电力建设2024，Vol.45Issue(12)：83-99,17.DOI:10.12204/j.issn.1000-7229.2024.12.007
计及综合需求响应的综合能源系统集群多能源精细化日前交易模型
Multi-Energy Refined Day-Ahead Trading Model of Integrated Energy System Cluster Considering Integrated Demand Response
摘要
Abstract
In the context of"double carbon"goals,mutual assistance in electricity among multiple integrated energy systems has become an effective approach to promote on-site renewable energy consumption and enhance the economic efficiency of integrated energy system clusters.Reasonable demand response resource scheduling schemes and adaptive multi-energy trading models have significant research value for improving renewable energy utilization.Therefore,a multi-energy day-ahead trading strategy integrated energy system cluster that considers the integrated demand response was proposed.First,integrated demand response was considered to develop an independent day-ahead optimal dispatch model for the integrated energy system,establishing energy supply and demand plans along with integrated demand response schemes.Second,a pricing strategy was formulated considering factors such as energy trading demand and transaction willingness,and an equivalent model for heating and electricity bidding strategies was constructed to perform simultaneous auction transactions for these energy types.Third,to further promote internal trading within the integrated energy system cluster and enhance renewable energy consumption,a quotation strategy was developed based on user satisfaction and other factors.In addition,a bilateral auction mechanism for electricity and heating demand response resources was designed.Finally,a numerical simulation was performed to verify the feasibility and effectiveness of the proposed model.关键词
综合能源系统集群(IESC)/需求响应资源/多能源交易/双向拍卖机制/竞标策略Key words
integrated energy system cluster(IESC)/demand response resources/multi-energy trading/bilateral auction mechanism/bidding strategy分类
信息技术与安全科学引用本文复制引用
李金鸿,刘洋,许立雄..计及综合需求响应的综合能源系统集群多能源精细化日前交易模型[J].电力建设,2024,45(12):83-99,17.基金项目
This work is supported by the Science and Technology Project of Sichuan Province(No.2023YFG0132). 四川省科技计划资助项目(2023YFG0132) （No.2023YFG0132）
