{"title":"平衡能源资源分配的公平与效率","authors":"Jiayi Li, Matthew Motoki, Baosen Zhang","doi":"arxiv-2403.15616","DOIUrl":null,"url":null,"abstract":"Bringing fairness to energy resource allocation remains a challenge, due to\nthe complexity of system structures and economic interdependencies among users\nand system operators' decision-making. The rise of distributed energy resources\nhas introduced more diverse heterogeneous user groups, surpassing the\ncapabilities of traditional efficiency-oriented allocation schemes. Without\nexplicitly bringing fairness to user-system interaction, this disparity often\nleads to disproportionate payments for certain user groups due to their utility\nformats or group sizes. Our paper addresses this challenge by formalizing the problem of fair energy\nresource allocation and introducing the framework for aggregators. This\nframework enables optimal fairness-efficiency trade-offs by selecting\nappropriate objectives in a principled way. By jointly optimizing over the\ntotal resources to allocate and individual allocations, our approach reveals\noptimized allocation schemes that lie on the Pareto front, balancing fairness\nand efficiency in resource allocation strategies.","PeriodicalId":501062,"journal":{"name":"arXiv - CS - Systems and Control","volume":"19 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Balancing Fairness and Efficiency in Energy Resource Allocations\",\"authors\":\"Jiayi Li, Matthew Motoki, Baosen Zhang\",\"doi\":\"arxiv-2403.15616\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bringing fairness to energy resource allocation remains a challenge, due to\\nthe complexity of system structures and economic interdependencies among users\\nand system operators' decision-making. The rise of distributed energy resources\\nhas introduced more diverse heterogeneous user groups, surpassing the\\ncapabilities of traditional efficiency-oriented allocation schemes. Without\\nexplicitly bringing fairness to user-system interaction, this disparity often\\nleads to disproportionate payments for certain user groups due to their utility\\nformats or group sizes. Our paper addresses this challenge by formalizing the problem of fair energy\\nresource allocation and introducing the framework for aggregators. This\\nframework enables optimal fairness-efficiency trade-offs by selecting\\nappropriate objectives in a principled way. By jointly optimizing over the\\ntotal resources to allocate and individual allocations, our approach reveals\\noptimized allocation schemes that lie on the Pareto front, balancing fairness\\nand efficiency in resource allocation strategies.\",\"PeriodicalId\":501062,\"journal\":{\"name\":\"arXiv - CS - Systems and Control\",\"volume\":\"19 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Systems and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2403.15616\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Systems and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2403.15616","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Balancing Fairness and Efficiency in Energy Resource Allocations
Bringing fairness to energy resource allocation remains a challenge, due to
the complexity of system structures and economic interdependencies among users
and system operators' decision-making. The rise of distributed energy resources
has introduced more diverse heterogeneous user groups, surpassing the
capabilities of traditional efficiency-oriented allocation schemes. Without
explicitly bringing fairness to user-system interaction, this disparity often
leads to disproportionate payments for certain user groups due to their utility
formats or group sizes. Our paper addresses this challenge by formalizing the problem of fair energy
resource allocation and introducing the framework for aggregators. This
framework enables optimal fairness-efficiency trade-offs by selecting
appropriate objectives in a principled way. By jointly optimizing over the
total resources to allocate and individual allocations, our approach reveals
optimized allocation schemes that lie on the Pareto front, balancing fairness
and efficiency in resource allocation strategies.