计及综合需求响应的综合能源系统主从博弈优化调度策略

Master-slave Game Optimal Scheduling Strategy of Integrated Energy SystemConsidering Integrated Demand Response

在面对不断增多的利益相关方和区域综合能源系统的物理耦合的背景下,提出了一种创新的调度策略,该策略考虑到多方的需求响应,并采用了多主体博弈的方式进行优化。首先,深入研究了各微网中不同负荷的实际特性和用户的响应行为,并建立了相应的多负荷综合需求响应模型;然后,将系统运营商作为上层领导者,微网负荷聚合商、集中式储能电站和风电场作为下层跟随者,构建了一个多主体主从博弈模型。在上层模型中,其目标是使系统运营商的售能收益最大化,通过优化来确定各微网的售能单价和补偿价格;而在下层模型中,致力于最小化各方的综合成本,通过优化来确定风电场的供能情况、各微网内多设备之间的能源出力情况以及储能电站的充放能策略。为了解决这个复杂的问题,最终采用了粒子群算法来求解上层主体模型,并使用Cplex求解器来求解下层从体模型,这两层模型相互影响,最终得到了博弈后的均衡策略。

In the context of facing the increasing number of stakeholders and the physical coupling of the regional integrated energy system,an innovative scheduling strategy is proposed,which takes into account the demand response of multiple parties and adopts a multi-subject game for optimization.First,the actual characteristics of different loads in each microgrid and the response behaviors of users are studied in depth,and a corresponding multi-load integrated demand response model is established.Then,a multi-subject master-slave game model is constructed by taking the system operator as the upper layer leader and the microgrid load aggregator,centralized energy storage plant and wind farm as the lower layer followers.In the upper layer model,the goal is to maximize the system operator′s revenue from energy sales,and to determine the unit price of energy sales and compensation price of each microgrid through optimization.And in the lower layer model,it is committed to minimizing the comprehensive cost of all parties,and determines the energy supply of wind farms,the energy output between multiple devices in each microgrid,and the charging and discharging strategies of energy storage plants through optimization.In order to solve this complex problem,the particle swarm algorithm is finally used to solve the upper layer subject model and the Cplex solver is used to solve the lower layer slave model,which interact with each other to finally obtain the equilibrium strategy after the game.