考虑居民用户可调节潜力的负荷聚合商日前投标决策优化模型研究  

Day-ahead Bidding Decision Optimization Model of Load Aggregators Considering Adjustable Potential of Residential Users

作　　者：刘金朋[1] 刘胡诗涵 张雨菲 邓嘉明 胡国松 李万鹏 LIU Jinpeng;LIU Hushihan;ZHANG Yufei;DENG Jiaming;HU Guosong;LI Wanpeng(School of Economics and Management,North China Electric Power University,Beijing 102206,China;School of International Education,North China Electric Power University,Beijing 102206,China)

机构地区：[1]华北电力大学经济与管理学院,北京102206 [2]华北电力大学国际教育学院,北京102206

出　　处：《智慧电力》2024年第2期71-78,122,共9页Smart Power

基　　金：国家自然科学基金资助项目(72074074);教育部人文社会科学研究规划基金项目(23YJA630062)。

摘　　要：负荷聚合商能够充分挖掘居民用户资源参与需求响应,深化居民用电可调节潜力量化分析对负荷精准调控与负荷聚合商模式智能推广具有重要作用。首先,基于居民用电负荷调控差异性,考虑居民典型用电电器综合满意度计量,构建居民柔性负荷可调节潜力分析模型;然后,考虑负荷聚合商参与市场交易的运营模式,构建基于非合作博弈理论的日前投标决策优化模型;最后,通过算例仿真验证模型的有效性及适用性。结果表明该模型能够兼顾调控潜力,有效支撑负荷聚合商最优投标决策,为负荷聚合商推广下统筹资源优化调控提供借鉴与参考。The load aggregator can fully excavate the potential for participating in residential user resource demand response,deepen the quantitative analysis on the adjustable potential of residential electricity consumption,and play an important role in precise load regulation and the intelligent promotion of load aggregator mode.Firstly,based on the differences in residential electricity load regulation,an analysis model for the adjustable potential of residential flexible loads is established by considering the comprehensive satisfaction measurement of typical household appliances.Then considering the operational mode of the load aggregators participating in market transactions,a non-cooperative game theory based day-ahead bidding decision optimization model is constructed.Finally,the effectiveness and applicability of the model are verified through a case simulation.The results indicate that the model can balance the regulatory potential,effectively support the optimal bidding decision of the load aggregators,and provide reference and guidance for the optimization and regulation of coordinated resources under the promotion of the load aggregators.

关 键 词：负荷聚合商 可调节潜力 非合作博弈 投标决策优化 

分 类 号：TM732[电气工程—电力系统及自动化]