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Low-Carbon Optimization Scheduling of Integrated Energy Systems Based on Bilateral Demand Response and Two-Level Stackelberg Game

Author

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  • Hua Pan

    (CHN ENERGY Investment Group Co., Ltd., Beijing 100011, China)

  • Qunli Wu

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Huiling Guo

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Jiayi Bai

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

Abstract

In the context of low-carbon energy transformation, fully utilizing the integrated demand response (IDR) resources on the load side can improve the operational flexibility and economy of the integrated energy system (IES). However, establishing a reasonable trading mechanism to enhance users’ participation in IDR has become a key issue that IES urgently needs to solve. To this end, this paper first establishes an IES model that includes electricity, heat, and gas. To reduce carbon emissions, a ladder-type carbon trading mechanism is introduced while adding low-carbon technologies such as carbon capture devices and power-to-gas conversion. Secondly, a bilateral IDR mechanism centered on the load aggregator (LA) is proposed, and a multi-agent operation model including IES, LA, and users is established. The IDR subsidy price is dynamically determined through a two-level Stackelberg game model involving IES, LA, and users. Then, through KKT conditions and the Big M method, the two-level game model is turned into an IES-LA game model, which is solved using a combination of the White Shark Optimization method and the Gurobi solver. The final simulation results show that the scheduling model can fully reflect the time value of IDR resources, and the IES cost is decreased by USD 152.22, while LA and user benefits are increased by USD 54.61 and USD 31.85. Meanwhile, the ladder-type carbon trading mechanism and low-carbon technology have effectively achieved low-carbon operation of the system.

Suggested Citation

  • Hua Pan & Qunli Wu & Huiling Guo & Jiayi Bai, 2024. "Low-Carbon Optimization Scheduling of Integrated Energy Systems Based on Bilateral Demand Response and Two-Level Stackelberg Game," Energies, MDPI, vol. 17(21), pages 1-26, November.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:21:p:5491-:d:1512905
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    References listed on IDEAS

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