摘要
负荷聚合商通过需求响应整合用户侧资源,并由此向电网提供负荷平抑服务以获得收益。因此,聚合商的响应定价策略和用户响应偏好直接影响用户响应精度,进而影响聚合商市场收益。文中将参与需求响应的负荷资源作为广义需求侧资源,提出基于价格激励的需求响应机制,建立考虑用户偏好的用户效用模型和聚合商收益模型。进而,以用户和聚合商两者利益最大化为目标构建主从博弈模型,求解模型获得聚合商最优补偿定价策略,分析用户用电弹性以优化用户响应。最后,采用美国PJM市场数据进行算例仿真,结果表明基于主从博弈的最优定价策略能够充分考虑用户响应偏好差异,有效降低用户综合成本,通过平抑负荷波动提高聚合商市场收益。
A load aggregator(LA) provides load smoothing services to the power grid and obtains revenue by integrating user-side resources through demand response. Therefore, the response pricing strategy of LA and users’ response preference will affect the accuracy of users’ response directly, and then affect the revenue of LA. The load resources involved in the demand response are regarded as generalized demand side resources(GDSRs), and demand response mechanism based on price incentives is proposed.Then, a user utility model considering user preference and an aggregator revenue model are constructed. Furthermore, aiming at maximizing the interests of both users and LA, a master-slave game model is established, which is calculated to obtain the optimal compensation pricing strategy of LA and analyze the users’ electricity elasticity to optimize users’ response. Finally, the data of American PJM market are used for simulation. The simulation results verify that the optimal pricing strategy based on the masterslave game can reduce users’ comprehensive cost effectively through full consideration of the differences in users’ response preference, and increase the market revenue of LA by smoothing the load fluctuation.
作者
孙伟卿
刘晓楠
向威
李宏仲
SUN Weiqing;LIU Xiaonan;XIANG Wei;LI Hongzhong(School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China;Shanghai Shenergy New Power Storage R&D Co.,Ltd.,Shanghai 201419,China;School of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200090,China)
出处
《电力系统自动化》
EI
CSCD
北大核心
2021年第1期159-167,共9页
Automation of Electric Power Systems
基金
国家自然科学基金资助项目(51777126)。
关键词
广义需求侧资源
需求响应
响应偏好
主从博弈
最优定价
generalized demand side resource
demand response
response preference
master-slave game
optimal pricing
