Optimal Operation of Generation Company’s Participating in Multiple Markets with Allocation and Exchange of Energy-Consuming Rights and Carbon Credits

The proposal of the energy-consuming right (ECR) market may lead to generation companies (GenCos) facing the risk of being overcharged due to the inaccurate calculation of carbon emission reduction, since it claims the same credit as the carbon market does. To estimate the carbon emission reduction accurately for the GenCos that participate in electricity, carbon, and ECR markets simultaneously, this paper proposes a market framework where a flexible exchange mechanism between the ECR and carbon markets is specially considered. To investigate the influence of the allocation and exchange of ECR and carbon credits on the behavior of GenCos that participate in multi-type markets, a bi-level model based on the leader–follower game theory is proposed. In the upper level of the proposed model, a decision problem for maximizing the profit of GenCos is developed, which is especially constrained to the primary allocation of ECR and carbon credits. While the multi-type market clearing model and an exchange mechanism between the ECR and carbon credits are proposed in the lower level of the model. The bi-level problem is converted into the mathematical program with equilibrium constraints (MPECs) through the Karush–Kuhn–Tucker (KKT) condition to solve. The results illustrate that the interaction between the ECR market and the carbon market can improve the energy efficiency and reduce the carbon emissions of GenCos.

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Publication Details

Journal
Energies
Published
2024-11-23
DOI
https://doi.org/10.3390/en17235884
Primary Topic
Integrated Energy Systems Optimization
Type
article
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article

Optimal Operation of Generation Company’s Participating in Multiple Markets with Allocation and Exchange of Energy-Consuming Rights and Carbon Credits

Muyao Li, Shilei Wu, Xun Dou, Hanyu Yang et al.
Energies
Integrated Energy Systems Optimization
article

Optimal Operation of Generation Company’s Participating in Multiple Markets with Allocation and Exchange of Energy-Consuming Rights and Carbon Credits

Muyao Li, Shilei Wu, Xun Dou, Hanyu Yang, Ye Zhang, Mengru Ding
article en

Abstract

The proposal of the energy-consuming right (ECR) market may lead to generation companies (GenCos) facing the risk of being overcharged due to the inaccurate calculation of carbon emission reduction, since it claims the same credit as the carbon market does. To estimate the carbon emission reduction accurately for the GenCos that participate in electricity, carbon, and ECR markets simultaneously, this paper proposes a market framework where a flexible exchange mechanism between the ECR and carbon markets is specially considered. To investigate the influence of the allocation and exchange of ECR and carbon credits on the behavior of GenCos that participate in multi-type markets, a bi-level model based on the leader–follower game theory is proposed. In the upper level of the proposed model, a decision problem for maximizing the profit of GenCos is developed, which is especially constrained to the primary allocation of ECR and carbon credits. While the multi-type market clearing model and an exchange mechanism between the ECR and carbon credits are proposed in the lower level of the model. The bi-level problem is converted into the mathematical program with equilibrium constraints (MPECs) through the Karush–Kuhn–Tucker (KKT) condition to solve. The results illustrate that the interaction between the ECR market and the carbon market can improve the energy efficiency and reduce the carbon emissions of GenCos.

EnergiesVol. 17(23)
Nanjing Tech University (CN), Inner Mongolia Electric Power (China) (CN), China Electric Power Research Institute
Affordable and clean energy
Openalex Percentile: Top 81%
Integrated Energy Systems Optimization
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Optimal Operation of Generation Company’s Participating in Multiple Markets with Allocation and Exchange of Energy-Consuming Rights and Carbon Credits — Muyao Li, Shilei Wu, et al. · Energies (2024) | TGRS Research Map | TGRS