{"title":"Assessment methodology for the resilience of energy systems in positive energy buildings","authors":"Chiho Jimba, Yutaro Akimoto, Keiichi Okajima","doi":"10.1016/j.prime.2025.100908","DOIUrl":null,"url":null,"abstract":"<div><div>Distributed renewable energy systems are emerging in communities and buildings in response to global warming. Concurrently, the frequency of large-scale power outages, which are often triggered by natural disasters and heavy rainfall, has increased. This trend highlights the necessity to develop robust energy systems that integrate distributed renewable energy with other sources. Economic and resilience assessments of photovoltaic (PV) and battery systems within infrastructure contexts have been extensively studied. However, resilience evaluation at the building level is necessary. Given that energy resilience encompasses various assessment aspects, the importance of employing multiple indicators for a comprehensive quantitative evaluation of resilience in PV and battery installations is increasing. This study introduced a methodology to quantitatively assess the resilience of energy systems. It employs multiple resilience indicators and simulates a power outage scenario in a positive energy building (PEB) equipped with PV and batteries. Additionally, this study analyzed the impact of different weather conditions on resilience. An assessment using multiple resilience indicators reveals that energy systems are more resilient on favorable weather days and that resilience is maximized when supply interruptions coincide with daylight hours. Furthermore, while no single indicator can measure resilience, this study shows that the use of multiple indicators enables the clarification and comparison of electricity supply and demand conditions during a disaster.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100908"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772671125000154","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Distributed renewable energy systems are emerging in communities and buildings in response to global warming. Concurrently, the frequency of large-scale power outages, which are often triggered by natural disasters and heavy rainfall, has increased. This trend highlights the necessity to develop robust energy systems that integrate distributed renewable energy with other sources. Economic and resilience assessments of photovoltaic (PV) and battery systems within infrastructure contexts have been extensively studied. However, resilience evaluation at the building level is necessary. Given that energy resilience encompasses various assessment aspects, the importance of employing multiple indicators for a comprehensive quantitative evaluation of resilience in PV and battery installations is increasing. This study introduced a methodology to quantitatively assess the resilience of energy systems. It employs multiple resilience indicators and simulates a power outage scenario in a positive energy building (PEB) equipped with PV and batteries. Additionally, this study analyzed the impact of different weather conditions on resilience. An assessment using multiple resilience indicators reveals that energy systems are more resilient on favorable weather days and that resilience is maximized when supply interruptions coincide with daylight hours. Furthermore, while no single indicator can measure resilience, this study shows that the use of multiple indicators enables the clarification and comparison of electricity supply and demand conditions during a disaster.