Blockchain-based optimization of operation and trading among multiple microgrids considering market fairness

The microgrid (MG) provides a viable pathway for integrating distributed energy resources (DERs). With the development of the electricity market, the current challenge lies in guiding DERs to enter the market correctly and establishing a fair and equitable market order. In this paper, a virtual power plant (VPP) model is established by aggregating multi-microgrids (MMGs) with an architecture that combines centralized management of the VPP and blockchain-based decentralized transactions between MGs. Market transactions increase the complexity of energy interactions between MGs in the VPP and generate a significant amount of associated data, thereby imposing higher demands on the fairness of transactions and data privacy. In this regard, a blockchain-based optimization method for the operation and trading among MMGs is developed. We design a priority-based bilateral auction model and introduce a malicious bid penalty mechanism to ensure the orderliness of energy interactions between different MGs. To ensure the privacy of transaction prices, a cryptographic algorithm based on Pedersen commitment is proposed, allowing the upper VPP to supervise the legality of electricity settlements under private prices. In the case study, the proposed model is solved by the Equilibrium Optimizer and CPLEX solver. The results show that the proposed method performs well in reducing costs, restraining malicious bids, and protecting price privacy, which is conducive to the healthy development of the electricity market. • A VPP model based-on MMGs is established, proposing an architecture combining centralized management of the upper VPP and blockchain-based decentralized transactions between MGs. • An optimization method for the operation and trading of MMGs within the VPP is proposed, incorporating a priority-based bilateral auction model and a malicious bid penalty mechanism to enhance market fairness. • An encryption algorithm based on Pedersen commitment is proposed to encrypt transaction prices, ensuring the privacy of participants while strengthening the market supervision.

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Publication Details

Journal
International Journal of Electrical Power & Energy Systems
Published
2025-02-22
DOI
https://doi.org/10.1016/j.ijepes.2025.110523
Citations
37
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
27.03
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article

Blockchain-based optimization of operation and trading among multiple microgrids considering market fairness

Tianguang Lü, Hongyu Zeng, Yu Guo, Xiaotong Xu et al.
37 citations
International Journal of Electrical Power & Energy Systems
Smart Grid Energy Management
27.03
article

Blockchain-based optimization of operation and trading among multiple microgrids considering market fairness

Tianguang Lü, Hongyu Zeng, Yu Guo, Xiaotong Xu, Yueping Yang, Qinzheng Wu, Hao Liu
article en
37 citations

Abstract

The microgrid (MG) provides a viable pathway for integrating distributed energy resources (DERs). With the development of the electricity market, the current challenge lies in guiding DERs to enter the market correctly and establishing a fair and equitable market order. In this paper, a virtual power plant (VPP) model is established by aggregating multi-microgrids (MMGs) with an architecture that combines centralized management of the VPP and blockchain-based decentralized transactions between MGs. Market transactions increase the complexity of energy interactions between MGs in the VPP and generate a significant amount of associated data, thereby imposing higher demands on the fairness of transactions and data privacy. In this regard, a blockchain-based optimization method for the operation and trading among MMGs is developed. We design a priority-based bilateral auction model and introduce a malicious bid penalty mechanism to ensure the orderliness of energy interactions between different MGs. To ensure the privacy of transaction prices, a cryptographic algorithm based on Pedersen commitment is proposed, allowing the upper VPP to supervise the legality of electricity settlements under private prices. In the case study, the proposed model is solved by the Equilibrium Optimizer and CPLEX solver. The results show that the proposed method performs well in reducing costs, restraining malicious bids, and protecting price privacy, which is conducive to the healthy development of the electricity market. • A VPP model based-on MMGs is established, proposing an architecture combining centralized management of the upper VPP and blockchain-based decentralized transactions between MGs. • An optimization method for the operation and trading of MMGs within the VPP is proposed, incorporating a priority-based bilateral auction model and a malicious bid penalty mechanism to enhance market fairness. • An encryption algorithm based on Pedersen commitment is proposed to encrypt transaction prices, ensuring the privacy of participants while strengthening the market supervision.

International Journal of Electrical Power & Energy SystemsVol. 166
Shandong University (CN), State Grid Corporation of China (China) (CN)
Openalex Percentile: Top 0%
Smart Grid Energy Management
27.03
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