基于改进匈牙利算法的非侵入式负荷匹配方法

针对非侵入式负荷监测中常用电力负荷开启与关闭的配对特性，本文提出了一种基于匈牙利算法的匹配方法。在该方法中，首先采用Prony滑动窗进行负荷事件检测，并以此提取投切前后的负荷变化特征信息；然后将负荷开启和关闭事件转换为二分图寻优匹配问题，结合增广路径寻找最大匹配的原理，建立功率代价矩阵模型，进而寻找负荷投入和切除的最佳匹配。进一步地，为了避免负荷事件开启和关闭的功率不对等，提出采用添加虚拟节点的策略对算法进行改进，引入灰色关联度评价与多重匹配策略。实验结果表明，所提出的方法能有效地识别出负荷的开启和关闭，为后续准确的负荷辨识奠定基础。

Non-Intrusive Load Matching Method Based on Improved Hungarian Algorithm

Aiming at the matching characteristics of appliances in non-intrusive load monitoring, this paper proposes a matching method based on Hungarian algorithm. This method using Prony sliding window algorithm to detect the event, and therefore extracts the characteristic change of the load information. The proposed method converts the power variation characteristics of appliances into a bipartite graph optimization matching problem and combines the augmented path to find the perfect match when appliances are turned on and off. Furthermore, in order to avoid the power of the load event being turned on and off is not equal, the algorithm is improved by adding virtual nodes. Also, we introduced grey correlation evaluation and multiple matching strategies in this paper. Experimental results show that the proposed method can identify the opening and closing of the load effectively, and lays a foundation for improving the accuracy of load identification.