考虑多负荷聚集商参与的系统日前-日内分层优化调度策略

Day-Ahead and Intra-day Time Scale Hierarchical Dispatch Strategy for Power System Considering Load Aggregators

需求响应(DR);负荷聚集商(LA);主从博弈;目标级联分析(ATC)中文摘要:需求响应(demand response,DR)技术是系统削峰填谷,提高运行经济性和风电消纳的重要手段。针对风电和需求侧资源的时间特性,考虑到电网调度层和负荷聚集商(load aggregator,LA)之间主从博弈的关系,建立了多负荷聚集商参与的日前-日内分层优化调度模型。针对日前风电和价格型需求响应(price-based demand response,PDR)资源的不确定性,采用基于场景和模糊机会约束相结合的方法建立日前调度模型;针对日内多聚集商参与系统运行,采用目标级联分析(analytical target cascading,ATC)法对日内模型解耦,实现了各部分的并行求解。文章算例中通过对PDR和负荷聚集商的调度分别使系统综合运行成本降低了4.5%和6%,且各负荷聚集商收益均高于最低收益率8%,说明所提出的分层优化调度策略能在减小系统综合经济成本的同时保证各负荷聚集商的收益,且在一定程度上增强了系统的调峰能力。

Demand response(DR)has been an important mean for peaking adjustment,operation economy raising and w ind curtailment reduction.Considering the time characteristics of w ind pow er and demand-side resources,as w ell as the stackelberg game betw een pow er grid dispatch and load aggregators(LAs),this paper establishes a tw o-stage hierarchical dispatch model.In this paper,a fuzzy chance constraint programming is used to deal with the uncertainties of wind power,loads and demand-side resources.Aiming at hierarchical distributed intra-day model with multiple load aggregators,this paper adopts analytical target cascading(ATC)in model decoupling,and the parallel solution of each part is realized.The test results show that the costs of power system has been decreased to 95.5%and 94%by dispatching DR and LAs,respectively,while each LA earnings have been increased more than 8%,which means the proposed strategy can enhance economy of power system and take all load aggregators earnings into account,and promote wind power accommodation as well.