{"title":"Renewable energy communities and mitigation of energy poverty: Instruments for policymakers and community managers","authors":"","doi":"10.1016/j.segan.2024.101471","DOIUrl":null,"url":null,"abstract":"<div><p>Energy poverty has been increasing since the early 2020s because of rising energy prices. This is attributed to geopolitical crises and the inclusion of the energy cost of <span><math><msub><mrow><mi>CO</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> pricing, which was historically an externality. Policymakers and citizens need new tools to address this issue, and energy communities are recognized as a valuable tool for mitigation. This study proposes two complementary approaches that relate to energy poverty and Renewable Energy Communities (RECs). The first aims to define and map energy poverty to support the policy in targeting measures and incentives. Using publicly available data, a new methodology is proposed for mapping energy poverty risk over a large territory with a fine granularity. The second approach taken sees REC managers at the center, who are tasked with sharing the economic benefits appropriately and equitably. A series of multi-criteria sharing mechanisms were developed and compared with the existing ones (e.g., based on Shapley value), including the energy poverty mitigation among them and the assessment of the impact of RECs on it. The results show that sharing methods can be one of the viable pathways for mitigating energy poverty through RECs without compromising the economy of non-vulnerable REC members.</p></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352467724002005/pdfft?md5=ba85db879c7a5b023294b0ab572bc8ba&pid=1-s2.0-S2352467724002005-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy Grids & Networks","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352467724002005","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}
引用次数: 0
Abstract
Energy poverty has been increasing since the early 2020s because of rising energy prices. This is attributed to geopolitical crises and the inclusion of the energy cost of pricing, which was historically an externality. Policymakers and citizens need new tools to address this issue, and energy communities are recognized as a valuable tool for mitigation. This study proposes two complementary approaches that relate to energy poverty and Renewable Energy Communities (RECs). The first aims to define and map energy poverty to support the policy in targeting measures and incentives. Using publicly available data, a new methodology is proposed for mapping energy poverty risk over a large territory with a fine granularity. The second approach taken sees REC managers at the center, who are tasked with sharing the economic benefits appropriately and equitably. A series of multi-criteria sharing mechanisms were developed and compared with the existing ones (e.g., based on Shapley value), including the energy poverty mitigation among them and the assessment of the impact of RECs on it. The results show that sharing methods can be one of the viable pathways for mitigating energy poverty through RECs without compromising the economy of non-vulnerable REC members.
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.