ABSTRACT
This chapter provides an understanding of opportunities for data mining and data science in electricity theft detection. However, the advent of smart meters and data mining has enabled utilities to employ sophisticated methods to find potential theft. Data mining is incidentally synonymous with the following approaches: knowledge discovery in databases, data dredging, knowledge extraction, knowledge mining, data archaeology, and fishing. A wide variety of data-mining methods exist in the literature, the application of data mining to electricity theft detection has focused on only a narrow scope of the available methods. Digital meters can facilitate electricity theft detection by providing more data to analyze since usage can be logged at finer intervals, 15-minutes intervals. For electricity theft detection, anomaly detection methods can be used to find load profiles which are statistically different from normal, and majority, profiles. The advent of digital metering has enabled the exploitation of data-mining methods for electricity theft detection.
