Cleaner Energy Systems最新文献

{"title":"Operational greenhouse gas emissions of various energy carriers for building heating","authors":"Jordi F.P. Cornette,&nbsp;Julien Blondeau","doi":"10.1016/j.cles.2024.100148","DOIUrl":"10.1016/j.cles.2024.100148","url":null,"abstract":"<div><div>The decarbonisation of the building heating sector requires a shift from decentralised fossil fuel heating appliances to systems converting energy carriers with low greenhouse gas (GHG) emissions. However, for certain energy carriers, a considerable portion of GHG emissions arises upstream during production, processing and transportation, rather than during energy conversion. Accurately quantifying these indirect GHG emissions typically requires life cycle assessments, which are often resource-intensive and impractical during the early stages of energy system design. This study introduces operational GHG emissions as a pragmatic metric for the preliminary assessment of energy carrier environmental impact in building heating applications. These operational GHG emissions include both direct CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions and indirect CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>, CH<span><math><msub><mrow></mrow><mrow><mn>4</mn></mrow></msub></math></span> and N<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>O emissions. Based on a comprehensive literature analysis, average estimates are proposed for the operational GHG emissions of various energy carriers within a European context, including natural gas, oil, coal and wood, as well as the average European and Belgian electricity grid, and hydrogen from various production methods. The findings underscore the significant contribution of indirect GHG emissions, as the selection of the energy carrier with the lowest environmental impact hinges on whether direct emissions alone or the broader operational GHG emissions are considered. By integrating operational GHG emissions into the early design stages of energy systems, stakeholders can make more informed decisions about which energy systems warrant further investigation, thereby facilitating more sustainable energy system development from the outset.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100148"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142327142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic and environmental impact assessment of renewable energy integration: A review and future research directions","authors":"Md Tasbirul Islam ,&nbsp;Sikandar Abdul Qadir ,&nbsp;Amjad Ali ,&nbsp;Muhammad Waseem Khan","doi":"10.1016/j.cles.2024.100162","DOIUrl":"10.1016/j.cles.2024.100162","url":null,"abstract":"<div><div>This review article critically examines papers on renewable energy integration (REI), with a specific focus on the economic and environmental impact assessments across multiple sectors, including agriculture, transportation, electricity production, buildings, and biofuel production. A total of 111 articles from the Web of Science Core Collection database were reviewed using a systematic literature review methodology and content analysis techniques. The results indicate that evaluation-type studies, particularly those employing optimization and simulation-based methods, such as techno-economic analysis (TEA) (28 papers) and life cycle assessment (LCA) (20 papers), were the most prominent approaches used for economic and environmental analyses. Optimization techniques such as mixed-integer linear programming (6 papers), genetic algorithms (GA) (5 papers), and particle swarm optimization (PSO) (4 papers) were widely applied. The quantitative analysis of impact assessment indicators shows that REI has yielded significant long-term positive results across multiple RE sources, sectors, and regions. A detailed examination of mathematical models (e.g., optimization techniques) and simulation modeling combined with LCA will assist future researchers in optimizing energy systems and enhancing sustainability in sectors such as agriculture and water desalination. The conceptual inclusion of circular economy within the research field needs to be more present among researchers, and most of the studies focused on technical aspects of RE integration and assessing impacts rather than identifying a systemic change across the sectors. Several future research directions have been identified across sectors, offering opportunities to advance the field. Policymakers will find this paper valuable for informed decision-making and the development of robust policy frameworks.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100162"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142707013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-Term forecasting of floating photovoltaic power generation using machine learning models","authors":"Mohd Herwan Sulaiman ,&nbsp;Mohd Shawal Jadin ,&nbsp;Zuriani Mustaffa ,&nbsp;Mohd Nurulakla Mohd Azlan ,&nbsp;Hamdan Daniyal","doi":"10.1016/j.cles.2024.100137","DOIUrl":"10.1016/j.cles.2024.100137","url":null,"abstract":"<div><p>Floating photovoltaic (FPV) power generation requires accurate short-term forecasting to optimize operational efficiency and enhance grid integration. This study investigates the application of machine learning models for predicting FPV power generation using data from the Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) solar installation, which has a capacity of 157.20 kWp. Data were collected at 15-minute intervals from January 15 to January 21, 2024, encompassing nine input features such as ambient temperature, transient horizontal irradiation, daily horizontal irradiation, AC voltages, and AC currents for phases A, B, and C, with the total active power in kW as the target variable. The dataset was divided into a training set (first five days) and a testing set (remaining two days), and five machine learning models—Neural Networks (NN), Random Forest (RF), Extreme Learning Machine (ELM), Support Vector Regression (SVR), and Long Short-Term Memory (LSTM)—were employed. The results indicate that the Neural Networks model consistently outperforms the other machine learning algorithms in terms of predictive accuracy. These findings underscore the efficacy of machine learning techniques in forecasting FPV power generation, which has significant implications for enhancing the operational efficiency and grid integration of floating solar installations.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100137"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000311/pdfft?md5=7ce96141a620bc0a687d5ccbf423c62a&pid=1-s2.0-S2772783124000311-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142012196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing energy access in rural areas: Intelligent microgrid management for universal telecommunications and electricity","authors":"Kanlou Zandjina Dadjiogou ,&nbsp;Ayité Sénah Akoda Ajavon ,&nbsp;Yao Bokovi","doi":"10.1016/j.cles.2024.100136","DOIUrl":"10.1016/j.cles.2024.100136","url":null,"abstract":"<div><p>In rural areas lacking an electricity grid, cell phone operators use generators to power their facilities. At the same time, however, the local population is finding it difficult to use the cell phones and other electronic devices for which these operators are deploying their efforts. This situation, due to the problem of access to energy, hinders universal access to telecommunications. The present study aims to solve this problem using microgrid techniques. A microgrid consisting of photovoltaic panels, a genset and storage batteries has been designed to meet the needs of cell phone operators' sites in Bapure, a rural locality in Togo. The focus is on managing energy flows between the various sources of the microgrid, and between the needs of the cell phone operators' site and those of the local population. To resolve the lack of solar irradiation data at Bapure, hourly solar irradiation was predicted using the Adaptive Neuro Fuzzy Inference System (ANFIS) algorithm to obtain a realistic result. Optimization studies were then carried out using the Particle Swarm Optimization (PSO) algorithm to determine the optimum system configuration to ensure continuity of service at the operator's site. The simulation results show that the proposed system has a surplus of energy production at all times, which can be used to supply electricity to the population at a cost equal to 0.0185 USD, with a solar energy utilization rate of 98,95 % and a generator that only needs to operate at 0.15 % throughout the year. The results obtained indicate that a renewable energy system can provide a more efficient solution for electrifying the rural mobile operator's sites and the local population, and can improve the quality of service for the telecommunications industries.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100136"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S277278312400030X/pdfft?md5=ae5f5c5d0670b19a102b4e6150630ef8&pid=1-s2.0-S277278312400030X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142049098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retraction notice to “Elasticity of substitution between clean energy and non-clean energy: Evidence from the Chinese electricity industry” [Cleaner Energy Systems 8 (2024) 100117]","authors":"Caifei Luo,&nbsp;Keyu Zhang","doi":"10.1016/j.cles.2024.100158","DOIUrl":"10.1016/j.cles.2024.100158","url":null,"abstract":"<div><div>This article has been retracted: please see Elsevier Policy on Article Withdrawal (<span><span>https://www.elsevier.com/about/policies/article-withdrawal</span><svg><path></path></svg></span>).</div><div>&lt; This article has been retracted at the request of the Authors.</div><div>Post-publication, the authors found that using these data, which are not based on officially published documents, as a foundation for scenario setting could lead to significant deviations in the final simulation results. Thus, the authors feel that the findings of the manuscript cannot be relied upon and that the article needs to be retracted.</div><div>The authors would like to apologize for any inconvenience caused to the readers.&gt;</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100158"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143103035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Oxy-hydrogen gas as a sustainable fuel for the welding industry: Alternative for oxy-acetylene gas","authors":"Juliet Attah ,&nbsp;Latifatu Mohammed ,&nbsp;Andrew Nyamful ,&nbsp;Paulina Donkor ,&nbsp;Anita Asamoah ,&nbsp;Mohammed Nafiu Zainudeen ,&nbsp;John Adjah ,&nbsp;Charles K. Klutse ,&nbsp;Sylvester Attakorah Birikorang ,&nbsp;Frederick Agyemang ,&nbsp;Owiredu Gyampo","doi":"10.1016/j.cles.2024.100160","DOIUrl":"10.1016/j.cles.2024.100160","url":null,"abstract":"<div><div>The urgent need to address climate change has prompted researchers to explore sustainable power generation methods using low or net-zero fuels and energy storage. Historically, gases derived from acetylene or LPG have been used for welding in factories. Despite its negative effects on the environment and human health, acetylene gas remains widely used. Examples of pollutants released from acetylene gas include carbon dioxide and carbon monoxide, both of which contribute to the greenhouse effect and global warming. There is a need for an alternative gas that is environmentally friendly, economically viable, and readily available. Hydrogen gas is currently used across various industries and is increasingly considered a potential primary fuel source for the future. In this study, a hydrogen fuel cell was used to produce HHO (brown) gas as a replacement for acetylene through electrolysis. The HHO gas was used to weld a randomly selected test piece, which was then evaluated alongside an acetylene-welded test piece. The integrity of both welds was assessed using dye-penetrant and radiographic testing, showing that welds from both gases were strong. Welding with HHO gas, followed by non-destructive inspection, also proved effective, with any defects attributed to inexperience in welding. The adoption of HHO gas in the welding industry is recommended due to its potential socio-economic benefits, health advantages, and environmental friendliness. Challenges related to initial investment costs may be mitigated as technology advances. Further research should focus on qualitative weld testing, economic and environmental impact assessments, and developing a business model for HHO systems.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100160"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142757001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Techno economic study of floating solar photovoltaic project in Indonesia using RETscreen","authors":"Muhammad Rifansyah,&nbsp;Dzikri Firmansyah Hakam","doi":"10.1016/j.cles.2024.100155","DOIUrl":"10.1016/j.cles.2024.100155","url":null,"abstract":"<div><div>The utilization of solar energy is crucial for the advancement of sustainable power generation on a worldwide scale, driven by environmental concerns and the depletion of fossil fuels. Indonesia's goal is to achieve carbon neutrality by 2060 and it is aggressively advocating for solar energy, which includes the implementation of new methods such as floating photovoltaic (PV) systems. This study evaluates the Techno-Economic Feasibility of Indonesia's Cirata 145 MW floating solar PV project by employing RETScreen technology. The objective is to improve the long-term financial stability, decrease greenhouse gas emissions, and suggest viable choices for improvement. Examining three scenarios that involve alterations in carbon emissions, energy pricing, and loan interest rates demonstrates different levels of project feasibility. The introduction of carbon tax emission pricing has a substantial impact on the feasibility of projects. This study provides useful insights into doing techno-economic feasibility assessments using RETScreen for floating photovoltaic (PV) systems. It demonstrates how modifying parameters can effectively mitigate project risks.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100155"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the impacts of low-carbon intensity hydrogen integration in oil refineries","authors":"Erik López-Basto ,&nbsp;Gijsbert Korevaar ,&nbsp;Samantha Eleanor Tanzer ,&nbsp;Andrea Ramírez Ramírez","doi":"10.1016/j.cles.2024.100161","DOIUrl":"10.1016/j.cles.2024.100161","url":null,"abstract":"&lt;div&gt;&lt;div&gt;This paper evaluates the potential impacts of introducing low-carbon intensity hydrogen technologies in two oil refineries with different complexity levels, emphasizing the role of hydrogen production in reducing CO&lt;sub&gt;2&lt;/sub&gt; emissions. The novelty of this work lies in three key aspects: Comprehensive system analysis of refinery complexity using real site data, integration of low-carbon Hydrogen technologies, long-term and short-term strategies. Two Colombian refineries serve as case studies, with technological solutions adapted to their complexity levels. The methodology involves evaluating different options for hydrogen production, accounting for improvement in technological efficiency over time.&lt;/div&gt;&lt;div&gt;The refinery systems were evaluated in a cost-optimization model built in Linny-r. Three different scenarios were considered, Business-As-Usual (BAU), high, and low-ambitions decarbonization scenarios, focusing on the time horizons of 2030 and 2050.&lt;/div&gt;&lt;div&gt;When comparing the two case studies, the preferred decarbonization strategy for both facilities involves the substitution of SMR technology with water electrolyzers powered by renewable electricity. Post-2030, biomass-based hydrogen technology is still a costly alternative; however, to achieve CO&lt;sub&gt;2&lt;/sub&gt; neutrality, negative emissions storage of biogenic CO&lt;sub&gt;2&lt;/sub&gt; emerges as an achievable alternative.&lt;/div&gt;&lt;div&gt;Our results indicate the achievability of CO&lt;sub&gt;2&lt;/sub&gt; reduction objectives in both refineries. Our results show that achieving long-term CO&lt;sub&gt;2&lt;/sub&gt; neutrality requires both refineries to increase renewable electricity production by 5 to 6 times for powering water electrolyzers, steam production by 2 to 2.5 times for CO&lt;sub&gt;2&lt;/sub&gt; capture, and supply of dry biomass by 2.6 to 4.5 kt/d.&lt;/div&gt;&lt;div&gt;The two most significant factors influencing the refining net margin in the decarbonization scenarios are primarily the CO&lt;sub&gt;2&lt;/sub&gt; and the renewable electricity prices. The short-term horizon emerges as the pivotal period, particularly within the high-ambition decarbonization scenarios. In this context, the medium complexity refinery demonstrates economic viability until a CO&lt;sub&gt;2&lt;/sub&gt; price of 140 €/t CO&lt;sub&gt;2&lt;/sub&gt;, while the high complexity refinery endures up to 205 €/t CO&lt;sub&gt;2&lt;/sub&gt;.&lt;/div&gt;&lt;div&gt;The high complexity refinery is better prepared to face the challenges of decarbonization and the impacts generated on the refining margin. Compared to the BAU scenario, the high complexity refinery shows a negative impact on the net margin that corresponds to a 40 % and 5 % reduction in the short and long term, respectively. Meanwhile, for the medium complexity refinery, the impact on net margin amounts to a 52 % reduction in the short term and a 27 % improvement in the long term.&lt;/div&gt;&lt;div&gt;Furthermore, our research highlights the significant potential for reducing CO&lt;sub&gt;2&lt;/sub&gt; emissions by fully eliminating the use of refinery gas as fuel, providing alternat","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100161"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the substitution within clean energy: Evidence from China's top 14 hydropower provinces","authors":"Yubao Wang,&nbsp;Huiyuan Pan,&nbsp;Junjie Zhen,&nbsp;Boyang Xu","doi":"10.1016/j.cles.2024.100152","DOIUrl":"10.1016/j.cles.2024.100152","url":null,"abstract":"<div><div>This paper quantitatively examines the substitution effects within China's clean energy sector, focusing on the hydropower and new energy generation sectors across the top 14 hydropower-producing provinces, which collectively contribute to over 80 % of the country's total hydropower output. To provide a comprehensive analysis of regions that significantly influence national trends, the study utilizes the Cross-Price Elasticity (CPE) and Morishima Elasticity of Substitution (MES). CPE measures how the quantity demanded of one energy source responds to a change in the price of another, while MES assesses the sensitivity of the ratio between two energy inputs to price changes. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model is employed to forecast energy substitution dynamics, offering robust predictive accuracy. The average MES between clean energy and thermal power is 0.663, indicating a moderate substitution relationship, with the effect more pronounced in summer. Additionally, the mean MES between hydropower and new energy generation is 2.067, reflecting a strong substitution effect between these two clean energy forms. Furthermore, the SARIMA model shows a mean squared error (MSE) as low as 0.0006 in some cases, demonstrating its robust predictive accuracy in forecasting energy substitution dynamics. These results offer empirical support for policies aimed at reducing reliance on thermal power and promoting clean energy development in key provinces.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100152"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing a hybrid wind-solar-biomass system with battery and hydrogen storage using generic algorithm-particle swarm optimization for performance assessment","authors":"Shree Om Bade,&nbsp;Olusegun Stanley Tomomewo","doi":"10.1016/j.cles.2024.100157","DOIUrl":"10.1016/j.cles.2024.100157","url":null,"abstract":"<div><div>This paper investigates the optimal design of a hybrid renewable energy system, integrating wind turbines, solar photovoltaic systems, biomass, and battery and hydrogen storage to ensure a reliable energy supply at the lowest annual cost for a residential load in Kern County, USA. The hybrid generic algorithm particle swarm optimization (GAPSO) algorithm was adopted to determine the optimal configuration of parameters and cost-effectiveness, considering technical, economic, environmental, and social performance indicators. The generic algorithm (GA) and particle swarm optimization (PSO) validate the effectiveness of the proposed technique, showcasing its efficiency in system optimization. The findings indicate that GAPSO outperforms GA and PSO due to its rapid convergence, lowest final fitness value, and stable optimization process. The hybrid GAPSO's performance, combined with the different capacities of wind turbines (4,561 kW), solar PV (8,480 kW), biomass (2,261 kW), battery banks (8,000 kWh), and fuel cells (2,392 kW), resulted in an annual cost of $6,239,193; energy cost and net present value of $0.48/kWh and $101,333,937. The system maintained a supply loss of 0.8 %, achieved an availability index of 99.2 %, a renewable energy fraction of 88.87 %, GHGs emission of 953,615 kg, land use of 3,842,875 m², and water consumption 528,678 L respectively. GAPSO achieved a 2.17 % and 0.01 % improvement in cost-effectiveness and 11.11 % increase in reliability compared to GA and PSO.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100157"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}