4.7 Article

Identification method of market power abuse of generators based on lasso-logit model in spot market

期刊

ENERGY
卷 238, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2021.121634

关键词

Spot market; Market power abuse; Lasso variable selection; Lasso-logit model; Identification method

资金

  1. National Natural Science Foundation of China [71972127]
  2. Humanities and Social Sciences Research Fund Project of the Ministry of Education [15YJCZH147]

向作者/读者索取更多资源

The study introduces the Lasso algorithm to improve model performance, successfully achieving accurate identification of market power abuse in the electricity spot market through the construction of indicator systems and model identification methods.
Accurate identification of violations of generators' market power abuse strongly guarantees that the electricity spot market operates smoothly. To reduce the collinearity of indicators and improve the model's performance, the least absolute shrinkage and selection operator (Lasso) is introduced into the binary logit model, and a method for identifying the market power abuse of generators based on the Lasso-logit model is proposed. First, an identification indicator system is constructed using three aspects: structural, behavioral, and impact indicators. Then, it is screened using the Lasso variable selection for identifying the market power abuse of generators. Based on these results, the Lasso-logit model for identifying the market power abuse of generators is established, and its performance is evaluated using the errors of two kinds and receiver operating characteristic (ROC) curve. Finally, the model is applied to an area's electricity spot market. The results show that the Lasso-logit model has a 96.6% correct rate and can be used to identify illegal generators of the market power abuse in the region. Indicators such as the high-price declaration rate, out-of-merit capacity index, marginal generator reaching the limit rate, market-clearing price and TOP-4 index have practical significance for identifying the market power abuse of generators. (c) 2021 Elsevier Ltd. All rights reserved.

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