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Deregulation on the delivery side of the power market has continuously been moving forward worldwide, which make bidirectional flow and interactions between customers and grids needs to be more refined and in-depth. Large-scale coverage of the advanced metering infrastructure (AMI) brings in skyrocketing of an immense amount of fine-grained, real-time consumption data and causes communication traffic congestion between meters and a cloud computing center. To tackle these two challenges, this paper proposes a modified IP-based non-intrusive load monitoring approach using appliance characteristics extracted by quadratic symbolic aggregate approximation (2-SAX). A 2-SAX algorithm is implemented to carry out dimensionality reduction on equipment load data and extracted the state’s transition behavior characteristics and operation probability characteristics of each device. The extracted features can use to modify the disaggregation results of integer programming for overcoming the shortcomings of the previous IP approach. The developed method is tested with AMPds dataset. The results of experiments illustrate the 2-SAX consequences in 38.82%, 52.46%, and 13.41% reduction in MAE, MAPE, and RMSE on the heat pump and achieves similar performance on the other appliances, compared with normal SAX. Meanwhile, the proposed method MIP-AC2S delivers significant accuracy advantage and competitive performance over IP, ALIP, and MIP disaggregation method.

A Modified IP-Based NILM Approach Using Appliance Characteristics Extracted by 2-SAX