计及用电行为聚类的智能小区互动化需求响应方法

针对复杂智能用电环境下智能用电小区的多用户日负荷需求响应问题,提出一种考虑用户用电行为聚类的互动需求响应方法。首先,以智能小区用户的基本负荷、可调度负荷、电动车负荷和储能装置负荷为约束条件,建立电网负荷波动最小优化目标的需求响应模型;然后,阐述了提出的智能小区互动化需求响应方法,将需求响应模型求解过程分解为电网侧子响应和用户侧子响应的协作互动过程;最后,基于用户侧用电行为聚类分析,采用行为矫正的混合粒子群优化算法实现需求响应模型的互动化方法求解。实验中与分时电价下的响应算法及无用户聚类的集中响应算法对比,其结果表明所提方法通过聚类分析与互动化策略能够在优化结果和算法性能方面优于对比方法。

Interactive Demand Response Method of Smart Community Considering Clustering of Electricity Consumption Behavior

To solve the users daily load demand response problem in the smart community under the complex, this paper proposes a bi-direction interactive demand response method amidst the smart grid and users, which considers the users'' clustering for the electricity consumption behavior. Firstly, this paper builds the demand response model aiming at minimizing the load fluctuation in the grid, in which the constraints include the base load, schedulable load, pure electric vehicles load and storing device load. Secondly, the proposed method is depicted in detail, the solution procedure for the demand response model is decomposed into interactive collaboration between the two subordinate responses and the grid and users. Finally, the proposed method is implemented by a hybrid particle swarm optimization algorithm based on the particle''s behavior modification, which is based on the clustering analysis of the users'' electricity consumption behavior. Simulation results show that the proposed method is superior in performance to the comparative algorithms in terms of the optimization results and algorithm complexity and by means of the clustering analysis and interaction mechanism.