多能虚拟电厂集群分布式鲁棒优化策略

A distributed robust optimization strategy for multi-energy virtual power plant clusters

随着可再生能源渗透率的不断提升,同时面对分散式源-荷-储协调优化需求,虚拟电厂(Virtual Power Plant,VPP)应运而生.但多主体代理的VPP如何协调运行是亟待解决的问题.为此提出了一种考虑双范数约束和纳什议价的多能虚拟电厂集群分布式鲁棒优化策略.首先,针对多能VPP规划运行问题,通过双范数约束构建了多能VPP分布式鲁棒优化模型,其次以交互成本最小化为目标,通过纳什谈判理论来构建议价模型;最后对所提出的三个多能VPP进行算例分析,数据结果表明所提出的优化策略能够在确保各个VPP公平竞争前提下,提升其收益以及VPP集群的整体收益.

With the continuous increase in the penetration rate of renewable energy and the need for decentralized source load storage coordination and optimization,virtual power plants(VPPs)have emerged.However,how to coordinate the operation of multi agent VPP is an urgent problem that needs to be solved.A distributed robust optimization strategy for multi energy virtual power plant clusters considering dual norm constraints and Nash bargaining is proposed.Firstly,for the planning and operation problem of multi energy VPP,a distributed robust optimization model for multi energy VPP was constructed using dual norm constraints.Secondly,with the goal of minimizing interaction costs,a bargaining model was constructed using Nash negotiation theory;Finally,a numerical analysis was conducted on the three proposed multi energy VPPs,and the data results showed that the proposed optimization strategy can improve their revenue and the overall revenue of the VPP cluster while ensuring fair competition among all VPPs.