Renewable Energy Focus最新文献_第7页

Federated deep MPC-enabled digital twin and multiagent learning framework for secure and scalable smart nano grid energy management 联邦深度mpc支持的数字孪生和多智能体学习框架，用于安全和可扩展的智能纳米电网能源管理

IF 5.9

Renewable Energy Focus Pub Date : 2026-03-01 Epub Date: 2025-09-17 DOI: 10.1016/j.ref.2025.100762

Ibrahim Sinneh Sinneh, Sun Yanxia

{"title":"Federated deep MPC-enabled digital twin and multiagent learning framework for secure and scalable smart nano grid energy management","authors":"Ibrahim Sinneh Sinneh, Sun Yanxia","doi":"10.1016/j.ref.2025.100762","DOIUrl":"10.1016/j.ref.2025.100762","url":null,"abstract":"<div><div>This study introduces a novel Federated Secure Dynamic Optimization Framework (FSDOF) to improve smart nano grid systems’ energy management, fault tolerance, and cybersecurity. The framework suggested combines Digital Twin (DT) technology and Multiagent Reinforcement Learning (MARL) to assist in real-time decision-making and decentralized control. In essence, FSDOF integrates three major components: Federated Deep Model Predictive Control (FD-MPC) to schedule energy optimally, SecureGraph-FedNet (SG-FedNet) to communicate through Graph Neural Networks and Autoencoders securely, and Dynamic Stochastic Neuro-Evolution Optimizer (DSNEO) to adaptively handle and optimize under uncertainty. The system demonstrated 98.52 % energy efficiency, DC voltage stabilization in 0.5 seconds, and Bit Error Rate (BER) of 0.012, which is better than the traditional DRL methods. SG-FedNet guarantees a security confidence of 0.99 in federated learning with differential privacy. Scalability and resilience of the system were confirmed by large-scale simulations on more than 100 nodes with less than 4 % performance degradation. These findings make FSDOF a scalable and strong solution to next-generation smart energy networks.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"56 ","pages":"Article 100762"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106263","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}

引用次数: 0

Optimal allocation of distributed generators and capacitor banks considering load models under stochastic load levels 随机负荷水平下考虑负荷模型的分布式发电机和电容器组优化配置

IF 5.9

Renewable Energy Focus Pub Date : 2026-03-01 Epub Date: 2025-10-22 DOI: 10.1016/j.ref.2025.100773

Moshood Akanni Alao, Olawale Muhammed Popoola

{"title":"Optimal allocation of distributed generators and capacitor banks considering load models under stochastic load levels","authors":"Moshood Akanni Alao, Olawale Muhammed Popoola","doi":"10.1016/j.ref.2025.100773","DOIUrl":"10.1016/j.ref.2025.100773","url":null,"abstract":"<div><div>Optimal allocation of distributed generators (DGs) and capacitor banks (CBs) is crucial for enhancing both the technical performance and environmental sustainability of distribution systems. Uncertainties arising from consumer behaviour, climatic conditions, and time-of-use introduce variability in load demands. Therefore, accounting for load demand uncertainty is essential for effective and sustainable distribution system planning. In this study, a novel fuzzified random number approach is employed to model the uncertainty in voltage-dependent non-linear load (VDL) models. An improved particle swarm optimization (IPSO) algorithm is then applied for the simultaneous allocation of DGs and CBs in radial distribution networks under both constant (CL) and stochastic VDL scenarios. The IPSO method is validated on the IEEE 33-bus system to evaluate the technical, economic, and environmental benefits of DG and CB allocation. Key results indicate that DGs operating at an optimal power factor (OPF-DGs) combined with CBs outperform unity-power-factor (UPF-DGs) and CBs under the CL model, achieving superior outcomes in terms of reduced power loss, lower voltage deviation, and enhanced voltage stability. Specifically, power loss reductions of 94.36% are achieved for UPF-DGs + CBs, compared to 94.89% for OPF-DGs + CBs under CLs. For defuzzified mixed VDLs, a power loss reduction of 93.92% is observed under OPF-DGs + CBs. The proposed approach also demonstrates significant economic benefits, including high net present values and cost savings, alongside substantial reductions in environmental emissions. Furthermore, sensitivity analysis highlights that considering different load mixes, rather than static or single-load configurations, is critical for optimal planning and economic dispatch of distribution systems with DGs and CBs. Incorporating load uncertainty provides a more realistic representation of system performance, emphasizing its importance in sustainable distribution network planning.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"56 ","pages":"Article 100773"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145362640","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}

引用次数: 0

Low-carbon optimal scheduling of integrated energy system with concentrating solar power based on entropy weight IGDT 基于熵权IGDT的聚光太阳能综合能源系统低碳优化调度

IF 5.9

Renewable Energy Focus Pub Date : 2025-12-01 Epub Date: 2025-08-08 DOI: 10.1016/j.ref.2025.100746

Ankang Miao , Yue Yuan , Junpeng Zhu , Mengda Li

{"title":"Low-carbon optimal scheduling of integrated energy system with concentrating solar power based on entropy weight IGDT","authors":"Ankang Miao , Yue Yuan , Junpeng Zhu , Mengda Li","doi":"10.1016/j.ref.2025.100746","DOIUrl":"10.1016/j.ref.2025.100746","url":null,"abstract":"<div><div>Concentrating solar power (CSP) can effectively mitigate the randomness and intermittency of solar resources. To accurately characterize the operation characteristics of the CSP and address the multiple uncertainties, this study establishes a low-carbon optimal scheduling model of an integrated energy system with CSP based on entropy weight information gap decision theory (IGDT). Firstly, based on the start-up characteristics of the CSP, a refined model of a multi-period cumulative heat start-up for the CSP is established. Then, considering the multiple uncertainties, the IGDT is applied to address the new uncertainties in energy and load power. The entropy weight method is employed to eliminate the subjectivity associated with the weights of multiple uncertain variables and their corresponding deviation factors. Finally, the IGDT optimization model is compared with the established stochastic model, robust model, and robust stochastic model. The sensitivity of the uncertainties of the opportunity and robust strategies is also analyzed. The case studies verify the validity and feasibility of the established model of IES with CSP based on entropy weight IGDT, which provides a reference for operational research in CSP and uncertainty research in energy systems.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"55 ","pages":"Article 100746"},"PeriodicalIF":5.9,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144826801","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}

引用次数: 0

A review of data-driven deep learning models for solar and wind energy forecasting 数据驱动的太阳能和风能预测深度学习模型综述

IF 4.2

Renewable Energy Focus Pub Date : 2025-12-01 Epub Date: 2025-07-21 DOI: 10.1016/j.ref.2025.100739

Shubham Shringi , Lalit Mohan Saini , Sanjeev Kumar Aggarwal

{"title":"A review of data-driven deep learning models for solar and wind energy forecasting","authors":"Shubham Shringi , Lalit Mohan Saini , Sanjeev Kumar Aggarwal","doi":"10.1016/j.ref.2025.100739","DOIUrl":"10.1016/j.ref.2025.100739","url":null,"abstract":"<div><div>Numerous papers using advanced Artificial Intelligence (AI) based models - such as deep neural networks (DNN), Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) networks - have been reported for solar and wind forecasting. However, a systematic quantitative comparison of these diverse studies remains underexplored. This paper presents a comprehensive review and critical comparison of data-driven forecasting methods based on key parameters, including forecasting horizon, input features, geographical location, forecasting accuracy, training/testing period data length, pre-processing techniques, model architecture, activation functions, training algorithms, and the simulation platforms. Special emphasis is placed on data preparation strategies and model optimization techniques that significantly influence forecasting performance and model robustness. The scope is focused on purely data-driven AI and hybrid approaches, excluding physical and statistical models. An exploration of the strengths and weaknesses of these methods underscores the significance of hybrid models, particularly those combining DNN. A key contribution of this study lies in its structured synthesis of performance outcomes from various reported works, methodically arranged by increasing testing data duration. This organization aids in identifying consistently reliable and high-performing models. The findings highlight the superior accuracy and adaptability of hybrid AI models, offering practical guidance for researchers, developers, and stakeholders in renewable energy forecasting and planning.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"55 ","pages":"Article 100739"},"PeriodicalIF":4.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144694322","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}

引用次数: 0

Dual-objective optimization of photovoltaic and electrolyzer size ratios for hydrogen production: economic and carbon emissions perspectives 光伏和电解槽制氢尺寸比的双目标优化：经济和碳排放视角

IF 5.9

Renewable Energy Focus Pub Date : 2025-12-01 Epub Date: 2025-08-09 DOI: 10.1016/j.ref.2025.100744

Francesco Guarino, Angelo Gucciardi, Fabio Massaro, Francesco Montana, Salvatore Ruffino

{"title":"Dual-objective optimization of photovoltaic and electrolyzer size ratios for hydrogen production: economic and carbon emissions perspectives","authors":"Francesco Guarino, Angelo Gucciardi, Fabio Massaro, Francesco Montana, Salvatore Ruffino","doi":"10.1016/j.ref.2025.100744","DOIUrl":"10.1016/j.ref.2025.100744","url":null,"abstract":"<div><div>Hydrogen is a zero-emissions fuel that, if generated from renewable energy sources, can play a vital role in reducing carbon emissions across multiple sectors. Green hydrogen production plants are constrained by the availability of renewable sources and there is not a common sizing criterion to couple water electrolyzers with renewable technologies. This study aims at filling the research gap involving the preliminary sizing of water electrolyzers to be coupled with photovoltaic systems according to different objectives and final production targets. The problem was formulated and addressed using a MILP optimization algorithm in MATLAB and solved according to the minimum costs and minimum carbon emissions criteria. Additionally, the optimization algorithm was run on three different final demand scenarios: hydrogen production from stand-alone plant, production to meet hydrogen final demand, and production to meet hydrogen and electricity final demands. Results show that the optimal ratio is between about 1.8 and 2 in the cases with cost minimization, but it increases up to 5.75 when both costs and carbon emissions are taken into account.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"55 ","pages":"Article 100744"},"PeriodicalIF":5.9,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144829437","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}

引用次数: 0

State-of-the-art of hierarchical microgrid technological framework: operational strategies with manifold barriers and future trajectories 分层微电网技术框架的最新技术：具有多种障碍和未来轨迹的运营策略

IF 5.9

Renewable Energy Focus Pub Date : 2025-12-01 Epub Date: 2025-07-30 DOI: 10.1016/j.ref.2025.100743

Abdul Latif , Abdelhakim Saim , Azeddine Houari , Ali Djerioui

{"title":"State-of-the-art of hierarchical microgrid technological framework: operational strategies with manifold barriers and future trajectories","authors":"Abdul Latif , Abdelhakim Saim , Azeddine Houari , Ali Djerioui","doi":"10.1016/j.ref.2025.100743","DOIUrl":"10.1016/j.ref.2025.100743","url":null,"abstract":"<div><div>Microgrids represent a critical and integral element in the advancement of smart grid technologies. These are diminutive-scale power systems, encompassing distributed energy resources. For the realization of the potential inherent in distributed generation, it is imperative to adopt a framework wherein the corresponding loads and generation are conceptualized as a sub-system, or more precisely, a microgrid. This article presents a comprehensive review of the scholarly literature pertaining to microgrid concept, technological applications. Research in this field is bifurcated into three primary domains: feasibility, control with management and stability strategies. Initially, the article delineates the various applications and categorizations of microgrids. Subsequently, it elucidates the objectives underlying microgrid control. Additionally, the article delves into the issue of small signal stability and hierarchal stability framework and clustering within microgrids, exploring various methodologies to enhance this aspect. Later, the paper scrutinizes the aspect of load frequency control within the microgrid paradigm. Additionally, numerous potential issues and barriers associated with microgrid implementation are identified and discussed. The paper concludes by delineating key areas for future microgrid research. This work aims to provide scientists, academician, and policymakers with comprehensive and structured knowledge about microgrids.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"55 ","pages":"Article 100743"},"PeriodicalIF":5.9,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144748593","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}

引用次数: 0

Techno-economic assessment of green hydrogen production via an optimized solar and wind system 通过优化的太阳能和风能系统进行绿色制氢的技术经济评估

IF 4.2

Renewable Energy Focus Pub Date : 2025-12-01 Epub Date: 2025-06-14 DOI: 10.1016/j.ref.2025.100726

Raj Sawhney , John Hearn , Ross Hibbett , Khaya Kingston , Makenna Parkinson , Mathias Zacarias , Joseph Majkut

{"title":"Techno-economic assessment of green hydrogen production via an optimized solar and wind system","authors":"Raj Sawhney , John Hearn , Ross Hibbett , Khaya Kingston , Makenna Parkinson , Mathias Zacarias , Joseph Majkut","doi":"10.1016/j.ref.2025.100726","DOIUrl":"10.1016/j.ref.2025.100726","url":null,"abstract":"<div><div>The economic feasibility of green hydrogen is integral to decarbonizing industries which are energy intensive and challenging to electrify via current power generation sectors. Cost-effective green hydrogen is dependent on the cost of both electrolyzer equipment and renewable energy production systems. In this study, the cost of producing green hydrogen was assessed worldwide. We produced a model using seven years of global solar and wind data to estimate the costs associated with off-grid, entirely emission-free, solar and wind hydrogen production facilities. These 6 costs were mapped across the world to visualize cost differences. We optimized for both the electrolyzer/renewable energy overfit and provide the option to combine solar and wind renewable systems, resulting in the lowest levelized cost of hydrogen at a given location. This procedure provides end users with the ability to toggle between wind, solar, and combined systems allowing for more realistic modeling and greater optionality. We incorporated country-level capital expenditure and operational expenditure data to more accurately model regional cost variations in global production costs. An analysis of these global costs resulted in a levelized cost of hydrogen range of $1 to > $5 per kilogram of hydrogen, in general agreement with public estimates.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"55 ","pages":"Article 100726"},"PeriodicalIF":4.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330420","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}

引用次数: 0

Optimal Interval based tuning of 3DOF-PID controllers for power system stabilizers and dynamic performance in multi machine power systems 基于最优区间的3DOF-PID控制器在多机电力系统稳定器及动态性能中的整定

IF 4.2

Renewable Energy Focus Pub Date : 2025-12-01 Epub Date: 2025-06-06 DOI: 10.1016/j.ref.2025.100727

R. Ramamoorthi , M. Sai Veerraju , M.V. Ramana Rao , T. Himaja

{"title":"Optimal Interval based tuning of 3DOF-PID controllers for power system stabilizers and dynamic performance in multi machine power systems","authors":"R. Ramamoorthi , M. Sai Veerraju , M.V. Ramana Rao , T. Himaja","doi":"10.1016/j.ref.2025.100727","DOIUrl":"10.1016/j.ref.2025.100727","url":null,"abstract":"<div><div>The removal of inadequately damped oscillations is necessary to guarantee the dependability and security of electrical power systems. This is especially crucial in modern power grids, where increasing interconnections between systems amplify the importance of stability. This manuscript proposes a Snow Ablation Optimizer (SAO) for optimal interval-based tuning of three degrees of freedom proportional-integral-derivative tilted-integral (3DOF-PID-TI) Controller for power system stabilizers (PSS) and dynamic performance in multi-machine power systems. The main objective is to optimize the performance of the PSS to enhance stability and effectively damp oscillations in power systems. The 3DOF-PID-TI controller parameter is adjusted using the SOA method. By then, the proposed approach has been incorporated into the MATLAB working platform, and the execution is calculated using the current system. The proposed technique displays better results in all existing methods such as the Wolf Optimizer algorithm (GWO), the Mayfly Optimization Algorithm (MOA), Improved Whale Optimization Algorithm (IWOA). The proposed method achieves 97%, surpassing the existing techniques with GWO at 84%, MOA at 76%, and IWOA at 64%. Additionally, the proposed SAO method demonstrates a settling time of 1.312 seconds, while the existing methods have longer settling times: GWO at 1.811 seconds, MOA at 2.969 seconds, and IWOA at 2.572 seconds. This enhancement highlights the better performance and optimization capability of the proposed method, emphasizing its effectiveness in optimizing PSS in multi-machine power systems contrasted to conventional optimization approaches.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"55 ","pages":"Article 100727"},"PeriodicalIF":4.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144338485","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}

引用次数: 0

Optimizing biomass re-collection center locations for vietnam’s growing bioenergy industry: An integrated dematel and gra approach 优化越南不断发展的生物能源产业的生物质再收集中心位置：一个综合的dematel和gra方法

IF 4.2

Renewable Energy Focus Pub Date : 2025-12-01 Epub Date: 2025-07-16 DOI: 10.1016/j.ref.2025.100740

Thi Be Oanh Cao , Duc Duy Nguyen , Thi Diem Chau Le

{"title":"Optimizing biomass re-collection center locations for vietnam’s growing bioenergy industry: An integrated dematel and gra approach","authors":"Thi Be Oanh Cao , Duc Duy Nguyen , Thi Diem Chau Le","doi":"10.1016/j.ref.2025.100740","DOIUrl":"10.1016/j.ref.2025.100740","url":null,"abstract":"<div><div>This study introduces a process for selecting potential locations that not only supports better decisions by balancing multiple criteria such as economic, social, and environmental factors but also clarifies the relationships among these criteria and highlights the most influential ones. The objective is to help decision-makers accurately and comprehensively identify key criteria, understand their interrelationships, and quickly determine the best location choices. An integration of two techniques, including the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Grey Relational Analysis (GRA), is proposed. Particularly, DEMATEL is used to determine attributes’ weights and relationships. GRA supports decision-makers in choosing the best option. A case study, a re-collection center in 13 provinces in the South of Vietnam, under consideration of 15 criteria formed from three pillars of the sustainable supply chain, is to describe the proposed process. Data were gathered from interviews with nine experts and specialized departments, including the General Statistics Office of Vietnam, the People’s Committee of Can Tho City, the Department of Labor, Invalids and Social Affairs, and the Department of Planning and Investment. The results show that the local and government policy criteria have the highest weight, and Ben Tre province is the best location. These contribute to selecting optimal facilities with complex criteria quickly and effectively for other developing countries and promoting bioenergy production, such as in Vietnam.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"55 ","pages":"Article 100740"},"PeriodicalIF":4.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144672203","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}

引用次数: 0

Modeling energy resilience and outage survivability of hybrid distributed energy resource system using REopt: A case study of a coastal institution 基于REopt的混合分布式能源系统能量弹性和停电生存能力建模——以某沿海机构为例

IF 4.2

Renewable Energy Focus Pub Date : 2025-12-01 Epub Date: 2025-07-10 DOI: 10.1016/j.ref.2025.100737

Md Mahmudul Hasan , Md Ezazul Kabir Shawon , Sayma Khandaker , Hadi Manap

{"title":"Modeling energy resilience and outage survivability of hybrid distributed energy resource system using REopt: A case study of a coastal institution","authors":"Md Mahmudul Hasan , Md Ezazul Kabir Shawon , Sayma Khandaker , Hadi Manap","doi":"10.1016/j.ref.2025.100737","DOIUrl":"10.1016/j.ref.2025.100737","url":null,"abstract":"<div><div>Energy systems must evolve to become more economical and resilient in response to the increasing frequency of climate-related disruptions. While several studies have presented renewable energy options, their resilience benefits, particularly in sensitive places, remain unexplored. This study analyzes the possibility of a hybrid distributed energy resource (DER) system to increase energy reliability and sustainability at the Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA), located in a coastal area with potential for flooding. The system configuration was evaluated using the REopt optimization software under an extended grid outage scenario utilizing a mixed-integer linear programming model. The results show that an efficient DER system could effectively maintain critical loads during long power outages while increasing energy autonomy. The findings additionally demonstrate that environmental performance and economic feasibility have significantly improved. Overall, this study indicates how hybrid DER systems can be used to improve energy resilience in vital infrastructures located in regions at risk of disasters.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"55 ","pages":"Article 100737"},"PeriodicalIF":4.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144606033","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}

引用次数: 0