Identification of Generating Units That Abuse Market Power in Electricity Spot Market Based on AdaBoost-DT Algorithm

Abstract

The identification of generating units that abuse market power is an essential part of risk prevention in a spot market, especially in the early stage of the construction of the spot market. In this study, a model for identifying generating units that abuse market power is designed based on the AdaBoost-DT algorithm. It is targeted at the imbalance between samples of generating units that abuse market power and normal generating units in the spot market. First, the four main methods by which market power is abused by generating units in the spot market are described: collusion, economic withholding, physical withholding, and extreme quotation. Second, the specific characteristics of the four methods are analyzed, and the identification indexes for generating units that abuse market power are established. Thereafter, a sample set of generating units that abuse market power using different methods is constructed. Furthermore, a training set is formed with samples of normal generating units to construct a model based on the AdaBoost-DT algorithm, for identifying generating units that abuse market power. Finally, the spot market data of a certain region are used for an example analysis. The results show that the accuracy of model identification is 97%, which validates the method.