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
Assessing the Additional Benefits of Thailand’s Approaches to Reduce Motor Vehicle Emissions
Energies 2024, 17(10), 2336; https://doi.org/10.3390/en17102336 (registering DOI) - 12 May 2024
Abstract
Air pollutants and greenhouse gases (GHGs) represent major challenges in our era, contributing to climate change and global health issues. These problems arise from a variety of well-known sources, including motor vehicles. Almost all nations, Thailand included, have formulated and implemented policies to
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Air pollutants and greenhouse gases (GHGs) represent major challenges in our era, contributing to climate change and global health issues. These problems arise from a variety of well-known sources, including motor vehicles. Almost all nations, Thailand included, have formulated and implemented policies to curb greenhouse gas (GHG) emissions in line with the requirements and commitments of the Paris Agreement. The evaluation of specific air pollutants and GHG emissions originating from road vehicles utilises the Thailand database, referencing the year 2019. Data intersections from 2019 to 2022 are grounded in actual data collected from relevant departments in Thailand, while projections for 2023–2030 are forecasted based on the baseline year. The secondary database used in the International Vehicle Emission model is adjusted according to real-world driving data to accurately reflect country-specific emission factors. Dynamic emission factors for specific air pollutants and GHGs are evaluated and integrated with the average Vehicle Kilometres Travelled (VKT) for each vehicle category. The Business-As-Usual (BAU) scenario is then examined, based on existing policies aimed at reducing air pollutants and GHG emissions in Thailand’s transport sector. These policies include strategies for the adoption of electric vehicles and the promotion of public transport to reduce VKT. Under the BAU scenario, the overall number of road vehicles in Thailand, including passenger cars, motorcycles, pickups, vans, trucks, and buses, is expected to increase by approximately 6.58% by 2030, leading to a rise in specific air pollutants and GHG emissions compared to the 2019 baseline. However, by adhering to Thailand’s strategies and transitioning to new electric passenger cars and buses, greenhouse gas emissions and specific air pollutants from the road transport sector will be significantly reduced.
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(This article belongs to the Topic Enabling Strategies and Policies toward a Sustainable Environment)
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Open AccessArticle
Design and Optimization of Cross-Corrugated Triangular Ducts with Trapezoidal Baffles Based on Response Surface Methodology and CFD
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Caihang Liang, Rui Zhang, Chaojian Mao, Yanfang Dong, Xiong Yao, Weipeng Hu and Zhenxing Li
Energies 2024, 17(10), 2335; https://doi.org/10.3390/en17102335 (registering DOI) - 12 May 2024
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Plate heat exchangers are widely used in the Heating, Ventilation, and Air Conditioning (HVAC) field. Cross-corrugated triangular ducts are commonly employed in plate heat exchangers. Inserting baffles into the cross-corrugated triangular ducts can improve the heat transfer performance of the plate heat exchangers.
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Plate heat exchangers are widely used in the Heating, Ventilation, and Air Conditioning (HVAC) field. Cross-corrugated triangular ducts are commonly employed in plate heat exchangers. Inserting baffles into the cross-corrugated triangular ducts can improve the heat transfer performance of the plate heat exchangers. This study focuses on intricate interdependencies among the flow channel apex angle, the trapezoidal baffle inclination angle, baffle position, and Reynolds number (Re) on heat transfer and pressure drop using response surface methodology (RSM) and computational fluid dynamic (CFD). To identify the factors that maximize the Nusselt number (Nu) and minimize friction factor (f), the RSM is used to design factors, conduct numerical studies, and establish regression equations. The results show that the apex angle, baffle angle, X-direction position, and Re have significantly affected Nu and f. Compared to a non-baffled channel with the same apex angle and Re conditions, the optimized channel enhances heat transfer by 1.54 times and has an almost identical pressure drop. The inclined baffle significantly enhances comprehensive performance at low Re. The synergistic effect of the heat transfer and pressure drop is most optimal when the apex angle of the flow channel is 90°, the trapezoidal baffle inclination angle is 52.5°, and the Re is 1000, with the baffle position at 0.625H in the X-direction.
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Open AccessArticle
Integration of Chemical Looping Combustion in the Graz Power Cycle
by
Carlos Arnaiz del Pozo, Susana Sánchez-Orgaz, Alberto Navarro-Calvo, Ángel Jiménez Álvaro and Schalk Cloete
Energies 2024, 17(10), 2334; https://doi.org/10.3390/en17102334 (registering DOI) - 12 May 2024
Abstract
: Effective decarbonization of the power generation sector requires a multi-pronged approach, including the implementation of CO2 capture and storage (CCS) technologies. The Graz cycle features oxy-combustion CO2 capture in a power production scheme which can result in higher thermal efficiencies
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: Effective decarbonization of the power generation sector requires a multi-pronged approach, including the implementation of CO2 capture and storage (CCS) technologies. The Graz cycle features oxy-combustion CO2 capture in a power production scheme which can result in higher thermal efficiencies than that of a combined cycle. However, the auxiliary consumption required by the air separation unit to provide pure O2 results in a significant energy penalty relative to an unabated plant. In order to mitigate this penalty, the present study explores the possibility of chemical looping combustion (CLC) as an alternative means to supply oxygen for conversion of the fuel. For a midscale power plant, despite reducing the levelized cost of electricity (LCOE) by approximately 12.6% at a CO2 tax of EUR 100/ton and a natural gas price of EUR 6.5/GJ and eliminating the energy penalty of CCS relative to an unabated combined cycle, the cost reductions of CLC in the Graz cycle were not compelling relative to commercially available post-combustion CO2 capture with amines. Although the central assumptions yielded a 3% lower cost for the Graz-CLC cycle, an uncertainty quantification study revealed an 85.3% overlap in the interquartile LCOE range with that of the amine benchmark, indicating that the potential economic benefit is small compared to the uncertainty of the assessment. Thus, this study indicates that the potential of CLC in gas-fired power production is limited, even when considering highly efficient advanced configurations like the Graz cycle.
Full article
(This article belongs to the Special Issue Next-Generation Clean Technologies for Low-Carbon Economy Transition)
Open AccessArticle
Extracting Accurate Parameters from a Proton Exchange Membrane Fuel Cell Model Using the Differential Evolution Ameliorated Meta-Heuristics Algorithm
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Badreddine Kanouni and Abdelbaset Laib
Energies 2024, 17(10), 2333; https://doi.org/10.3390/en17102333 (registering DOI) - 12 May 2024
Abstract
The electrochemical proton exchange membrane fuel cell (PEMFC) is an electrical generator that utilizes a chemical reaction mechanism to produce electricity, serving as a sustainable and environmentally friendly energy source. To thoroughly analyze and develop the features and performance of a PEMFC, it
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The electrochemical proton exchange membrane fuel cell (PEMFC) is an electrical generator that utilizes a chemical reaction mechanism to produce electricity, serving as a sustainable and environmentally friendly energy source. To thoroughly analyze and develop the features and performance of a PEMFC, it is essential to use a precise model that incorporates exact parameters to effectively suit the polarization curve. In addition, parameter extraction plays a crucial role in the simulation analysis, evaluation, optimum control, and fault detection of the proton exchange membrane fuel cell (PEMFC) system. Despite the development of many algorithms for parameter extraction in PEMFC, obtaining accurate and trustworthy results rapidly remains a challenge. This study presents a hybridized algorithm, namely differential evolution ameliorated (DEA) for reliably estimating PEMFC model parameters. To evaluate the proposed DEA-based parameter identification, a comparison analysis with previously published methods is conducted using MATLAB/SimulinkTM (R2016b, MathWorks, Natick, MA, USA) in terms of system correctness and convergence process. The proposed DEA algorithm is tested to extract the parameters of two PEMFC models: SR-12,500 W and 250 W. The sum of the squared errors (SSE) between the experimental and the obtained voltage data is defined as an objective function. The simulation results prove that the suggested DEA algorithm is capable of identifying the optimal PEMFC parameters rapidly and accurately in comparison with other optimization algorithms.
Full article
(This article belongs to the Topic Thermal-Related Design, Application, and Optimization of Fuel Cells and Batteries)
Open AccessArticle
Investigation on the Possibility of Improving the Performance of a Silicon Cell Using Selected Dye Concentrator
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Ewa Brągoszewska, Bartłomiej Milewicz and Agata Wajda
Energies 2024, 17(10), 2332; https://doi.org/10.3390/en17102332 (registering DOI) - 12 May 2024
Abstract
There are many opportunities to increase the efficiency of photovoltaic cells. These include solutions such as tracking mechanisms, hybrid systems or dye concentrators. Importantly, their implementation can reduce the number of silicon cells in installations, leading to reduced environmental impact. The principle of
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There are many opportunities to increase the efficiency of photovoltaic cells. These include solutions such as tracking mechanisms, hybrid systems or dye concentrators. Importantly, their implementation can reduce the number of silicon cells in installations, leading to reduced environmental impact. The principle of a dye concentrator is to focus sunlight onto the surface of PV modules, increasing electricity production. In this study, the potential for increased PV cell efficiency is investigated using a selected dye concentrator—tinted and luminescent acrylic glass (polymethylmethacrylate, PMMA) in yellow and red colors. The experiment included multiple measurement calibrations, such as the temperature of the silicon cell under test and the irradiation, as well as different variants of PV systems consisting of a silicon cell and different types of PMMA. Overall, the results show an increase in PV cell performance and the dependence of the increase on the type of PMMA used. The most favorable of the PV systems tested appeared to be the combination of a PV cell with a red luminescent PV, for which an average efficiency improvement of 1.21% was obtained.
Full article
(This article belongs to the Special Issue Renewable and Sustainable Energy in Light of Energy Transition Processes)
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A Reviewed Turn at of Methods for Determining the Type of Fault in Power Transformers Based on Dissolved Gas Analysis
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Ancuța-Mihaela Aciu, Sorin Enache and Maria-Cristina Nițu
Energies 2024, 17(10), 2331; https://doi.org/10.3390/en17102331 (registering DOI) - 12 May 2024
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Since power transformers are the most important pieces of equipment in electricity transmission and distribution systems, special attention must be paid to their maintenance in order to keep them in good condition for a long time. This paper reviews the main steps in
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Since power transformers are the most important pieces of equipment in electricity transmission and distribution systems, special attention must be paid to their maintenance in order to keep them in good condition for a long time. This paper reviews the main steps in the process of diagnosing the health of power transformer insulation, which involves the science of analysing the gases dissolved in power transformer oil for effective identification of faults. An accurate diagnosis of incipient faults is favourable to sustainable development and necessary to maintain a reliable supply of electricity. The methods presented for fault diagnosis in mineral-oil-immersed power transformers are divided into analytical and graphical methods and have been found to be simple, economical and effective. After describing the methods, both their strengths and weaknesses were identified, and over the years, the methods were complemented to provide highly accurate information, validated by field inspections. This paper focuses on practical information and applications to manage maintenance based on accurate and up-to-date data. The contents of this paper will be of particular use to engineers who manufacture, monitor and/or use high-power transformers in the energy sector, as well as to undergraduate, master’s and PhD students interested in such applications.
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Open AccessArticle
Using Transfer Learning and XGBoost for Early Detection of Fires in Offshore Wind Turbine Units
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Anping Wan, Chenyu Du, Wenbin Gong, Chao Wei, Khalil AL-Bukhaiti, Yunsong Ji, Shidong Ma, Fareng Yao and Lizheng Ao
Energies 2024, 17(10), 2330; https://doi.org/10.3390/en17102330 (registering DOI) - 11 May 2024
Abstract
To improve the power generation efficiency of offshore wind turbines and address the problem of high fire monitoring and warning costs, we propose a data-driven fire warning method based on transfer learning for wind turbines in this paper. This paper processes wind turbine
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To improve the power generation efficiency of offshore wind turbines and address the problem of high fire monitoring and warning costs, we propose a data-driven fire warning method based on transfer learning for wind turbines in this paper. This paper processes wind turbine operation data in a SCADA system. It uses an extreme gradient-boosting tree (XGBoost) algorithm to build an offshore wind turbine unit fire warning model with a multiparameter prediction function. This paper selects some parameters from the dataset as input variables for the model, with average cabin temperature, average outdoor temperature, average cabin humidity, and average atmospheric humidity as output variables. This paper analyzes the distribution information of input and output variables and their correlation, analyzes the predicted difference, and then provides an early warning for wind turbine fires. This paper uses this fire warning model to transfer learning to different models of offshore wind turbines in the same wind farm to achieve fire warning. The experimental results show that the prediction performance of the multiparameter is accurate, with an average MAPE of 0.016 and an average RMSE of 0.795. It is better than the average MAPE (0.051) and the average RMSE (2.020) of the prediction performance of a backpropagation (BP) neural network, as well as the average MAPE (0.030) and the average RMSE (1.301) of the prediction performance of random forest. The transfer learning model has good prediction performance, with an average MAPE of 0.022 and an average RMSE of 1.469.
Full article
(This article belongs to the Section A3: Wind, Wave and Tidal Energy)
Open AccessArticle
A Neural Network Forecasting Approach for the Smart Grid Demand Response Management Problem
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Slim Belhaiza and Sara Al-Abdallah
Energies 2024, 17(10), 2329; https://doi.org/10.3390/en17102329 (registering DOI) - 11 May 2024
Abstract
Demand response management (DRM) plays a crucial role in the prospective development of smart grids. The precise estimation of electricity demand for individual houses is vital for optimizing the operation and planning of the power system. Accurate forecasting of the required components holds
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Demand response management (DRM) plays a crucial role in the prospective development of smart grids. The precise estimation of electricity demand for individual houses is vital for optimizing the operation and planning of the power system. Accurate forecasting of the required components holds significance as it can substantially impact the final cost, mitigate risks, and support informed decision-making. In this paper, a forecasting approach employing neural networks for smart grid demand-side management is proposed. The study explores various enhanced artificial neural network (ANN) architectures for forecasting smart grid consumption. The performance of the ANN approach in predicting energy demands is evaluated through a comparison with three statistical models: a time series model, an auto-regressive model, and a hybrid model. Experimental results demonstrate the ability of the proposed neural network framework to deliver accurate and reliable energy demand forecasts.
Full article
(This article belongs to the Topic AI and Computational Methods for Modelling, Simulations and Optimizing of Advanced Systems: Innovations in Complexity)
Open AccessArticle
Adaptive Design of Solar-Powered Energy Systems Based on Daily Clearness State Evolution
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Dong Liang, Long Ma, Peng Wang, Yuanxia Li and Yiping Luo
Energies 2024, 17(10), 2328; https://doi.org/10.3390/en17102328 (registering DOI) - 11 May 2024
Abstract
The optimal designing of the hybrid energy system (HES) is a challenging task due to the multiple objectives and various uncertainties. Especially for HES, primarily powered by solar energy, the reference solar radiation data directly impact the result of the optimization design. To
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The optimal designing of the hybrid energy system (HES) is a challenging task due to the multiple objectives and various uncertainties. Especially for HES, primarily powered by solar energy, the reference solar radiation data directly impact the result of the optimization design. To incorporate the stochastic characteristics of solar radiation into the sizing process, a data-driven stochastic modeling method for solar radiation is proposed. The method involves two layers of stochastic processes that capture the intraday variation and daily evolution of solar radiation. First, the clearness index (CI) is introduced to describe the radiation intensity at different times. Then, the daily clearness state (DCS) is proposed, based on the statistical indicators of the intraday CI. The Markov model is used to describe the stochastic evolutionary characteristics between different DCSs. The probabilistic distribution of the CI under different DCS is obtained based on the diffusion kernel density estimation (DKDE), which is used for the stochastic generation of the CI at various times of the day. Finally, the radiation profile required for the optimal design is obtained by the stochastic generation of the DCS sequences and the intraday clearness index under corresponding states. A case study of an off-grid solar-powered HES is provided to illustrate this methodology.
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(This article belongs to the Section A: Sustainable Energy)
Open AccessArticle
Comparison of the Sample Preparation Strategies and Impacts on the Tensile Strength of Gas Shale with Variable Moisture Conditions
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Liuqing Shu, Lingzhi Xie, Bo He and Yao Zhang
Energies 2024, 17(10), 2327; https://doi.org/10.3390/en17102327 (registering DOI) - 11 May 2024
Abstract
Moisture significantly affects the mechanical behavior of gas shale and further determines the hydraulic fracturing performance, as it is more attractive. Nevertheless, batch experiments have usually involved variable methodologies regarding the preparation of moisture-contained shale specimens in the sequence (and/or frequency) of drying
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Moisture significantly affects the mechanical behavior of gas shale and further determines the hydraulic fracturing performance, as it is more attractive. Nevertheless, batch experiments have usually involved variable methodologies regarding the preparation of moisture-contained shale specimens in the sequence (and/or frequency) of drying and soaking treatments. Accordingly, this work investigates how the preparation methodology influences the test results of moisture-contained shale samples. This study compares three commonly used shale sample preparation strategies for acquiring different moisture contents, that is, “dry-wet”, “dry-wet-dry”, and “wet-dry-wet” strategies, followed by a Brazilian splitting test for the mechanical parameters. The results show that under the same saturation conditions, the longer the soaking time during sample preparation, the higher the degradation degree of shale tensile strength. Meanwhile, prolonged soaking can lead to a more discrete distribution of strength values, and the failure mode may deviate from the Brazilian splitting theory model. Under the combined influence of moisture content and soaking time, the tensile strength of shale decreases approximately linearly with increasing saturation, while the degradation degree increases nonlinearly with increasing saturation, and the degradation rate changes from slow to fast. According to the observation of the microstructure of hydrated shale, prolonged soaking can lead to an increase in the expansion of clay minerals in shale by hydration, resulting in looser and more fragmented internal structure, and further degradation in shale strength. In order to weaken the interference of hydration when studying the effect of moisture content on the tensile strength of shale, the soaking time should be minimized as much as possible during the preparation process.
Full article
(This article belongs to the Special Issue Application and Optimization of CCUS Technology in Shale Gas Production and Storage)
Open AccessArticle
A Practical Hybrid Hysteresis Model for Calculating Iron Core Losses in Soft Magnetic Materials
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Xiaotong Fu, Shuai Yan, Zhifu Chen, Xiaoyu Xu and Zhuoxiang Ren
Energies 2024, 17(10), 2326; https://doi.org/10.3390/en17102326 (registering DOI) - 11 May 2024
Abstract
Accurately calculating the losses of ferromagnetic materials is crucial for optimizing the design and ensuring the safe operation of electrical equipment such as motors and power transformers. Commonly used loss calculation models include the Bertotti empirical formula and hysteresis models. In this paper,
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Accurately calculating the losses of ferromagnetic materials is crucial for optimizing the design and ensuring the safe operation of electrical equipment such as motors and power transformers. Commonly used loss calculation models include the Bertotti empirical formula and hysteresis models. In this paper, a new hybrid hysteresis model method is proposed to calculate losses—namely, the combination of the Jiles–Atherton hysteresis model (J–A) and the Fourier hysteresis model. The traditional Jiles–Atherton hysteresis model is mainly suitable for fitting the saturation hysteresis loop, but the fitting error is relatively large for internal minor hysteresis loops. In contrast, the Fourier hysteresis model is suitable for fitting the minor hysteresis loops because the corresponding magnetic induction strength or magnetic field is lower and the waveform distortion is small. Moreover, Fourier series expansion can be expressed with fewer terms, which is convenient for parameter fitting. Through examples, the results show that the hybrid hysteresis model can take advantage of the strengths of each model, not only reducing computational complexity, but also ensuring high fitting accuracy and loss calculation accuracy.
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(This article belongs to the Section F3: Power Electronics)
Open AccessArticle
A Study on the Techno-Economics Feasibility of a 19.38 KWp Rooftop Solar Photovoltaic System at Al-Abrar Mosque, Saudi Arabia
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Abdulaziz S. Alaboodi and Sultan J. Alharbi
Energies 2024, 17(10), 2325; https://doi.org/10.3390/en17102325 (registering DOI) - 11 May 2024
Abstract
This research paper presents a comprehensive study on the implementation of photovoltaic (PV) energy systems at Al-Abrar Mosque in Saudi Arabia. The primary objective was to explore optimal regional solar power strategies. By synergistically integrating technical evaluations of the PV system with economic
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This research paper presents a comprehensive study on the implementation of photovoltaic (PV) energy systems at Al-Abrar Mosque in Saudi Arabia. The primary objective was to explore optimal regional solar power strategies. By synergistically integrating technical evaluations of the PV system with economic analyses, including the payback period and levelized cost of energy (LCOE), alongside an investigation of net metering and net billing scenarios, we delineated a pathway toward achieving net zero billing for the mosque’s energy requirements. This study examined two scenarios: Scenario I involved net metering, while Scenario II explored net billing. Our theoretical and simulation results, derived from detailed analyses conducted using PVsyst software, unequivocally demonstrated the superiority of net metering for this specific application. With net metering, the mosque’s energy needs can be efficiently met using minimal infrastructure—comprising only 34 photovoltaic modules and a single inverter. In contrast, net billing requires significantly higher resource demands, underscoring the economic and spatial advantages of net metering. Additionally, the payback period for Scenario I is 7.9 years, while for Scenario II, it extends to 87 years. Through rigorous simulations, this study reaffirmed the practicality and feasibility of the net metering approach within the context of Saudi Arabia. Furthermore, our research provides actionable insights for implementing sustainable solutions at specific sites, such as the Al-Abrar Mosque, and contributes to advancing renewable energy knowledge in the region.
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(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)
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Open AccessArticle
Experimental Investigation of the Viscosity and Density of Microencapsulated Phase Change Material Slurries for Enhanced Heat Capacity and Transfer
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Bartlomiej Nalepa, Krzysztof Dutkowski, Marcin Kruzel, Boguslaw Bialko and Bartosz Zajaczkowski
Energies 2024, 17(10), 2324; https://doi.org/10.3390/en17102324 (registering DOI) - 11 May 2024
Abstract
Working fluids that incorporate solid microencapsulated phase change materials (MPCMs) can benefit from properties such as density and viscosity, which are crucial for improving heat capacity and transfer. However, limited data are available on these parameters for specific slurry and mass ratios. In
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Working fluids that incorporate solid microencapsulated phase change materials (MPCMs) can benefit from properties such as density and viscosity, which are crucial for improving heat capacity and transfer. However, limited data are available on these parameters for specific slurry and mass ratios. In this study, we present a comparative analysis of the experimental results on the viscosity of three different MPCM aqueous dispersions, namely MPCM 31-S50, MPCM 25-S50, and Micronal 5428X. Varying MPCM mass ratios of distilled water were used to obtain different mass concentrations of the phase change material (PCM), and the resulting slurries were analysed at temperatures ranging from 15 to 40 °C. Our findings showed that all slurries exhibited non-Newtonian characteristics at low shear rates, with viscosity stabilising at higher shear rates, resulting in the characteristics of a Newtonian fluid. The viscosity results were highly dependent on the type of MPCM base dispersion, particularly at high mass ratios, with the slurries having viscosities higher than those of water. Furthermore, we conducted density experiments as a function of temperature, using a flow test setup and a Coriolis flowmeter (Endress+Hauser, Reinach, Switzerland) to determine the density of two MPCMs, namely MPCM 25-S50 and Micronal 5428X. The test samples were prepared at mass concentrations of 10%, 15%, and 20% of the phase change material. We found significant differences in density and viscosity for different MPCM slurries as a result of both the PCM concentration and the material studied. Our results also revealed an apparent PCM phase change process, in which the slurry density significantly decreased in the temperature range of the phase transition from solid to liquid.
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(This article belongs to the Collection Advances in Heat Transfer Enhancement)
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Open AccessArticle
Design, Simulation and Optimization of a Novel Transpired Tubular Solar Air Heater
by
Hossain Nemati
Energies 2024, 17(10), 2323; https://doi.org/10.3390/en17102323 (registering DOI) - 11 May 2024
Abstract
In this paper, a novel tubular solar air heater is introduced. In this air heater, the hot boundary layer is drawn into the absorber tube and can provide thermal energy at moderate temperatures. Several different cases were simulated and a correlation was proposed
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In this paper, a novel tubular solar air heater is introduced. In this air heater, the hot boundary layer is drawn into the absorber tube and can provide thermal energy at moderate temperatures. Several different cases were simulated and a correlation was proposed to predict the collector’s effectiveness as a function Rayleigh number and Reynolds number. An equation was derived to find the effectiveness of this collector. Finally, a real case was studied with non-uniform solar flux distribution, as well as radiation heat loss. Good agreement was found between the results and those derived by the proposed analytical method. For different suction values, the first-law and the second-law efficiencies were calculated. Based on the exergy analysis, exergy destruction in absorption is the dominant factor that is unavoidable in low-temperature collectors. It was shown that there is an optimum suction value at which the second-law efficiency is maximized. At the optimum point, temperature rise can reach 54 K, which is hardly possible with a flat plate collector. Based on the exergy analysis, the relation between tube wall temperature and air outlet temperature in their dimensionless forms at the optimum working condition was derived, and it was shown that effectiveness at the optimum working condition is around 0.5. This means that the air temperature rise shall be half of the temperature difference between collector wall and the ambient temperatures. A high outlet temperature besides the low cost of construction and maintenance are the main advantages of this air heater. With such a high temperature rise, this type of collector can increase the use of solar energy in domestic applications.
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(This article belongs to the Topic Advances in Solar Heating and Cooling)
Open AccessArticle
Time-Dependent Multi-Particle Model Describing the Hydrogen Absorption of Nanocrystalline Magnesium Powders: A Case Study
by
Ádám Révész and Áron Pintér
Energies 2024, 17(10), 2322; https://doi.org/10.3390/en17102322 (registering DOI) - 11 May 2024
Abstract
Classical kinetic models describing the hydrogen absorption of nanocrystalline metallic hydrides generally do not involve any parameter related to the change in the crystallite size during the hydrogenation at constant temperature. In the present investigation, ball-milled nanocrystalline Mg powders exhibiting lognormal crystallite size
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Classical kinetic models describing the hydrogen absorption of nanocrystalline metallic hydrides generally do not involve any parameter related to the change in the crystallite size during the hydrogenation at constant temperature. In the present investigation, ball-milled nanocrystalline Mg powders exhibiting lognormal crystallite size distribution have been subjected to hydrogen absorption in a Sievert-type apparatus. Partially absorbed states were achieved by interrupting the hydrogenation cycle at different hydrogen content, i.e., when 15%, 50%, and 90% of Mg powder transformed to MgH2. The evolution of the characteristic size of the nucleating MgH2 phase was determined from X-ray diffraction analysis. Considering the crystallite size distribution of the as-milled powder agglomerate as well as the growth during the isothermal hydrogenation process, a time-dependent multi-particle reaction function was developed. It was shown unambiguously for this case study that the measured hydrogen absorption curve of the ball-milled Mg powder shows the best correlation with this model when it is compared to classical kinetic functions or the previously developed multi-particle reaction function excluding the change in the average crystallite size during hydrogenation.
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(This article belongs to the Section A5: Hydrogen Energy)
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Open AccessArticle
Reservoir Simulations of Hydrogen Generation from Natural Gas with CO2 EOR: A Case Study
by
Krzysztof Miłek, Wiesław Szott, Jarosław Tyburcy and Alicja Lew
Energies 2024, 17(10), 2321; https://doi.org/10.3390/en17102321 (registering DOI) - 11 May 2024
Abstract
This paper addresses the problem of hydrogen generation from hydrocarbon gases using Steam Methane Reforming (SMR) with byproduct CO2 injected into and stored in a partially depleted oil reservoir. It focuses on the reservoir aspects of the problem using numerical simulation of
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This paper addresses the problem of hydrogen generation from hydrocarbon gases using Steam Methane Reforming (SMR) with byproduct CO2 injected into and stored in a partially depleted oil reservoir. It focuses on the reservoir aspects of the problem using numerical simulation of the processes. To this aim, a numerical model of a real oil reservoir was constructed and calibrated based on its 30-year production history. An algorithm was developed to quantify the CO2 amount from the SMR process as well as from the produced fluids, and optionally, from external sources. Multiple simulation forecasts were performed for oil and gas production from the reservoir, hydrogen generation, and concomitant injection of the byproduct CO2 back to the same reservoir. EOR from miscible oil displacement was found to occur in the reservoir. Various scenarios of the forecasts confirmed the effectiveness of the adopted strategy for the same source of hydrocarbons and CO2 sink. Detailed simulation results are discussed, and both the advantages and drawbacks of the proposed approach for blue hydrogen generation are concluded. In particular, the question of reservoir fluid balance was emphasized, and its consequences were presented. The presented technology, using CO2 from hydrogen production and other sources to increase oil production, also has a significant impact on the protection of the natural environment via the elimination of CO2 emission to the atmosphere with concomitant production of H2.
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(This article belongs to the Section A5: Hydrogen Energy)
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Open AccessArticle
Simulation and Experimental Verification of Dispersion and Explosion of Hydrogen–Methane Mixture in a Domestic Kitchen
by
Haidong Xu, Qiang Deng, Xiaomei Huang, Du Li and Fengwen Pan
Energies 2024, 17(10), 2320; https://doi.org/10.3390/en17102320 (registering DOI) - 11 May 2024
Abstract
Hydrogen is a carbon-free energy source that can be obtained from various sources. The blending of hydrogen represents a transitional phase in the shift from natural gas systems to hydrogen-based systems. However, concerns about the safety implications of introducing hydrogen have led to
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Hydrogen is a carbon-free energy source that can be obtained from various sources. The blending of hydrogen represents a transitional phase in the shift from natural gas systems to hydrogen-based systems. However, concerns about the safety implications of introducing hydrogen have led to extensive discussions. This paper utilizes Fluent 17.0 numerical simulation software to simulate the leakage of hydrogen-blended natural gas in a closed domestic kitchen and analyze the concentration distribution and its variation pattern after a leakage. An experimental platform is set up, and a mixture of nitrogen and helium gas is used as a substitute for hydrogen-blended natural gas for the simulations and experiments. The simulation results demonstrate that the leaked gas spreads and accumulates towards the top of the space, gradually filling the entire area as the leak persists. As the hydrogen content in the leaked gas increases, the dispersion capacity of the gas in the confined space also increases. Furthermore, as the flow rate of the leaked gas increases, the average concentration of the leaked gas rises, and the gas stratification in the confined kitchen diminishes. The concentration distribution observed in the experiments aligns with the simulation results. After establishing the feasibility conditions of the model, the dispersion of the hydrogen-blended natural gas in the kitchen is further simulated. The results suggest that blending hydrogen into the gas enhances the dispersion of the gas after a leak, leading to a wider distribution within the kitchen and an increased risk in the event of a leak. Additionally, this paper employs the CASD module of FLACS 11.0 software to construct a three-dimensional geometric model of the domestic kitchen for simulation studies on the explosion of hydrogen-blended natural gas in a confined space. By adjusting the hydrogen ratio in the combustible gases present in the space and examining the variations in hydrogen concentration and external conditions, such as opening or closing the door, the influence on parameters including the peak explosion pressure, explosion overpressure, explosion flame temperature, and explosion response time are examined. Furthermore, the extent of the explosion area is determined, and the effect of hydrogen on the blast is clarified.
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(This article belongs to the Special Issue Hydrogen Safety for Energy Applications)
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Open AccessArticle
A Study of the Thermal Management and Discharge Strategies of Lithium-Ion Batteries in a Wide Temperature Range
by
Kaixuan Li, Chen Sun, Mingjie Zhang, Shuping Wang, Bin Wei, Yifeng Cheng, Xing Ju and Chao Xu
Energies 2024, 17(10), 2319; https://doi.org/10.3390/en17102319 (registering DOI) - 11 May 2024
Abstract
The performance of lithium-ion batteries is greatly influenced by various factors within their operating environment, which can significantly impact their overall efficiency and effectiveness. In this paper, a multi-physics field electrochemical thermal model is established to measure the physical parameters of a battery
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The performance of lithium-ion batteries is greatly influenced by various factors within their operating environment, which can significantly impact their overall efficiency and effectiveness. In this paper, a multi-physics field electrochemical thermal model is established to measure the physical parameters of a battery module during the charge/discharge process. The effects of working temperature, current rate, and convective heat transfer coefficient are investigated by establishing an electrochemical and thermal model. The results are obtained by conducting numerous parameterized scans to analyze the system’s state across various operating conditions, enabling the determination of its temperature and the selection of appropriate cooling measures accordingly. Based on the internal and external conditions of battery operation, parameter selection corresponding to the operating range is divided into several stages, with thermal management strategies provided for each stage. The existing framework facilitates the design of battery packs equipped with efficient thermal management strategies, thereby enhancing the battery systems’ reliability and performance. Furthermore, it aids in establishing optimal operational and safety boundaries for batteries.
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(This article belongs to the Topic Battery Design and Management)
Open AccessArticle
Optimizing High-Voltage Direct Current Transmission Corridors: Dynamic Thermal Line Rating for Enhanced Renewable Generation and Greenhouse Gas Emission Reductions
by
Veenavi Pemachandra, Petr Musilek and Gregory Kish
Energies 2024, 17(10), 2318; https://doi.org/10.3390/en17102318 (registering DOI) - 11 May 2024
Abstract
Recently, significant attention has been paid to the large-scale use of renewable energy through high-voltage direct current (HVDC) because of its economic feasibility. At the same time, the growing demand for electricity and the increasing penetration of renewable energy sources have prompted the
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Recently, significant attention has been paid to the large-scale use of renewable energy through high-voltage direct current (HVDC) because of its economic feasibility. At the same time, the growing demand for electricity and the increasing penetration of renewable energy sources have prompted the electric power industry to explore methods to optimize the use of the existing grid infrastructure. Dynamic thermal line rating (DTLR) is a technique that allows transmission lines to operate at their maximum capacity, considering their real-time operating conditions. The majority of existing research on this topic has focused predominantly on employing DTLR in alternating current systems and exploring their applications. This study presents a novel approach by applying DTLR to HVDC transmission corridors, with the aim of maximizing the utilization of their capacity and facilitating increased integration of renewable energy. The performance of the proposed approach is evaluated by conducting a case study for an HVDC transmission line in Alberta, Canada. On average, the mean increase in ampacity above the static rating is 64% during winter and 34% during summer. This additional capacity can be used to integrate wind energy, replacing coal-fired generation. This leads to a significant reduction in greenhouse gas emissions, also quantified in this contribution.
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(This article belongs to the Section F: Electrical Engineering)
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Coordinated Control of Proton Exchange Membrane Electrolyzers and Alkaline Electrolyzers for a Wind-to-Hydrogen Islanded Microgrid
by
Zhanfei Li, Zhenghong Tu, Zhongkai Yi and Ying Xu
Energies 2024, 17(10), 2317; https://doi.org/10.3390/en17102317 (registering DOI) - 11 May 2024
Abstract
In recent years, the development of hydrogen energy has been widely discussed, particularly in combination with renewable energy sources, enabling the production of “green” hydrogen. With the significant increase in wind power generation, a promising solution for obtaining green hydrogen is the development
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In recent years, the development of hydrogen energy has been widely discussed, particularly in combination with renewable energy sources, enabling the production of “green” hydrogen. With the significant increase in wind power generation, a promising solution for obtaining green hydrogen is the development of wind-to-hydrogen (W2H) systems. However, the high proportion of wind power and electrolyzers in a large-scale W2H system will bring about the problem of renewable energy consumption and frequency stability reduction. This paper analyzes the operational characteristics and economic feasibility of mainstream electrolyzers, leading to the proposal of a coordinated hydrogen production scheme involving both a proton exchange membrane (PEM) electrolyzer and an alkaline (ALK) electrolyzer. Subsequently, a coordinated control based on Model Predictive Control (MPC) is proposed for system frequency regulation in a large-scale W2H islanded microgrid. Finally, simulation results demonstrate that the system under PEM/ALK electrolyzers coordinated control not only flexibly accommodates fluctuating wind power but also maintains frequency stability in the face of large disturbances. Compared with the traditional system with all ALK electrolyzers, the frequency deviation of this system is reduced by 25%, the regulation time is shortened by 80%, and the demand for an energy storage system (ESS) is reduced. The result validates the effectiveness of MPC and the benefits of the PEM/ALK electrolyzers coordinated hydrogen production scheme.
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(This article belongs to the Topic Advanced Operation, Control, and Planning of Intelligent Energy Systems)
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