摘要
Abstract
To address the challenges of multi-agent interest coordination,insufficient characterization of network usage costs in P2P trading,and wind-solar generation uncertainty in the coordinated operation of distribution networks and multi-microgrids(MMGs),this paper proposes a coordinated optimization and scheduling method considering wheeling charges and uncertainties.First,a Stackelberg game model is established between the distribution network operator(DNO)and the MMGs alliance,and a wheeling charge mechanism based on electrical distance is introduced to characterize network usage costs.In this framework,the DNO acts as the leader and determines time-of-use electricity prices,while the MMGs alliance,as the follower,optimizes its operational decisions under given prices.To address renewable generation uncertainty,a time-series generative adversarial network combined with the K-medoids method is adopted to generate and reduce representative scenarios.A distributionally robust optimization model incorporating both 1-norm and ∞-norm constraints is then developed to obtain the optimal operation strategy of the MMGs alliance.Subsequently,an asymmetric Nash bargaining mechanism is employed to allocate alliance profits and determine the P2P trading prices among microgrids.Finally,to enhance solution efficiency and preserve privacy,a solution framework integrating an improved sardine optimization algorithm and a column-and-constraint generation method is proposed,while the alternating direction method of multipliers is used to solve the profit allocation problem in a distributed manner.Case studies on the modified IEEE 33-bus system verify the effectiveness and superiority of the proposed method.关键词
多微电网/配电网/博弈论/过网费/分布鲁棒优化Key words
multi-microgrids/distribution network/game theory/wheeling charge/distributionally robust optimization分类
信息技术与安全科学
