Dazhou Ping , Chaosu Li , Xiaojun Yu , Zhengxuan Liu , Ran Tu , Yuekuan Zhou
{"title":"在香港建立城市规模的信息模型，利用最佳电池储能实现城市能源复原力","authors":"Dazhou Ping , Chaosu Li , Xiaojun Yu , Zhengxuan Liu , Ran Tu , Yuekuan Zhou","doi":"10.1016/j.apenergy.2024.124813","DOIUrl":null,"url":null,"abstract":"<div><div>Climate change and extreme weather events are imposing threats to city power systems with regional power shortages. To enhance urban power system's resilience amid climate change, photovoltaic (PV) and battery energy storage systems (BESS) are crucial for maintaining self-sufficient power during outages. However, the optimal installation location and capacity sizing of BESS remain uncertain when considering multi-criteria, including safety, energy flexibility, accessibility and energy resilience. This study proposes a new approach, i.e., Geographic Information System (GIS) integrated with Multi-Criteria Decision-Making (MCDM) and capacitated p-median problem, to identify optimal installation locations and capacity allocation of BESS. This approach comprehensively considers geographical conditions (such as slope, land use, open space), safety, energy flexibility, accessibility and energy resilience, while accounting for the entire distribution network's granularity, intermittent solar supply, and unstable electricity demand. The methodology can guide the optimal BESS siting and sizing for energy resilience under future climate change and associated extreme weather events. Results indicate that suitable installation locations based on the proposed GIS-MCDM method are concentrated in central and southern regions in Yau Tsim Mong. Subsequently, BESS with the optimal and specific installation location and capacity allocation is in districts with high electricity demand and favourable safety geographical conditions. Compared to BESS without GIS-MCDM, the optimal BESS deployment with GIS-MCDM decreases the power shortage from 13,184 MWh to 12,931 MWh. Additionally, it increases the maximum power shortage reduction density from 176.04 kWh/m<sup>2</sup> to 364.2 kWh/m<sup>2</sup>, and the area with a power shortage reduction above 100 kWh/m<sup>2</sup> expands from 1.24 × 10<sup>5</sup> m<sup>2</sup> to 2.17 × 10<sup>5</sup> m<sup>2</sup>. This study contributes a new approach to determine optimal BESS installation locations and capacity allocation in urban-scale information modelling, planning and deployment, with frontier guidelines for system designers and urban planners to collaboratively develop resilience and survivability of urban power systems under extreme events.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124813"},"PeriodicalIF":10.1000,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"City-scale information modelling for urban energy resilience with optimal battery energy storages in Hong Kong\",\"authors\":\"Dazhou Ping , Chaosu Li , Xiaojun Yu , Zhengxuan Liu , Ran Tu , Yuekuan Zhou\",\"doi\":\"10.1016/j.apenergy.2024.124813\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Climate change and extreme weather events are imposing threats to city power systems with regional power shortages. To enhance urban power system's resilience amid climate change, photovoltaic (PV) and battery energy storage systems (BESS) are crucial for maintaining self-sufficient power during outages. However, the optimal installation location and capacity sizing of BESS remain uncertain when considering multi-criteria, including safety, energy flexibility, accessibility and energy resilience. This study proposes a new approach, i.e., Geographic Information System (GIS) integrated with Multi-Criteria Decision-Making (MCDM) and capacitated p-median problem, to identify optimal installation locations and capacity allocation of BESS. This approach comprehensively considers geographical conditions (such as slope, land use, open space), safety, energy flexibility, accessibility and energy resilience, while accounting for the entire distribution network's granularity, intermittent solar supply, and unstable electricity demand. The methodology can guide the optimal BESS siting and sizing for energy resilience under future climate change and associated extreme weather events. Results indicate that suitable installation locations based on the proposed GIS-MCDM method are concentrated in central and southern regions in Yau Tsim Mong. Subsequently, BESS with the optimal and specific installation location and capacity allocation is in districts with high electricity demand and favourable safety geographical conditions. Compared to BESS without GIS-MCDM, the optimal BESS deployment with GIS-MCDM decreases the power shortage from 13,184 MWh to 12,931 MWh. Additionally, it increases the maximum power shortage reduction density from 176.04 kWh/m<sup>2</sup> to 364.2 kWh/m<sup>2</sup>, and the area with a power shortage reduction above 100 kWh/m<sup>2</sup> expands from 1.24 × 10<sup>5</sup> m<sup>2</sup> to 2.17 × 10<sup>5</sup> m<sup>2</sup>. This study contributes a new approach to determine optimal BESS installation locations and capacity allocation in urban-scale information modelling, planning and deployment, with frontier guidelines for system designers and urban planners to collaboratively develop resilience and survivability of urban power systems under extreme events.</div></div>\",\"PeriodicalId\":246,\"journal\":{\"name\":\"Applied Energy\",\"volume\":\"378 \",\"pages\":\"Article 124813\"},\"PeriodicalIF\":10.1000,\"publicationDate\":\"2024-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Energy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0306261924021962\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0306261924021962","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
City-scale information modelling for urban energy resilience with optimal battery energy storages in Hong Kong
Climate change and extreme weather events are imposing threats to city power systems with regional power shortages. To enhance urban power system's resilience amid climate change, photovoltaic (PV) and battery energy storage systems (BESS) are crucial for maintaining self-sufficient power during outages. However, the optimal installation location and capacity sizing of BESS remain uncertain when considering multi-criteria, including safety, energy flexibility, accessibility and energy resilience. This study proposes a new approach, i.e., Geographic Information System (GIS) integrated with Multi-Criteria Decision-Making (MCDM) and capacitated p-median problem, to identify optimal installation locations and capacity allocation of BESS. This approach comprehensively considers geographical conditions (such as slope, land use, open space), safety, energy flexibility, accessibility and energy resilience, while accounting for the entire distribution network's granularity, intermittent solar supply, and unstable electricity demand. The methodology can guide the optimal BESS siting and sizing for energy resilience under future climate change and associated extreme weather events. Results indicate that suitable installation locations based on the proposed GIS-MCDM method are concentrated in central and southern regions in Yau Tsim Mong. Subsequently, BESS with the optimal and specific installation location and capacity allocation is in districts with high electricity demand and favourable safety geographical conditions. Compared to BESS without GIS-MCDM, the optimal BESS deployment with GIS-MCDM decreases the power shortage from 13,184 MWh to 12,931 MWh. Additionally, it increases the maximum power shortage reduction density from 176.04 kWh/m2 to 364.2 kWh/m2, and the area with a power shortage reduction above 100 kWh/m2 expands from 1.24 × 105 m2 to 2.17 × 105 m2. This study contributes a new approach to determine optimal BESS installation locations and capacity allocation in urban-scale information modelling, planning and deployment, with frontier guidelines for system designers and urban planners to collaboratively develop resilience and survivability of urban power systems under extreme events.
期刊介绍：
Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.
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