基于模糊激励型需求响应的微电网两阶段优化调度模型

针对微电网中风电和负荷不确定性,提出一种基于价格型需求响应(price-based demand response,PBDR)的日前负荷调度和基于激励型需求响应(incentive-based demand response,IBDR)的实时负荷调度的两阶段优化调度模型。在日前阶段,根据用户需求对电价的响应,引入需求价格弹性建立了用户响应模型;在实时调度阶段,为了挖掘不同用户参与需求响应的积极性,利用模糊工具求出不同用户的动态激励方案,提高需求响应项目的参与度。算例分析结果表明,两阶段调度模型相较于只采用日前价格型需求响应提高了风电消纳能力,增加了电网和用户的经济效益;而较于只采用实时激励型需求响应增强了削峰填谷作用,提高系统运行的平稳性。同时动态激励价格比固定式激励价格使负荷曲线峰谷差更小,进一步减少了弃风量。

Two-Stage Optimal Dispatching Model of Microgrid Based on Fuzzy Incentive Demand Response

Aiming at the uncertainty of wind power and load in microgrid， a two-stage optimal scheduling model based on price demand response and incentive demand response is proposed. In the day-ahead stage， according to the response of the user's demand to the electricity price， the user's response model is established by introducing the demand price elasticity. In the real-time scheduling stage， in order to mine the corresponding enthusiasm of different users to participate in the demand， the dynamic incentive schemes of different users are calculated by using the fuzzy tools to improve the participation of demand-response projects. The analysis results show that the two-stage scheduling model can not only improve the stability of the system operation， effectively solve the problem of wind power accommodation， but also increase the economic benefits of the grid and users.