An aggregation strategy of air conditioning loads considering diversity of the load

Abstract

Through the reasonable aggregation and control of air conditioning loads (ACLs), the peak load of power grid can be reduced and the contradiction between supply and demand can be alleviated without affecting or less affecting the comfort of users. In order to further tap the demand response ability of aggregated loads, an aggregation strategy of ACLs considering diversity of the load is proposed. Firstly, grey relational analysis method is used to extract the thermal environmental characteristic parameters with high correlation to different categories of ACLs. Then, ACLs are classified by KNN algorithm; Finally, according to different control modes of ACLs, k-means algorithm is used to aggregate the load to obtain aggregated power. Through simulation verification, the aggregation strategy that retains the diversity of ACLs has high accuracy and can improve the aggregated active power capacity effectively. The strategy has higher practical application value.