Journal Description
Energies
Energies
is a peer-reviewed, open access journal of related scientific research, technology development, engineering policy, and management studies related to the general field of energy, from technologies of energy supply, conversion, dispatch, and final use to the physical and chemical processes behind such technologies. Energies is published semimonthly online by MDPI. The European Biomass Industry Association (EUBIA), Association of European Renewable Energy Research Centres (EUREC), Institute of Energy and Fuel Processing Technology (ITPE), International Society for Porous Media (InterPore), CYTED and others are affiliated with Energies and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, RePEc, Inspec, CAPlus / SciFinder, and other databases.
- Journal Rank: CiteScore - Q1 (Engineering (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.1 days after submission; acceptance to publication is undertaken in 3.3 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Sections: published in 41 topical sections.
- Testimonials: See what our editors and authors say about Energies.
- Companion journals for Energies include: Fuels, Gases, Nanoenergy Advances and Solar.
Impact Factor:
3.2 (2022);
5-Year Impact Factor:
3.3 (2022)
Latest Articles
Design of an Axial-Type Magnetic Gear with Auxiliary Flux-Enhancing Structure
Energies 2024, 17(9), 2207; https://doi.org/10.3390/en17092207 - 03 May 2024
Abstract
In this paper, a new axial-type magnetic gear with an auxiliary flux-enhancing structure (AFS-AMG) is proposed. Compared to conventional AMGs, it has a higher torque density and higher permanent magnet (PM) utilization factor. Firstly, the design rules and operating principles of the proposed
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In this paper, a new axial-type magnetic gear with an auxiliary flux-enhancing structure (AFS-AMG) is proposed. Compared to conventional AMGs, it has a higher torque density and higher permanent magnet (PM) utilization factor. Firstly, the design rules and operating principles of the proposed AFS-AMG are elaborated. Then, the mapping relation between the radial-type magnetic gears (RMGs) and AMGs are elucidated. Compared to its counterparts in RMGs, the AFS-AMG achieves a small size. Then, the geometrical parameters of the AFS-AMG are optimized to obtain better electromagnetic performance, where the torque density per volume and per PM volume is adopted as the evaluation standard. Finally, three different AMG topologies are constructed in finite element analysis (FEA) software for comparison. It is proven that the AFS-AMG has the largest torque density per volume and per PM volume.
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Open AccessArticle
Prospective Life Cycle Assessment of Biological Methanation in a Trickle-Bed Pilot Plant and a Potential Scale-Up
by
Michael Heberl, Christian Withelm, Anja Kaul, Daniel Rank and Michael Sterner
Energies 2024, 17(9), 2206; https://doi.org/10.3390/en17092206 - 03 May 2024
Abstract
The fluctuating nature of renewable energies results in the need for sustainable storage technologies to defossilize the energy system without other negative consequences for humans and the environment. In this study, a pilot-scale trickle-bed reactor for biological methanation and various scale-up scenarios for
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The fluctuating nature of renewable energies results in the need for sustainable storage technologies to defossilize the energy system without other negative consequences for humans and the environment. In this study, a pilot-scale trickle-bed reactor for biological methanation and various scale-up scenarios for 2024 and 2050 were investigated using life cycle assessment. A best- and worst-case scenario for technology development until 2050 was evolved using cross-consistency analysis and a morphological field, based on which the data for the ecological models were determined. The results show that the plant scale-up has a very positive effect on the ecological consequences of methanation. In the best-case scenario, the values are a factor of 23–780 lower than those of the actual plant today. A hot-spot analysis showed that electrolysis operation has an especially large impact on total emissions. The final Monte Carlo simulation shows that the technology is likely to achieve a low global warming potential with a median of 104.0 kg CO2-eq/MWh CH4 and thus can contribute to decarbonization.
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(This article belongs to the Topic Sustainable Energy Technology, 2nd Volume)
Open AccessArticle
Experimental Characterization of Commercial Scroll Expander for Micro-Scale Solar ORC Application: Part 1
by
Maurizio De Lucia, Giacomo Pierucci, Maria Manieri, Gianmarco Agostini, Emanuele Giusti, Michele Salvestroni, Francesco Taddei, Filippo Cottone and Federico Fagioli
Energies 2024, 17(9), 2205; https://doi.org/10.3390/en17092205 - 03 May 2024
Abstract
In order to reduce greenhouse gas emissions and achieve global decarbonisation, it is essential to find sustainable and renewable alternatives for electricity production. In this context, the development of distributed generation systems, with the use of thermodynamic and photovoltaic solar energy, wind energy
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In order to reduce greenhouse gas emissions and achieve global decarbonisation, it is essential to find sustainable and renewable alternatives for electricity production. In this context, the development of distributed generation systems, with the use of thermodynamic and photovoltaic solar energy, wind energy and smart grids, is fundamental. ORC power plants are the most appropriate systems for low-grade thermal energy recovery and power conversion, combining solar energy with electricity production. The application of a micro-scale ORC plant, coupled with Parabolic Trough Collectors as a thermal source, can satisfy domestic user demand in terms of electrical and thermal power. In order to develop a micro-scale ORC plant, a commercial hermetic scroll compressor was tested as an expander with HFC-245fa working fluid. The tests required the construction of an experimental bench with monitoring and control sensors. The aim of this study is the description of the scroll performances to evaluate the application and develop optimization strategies. The maximum isentropic effectiveness is reached for an expansion ratio close to the volumetric expansion ratio of the scroll, and machine isentropic effectiveness presents small variations in a wide range of working conditions. The filling factor is always higher than one, due to leakage in the mechanical seals of the scroll or other inefficiencies. This study demonstrates that using a commercial scroll compressor as an expander within an ORC system represents a valid option for such applications, but it is necessary to improve the mechanical seals of the machine and utilize a dedicated control strategy to obtain the maximum isentropic effectiveness.
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(This article belongs to the Special Issue Advanced Solar Technologies and Thermal Energy Storage)
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Analysis, Design and Effectuation of a Tapped Inductor Current Converter with Fractional Output for Current Source Systems
by
Jie Mei, Ka Wai Eric Cheng and Teke Hua
Energies 2024, 17(9), 2204; https://doi.org/10.3390/en17092204 - 03 May 2024
Abstract
This article proposes a new connection method of tapped inductors that works in the current source, which enables the current-mode power converter circuit to have a new topological relationship. Usually, in a switched-inductor circuit, a stable output multiple is obtained through the connection
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This article proposes a new connection method of tapped inductors that works in the current source, which enables the current-mode power converter circuit to have a new topological relationship. Usually, in a switched-inductor circuit, a stable output multiple is obtained through the connection of the inductor and the switching devices. This is because the tapped point on the inductor varies, and the magnetomotive force (mmf) of inductance is adjusted. Thereby, the output current is controlled by the states of switching devices within a certain range. This optimized circuit structure can adjust the output current according to load changes in practical applications without changing the input power supply. The proposed method has been verified for its feasibility through detailed analysis and hardware work. The principal analysis based on the flux linkage and the PSIM simulation confirms that the theoretical circuit can be implemented. Finally, a hardware circuit is built to obtain real and feasible conclusions, and it is verified that the circuit can achieve a stable output and variable current within a specific range. The proposed work presents an alternative power conversion methodology using the active switching of mmf, and it is a stable and simple power conversion technique.
Full article
(This article belongs to the Section F3: Power Electronics)
Open AccessArticle
Machine Learning and Weather Model Combination for PV Production Forecasting
by
Amedeo Buonanno, Giampaolo Caputo, Irena Balog, Salvatore Fabozzi, Giovanna Adinolfi, Francesco Pascarella, Gianni Leanza, Giorgio Graditi and Maria Valenti
Energies 2024, 17(9), 2203; https://doi.org/10.3390/en17092203 - 03 May 2024
Abstract
Accurate predictions of photovoltaic generation are essential for effectively managing power system resources, particularly in the face of high variability in solar radiation. This is especially crucial in microgrids and grids, where the proper operation of generation, load, and storage resources is necessary
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Accurate predictions of photovoltaic generation are essential for effectively managing power system resources, particularly in the face of high variability in solar radiation. This is especially crucial in microgrids and grids, where the proper operation of generation, load, and storage resources is necessary to avoid grid imbalance conditions. Therefore, the availability of reliable prediction models is of utmost importance. Authors address this issue investigating the potential benefits of a machine learning approach in combination with photovoltaic power forecasts generated using weather models. Several machine learning methods have been tested for the combined approach (linear model, Long Short-Term Memory, eXtreme Gradient Boosting, and the Light Gradient Boosting Machine). Among them, the linear models were demonstrated to be the most effective with at least an RMSE improvement of 3.7% in photovoltaic production forecasting, with respect to two numerical weather prediction based baseline methods. The conducted analysis shows how machine learning models can be used to refine the prediction of an already established PV generation forecast model and highlights the efficacy of linear models, even in a low-data regime as in the case of recently established plants.
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(This article belongs to the Special Issue Climate Changes and the Impacts on Power and Energy Systems)
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Open AccessArticle
Regression Modeling of Daily PM2.5 Concentrations with a Multilayer Perceptron
by
Szymon Hoffman, Rafał Jasiński and Janusz Baran
Energies 2024, 17(9), 2202; https://doi.org/10.3390/en17092202 - 03 May 2024
Abstract
Various types of energetic fuel combustion processes emit dangerous pollutants into the air, including aerosol particles, marked as PM10. Routine air quality monitoring includes determining the PM10 concentration as one of the basic measurements. At some air monitoring stations, the
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Various types of energetic fuel combustion processes emit dangerous pollutants into the air, including aerosol particles, marked as PM10. Routine air quality monitoring includes determining the PM10 concentration as one of the basic measurements. At some air monitoring stations, the PM10 measurement is supplemented by the simultaneous determination of the concentration of PM2.5 as a finer fraction of suspended particles. Since the PM2.5 fraction has a significant share in the PM10 fraction, the concentrations of both types of particles should be strongly correlated, and the concentrations of one of these fractions can be used to model the concentrations of the other fraction. The aim of the study was to assess the error of predicting PM2.5 concentration using PM10 concentration as the main predictor. The analyzed daily concentrations were measured at 11 different monitoring stations in Poland and covered the period 2010–2021. MLP (multilayer perceptron) artificial neural networks were used to approximate the daily PM2.5 concentrations. PM10 concentrations and time variables were tested as predictors in neural networks. Several different prediction errors were taken as measures of modeling quality. Depending on the monitoring station, in models with one PM10 predictor, the RMSE error values were in the range of 2.31–6.86 μg/m3. After taking into account the second predictor D (date), the corresponding RMSE errors were lower and were in the range of 2.06–5.54 μg/m3. Our research aimed to find models that were as simple and universal as possible. In our models, the main predictor is the PM10 concentration; therefore, the only condition to be met is monitoring the measurement of PM10 concentrations. We showed that models trained at other air monitoring stations, so-called foreign models, can be successfully used to approximate PM2.5 concentrations at another station.
Full article
(This article belongs to the Collection Energy Economics and Policy in Developed Countries)
Open AccessArticle
Empowering Sustainability: Understanding Determinants of Consumer Investment in Microgrid Technology in the UAE
by
Hussain Abdalla Sajwani, Bassel Soudan and Abdul Ghani Olabi
Energies 2024, 17(9), 2201; https://doi.org/10.3390/en17092201 - 03 May 2024
Abstract
This study aims to analyze the determinants that influence the consumers’ disposition to invest in microgrid technology in the United Arab Emirates (UAE). This research offers valuable insights for policymakers on investors’ motivations to develop strategies to foster microgrid technology adoption through end-user
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This study aims to analyze the determinants that influence the consumers’ disposition to invest in microgrid technology in the United Arab Emirates (UAE). This research offers valuable insights for policymakers on investors’ motivations to develop strategies to foster microgrid technology adoption through end-user investments leading to a reduction in microgrid high capital cost. The study employed descriptive statistics, correlation, and regression analyses to analyze the responses of a sample of property owners to a quantitative survey. The study examines such variables as strategic alignment, profitability, digitization, renewable energy utilization, CO2 emission reduction, and disaster recovery readiness. The data collected reveal a moderate level of understanding and cost-awareness of microgrid technology among the respondents, with a mean of 2.46 out of 5. Notably, the data highlight the significant influence of strategic alignment with the UAE’s national energy goals on the respondents’ inclination to invest in microgrids, with a strong positive correlation of 0.942 at the 0.01 level (two-tailed). By comparison, profitability and disaster recovery have a comparatively weaker correlation. Furthermore, based on the data collected during this study, it has been determined that there is a strong value added by the microgrid initiatives considering the UAE’s strategic direction and the positive influence of reduced CO2. The regression models used were highly significant at F = 85.690. There is an acceptable level of multicollinearity with VIF values ranging from 1.087 to 2.155. UAE Strategy has low collinearity. UAE Strategy emerges as the only significant predictor of willingness to invest (p < 0.001) in the stepwise regression analysis. The analysis shows that villa and townhouse owners are willing to invest in community microgrid given that it is aligned with UAE strategy and leads to CO2 emissions reduction.
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(This article belongs to the Topic Sustainable Energy: Efficient Technological Solutions Combining Environmental, Economic, Political and Social Aspects)
Open AccessArticle
Convex Relaxations of Maximal Load Delivery for Multi-Contingency Analysis of Joint Electric Power and Natural Gas Transmission Networks
by
Byron Tasseff, Carleton Coffrin and Russell Bent
Energies 2024, 17(9), 2200; https://doi.org/10.3390/en17092200 - 03 May 2024
Abstract
Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically
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Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically operated independently, coordination of these systems during severe disruptions can allow for targeted delivery to lifeline services, including gas delivery for residential heating and power delivery for critical facilities. To address the challenge of estimating maximum joint network capacities under such disruptions, we consider the task of determining feasible steady-state operating points for severely damaged systems while ensuring the maximal delivery of gas and power loads simultaneously, represented mathematically as the nonconvex joint Maximal Load Delivery (MLD) problem. To increase its tractability, we present a mixed-integer convex relaxation of the MLD problem. Then, to demonstrate the relaxation’s effectiveness in determining bounds on network capacities, exact and relaxed MLD formulations are compared across various multi-contingency scenarios on nine joint networks ranging in size from 25 to 1191 nodes. The relaxation-based methodology is observed to accurately and efficiently estimate the impacts of severe joint network disruptions, often converging to the relaxed MLD problem’s globally optimal solution within ten seconds.
Full article
(This article belongs to the Special Issue Reliability Evaluation of Integrated Electricity and Natural Gas Systems)
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Empowering Students to Create Climate-Friendly Schools
by
Oliver Wagner, Lena Tholen, Sebastian Albert-Seifried and Julia Swagemakers
Energies 2024, 17(9), 2199; https://doi.org/10.3390/en17092199 - 03 May 2024
Abstract
In Germany, there are over 32,000 schools, representing great potential for climate protection. On the one hand, this applies to educational work, as understanding the effects of climate change and measures to reduce GHG emissions is an important step to empower students with
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In Germany, there are over 32,000 schools, representing great potential for climate protection. On the one hand, this applies to educational work, as understanding the effects of climate change and measures to reduce GHG emissions is an important step to empower students with knowledge and skills. On the other hand, school buildings are often in bad condition, energy is wasted, and the possibilities for using renewable energies are hardly used. In our “Schools4Future” project, we enabled students and teachers to draw up their own CO2 balances, identify weaknesses in the building, detect wasted electricity, and determine the potential for using renewable energies. Emissions from the school cafeteria, school trips, and paper consumption could also be identified. The fact that the data can be collected by the students themselves provides increased awareness of the contribution made to the climate balance by the various school areas. The most climate-friendly school emits 297 kg whilst the school with the highest emissions emits over one ton CO2 per student and year. Our approach is suitable to qualify students in the sense of citizen science, carry out a scientific investigation, experience self-efficacy through one’s own actions, and engage politically regarding their concerns.
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(This article belongs to the Special Issue Selected Papers from the SDEWES 2023 Conference on Sustainable Development of Energy, Water, and Environment Systems)
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Diagnostics of Interior PM Machine Rotor Faults Based on EMF Harmonics
by
Natalia Radwan-Pragłowska and Tomasz Wegiel
Energies 2024, 17(9), 2198; https://doi.org/10.3390/en17092198 - 03 May 2024
Abstract
This article presents a detailed study on the diagnosis of rotor faults in an Interior Permanent Magnet Machine based on a mathematical model. The authors provided a wide literature review, mentioning the fault diagnosis methods used for Permanent Magnet Machines. The research emphasizes
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This article presents a detailed study on the diagnosis of rotor faults in an Interior Permanent Magnet Machine based on a mathematical model. The authors provided a wide literature review, mentioning the fault diagnosis methods used for Permanent Magnet Machines. The research emphasizes the necessity of precise assumptions regarding winding construction to accurately analyze the additional harmonics appearing in rotor faults caused by electromotive force (EMF), i.e., rotor eccentricity and magnet damage. The article also discusses specific features appearing in the spectrum of air gap permeance functions and the impact of rotor eccentricity and magnet damage on PM flux density distribution and as a consequence on EMF stator windings. The novelty of the presented content is the analysis of induced EMFs for cases of the simultaneous occurrence of rotor eccentricity and PM damage. The findings of this study provide valuable insights for the diagnosis and understanding of internal asymmetries in Interior PM Machines.
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(This article belongs to the Special Issue New Solutions in Electric Machines and Motor Drives: 2nd Edition)
Open AccessArticle
An Assessment of a Photovoltaic System’s Performance Based on the Measurements of Electric Parameters under Changing External Conditions
by
Agata Zdyb and Dariusz Sobczyński
Energies 2024, 17(9), 2197; https://doi.org/10.3390/en17092197 - 03 May 2024
Abstract
This article presents an analysis of the performance of a 14.04 kWp grid-connected photovoltaic (PV) installation consisting of monocrystalline silicon, polycrystalline silicon and bifacial glass–glass monocrystalline silicon modules. The photovoltaic system was mounted in Poland, a location characterized by temperate climate conditions. On
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This article presents an analysis of the performance of a 14.04 kWp grid-connected photovoltaic (PV) installation consisting of monocrystalline silicon, polycrystalline silicon and bifacial glass–glass monocrystalline silicon modules. The photovoltaic system was mounted in Poland, a location characterized by temperate climate conditions. On the basis of the obtained results, the photovoltaic parameters were determined in accordance with the international standard. The annual energy yield of the entire system was 1033 kWh/kWp, and the performance ratio achieved was 83%. The highest average daily final yield was in the range of 4.0–4.5 kWh/kWp for each photovoltaic technology under investigation. In the cold part of the year, the efficiency of the photovoltaic modules was estimated to be 15%, and it was estimated to be 7% during the warm part of the year. Array capture losses accounted for around 0.75 kWh/kWp of energy loss per day, whereas the inverter efficiency was over 95% during the months that are beneficial for energy production.
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(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)
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Performance of Corn Cob Combustion in a Low-Temperature Fluidized Bed
by
Rolandas Paulauskas, Marius Praspaliauskas, Ignas Ambrazevičius, Kęstutis Zakarauskas, Egidijus Lemanas, Justas Eimontas and Nerijus Striūgas
Energies 2024, 17(9), 2196; https://doi.org/10.3390/en17092196 - 03 May 2024
Abstract
This study investigates the combustion of agricultural biomass rich in alkali elements in the fluidized bed. The experiments were performed with smashed corn cob in a 500 kW fluidized bed combustor which was designed for work under low bed temperatures (650–700 °C). During
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This study investigates the combustion of agricultural biomass rich in alkali elements in the fluidized bed. The experiments were performed with smashed corn cob in a 500 kW fluidized bed combustor which was designed for work under low bed temperatures (650–700 °C). During the experiments, the formed compounds from corn cob combustion were measured by sampling particulate matter, and mineral compositions were determined. Also, the temperature profile of the FBC was established. It was determined that the emissions of K and Na elements from the FBC increased from 4 to 7.3% and from 1.69 to 3%, respectively, changing the bed temperature from 650 to 700 °C. Though alkali emissions are reduced at a 650 °C bed temperature, CO emissions are higher by about 50% compared to the case of 700 °C. The addition of 3% of dolomite reduced the pollutant emissions and alkali emissions as well. Potassium content decreased by about 1% and 4%, respectively, at the bed temperatures of 650 °C and 700 °C. The NOx emissions were less than 300 mg/m3 and did not exceed the limit for medium plants regarding DIRECTIVE (EU) 2015/2193. During extended experiments lasting 8 h, no agglomeration of the fluidized bed was observed. Moreover, the proposed configuration of the FBC and its operational parameters prove suitable for facilitating the efficient combustion of agricultural biomass.
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(This article belongs to the Special Issue Efficient Utilization of Thermal Energy: Advanced Biomass Combustion Technologies)
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Prosumer Impact on Cellular Power Systems
by
Jens Maiwald and Tino Schütte
Energies 2024, 17(9), 2195; https://doi.org/10.3390/en17092195 - 03 May 2024
Abstract
This paper explores the impact of an increasing number of prosumers in electricity supply systems and investigates how market mechanisms can mitigate the negative effects. The Regional Energy Market Model simulates a supply system based on cellular structures, employing agent-based modeling to capture
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This paper explores the impact of an increasing number of prosumers in electricity supply systems and investigates how market mechanisms can mitigate the negative effects. The Regional Energy Market Model simulates a supply system based on cellular structures, employing agent-based modeling to capture individual behaviors and simulate real market dynamics. This study includes various supply scenarios, such as a solely photovoltaic scenario and a technically diversified scenario with biogas-fueled combined heat and power units. For each scenario, fixed and flexible pricing scenarios are simulated to analyze their effects. The findings reveal that systems heavily reliant on photovoltaics experience negative effects at certain points due to seasonal limitations, while technically diversified supply scenarios demonstrate fewer drawbacks. Flexible pricing systems stimulate demand in a manner beneficial to the system, creating regional added value, and contributing to the balance between generation and consumption, depending on the supply scenario. However, the study underscores that economic incentives alone are insufficient for balancing generation and consumption. The results highlight the importance of exploring opportunities through the interplay of economic incentive mechanisms and technical possibilities.
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(This article belongs to the Special Issue Smart Grid and Energy Storage)
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Optimal Selection of Distribution, Power, and Type of Luminaires for Street Lighting Designs Using Multi-Criteria Decision Model
by
Nataly Gabriela Valencia Pavón, Alexander Aguila Téllez, Marcelo García Torres, Javier Rojas Urbano and Narayanan Krishnan
Energies 2024, 17(9), 2194; https://doi.org/10.3390/en17092194 - 03 May 2024
Abstract
This article introduces an innovative design method for public lighting systems that surpasses the limitations of conventional approaches, which rely on predefined lamp characteristics and spatial arrangements. By employing a linear additive model to solve a multi-criteria decision model, our study proposes an
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This article introduces an innovative design method for public lighting systems that surpasses the limitations of conventional approaches, which rely on predefined lamp characteristics and spatial arrangements. By employing a linear additive model to solve a multi-criteria decision model, our study proposes an optimal design methodology considering several key aspects, including the distance between lamps, their type, power, and light distribution. The goal is to achieve optimal illumination that enhances visibility on public roads for drivers and pedestrians while simultaneously minimizing glare and installation costs and maximizing energy efficiency. The proposed methodology is implemented through an algorithm developed in MATLAB R2023b, with results validated through simulations in DIALux evo 12.0. This information is used to construct a decision matrix, assessed using the CRITIC method across 180 different scenarios within a specific case study. The findings demonstrate the effectiveness of multi-criteria decision-making as a tool for significantly improving the planning and design of lighting in public illumination systems, allowing for selecting the optimal combination of parameters that ensure the best lighting conditions.
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(This article belongs to the Section F: Electrical Engineering)
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Open AccessEditorial
Recent Advances in Power Quality Analysis and Robust Control of Renewable Energy Sources in Power Grids
by
Dinko Vukadinović
Energies 2024, 17(9), 2193; https://doi.org/10.3390/en17092193 - 03 May 2024
Abstract
In modern power grids with a large share of distributed power production, achieving high-power quality is a challenging task [...]
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(This article belongs to the Special Issue Recent Advances in Power Quality Analysis and Robust Control of Renewable Energy Sources in Power Grids)
Open AccessArticle
Enhanced Torrefied Oil-Palm Biomass as an Alternative Bio-Circular Solid Fuel: Innovative Modeling of Optimal Conditions and Ecoefficiency Analysis
by
Attaso Khamwichit, Jannisa Kasawapat, Narongsak Seekao and Wipawee Dechapanya
Energies 2024, 17(9), 2192; https://doi.org/10.3390/en17092192 - 02 May 2024
Abstract
Energy production from coal combustion is responsible for nearly 40% of global CO2 emissions including SOx and NOx. This study aims to produce solid biomass fuels from oil-palm residues by torrefaction, having a high heating value (HHV) equivalent to
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Energy production from coal combustion is responsible for nearly 40% of global CO2 emissions including SOx and NOx. This study aims to produce solid biomass fuels from oil-palm residues by torrefaction, having a high heating value (HHV) equivalent to fossil coals. The experiments were designed using Design Expert version 13 software to optimize the conditions affecting the fuel characteristics of the torrefied products. The statistical analysis suggested that the optimal conditions to achieve a high HHV and fixed carbon content while retaining the mass yield of biomass mainly depended on the temperature and torrefying time, while the size played a less important role in affecting the properties. The optimal conditions were observed to be at 283 °C (120 min) for EFBs, 301 °C (111 min) for PF, and 285 °C (120 min) for PKSs. The maximum HHV of 5229, 5969, and 5265 kcal/kg were achieved for the torrefied EFBs, PF, and PKSs, respectively. The energy efficiency of torrefied biomass was increased to 1.25–1.35. Ecoefficiency analysis suggested that torrefaction should be carried out at high temperatures with a short torrefying time. This low-cost bio-circular torrefied biomass showed promising fuel characteristics that could be potentially used as an alternative to coals.
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(This article belongs to the Special Issue Bioenergy and Waste-to-Energy Technologies to Reach Climate Neutrality)
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Application of Machine Learning for Shale Oil and Gas “Sweet Spots” Prediction
by
Hongjun Wang, Zekun Guo, Xiangwen Kong, Xinshun Zhang, Ping Wang and Yunpeng Shan
Energies 2024, 17(9), 2191; https://doi.org/10.3390/en17092191 - 02 May 2024
Abstract
With the continuous improvement of shale oil and gas recovery technologies and achievements, a large amount of geological information and data have been accumulated for the description of shale reservoirs, and it has become possible to use machine learning methods for “sweet spots”
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With the continuous improvement of shale oil and gas recovery technologies and achievements, a large amount of geological information and data have been accumulated for the description of shale reservoirs, and it has become possible to use machine learning methods for “sweet spots” prediction in shale oil and gas areas. Taking the Duvernay shale oil and gas field in Canada as an example, this paper attempts to build recoverable shale oil and gas reserve prediction models using machine learning methods and geological and development big data, to predict the distribution of recoverable shale oil and gas reserves and provide a basis for well location deployment and engineering modifications. The research results of the machine learning model in this study are as follows: ① Three machine learning methods were applied to build a prediction model and random forest showed the best performance. The R2 values of the built recoverable shale oil and gas reserves prediction models are 0.7894 and 0.8210, respectively, with an accuracy that meets the requirements of production applications; ② The geological main controlling factors for recoverable shale oil and gas reserves in this area are organic matter maturity and total organic carbon (TOC), followed by porosity and effective thickness; the main controlling factor for engineering modifications is the total proppant volume, followed by total stages and horizontal lateral length; ③ The abundance of recoverable shale oil and gas reserves in the central part of the study area is predicted to be relatively high, which makes it a favorable area for future well location deployment.
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(This article belongs to the Section H1: Petroleum Engineering)
Open AccessArticle
Experimental Study on Thermal Environment and Thermal Comfort of Passenger Compartment in Winter with Personal Comfort System
by
Yuxin Hu, Lanping Zhao, Xin Xu, Guomin Wu and Zhigang Yang
Energies 2024, 17(9), 2190; https://doi.org/10.3390/en17092190 - 02 May 2024
Abstract
The combined heating method of seat heating and air conditioning (A/C) was applied in the passenger compartment under different experiment conditions, using thermocouples to continuously measure the wall surfaces and air temperatures in the passenger compartment and the passengers’ skin temperatures of 17
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The combined heating method of seat heating and air conditioning (A/C) was applied in the passenger compartment under different experiment conditions, using thermocouples to continuously measure the wall surfaces and air temperatures in the passenger compartment and the passengers’ skin temperatures of 17 segments. Meanwhile, a subjective evaluation questionnaire survey was conducted using a nine-point evaluation scale on the local and overall thermal sensation and thermal comfort of the passengers, and the data from the questionnaire were analyzed with the ANOVA method. The results showed that the use of the heating pad directly affected the changes in human skin temperature, which in turn affected the local and overall thermal sensation and thermal comfort. For the two thermally stimulated segments of the back and under the thighs, the skin temperature of the back was higher than that of the thighs. Using the heating pad resulted in a rapid increase in the mean skin temperature in the early period of the experiment. Thermal sensation of the back and under-thighs shifted rapidly towards the hot zone in the first 10 min, and then settled around +3, with even more significant differences between the groups. Thermal sensations in non-thermally stimulated segments changed in relation to their position on the heating pad, with slower changes in those at the “distal” end of the body, the head and the feet. Continued use of the heating pads at lower ambient temperatures maintained overall thermal comfort at a neutral level in the range of 0–1, whereas at higher ambient temperatures there was a gradual deterioration of local and overall thermal comfort.
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(This article belongs to the Section B: Energy and Environment)
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Open AccessArticle
A Comparative Study on Load Assessment Methods for Offshore Wind Turbines Using a Simplified Method and OpenFAST Simulations
by
Satish Jawalageri, Subhamoy Bhattacharya, Soroosh Jalilvand and Abdollah Malekjafarian
Energies 2024, 17(9), 2189; https://doi.org/10.3390/en17092189 - 02 May 2024
Abstract
Simplified methods are often used for load estimations during the initial design of the foundations of offshore wind turbines (OWTs). However, the reliability of simplified methods for designing different OWTs needs to be studied. This paper provides a comparative study to evaluate the
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Simplified methods are often used for load estimations during the initial design of the foundations of offshore wind turbines (OWTs). However, the reliability of simplified methods for designing different OWTs needs to be studied. This paper provides a comparative study to evaluate the reliability of simplified approaches. The foundation loads are calculated for OWTs at the mudline level using a simplified approach and OpenFAST simulations and compared. Three OWTs, NREL 5 MW, DTU 10 MW, and IEA 15 MW, are used as reference models. An Extreme Turbulence Model wind load at a rated wind speed, combined with a 50-year Extreme Wave Height (EWH) and Extreme Operating Gust (EOG) wind load and a 1-year maximum wave height are used as the load combinations in this study. In addition, the extreme loads are calculated using both approaches for various metocean data from five different wind farms. Further, the pile penetration lengths calculated using the mudline loads via two methods are compared. The results show that the simplified method provides conservative results for the estimated loads compared to the OpenFAST results, where the extent of conservativism is studied. For example, the bending moment and shear force at the mudline using the simplified approach are 23% to 69% and 32% to 53% higher compared to the OpenFAST results, respectively. In addition, the results show that the simplified approach can be effectively used during the initial phases of monopile foundation design by using factors such as 1.5 and 2 for the shear force and bending moment, respectively.
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(This article belongs to the Special Issue Offshore Wind Support Structure Design)
Open AccessArticle
Research on Hybrid Rectifier for High Power Electrolytic Hydrogen Production Based on Modular Multilevel Converter
by
Cheng Huang, Yang Tan and Xin Meng
Energies 2024, 17(9), 2188; https://doi.org/10.3390/en17092188 - 02 May 2024
Abstract
Aiming at the problem that silicon-controlled rectifiers (SCR) and pulse width modulation (PWM) rectifiers cannot balance high power levels, high hydrogen production efficiency, and high grid connected quality in the current research on rectifier power supplies for electrolytic hydrogen production, a new hybrid
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Aiming at the problem that silicon-controlled rectifiers (SCR) and pulse width modulation (PWM) rectifiers cannot balance high power levels, high hydrogen production efficiency, and high grid connected quality in the current research on rectifier power supplies for electrolytic hydrogen production, a new hybrid rectifier topology based on a modular multilevel converter (MMC) is proposed. The hybrid topology integrates a silicon-controlled rectifier (SCR) with an auxiliary power converter, wherein the SCR is designated as the primary power source for electrolytic hydrogen production. The auxiliary converter employs a cascaded modular multilevel converter (MMC) and an input-series-output-parallel (ISOP) phase-shifted full-bridge (PSFB) arrangement. This configuration allows the auxiliary converter to effectively mitigate AC-side harmonics and minimize DC-side ripple, concurrently transmitting a small amount of power. The effectiveness of the hybrid rectifier in achieving low ripple and harmonic distortion outputs was substantiated through hardware-in-the-loop experiments. Notably, the hybrid topology is characterized by its enhanced electric-to-hydrogen conversion efficiency, elevated power density, cost efficiency, and improved grid compatibility.
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(This article belongs to the Special Issue Power Electronics Applications in Microgrid and Renewable Energy Systems)
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