on a combination of magnetic and non-magnetic materials, is investigated. The finite element technique is used to calculate the cogging torque of a real PMSG design for a small wind turbine, with and without using compound pre-slotting. The results show that cogging torque can be reduced by a factor of 48% with this technique, while avoiding the main drawback of the conventional closed slot technique: the reduction of induced voltage due to leakage flux between stator teeth. Furthermore, through a combination of pre-slotting and other cogging torque optimization techniques, cogging torque can be reduced by 84% for a given design. Full article

Energy and life cycle cost analysis were employed to identify the most-cost effective ground envelope design for a greenhouse that employs supplemental lighting located in Ottawa, Ontario, Canada (45.4° N). The envelope design alternatives that were investigated consist of installing insulation vertically around the perimeter and horizontally beneath the footprint of a greenhouse with a concrete slab and unfinished soil floor. Detailed thermal interaction between the greenhouse and the ground surface is achieved by considering 3-dimensional conduction heat transfer within the TRNSYS 17.2 simulation software. The portion of total heat loss that occurred through the ground was approximately 4% and permutations in ground insulation design reduced heating energy consumption by up to 1%. For the two floor designs, the highest net savings was achieved when perimeter and floor zone horizontal insulation was installed whereas a financial loss occurred when it was also placed beneath the crop zone. However, in all cases, the improvement in economic performance was small (net savings below $4000 and reduction in life cycle under 0.2%). Combined energy and life cycle cost analysis is valuable for selecting optimal envelope designs that are capable of lowering energy consumption, improving economics and enhancing greenhouse durability. Full article

Renewable energy technologies (RETs) are crucial for solving the world’s energy dilemma. However, the diffusion rate of RETs is still dissatisfactory. One critical reason is that conventional energy technologies (CETs) are dominating energy markets. Emergent technologies that have inferior initial performance but eventually become new dominators of markets are frequently observed in various industries, which can be explained with the disruptive innovation theory (DIT). DIT suggests that instead of competing with incumbent technologies in the dominated dimension, redefining the competition on a two-dimensional basis is wise. Aiming at applying DIT to RET diffusion, this research builds an agent-based model (ABM) considering the order of entering the market, price, preference changing and RET improvement rate to simulate the competition dynamics between RETs and CETs. The findings include that the order of entering the market is crucial for a technology’s success; disruptive innovation is an effective approach to cope with the disadvantage of RETs as latecomers; generally, lower price, higher consistency with consumers’ preferences and higher improvement rate in the conventional dimension are beneficial to RET diffusion; counter-intuitively, increasing RET’s improvement rate in the conventional dimension is beneficial to RET diffusion when the network is sparse; while it is harmful when the network is densified. Full article

In this paper, an intelligent control strategy for DC/DC converters is proposed. The converter connects two DC busses, a high-voltage and a low-voltage bus. The control scheme is composed by a two-layer architecture, a low-level control based on the concept of sliding manifold, and high gain control, and a high-level control used to guarantee the achievement of various objectives. The proposed control strategies are based on solid mathematical arguments, with stability proofs for the non-linear case, and decision trees for parameter selection. The paper results are analyzed and discussed by using simulation at different detail levels in MATLAB/Stateflow/PowerSystem, and validated by experimental results, also considering MIL standard performance indices. Full article

The high current ripple and torque ripple are the main drawbacks of the switched reluctance motor (SRM) since the nonlinearity and double saliency, which limits its applications. In order to eliminate the current variation and torque ripple, an optimized pulse width modulation (PWM) control is presented in this paper. The voltage ratio duty is able to be predicted precisely according to the information of the motor running parameter. Based on torque sharing functions (TSFs), the current profile is pre-computed and four regions are defined according to the reference current profiles. The three modes, excitation, demagnetization and freewheeling, are flexibly chosen according to the characteristic of the current profile. It is indicated that it is better than that of conventional PWM modulation in terms of current ripple and the current tracing performance is improved without increasing the switching frequency or changing the hysteresis band. The current ripple is defined as the peak-to-peak value dividing the average value and it is reduced by 40%. A comparison in terms of the torque ripple and copper loss is also carried out: the torque ripple is significantly reduced via the proposed scheme under both magnetic linear and saturation conditions. The torque ripple and copper loss are reduced by about 70% and 12%, respectively. The validity and effectiveness of the proposed control strategy is verified by simulation and experimental results. Full article

Ridesharing is becoming popular in many cities in China where transportation alternatives are easily accessible. Individuals typically access services by smartphone app developed by ridesharing company to join a trip offered by other private vehicle’s drivers who share same or geographically close destination. However, there are some internal differences within this region indicating the service heterogeneity of ridesharing. In order to discover this regional heterogeneity, this paper chooses Beijing–Tianjin–Hebei (BTH) region as research target and uses BTH regional ridesharing data provided by DiDi Chuxing Company. Then, this paper conducts an in-depth study by summarizing the travel pattern characteristics and evaluating the environmental impacts that result from individuals participating in ridesharing services. Lifecycle analysis of fuel and environmental input–output are applied to estimate the direct and indirect environmental impact separately. The results reveal heterogeneous spatial heterogeneous of ridesharing, including travel pattern and environmental influence caused by service demand and supply, which results from the unbalance of regional development and infrastructure construction condition of the transportation system, and other travel behavior differences. Full article

Dent is a common form of defect on oil and gas pipeline. Some dents will undergo elastic or plastic recovery due to changes in internal pressure, also known as springback. To analyze the springback law of an API X60 pipeline with a dent defect, the secondary development technology of finite element software ABAQUS was used for parametric modeling of a dented pipeline. Using this model, the effects of various factors (wall thickness, internal pressure, indenter size, dent location, and dent depth) on the springback coefficient of a dented pipeline were analyzed. The significance of each factor was analyzed by combining an orthogonal experimental design with the Grey correlation degree. Finally, nonlinear regression analysis was used to obtain formulas for the springback coefficient as a function of the influential factors. The results show that the springback coefficient of the dented pipeline after pressurization was between 0.15 and 0.65, and the factor that had the largest effect on the springback coefficient was the dent location. The springback coefficient of the dented pipeline after de-pressurization was between 1.1 and 1.5, and the factor that had the largest effect on the springback coefficient was the internal pressure. The formulas that relate the springback coefficient and various influential factors can be used as a reference for estimating the springback of dented pipelines. Full article

A micro hydropower plant of the run-of-river type is considered to be the most cost-effective investment in developing counties. This paper presents a novel methodology to improve flow estimation, without using the flow direction curve (FDC) method, to determine the turbine type and size to operate consistently. A higher precision is obtained through the use of seasonal flow occurrence data, irrigation variability, and fitting the best probability distribution function (PDF) using flow data. Flow data are grouped in classes based on the flow rate range. This method will need a larger dataset but it is reduced to a tractable amount by using the PDF. In the first part of the algorithm, the average flow of each range is used to select the turbine type. The second part of the algorithm determines the optimal size of the turbine type in a more accurate way, based on minimum and maximum flow rates in each class range instead of the average flow rate. A newly developed micro hydropower plant was installed and used for validation at Baan Khun Pae, Chiang Mai Province. It was found, over four years of observation from 2014–2018, that the plant capacity factor was 82%. Full article

Electrical modelling of rail tracks with multiple running trains is complex due to the difficulties in solving the power flow. The train positions, speed and acceleration are constantly varying resulting in a nonlinear system. In this work, a method is proposed for modelling DC electric railways to support power flow analysis of a simulated metro train service. The method exploits the MathWorks simulation tool Simscape, using it to model the mechanical and electrical characteristics of the rail track system. The model can be simulated to provide voltages at any position in the track and additionally, the voltages seen by any train. The model includes regenerative braking on trains, this is demonstrated to cause overvoltage in the feeding line if it is higher than the power demand of the other trains at that time. Braking resistors are used to protect the network from overvoltage by burning the excess energy. Through the implementation of Energy Storage Systems (ESSs), it will be possible to improve the energy efficiency and remove timetabling restrictions of electric railways by effectively controlling the rail track voltage. The paper proposes several methods to validate the model. Full article

In lieu of reliable scaling rules, hydraulic pump and motor manufacturers pay a high monetary and temporal price for attempting to expand their production lines by scaling their existing units to other sizes. The challenge is that the lubricating interfaces, which are the key elements in determining the performance of a positive displacement machine, are not easily scalable. This article includes an analysis of the size-dependence of these units with regard to the significant physical phenomena describing the behavior of their three most critical lubricating interfaces. These phenomena include the non-isothermal elastohydrodynamic effects in the fluid domain, and the heat transfer and thermal elastic deflection in the solid domain. The performance change due to size variation is found to be unavoidable and explained through fundamental physics. The results are demonstrated using a numerical fluid–structure–thermal interaction model over a wide range of unit sizes. Based on the findings, a guide to scaling swashplate-type axial piston machines such as to uphold their efficiency is proposed. Full article