基于电器状态关联分析的民可平移负荷辨识

Resident Shiftable Loads Monitoring Based on Load States Set Correlation Analysis

为了提升居民用户参与需求响应的积极性,考虑居民用户的舒适度和使用习惯是非常重要的。该文提出一种基于负荷状态集关联分析的居民用户可平移负荷辨识。首先提出了滑动均值负荷状态提取法,通过负荷的电流值提取负荷的工作状态,形成负荷状态集。然后建立负荷状态集关联分析模型,并利用FP-Growth算法求解,得到负荷的强关联性和时间关联性。最后对于需要进行可平移负荷辨识的日用电负荷状态集进行强关联状态集合划分,并根据负荷状态集的时间关联性确定其是否可平移以及平移可接受时段,从而完成可平移负荷辨识,为居民需求响应的分布式控制、家庭用能管理优化提供数据基础。

To guide residents to participate demand response,a shiftable load monitoring algorithm was proposed based on the analysis of load states set correlation.Firstly,a sliding average method was introduced to extract the load states,which extracts load’s working states from its current value and form the load states set.Then load states set correlation analysis model was established,load states correlation and load characteristic time could be obtained by using FP-Growth solver.The former leads to a strongcorrelated loads set from the data of daily electricity demand,while the latter determines whether the loads set is shiftable and the time period of being shiftable.The daily shiftable loads monitoring was achieved from both results,which can provide necessary data to distributed control of resident demand response and optimization of household energy management.