Renewable Energy Focus最新文献

{"title":"Green microgrid’s LFC using recursive step-by-step optimized multi-stage fuzzy controller with separated inference systems","authors":"H. Shayeghi ,&nbsp;A. Rahnama ,&nbsp;N. Bizon","doi":"10.1016/j.ref.2024.100625","DOIUrl":"10.1016/j.ref.2024.100625","url":null,"abstract":"<div><p>Amidst the growing integration of renewable energy sources (RES), the efficient administration of load-frequency control (LFC) in microgrids (MG) continues to be a significant challenge. In response to the complexities of modern MGs operations, this study introduces a novel two-stage fuzzy controller aimed at enhancing the system’s dynamic responses. The proposed controller consists of two levels, each of which contains a separate and autonomous fuzzy inference system (FIS). The proposed controller includes proportional (P) and derivative (D) control operators in the first level, and in the second level, the combination of proportional and integral (I) operators is used. The suggested fuzzy P-fuzzy D multiplied by 1+(fuzzy P - fuzzy I) which is named FPFD-(1+FPFI) controller parameters are tuned by solving an optimization problem to reduce energy wastage and prevent undesirable dynamic responses. The parameters of the controller and the membership functions (MF) at each level are both optimized. The optimization process utilizes an enhanced particle swarm optimization (PSO) algorithm. The decisive superiority of the FPFD-(1+FPFI) controller has been confirmed by evaluating its performance in an all-renewable MG compared to conventional controllers. Reduction of frequency deviation in the face of disturbances in the demand side or production of renewables, better performance in the presence of uncertainty in the parameters of the system model, better dynamic responses against nonlinear factors such as time delays, and also, robustness against cyberattacks are prominent features of the proposed FPFD-(1+FPFI) controller. In addition, the results of the studies show that the controller, with its fast and accurate performance, reduces the dependence on the energy storage systems to maintain the stability of the system by more than 40%. The efficiency of the proposed controller is also verified through laboratory scale evaluation.</p></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"51 ","pages":"Article 100625"},"PeriodicalIF":4.2,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142167988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing and Exploring Untapped Micro-Hydro Hybrid Systems: a Multi-Objective Approach for Crystal Lake as a Large-Scale Energy Storage Solution","authors":"Sharaf K. Magableh,&nbsp;Oraib Dawaghreh,&nbsp;Caisheng Wang","doi":"10.1016/j.ref.2024.100624","DOIUrl":"10.1016/j.ref.2024.100624","url":null,"abstract":"<div><p>Increasing electricity demand and concerns about climate change and fossil fuel consumption have highlighted the importance of renewable energy resources and storage systems. This paper proposes a method for exploring untapped pumped hydro storage potentials to accommodate intermittent renewable energy generation profiles. Hourly measured data from 2022 in Benzie County, Michigan, United States, were gathered for system sizing and a thorough, realistic analysis. By employing the multi-objective grey wolf optimization algorithm, we formulated optimal sizing and energy-management strategies for three different scenarios. Unlike similar studies, the 3^rd with triple objective functions (OFs) scenario aims to maximize both reliability and ecological OFs while minimizing the cost OF. It has shown promising results with multiple solutions, considering economic, environmental, and reliability factors. A case study conducted in Crystal Lake, Michigan, revealed that although Crystal Lake would function only as a micro-hydro power facility, it is a promising and huge storage unit with a substantial storage capacity of around 14.9734GWh. The system investigated is significant in the USA due to its rapid deployment capabilities, minimal construction requirements, and ease of integration with the distribution grid. The fuzzy logic method was employed to identify the best non-dominant solution among the other solutions. These outcomes include a notably low levelized cost of energy at 0.046147$/kWh, a robust index of reliability of 99.705%, and a significant reduction in CO₂ emissions amounting to 7.9142×10³ tons/year, when considering the triple OFs. The paper’s methodology provides valuable insights for regions aiming to utilize renewable energy from untapped storage sources.</p></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"51 ","pages":"Article 100624"},"PeriodicalIF":4.2,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142167987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Technician assignment in multi-shift maintenance schedules in an offshore wind farm","authors":"Md Imran Hasan Tusar ,&nbsp;Bhaba R Sarker","doi":"10.1016/j.ref.2024.100616","DOIUrl":"10.1016/j.ref.2024.100616","url":null,"abstract":"<div><p>Offshore wind farms are becoming more and more important to sustainable energy strategies, yet their maintenance presents unique logistical challenges. The focus of this research is the <em>Technician Assignment Problem (TAP)</em> which involves a complicated and fluctuating scheduling problem. The key objective is to determine the most effective assignment of technicians to maintenance tasks to maximize operational efficiency and ensure reliable service. This study introduces a mathematical optimization model that processes numerous variables—technician availability, skill sets, and temporal constraints—to minimize unmet maintenance needs and ensure equitable workload distribution. The model is based on assumptions derived from actual operational conditions and human resource practices, guaranteeing that its results are not only theoretically valid but also practically feasible. <em>TAP</em> adheres to labor regulations, employs human resource capabilities, and aims for a smart assignment of workforce. It complies with restrictions that prevent excessive work, require breaks, and ensure that technicians are assigned tasks that match their skills, thus promoting the well-being of the workforce and the efficiency of operations. The computational investigation of the model shows that it has a remarkable ability to improve scheduling decisions which effectively reduce unassigned positions and uniformly distribute work hours. In essence, this research contributes a methodologically robust framework to the field of workforce scheduling, with the potential to inform the maintenance strategies of offshore wind farms and similar complex service systems.</p></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"51 ","pages":"Article 100616"},"PeriodicalIF":4.2,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755008424000802/pdfft?md5=c3372bd2c2ce9bd496f06d74dc3a53be&pid=1-s2.0-S1755008424000802-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142150292","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":"A Three-Step Weather Data Approach in Solar Energy Prediction Using Machine Learning","authors":"Tolulope Olumuyiwa Falope ,&nbsp;Liyun Lao ,&nbsp;Dawid Hanak","doi":"10.1016/j.ref.2024.100615","DOIUrl":"10.1016/j.ref.2024.100615","url":null,"abstract":"<div><p>Solar energy plays a critical part in lowering CO₂ emissions and other greenhouse gases when integrated into the grid. Higher solar energy penetration is hindered by its intermittency leading to reliability issues. To forecast solar energy production, this study suggests a three-step forecasting method that selects weather variables with a moderate to strong positive correlation to solar radiation using Pearson correlation coefficient analysis. Low-level data fusion is used to combine weather inputs from a reliable local weather station and an on-site weather station, significantly improving the forecasting model’s accuracy regardless of the machine learning method used. Weather data was obtained from the Kisanhub Weather Station located in Cranfield University, UK and the meteorological station in Bedford, UK. In addition, PV power supply data was obtained from four solar plants. Using the Regression Learner app in MATLAB, the proposed architecture is tested on a utility scale solar plant (1 MW), showing a 6% and 13% prediction accuracy improvement when compared to solely using data from the on-site and local weather station respectively. It is further validated using data from three residential rooftop solar systems (8 kW, 10.5 kW and 15 kW), achieving root-mean square values of 0.0984, 0.0885, and 0.1425 respectively. The data was pre-processed using both rescaling and list-wise deletion methods. Training and testing data from the 1 MW solar plant was divided into 75% and 25% respectively, while 100% of the residential rooftop solar plants was used for validation.</p></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"50 ","pages":"Article 100615"},"PeriodicalIF":4.2,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755008424000796/pdfft?md5=8d81b05eac4c4762d69e0fae4c13611b&pid=1-s2.0-S1755008424000796-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142058525","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":"A review of the use of different technologies/methods for the transmission of solar radiation for lighting purposes using optical fibers","authors":"Prashant Upadhyay,&nbsp;Piyush Kuchhal,&nbsp;Surajit Mondal","doi":"10.1016/j.ref.2024.100614","DOIUrl":"10.1016/j.ref.2024.100614","url":null,"abstract":"<div><p>The use of solar radiation for lighting purposes has gained significant attention in recent years because of its potential to provide a sustainable and renewable source of energy. One approach to harnessing solar radiation for lighting is through the use of optic fiber technology, which allows for the efficient transmission of light from a source to a desired location. This review provides a comprehensive analysis of the different technologies and methods used for the transmission of solar radiation for lighting purposes using optic fibers. The first topic of our discussion was the basic principles of optic fiber technology and its applications in solar lighting to examine the different methods used for coupling solar radiation into optic fibers, such as the use of solar concentrators, mirrors, and lenses. Finally, this review introduces the challenges and prospects of using optic fiber technology for solar lighting applications and the current development status of this technology. This review concludes that optic fiber technology is a promising approach for the transmission of solar radiation for lighting purposes and has the potential to provide significant energy savings and environmental benefits. However, further research is needed to optimize the efficiency of optic fiber systems and to develop cost-effective solutions for their implementation in real-world applications.</p></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"50 ","pages":"Article 100614"},"PeriodicalIF":4.2,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142006774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Paving the way for low-carbon hydrogen supply chain deployment by exploring the potential of renewable energies and multisectoral hydrogen demand: Case study of France","authors":"Renato Luise ,&nbsp;Annabelle Brisse ,&nbsp;Catherine Azzaro-Pantel","doi":"10.1016/j.ref.2024.100613","DOIUrl":"10.1016/j.ref.2024.100613","url":null,"abstract":"&lt;div&gt;&lt;p&gt;France has set ambitious targets for hydrogen production in its National Roadmap, aiming to install at least 6.5 GW of electrolyzer capacity and produce 700,000 tons of hydrogen annually by 2030. The country is focusing on producing renewable or low-carbon hydrogen primarily through electrolysis. However, it faces significant barriers in rapidly scaling up renewable energy infrastructure and may need to consider import strategies to address potential shortages. Addressing these challenges requires investigating whether the availability of renewable energy for the production of electrolytic hydrogen could become a limiting factor for hydrogen adoption and potentially act as a bottleneck in its market integration. The methodology merges forecasts from the public and private sectors to address both renewable and non-renewable electricity production and the energy needed for rising hydrogen demand. The approach developed involves estimating France’s renewable energy supply up to 2050 and determines how much of this energy can be allocated to hydrogen production to ensure it remains carbon-free and genuinely renewable. Unlike many existing roadmaps that take a more general approach, the innovative part of this study is developing a territorial perspective to conduct a detailed analysis of potential mismatches between hydrogen supply and demand.&lt;/p&gt;&lt;p&gt;Three distinct sources of electricity are considered for the electrolyzers, which could be connected to the grid or directly to renewable power plants: low-carbon electricity from the French grid, renewable electricity from re-powered solar and wind farms, and renewable electricity from newly installed power plants. Total electricity demand is projected to rise from 475 TWh/y in 2020 to 754 TWh/y in 2050, with the share of renewable energy increasing from 19% in 2020 to 69% in 2050.&lt;/p&gt;&lt;p&gt;The study evaluates the demand for hydrogen in two key sectors, industry, which is heavily dependent on hydrogen, and mobility, which currently has a more modest contribution. Hydrogen demand is expected to increase from nearly 310 ktons per day in 2025 to over 2650 ktons per day by 2050.&lt;/p&gt;&lt;p&gt;Given an average specific consumption of 55 kWh of electricity per kg of hydrogen produced, the total electricity demand for electrolytic hydrogen production is projected to grow from 17 TWh/year in 2025 to 146 TWh/year in 2050.&lt;/p&gt;&lt;p&gt;It can be concluded that allocating the entire anticipated production from re-powered solar and on-shore wind farms in the coming years will not be sufficient to meet the electricity demand required for electrolytic hydrogen production. To prevent renewable energy from becoming a bottleneck for hydrogen market integration and to avoid the need for hydrogen imports, it is crucial to allocate 5% to 10% of the projected renewable output from newly installed plants to address the increasing hydrogen demand. This result is key to creating an optimal design model for hydrogen supply chains.&lt;/p&gt;&lt;/di","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"50 ","pages":"Article 100613"},"PeriodicalIF":4.2,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"System dynamics modeling of leveraging geothermal potential in Indonesia towards emission reduction effort: A case study in Indonesia state-owned energy enterprise","authors":"Dhamar Yudho Aji,&nbsp;Utomo Sarjono Putro","doi":"10.1016/j.ref.2024.100612","DOIUrl":"10.1016/j.ref.2024.100612","url":null,"abstract":"<div><p>In the face of the global climate crisis, geothermal energy emerges as a crucial, sustainable, and low-carbon solution to reduce greenhouse gas emissions and foster economic growth. Despite significant research into geothermal energy in Indonesia, gaps remain in understanding how dynamic interactions among variables can enhance its potential for emission reduction. Therefore, this research aims to identify and analyze the variables influencing geothermal development and their impact on emissions. Employing the system dynamics approach, the study examines the interactions among key factors such as economic growth, energy demand, and policy measures over a projected period from 2022 to 2122. Key findings reveal that strategic interventions like increasing the carbon credit price, implementing carbon taxes, and enhancing renewable energy mix can dramatically reduce national and internal company emissions while advancing geothermal capacity. The study recommends robust government policies and incentives to foster investment in renewable energy, highlighting the crucial role of financial strategies and external funding in achieving Indonesia’s geothermal targets efficiently.</p></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"51 ","pages":"Article 100612"},"PeriodicalIF":4.2,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142150291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"4E analysis and multi-objective optimization of a novel multi-generating cycle based on waste heat recovery from solid oxide fuel cell fed by biomass","authors":"Arian Shabruhi Mishamandani ,&nbsp;Amir Qatarani Nejad ,&nbsp;Najmeh Shabani ,&nbsp;Gholamreza ahmadi","doi":"10.1016/j.ref.2024.100610","DOIUrl":"10.1016/j.ref.2024.100610","url":null,"abstract":"<div><p>The present study optimizes a novel developed cycle including solid oxide fuel cell (SOFC) fed by synthesis gas produced from biomass as well as gas turbine (GT), supercritical carbon dioxide cycle (SCO₂), transcritical carbon dioxide cycle (TCO₂), Organic Rankine Cycle (ORC), thermoelectric generator (TEG), and reverse osmosis (RO)- based desalination. Energy, exergy, exergoeconomic and exergoenvironmental analyses on the developed cycle were investigated. Multi-objective optimization was carried out using of Genetic algorithm using generated power and exergy destruction as objective functions. Sankey diagram data indicate that afterburner holds the highest portion of the total exergy destruction 46.5% (692.24 kW), followed by SOFC which is 20.48% (304.51 kW). Moreover, optimization results showed that the total net power, first and second laws of thermodynamic efficiencies increased by 2.6%, 0.96% and 0.83%, respectively, while exergy destruction decreased by 1%. Furthermore, such a power increase (18.53 kW) using the freshwater produced by RO leads to daily production of 17040 liters of drinking water. According to the exergoeconomic analysis, the minimum flow value pertains to GT at a value of 0.0119 $/GJ, while the TCO₂ turbine has the highest value which is 0.2867 $/GJ. The system product cost rate and exergy destruction cost rate reached 27.0353 $/h, and 10.7012 $/h, respectively. In the case of the exergoenvironmental one, the maximum environmental impact is related to the SCO₂ turbine 0.0212 Pts/GJ, while SOFC has the lowest (0.0002 Pts/GJ). The system product environmental impact and exergy destruction were achieved at optimum values of 2.7503 $/h, and 4.1576 <span><math><mrow><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mo>-</mo><mn>7</mn></mrow></msup></mrow></math></span> $/h, respectively.</p></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"50 ","pages":"Article 100610"},"PeriodicalIF":4.2,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141963368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Co-located offshore wind and floating solar farms: A systematic quantitative literature review of site selection criteria","authors":"Fida Ali ,&nbsp;Amir Etemad-Shahidi ,&nbsp;Rodney A. Stewart ,&nbsp;Mohammad J. Sanjari ,&nbsp;Jennifer A. Hayward ,&nbsp;Robert C. Nicholson","doi":"10.1016/j.ref.2024.100611","DOIUrl":"10.1016/j.ref.2024.100611","url":null,"abstract":"<div><p>Offshore wind farms (OWF) and floating solar photovoltaic farms (FPV) are becoming crucial parts of global renewable energy plans. Combining OWF and FPV offers a promising approach to improving energy generation efficiency and cutting costs through shared infrastructure and operational synergies. This systematic review assesses key criteria for identifying suitable co-location sites; focusing on environmental regulations, resource availability, economic viability, social acceptance, and technological readiness. The study highlights that environmental protection laws and legal limitations are the primary factors affecting site feasibility, in addition to factors such as distance from existing infrastructure and economic considerations. Despite potential benefits, the existing challenges are the early stage of FPV technology and its low resilience in offshore environments. The findings underline the potential of co-located OWF-FPV projects to reduce the costs associated with offshore renewables, particularly in densely populated coastal areas with limited land availability. Strategic resource allocation and policy support are essential for overcoming these obstacles and promoting the development of sustainable offshore energy solutions. These findings serve researchers and practitioners alike, by offering insights for a better allocation of resources and efforts to foster the co-location development of OWF and FPV in the future.</p></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"50 ","pages":"Article 100611"},"PeriodicalIF":4.2,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755008424000759/pdfft?md5=06fa8bf4c76eb04721a2bd2bc7ce413d&pid=1-s2.0-S1755008424000759-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041139","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":"Optimal building integrated photovoltaic sizing approach according to load profile under zero export restrictions with real data validation","authors":"S. Huseinbegović,&nbsp;A. Smajkić,&nbsp;L. Ahmethodžić,&nbsp;S. Smaka,&nbsp;S. Gajip","doi":"10.1016/j.ref.2024.100605","DOIUrl":"10.1016/j.ref.2024.100605","url":null,"abstract":"<div><p>This paper focuses on optimal sizing of building-integrated photovoltaic (BIPV) without energy storage system (ESS) in a zero power/energy export (ZE) power system, considering several types of buildings/consumers. BIPV systems have gained significant popularity in the development of low-carbon smart cities because they offer several key advantages, such as utilizing locally available renewable energy sources (RES) and reducing dependence on fossil fuels and greenhouse gases emissions. However, the implementation of BIPV system faces challenges due to legal, regulatory, and technical restrictions imposed by the power distribution system operator, sometimes resulting in ZE requirements. In this case, one of the major challenges is the optimal sizing of BIPV system, considering both technical and economic parameters, especially if there is no ESS. The objective function presented in this paper integrates the internal rate of return on investment and the self-sufficiency rate of BIPV system. The primary goal is to optimize both the cost-effectiveness and self-sufficiency of BIPV system, along with minimizing the cost of energy consumption from the power grid over a ten-year period. Additionally, the presented approach accounts for varying tariff rates, different load profiles, price fluctuations during the exploitation period, and the variation of the efficiency of BIPV system over time. As case studies, the presented approach is validated and assessed on real data sets of several different examples of BIPV systems without ESS, considering ZE as the constraint.</p></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"50 ","pages":"Article 100605"},"PeriodicalIF":4.2,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141962932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}