Elsevier

Energy

Volume 238, Part A, 1 January 2022, 121634
Energy

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

https://doi.org/10.1016/j.energy.2021.121634Get rights and content

Highlights

  • An identification indicator system for generators' market power abuse is constructed.

  • The Lasso-logit model is used to identify the generators of market power abuse.

  • The important indicators for identifying the market power abuse is obtained.

Abstract

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.

Section snippets

Indicator system for identifying the market power abuse of generators

The construction of a scientific indicator system is the basis for accurately identifying the market power abuse of generators. Based on the supervision indicators of generator transaction behavior in domestic and foreign power markets [[31], [32], [33]], combined with China's power market's actual application, this section constructs an indicator system for identifying the market power abuse of generators.

Case analysis

Based on the electricity market's spot transaction data in a certain region, this study analyzes the 7-day transaction data of 174 thermal generators as the research objective. The market is cleared every 15 min, and 96 clearings on a certain day are selected as the research cycle.

In China's day-ahead market, generators submit the declaration curve one day in advance. Therefore, this study determines the declared capacity of each segment based on the declaration curve of the generators.

Conclusions

With the advancement of the electricity spot market, the electricity market's massive data exhibit features such as non-equilibrium and high-dimensionality, which poses a challenge for accurately identifying the market power abuse of generators. This study designs an indicator system for identifying the market power abuse of generators, introduces Lasso variable selection into the binary logit model, and proposes an identification method for the market power abuse of generators based on the

Role of the funding source

Bo Sun and Minmin Teng provided financial support for the conducting of the study and preparation of the article. Bo Sun formulated overarching study goals. Minmin Teng supervised the planning and execution of the study.

Author contributions

Bo Sun: Conceptualization, Funding acquisition. Ruilin Deng: Methodology, Software, Validation, Writing – original draft. Bin Ren: Investigation. Minmin Teng: Funding acquisition, Supervision. Siyuan Cheng: Writing- Reviewing and Editing. Fan Wang: Data curation, Visualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

This work was supported by the National Natural Science Foundation of China [grant number 71972127] and the Humanities and Social Sciences Research Fund Project of the Ministry of Education [grant number 15YJCZH147].

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