Shunyu Li , Jing Zhang , Yu He , Gang Lv , Ying Liu , Xiangxie Hu , Zhiyang Wang , Xuan Ao
{"title":"考虑用户满意度和热惯性的用户级综合能源系统两阶段容量分配优化方法","authors":"Shunyu Li , Jing Zhang , Yu He , Gang Lv , Ying Liu , Xiangxie Hu , Zhiyang Wang , Xuan Ao","doi":"10.1016/j.gloei.2024.03.001","DOIUrl":null,"url":null,"abstract":"<div><div>Integrated-energy systems (IESs) are key to advancing renewable-energy utilization and addressing environmental challenges. Key components of IESs include low-carbon, economic dispatch and demand response, for maximizing renewable-energy consumption and supporting sustainable-energy systems. User participation is central to demand response; however, many users are not inclined to engage actively; therefore, the full potential of demand response remains unrealized. User satisfaction must be prioritized in demand-response assessments. This study proposed a two-stage, capacity-optimization configuration method for user-level energy systems considering thermal inertia and user satisfaction. This method addresses load coordination and complementary issues within the IES and seeks to minimize the annual, total cost for determining equipment capacity configurations while introducing models for system thermal inertia and user satisfaction. Indoor heating is adjusted, for optimizing device output and load profiles, with a focus on typical, daily, economic, and environmental objectives. The study findings indicate that the system thermal inertia optimizes energy-system scheduling considering user satisfaction. This optimization mitigates environmental concerns and enhances clean-energy integration.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 2","pages":"Pages 300-315"},"PeriodicalIF":1.9000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Two-Stage capacity allocation optimization method for user-level integrated energy systems considering user satisfaction and thermal inertia\",\"authors\":\"Shunyu Li , Jing Zhang , Yu He , Gang Lv , Ying Liu , Xiangxie Hu , Zhiyang Wang , Xuan Ao\",\"doi\":\"10.1016/j.gloei.2024.03.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Integrated-energy systems (IESs) are key to advancing renewable-energy utilization and addressing environmental challenges. Key components of IESs include low-carbon, economic dispatch and demand response, for maximizing renewable-energy consumption and supporting sustainable-energy systems. User participation is central to demand response; however, many users are not inclined to engage actively; therefore, the full potential of demand response remains unrealized. User satisfaction must be prioritized in demand-response assessments. This study proposed a two-stage, capacity-optimization configuration method for user-level energy systems considering thermal inertia and user satisfaction. This method addresses load coordination and complementary issues within the IES and seeks to minimize the annual, total cost for determining equipment capacity configurations while introducing models for system thermal inertia and user satisfaction. Indoor heating is adjusted, for optimizing device output and load profiles, with a focus on typical, daily, economic, and environmental objectives. The study findings indicate that the system thermal inertia optimizes energy-system scheduling considering user satisfaction. This optimization mitigates environmental concerns and enhances clean-energy integration.</div></div>\",\"PeriodicalId\":36174,\"journal\":{\"name\":\"Global Energy Interconnection\",\"volume\":\"8 2\",\"pages\":\"Pages 300-315\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2025-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Global Energy Interconnection\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2096511725000313\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Energy Interconnection","FirstCategoryId":"1087","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2096511725000313","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Two-Stage capacity allocation optimization method for user-level integrated energy systems considering user satisfaction and thermal inertia
Integrated-energy systems (IESs) are key to advancing renewable-energy utilization and addressing environmental challenges. Key components of IESs include low-carbon, economic dispatch and demand response, for maximizing renewable-energy consumption and supporting sustainable-energy systems. User participation is central to demand response; however, many users are not inclined to engage actively; therefore, the full potential of demand response remains unrealized. User satisfaction must be prioritized in demand-response assessments. This study proposed a two-stage, capacity-optimization configuration method for user-level energy systems considering thermal inertia and user satisfaction. This method addresses load coordination and complementary issues within the IES and seeks to minimize the annual, total cost for determining equipment capacity configurations while introducing models for system thermal inertia and user satisfaction. Indoor heating is adjusted, for optimizing device output and load profiles, with a focus on typical, daily, economic, and environmental objectives. The study findings indicate that the system thermal inertia optimizes energy-system scheduling considering user satisfaction. This optimization mitigates environmental concerns and enhances clean-energy integration.