Asja Alic , Alessandra Spada , Silvia Zordan , Antonio De Paola , Vincenzo Trovato
{"title":"可再生能源社区光伏电池储能系统的优化运行与改造:一种动态规划方法","authors":"Asja Alic , Alessandra Spada , Silvia Zordan , Antonio De Paola , Vincenzo Trovato","doi":"10.1016/j.segan.2025.101976","DOIUrl":null,"url":null,"abstract":"<div><div>This paper presents a novel Dynamic Programming algorithm designed to optimize the operation of an Integrated-Photovoltaic Battery Storage System arbitraging in the Wholesale Energy Market and participating in the Capacity Market. The optimization takes into account the energy capacity degradation of the battery and envisages the possibility of revamping actions to replace battery cells and ensure delivery of the discharge capacity contracted in the Capacity Market over the whole optimization horizon. The correctness of the proposed model is validated against an existing Mixed-Integer Linear Programming solution. The model is then further extended to simulate the operation of the Integrated Photovoltaic Battery System within a Renewable Energy Community, offering useful insights about the techno-economic advantages of fostering the local self-consumption. A comprehensive set of case studies has been conducted over a 10-years planning horizon with hourly granularity, considering the Italian energy markets and the applicable regulatory framework. Additional sensitivity studies expand the results by assessing the impact of different input parameters, geographical locations and number of participating members of the Renewable Energy Community.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"44 ","pages":"Article 101976"},"PeriodicalIF":5.6000,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal operation and revamping of a battery storage integrated with photovoltaic in renewable energy communities: A dynamic programming approach\",\"authors\":\"Asja Alic , Alessandra Spada , Silvia Zordan , Antonio De Paola , Vincenzo Trovato\",\"doi\":\"10.1016/j.segan.2025.101976\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper presents a novel Dynamic Programming algorithm designed to optimize the operation of an Integrated-Photovoltaic Battery Storage System arbitraging in the Wholesale Energy Market and participating in the Capacity Market. The optimization takes into account the energy capacity degradation of the battery and envisages the possibility of revamping actions to replace battery cells and ensure delivery of the discharge capacity contracted in the Capacity Market over the whole optimization horizon. The correctness of the proposed model is validated against an existing Mixed-Integer Linear Programming solution. The model is then further extended to simulate the operation of the Integrated Photovoltaic Battery System within a Renewable Energy Community, offering useful insights about the techno-economic advantages of fostering the local self-consumption. A comprehensive set of case studies has been conducted over a 10-years planning horizon with hourly granularity, considering the Italian energy markets and the applicable regulatory framework. Additional sensitivity studies expand the results by assessing the impact of different input parameters, geographical locations and number of participating members of the Renewable Energy Community.</div></div>\",\"PeriodicalId\":56142,\"journal\":{\"name\":\"Sustainable Energy Grids & Networks\",\"volume\":\"44 \",\"pages\":\"Article 101976\"},\"PeriodicalIF\":5.6000,\"publicationDate\":\"2025-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sustainable Energy Grids & Networks\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352467725003583\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy Grids & Networks","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352467725003583","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Optimal operation and revamping of a battery storage integrated with photovoltaic in renewable energy communities: A dynamic programming approach
This paper presents a novel Dynamic Programming algorithm designed to optimize the operation of an Integrated-Photovoltaic Battery Storage System arbitraging in the Wholesale Energy Market and participating in the Capacity Market. The optimization takes into account the energy capacity degradation of the battery and envisages the possibility of revamping actions to replace battery cells and ensure delivery of the discharge capacity contracted in the Capacity Market over the whole optimization horizon. The correctness of the proposed model is validated against an existing Mixed-Integer Linear Programming solution. The model is then further extended to simulate the operation of the Integrated Photovoltaic Battery System within a Renewable Energy Community, offering useful insights about the techno-economic advantages of fostering the local self-consumption. A comprehensive set of case studies has been conducted over a 10-years planning horizon with hourly granularity, considering the Italian energy markets and the applicable regulatory framework. Additional sensitivity studies expand the results by assessing the impact of different input parameters, geographical locations and number of participating members of the Renewable Energy Community.
期刊介绍:
Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.