基于主从博弈的智能小区代理商定价策略及电动汽车充电管理

Stackelberg Game Based Retailer Pricing Scheme and EV Charging Management in Smart Residential Area

智能电网的负荷包括传统负荷和主动负荷,我国配电网侧的主动负荷主要由电动汽车构成,功率需求随电价变化是其重要特点之一。随着电动汽车的普及,代理商将在小区电动汽车充电管理中扮演重要角色。如何制定代理商的定价与购电策略,实现代理商与电动汽车车主双赢,成为重要的研究课题。基于以上原因,提出了一种未来智能小区代理商的定价及购电策略,将代理商和车主各自追求利益最大化建模为主从博弈。该模型亦可为研究电动汽车参与的需求侧响应提供重要的借鉴。另外,还进一步通过Karush-KuhnTucker最优性条件和线性规划对偶定理将此博弈模型转化为混合整数线性规划问题进行求解,最终获得全局最优的定价策略。

The smart grid contains conventional loads and active loads. In China, the latter mainly consist of electric vehicles （EV）. One important feature of active loads is that their demand will vary in response to the electricity price. With the popularization of EVs, the retailer will play an increasingly important role in residential EV charging management. How to determine the real-time electricity price and the energy purchase strategy in the wholesale market while accounting for the profit of the retailer and EV owners becomes an important topic. To this end, this paper formulates the optimal pricing and dispatch problem of smart grid retailers as a Stackelberg game, in which the upper level maximizes the retailer＇s benefit, while the lower level minimizes the charging cost of each EV. The proposed method also provides important reference for the research on demand response management. The Stackelberg game model is transformed into a mixed integer linear program by jointly using the Karush-Kuhn-Tucker （KKT） optimality condition as well as the duality theorem of linear programming. Finally the global optimal pricing strategy can be computed by using commercial solvers.