Identification of Collusive Bidding Behavior in the Electricity Spot Market Based on Euclidean Distance and Density-Based Clustering

• Published in: 2024 4th International Conference on Energy Engineering and Power Systems (EEPS) pp. 1269 - 1275
• Main Authors: Fu, Jingyu, Zhou, Tao, Zhao, Xueting, Xiong, Yiheng, Qi, Hui, Zhang, Wei, Zhao, Jiaxin
• Format: Conference Proceeding
• Language: English
• Published: IEEE 09.08.2024
• Subjects: collusive offer recognition; component; density-based clustering; Electricity; Electricity supply industry; euclidean distance; Government; Power markets; Power systems; Pricing; Regulation; Supply and demand; Telephone sets; Vectors
• DOI: 10.1109/EEPS63402.2024.10804404

With the advancement of the construction of the electricity spot market, some electricity spot pilot areas have successively appeared the situation that the market main body conspires to quote to obtain common profit, which seriously jeopardizes the fairness of the market competition. In this context, the article establishes a set of methods that can identify the collusive quotation of power generation subjects in the electricity spot market. The article first defines the concept of collusive quoting behavior, and makes it clear that the regulatory focus of collusive quoting behavior is the quoting similarity behavior in on-floor trading. Secondly, it constructs a technical means to identify collusive offers in the spot electricity market based on capacity point price-Euclidean distance-density-based clustering, and designs a logical system to discriminate collusive offers that can minimize the risk of collusive misjudgment. Finally., the validity and feasibility of the collusive offer identification scheme is verified based on the bidding data of an electricity market simulation experiment.