Abstract
Non-intrusive load identification can help users understand the power consumption of various equipment, and at the same time can help the grid understand the load composition of the power system. This paper proposes a nonintrusive load identification method based on AP clustering to realize effective non-intrusive identification of partial resident load. First, the method uses the sliding window bilateral cumulative sum transient event detection algorithm to determine the switching time of the device. Then, three types of characteristics are extracted: active power change, reactive power change, and fundamental current amplitude change. After that, AP clustering algorithm is used to divide the three types of load characteristics. Finally, the BLUED data set is used to verify the effectiveness of the method.
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