电网技术
電網技術
전망기술
Power System Technology
2015年
4期
939-945
,共7页
魏韡%陈玥%刘锋%梅生伟%田芳%张星
魏韡%陳玥%劉鋒%梅生偉%田芳%張星
위위%진모%류봉%매생위%전방%장성
智能电网%电动汽车充电%定价%主从博弈
智能電網%電動汽車充電%定價%主從博弈
지능전망%전동기차충전%정개%주종박혁
smart grid%electric vehicles charging%pricing%stackelberg game
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-Kuhn- Tucker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。
智能電網的負荷包括傳統負荷和主動負荷,我國配電網側的主動負荷主要由電動汽車構成,功率需求隨電價變化是其重要特點之一。隨著電動汽車的普及,代理商將在小區電動汽車充電管理中扮縯重要角色。如何製定代理商的定價與購電策略,實現代理商與電動汽車車主雙贏,成為重要的研究課題。基于以上原因,提齣瞭一種未來智能小區代理商的定價及購電策略,將代理商和車主各自追求利益最大化建模為主從博弈。該模型亦可為研究電動汽車參與的需求側響應提供重要的藉鑒。另外,還進一步通過 Karush-Kuhn- Tucker最優性條件和線性規劃對偶定理將此博弈模型轉化為混閤整數線性規劃問題進行求解,最終穫得全跼最優的定價策略。
지능전망적부하포괄전통부하화주동부하,아국배전망측적주동부하주요유전동기차구성,공솔수구수전개변화시기중요특점지일。수착전동기차적보급,대리상장재소구전동기차충전관리중분연중요각색。여하제정대리상적정개여구전책략,실현대리상여전동기차차주쌍영,성위중요적연구과제。기우이상원인,제출료일충미래지능소구대리상적정개급구전책략,장대리상화차주각자추구이익최대화건모위주종박혁。해모형역가위연구전동기차삼여적수구측향응제공중요적차감。령외,환진일보통과 Karush-Kuhn- Tucker최우성조건화선성규화대우정리장차박혁모형전화위혼합정수선성규화문제진행구해,최종획득전국최우적정개책략。
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.