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
Small-Scale Battery Energy Storage System for Testing Algorithms Aimed at Peak Power Reduction
Energies 2024, 17(9), 2217; https://doi.org/10.3390/en17092217 (registering DOI) - 04 May 2024
Abstract
This study describes a laboratory model of a battery energy storage system (BESS) designed for testing algorithms aimed at reducing peak power consumption in railway traction substations. The system comprises a DC/DC converter and battery energy storage. This article details a laboratory model
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This study describes a laboratory model of a battery energy storage system (BESS) designed for testing algorithms aimed at reducing peak power consumption in railway traction substations. The system comprises a DC/DC converter and battery energy storage. This article details a laboratory model of a bidirectional buck-boost DC/DC converter, which is used to transfer energy between the battery energy storage and a DC line. It presents an analysis of DC/DC converter systems along with simulation studies. Furthermore, the results of laboratory tests on the DC/DC converter model are also provided. The control algorithm of the system in the traction substation is focused on reducing peak power, offering benefits such as lower charges for the railway operator due to the possibility of reducing contracted power requirements. From the perspective of the power grid, the reduction in power fluctuations and, consequently, voltage sags, is advantageous. This paper includes a description of a hardware simulator for verifying the system’s control algorithms. The verification of the control algorithms was performed through experimental tests conducted on a laboratory model (a hardware simulator) of the system for dynamic load reduction in traction substations, on a power scale of 1:1000 (5.5 kW). The experimental tests on the laboratory model (hardware simulator) demonstrated the effectiveness of the algorithm in reducing the peak power drawn from the power source.
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(This article belongs to the Collection Featured Papers in Electrical Power and Energy System)
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Permeability: The Driving Force That Influences the Mechanical Behavior of Polymers Used for Hydrogen Storage and Delivery
by
Emanuele Sgambitterra and Leonardo Pagnotta
Energies 2024, 17(9), 2216; https://doi.org/10.3390/en17092216 (registering DOI) - 04 May 2024
Abstract
This article explores the main mechanisms that can generate damage in polymers and polymer-based materials used for hydrogen storage and distribution infrastructures. All of these mechanisms are driven by the permeability process that is enhanced by the operating temperature and pressure conditions. Hydrogen
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This article explores the main mechanisms that can generate damage in polymers and polymer-based materials used for hydrogen storage and distribution infrastructures. All of these mechanisms are driven by the permeability process that is enhanced by the operating temperature and pressure conditions. Hydrogen storage and delivery systems typically work under high pressure and a relatively wide range of temperatures, especially during the filling and emptying processes. Therefore, it is of great interest to better understand how this phenomenon can influence the integrity of polymer-based hydrogen infrastructures in order to avoid catastrophic events and to better design/investigate new optimized solutions. The first part of this paper discusses the main storage and delivery solutions for gas and liquid hydrogen. Then, the physics of the permeability is investigated with a focus on the effect of pressure and temperature on the integrity of polymers working in a hydrogen environment. Finally, the main mechanisms that mostly induce damage in polymers operating in a hydrogen environment and that influence their mechanical properties are explored and discussed. Particular focus was placed on the rapid gas decompression and aging phenomena. In addition, some of the limits that still exist for a reliable design of polymer-based storage and delivery systems for hydrogen are pointed out.
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(This article belongs to the Special Issue Hydrogen-Based Energy Systems for Sustainable Transportation)
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Research on Fault Identification of Hybrid Multi-Feed High-Voltage Direct Current System Based on Line Commutated Converter and Voltage Source Converter
by
Ting Wang, Kun Chen, Long’en Zhang, Xingyang Hu, Hengxuan Li and Pangqi Ye
Energies 2024, 17(9), 2215; https://doi.org/10.3390/en17092215 (registering DOI) - 04 May 2024
Abstract
With the rapid development of voltage source converter (VSC) and line commutated converter (LCC) technology and the relative concentration of power and load, the inverter station of the flexible DC system is fed into the same AC bus with the conventional DC rectifier
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With the rapid development of voltage source converter (VSC) and line commutated converter (LCC) technology and the relative concentration of power and load, the inverter station of the flexible DC system is fed into the same AC bus with the conventional DC rectifier station, and the high-voltage direct current (HVDC) parallel hybrid feed system is formed in structure. As the electrical distance between the converter stations is very close, when a fault occurs in the near area, the current on the AC wiring on the VSC side will fluctuate greatly, resulting in the misoperation of the AC wiring protection. For this reason, this paper proposes a fault identification method based on VSC/LCC hybrid multi-fed HVDC system, which discriminates the fault and outputs the protection signal according to the protection criterion, and logically judges the combination of the output protection signal to identify the fault type. The simulation results show that the method can identify all kinds of faults of hybrid multi-feed DC system and solve the problem of protection misoperation of the hybrid multi-feed DC system.
Full article
(This article belongs to the Section F6: High Voltage)
Open AccessArticle
A Three-Level Neutral-Point-Clamped Converter Based Standalone Wind Energy Conversion System Controlled with a New Simplified Line-to-Line Space Vector Modulation
by
Tarak Ghennam, Lakhdar Belhadji, Nassim Rizoug, Bruno Francois and Seddik Bacha
Energies 2024, 17(9), 2214; https://doi.org/10.3390/en17092214 (registering DOI) - 04 May 2024
Abstract
Wind power systems, which are currently being constructed for the electricity worldwide market, are mostly based on Doubly Fed Induction Generators (DFIGs). To control such systems, multilevel converters are increasingly preferred due to the well-known benefits they provide. This paper deals with the
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Wind power systems, which are currently being constructed for the electricity worldwide market, are mostly based on Doubly Fed Induction Generators (DFIGs). To control such systems, multilevel converters are increasingly preferred due to the well-known benefits they provide. This paper deals with the control of a standalone DFIG-based Wind Energy Conversion System (WECS) by using a three-level Neutral-Point-Clamped (NPC) converter. The frequency and magnitude of the stator output voltage of the DFIG are controlled and fixed at nominal values despite the variable rotor speed, ensuring a continuous AC supply for three-phase loads. This task is achieved by controlling the DFIG rotor currents via a PI controller combined with a new Simplified Direct Space Vector Modulation strategy (SDSVM), which is applied to the three-level NPC converter. This strategy is based on the use of a line-to-line three-level converter space vector diagram without using Park transformation and then simplifying it to that of a two-level converter. The performance of the proposed SDSVM technique in terms of controlling the three-level NPC-converter-based standalone WECS is demonstrated through simulation results. The whole WECS control and the SDSVM strategy are implemented on a dSPACE DS 1104 board that drives a DFIG-based wind system test bench. The obtained experimental results confirm the validity and performance in terms of control.
Full article
(This article belongs to the Special Issue Trends and Prospects in DC–DC/DC–AC Converters and Their Control Techniques for Renewable Energy Applications)
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New Uses for Coal Mines as Potential Power Generators and Storage Sites
by
Juan Pous de la Flor, Juan Pous Cabello, María de la Cruz Castañeda, Marcelo Fabián Ortega and Pedro Mora
Energies 2024, 17(9), 2213; https://doi.org/10.3390/en17092213 (registering DOI) - 04 May 2024
Abstract
In the context of sustainable development, revitalising the coal sector is a key challenge. This article examines how five innovative technologies can transform abandoned or in-use coal mines into sustainable energy centres. From solar thermal to compressed air energy storage, these solutions offer
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In the context of sustainable development, revitalising the coal sector is a key challenge. This article examines how five innovative technologies can transform abandoned or in-use coal mines into sustainable energy centres. From solar thermal to compressed air energy storage, these solutions offer a path to a more sustainable future while addressing the decline in coal production. This approach not only promotes energy efficiency but also contributes to the mitigation of environmental impacts, thus consolidating the transition to a more responsible energy model. Thus, in this document, the reader can find the explanation of why we have opted for these technologies and not other existing ones. In addition, the economic, environmental and technical feasibility of the different technologies is analysed. Finally, real cases of the successful application of these technologies will be presented once they have gone beyond the project idea phase, and the reasons why we are calling for their transposition to the coal industry in the search for its revitalisation will be explained.
Full article
(This article belongs to the Special Issue Energy from Coal Mining: Technology, Simulations and Experiments)
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Approach for Calculating and Analyzing Carbon Emissions and Sinks of Villages: A Case Study in Northern China
by
Tiantian Du, Yan Jiao, Yue Zhang, Ziyu Jia, Jueqi Wang, Jinhao Zhang and Zheng Cheng
Energies 2024, 17(9), 2212; https://doi.org/10.3390/en17092212 (registering DOI) - 04 May 2024
Abstract
Despite a gradual decline in rural population due to urbanization, as of 2022, approximately 35% of China’s total population still resides in villages. Over a span of 40 years, carbon emissions from villages have significantly surged, with a sevenfold increase from energy consumption
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Despite a gradual decline in rural population due to urbanization, as of 2022, approximately 35% of China’s total population still resides in villages. Over a span of 40 years, carbon emissions from villages have significantly surged, with a sevenfold increase from energy consumption and a 46% rise from agriculture. Consequentially, the development of low-carbon villages is imperative. A comprehensive understanding of the primary sources of carbon emissions in villages is crucial for implementing practical and effective strategies towards low-carbon development. However, limited research has been conducted on quantifying carbon emissions and sinks for Chinese villages. This study aims to address this gap by proposing a methodology for assessing carbon emissions in villages, including the emissions of CO2, CH4 and N2O. Inspired by the IPCC standard methodology for greenhouse gas emissions at national levels and provincial greenhouse gas inventory guidelines customized for China’s context incorporating localized characteristics, this approach has been applied to seven villages in Northern China based on field investigations. Employing a range of methods including field surveys, questionnaires, statistical records and big-data platforms, we collected the carbon emission activity levels of the seven villages using the most up-to-date carbon emission factors. Subsequently, the collected data and facts are quantitatively processed to generate results that are compared among the seven villages. These findings are also compared with those from other studies. The analysis indicates that the primary industries in these villages significantly influence the total carbon emissions. Moreover, the study reveals that energy consumption in buildings, agriculture, transportation and waste disposal are the most influential emission sources. These findings provide valuable insights into the carbon emission landscape of villages and can serve as a guide for implementing strategies and policies aimed at promoting low-carbon development in the rural areas of Northern China.
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(This article belongs to the Section B: Energy and Environment)
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Cold Energy Storage via Hydrates Production with Pure CO2 and CO2/N2 (70/30 and 50/50 vol%) Mixtures: Quantification and Comparison between Energy Stored and Energy Spent
by
Alberto Maria Gambelli, Federico Rossi and Giovanni Gigliotti
Energies 2024, 17(9), 2211; https://doi.org/10.3390/en17092211 (registering DOI) - 04 May 2024
Abstract
Gas hydrates represent an attractive opportunity for gas storage. These ice-like structures can be produced both for the final disposal of greenhouse gases such as carbon dioxide in the solid form and for the storage of energy gases, such as methane, propane, and
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Gas hydrates represent an attractive opportunity for gas storage. These ice-like structures can be produced both for the final disposal of greenhouse gases such as carbon dioxide in the solid form and for the storage of energy gases, such as methane, propane, and others, with the possibility of reaching energy densities comparable with those of pressurised vessels, but at lower pressures. In addition, gas hydrates can be directly produced for their capability to act as phase change materials at temperatures higher than 0 °C. This research deals with cold energy storage via the production of gas hydrate into a lab-scale apparatus. Hydrates were produced with pure carbon dioxide and with CO2/N2 mixtures (70/30 and 50/50 vol%). For each mixture, the amount of energy spent for hydrates production and cold energy stored were calculated, and the results were compared among each other. The addition of nitrogen to the system allowed us to maximise the energy stored/energy spent ratio, which passed from 78.06% to 109.04%; however, due to its molecular size and the consequent impossibility to stabilise the occupied water cages, nitrogen caused a reduction in the total quantity of hydrates produced, which was obviously proportional to the energy stored. Therefore, the concentration of nitrogen in the mixtures need to be carefully determined in order to optimise the Estored/Espent ratio.
Full article
(This article belongs to the Special Issue Gas Hydrates: A Future Clean Energy Resource)
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The Comparison of Physical and Chemical Properties of Pellets and Briquettes from Hemp (Cannabis sativa L.)
by
Kamil Roman and Emilia Grzegorzewska
Energies 2024, 17(9), 2210; https://doi.org/10.3390/en17092210 (registering DOI) - 04 May 2024
Abstract
The adaptation of lignocellulosic materials such as Cannabis sativa L. as a new renewable energy source is linked to the fact that the technology must be developed to be able to adapt to local market conditions. Bioenergy consumers are faced with this problem
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The adaptation of lignocellulosic materials such as Cannabis sativa L. as a new renewable energy source is linked to the fact that the technology must be developed to be able to adapt to local market conditions. Bioenergy consumers are faced with this problem because, when it comes to the selection of briquettes and pellets for energy production, there are only individual standards in place. This research is intended to provide a better understanding of hemp product potential as a new material that can be used in the production of pellets and briquettes for biofuel purpose. Nevertheless, the anisotropic raw material interferes with the compaction process and may expose a poor durability of the pellets and briquettes. The research that was conducted evaluated the conditions of the biofuels by measuring the physical and chemical parameters. The ash content, compressive strength, and durability of the samples were examined. The statistical data analysis was performed after the strength tests on the prepared samples.
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(This article belongs to the Special Issue Advanced Biofuels: Production, Characterization and Upgrade)
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Multi Criteria Frameworks Using New Meta-Heuristic Optimization Techniques for Solving Multi-Objective Optimal Power Flow Problems
by
Murtadha Al-Kaabi, Virgil Dumbrava and Mircea Eremia
Energies 2024, 17(9), 2209; https://doi.org/10.3390/en17092209 (registering DOI) - 04 May 2024
Abstract
This article develops two metaheuristics optimization techniques, Grey Wolf Optimizer (GWO) and Harris Hawks Optimization (HHO), to handle multi-objective optimal power flow (MOOPF) issues. Multi Objective GWO (MOGWO) and Multi Objective HHO (MOHHO) are the names of the developed techniques. By combining these
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This article develops two metaheuristics optimization techniques, Grey Wolf Optimizer (GWO) and Harris Hawks Optimization (HHO), to handle multi-objective optimal power flow (MOOPF) issues. Multi Objective GWO (MOGWO) and Multi Objective HHO (MOHHO) are the names of the developed techniques. By combining these optimization techniques with Pareto techniques, the non-dominated solution set can be obtained. These developed approaches are characterized by simplicity and have few control parameters. Fuel cost, emissions, real power losses, and voltage deviation were the four objective functions considered. The theories used to determine the best compromise solution and organize the Pareto front options are the fuzzy membership equation and the crowding distance approach, respectively. To validate and evaluate the performance of the presented techniques, two standard IEEE bus systems—30-bus and 57-bus power systems—were proposed. Bi, Tri, and Quad objective functions with 21 case studies are the types of objective functions and the scenarios that were applied in this paper. As compared to the results of the most recent optimization techniques documented in the literature, the comparative analysis results for the proposed methodologies demonstrated the superiority and robustness of MOGWO and MOHHO.
Full article
(This article belongs to the Section F1: Electrical Power System)
Open AccessArticle
Novel Self-Organizing Probability Maps Applied to Classification of Concurrent Partial Discharges from Online Hydro-Generators
by
Rodrigo M. S. de Oliveira, Filipe C. Fernandes and Fabrício J. B. Barros
Energies 2024, 17(9), 2208; https://doi.org/10.3390/en17092208 (registering DOI) - 04 May 2024
Abstract
In this paper, we present an unprecedented method based on Kohonen networks that is able to automatic recognize partial discharge (PD) classes from phase-resolved partial discharge (PRPD) diagrams with features of various simultaneous PD patterns. The PRPD diagrams were obtained from the stator
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In this paper, we present an unprecedented method based on Kohonen networks that is able to automatic recognize partial discharge (PD) classes from phase-resolved partial discharge (PRPD) diagrams with features of various simultaneous PD patterns. The PRPD diagrams were obtained from the stator windings of a real-world hydro-generator rotating machine. The proposed approach integrates classification probabilities into the Kohonen method, producing self-organizing probability maps (SOPMs). For building SOPMs, a group of PRPD diagrams, each containing a single PD pattern for training the Kohonen networks and single- and multiple-class-featured samples for obtaining final SOPMs, is used to calculate the probabilities of each Kohonen neuron to be associated with the various PD classes considered. At the end of this process, a self-organizing probability map is produced. Probabilities are calculated using distances, obtained in the space of features, between neurons and samples. The so-produced SOPM enables the effective classification of PRPD samples and provides the probability that a given PD sample is associated with a PD class. In this work, amplitude histograms are the features extracted from PRPDs maps. Our results demonstrate an average classification accuracy rate of approximately 90% for test samples.
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(This article belongs to the Special Issue Energy, Electrical and Power Engineering 2024)
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Design of an Axial-Type Magnetic Gear with Auxiliary Flux-Enhancing Structure
by
Fang Li, Hang Zhao and Xiangdong Su
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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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.
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(This article belongs to the Special Issue Reliability Evaluation of Integrated Electricity and Natural Gas Systems)
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Open AccessArticle
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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Open AccessArticle
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)
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