基于结构熵权法的非侵入式家电识别研究

Recognition research for non-intrusive appliances based on structure entropy weight method

单一特征所得到的识别结果可能会与实际用电情况不一致,并且居民用电行为是影响负荷识别的重要因素之一,为了更可靠地提升非侵入式电力负荷的分解能力,提出将居民用电行为作为负荷识别的特征之一,并通过结构熵权法将居民用电行为与有功功率、无功功率和电流谐波特征相结合的多特征识别算法,即将定量分析的熵值法和定性分析的主观赋值法相结合,确定最终权值,获得负荷识别结果。最后,采用案例分析,对采用结构熵权法的多特征识别算法与单一特征以及未考虑居民用电行为的负荷识别方式进行对比。结果证明,考虑居民用电行为的多特征识别算法可以有效地提高负荷识别的准确率。

The recognition result of the single feature may be inconsistent with the actual electricity consumption situation,and the residential electricity behavior is one of the important factors that affect the load identification.In order to improve the decomposition ability of non-intrusive electric load more reliably,the residential electricity behavior is proposed to be as one of the characteristics of load identification,and through the structural entropy method,the residential electricity behavior is related to active power,reactive power and current harmonics feature combination of the multi-feature recognition algorithm,that is,the quantitative analysis of the entropy method and qualitative analysis of the subjective assignment method to determine the final weight,access to load recognition results.Finally,the multifeature recognition algorithm with structural entropy method is compared with the single feature and the load recognition mode without taking into account the behavior of residents.The results show that the multi-feature recognition algorithm considering the behavior of residents can effectively improve the accuracy rate of load identification.