Research on a Low-Carbon Optimization Strategy for Regional Power Grids Considering a Dual Demand Response of Electricity and Carbon

Famei Ma (), Liming Ying, Xue Cui and Qiang Yu
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Famei Ma: Hubei Key Laboratory of Power Equipment & System Security for Integrated Energy, School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Liming Ying: Hubei Key Laboratory of Power Equipment & System Security for Integrated Energy, School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Xue Cui: Hubei Key Laboratory of Power Equipment & System Security for Integrated Energy, School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Qiang Yu: Yunnan Power Grid Co., Ltd., Grid Planning and Construction Research Center, Kunming 650011, China

Sustainability, 2024, vol. 16, issue 16, 1-20

Abstract: Considering the characteristics of the power system, where “the source moves with the load”, the load side is primarily responsible for the carbon emissions of the regional power grid. Consequently, users’ electricity consumption behavior has a significant impact on system carbon emissions. Therefore, this paper proposes a multi-objective bi-level optimization strategy for source-load coordination, considering dual demand responses for both electricity and carbon. The upper layer establishes a multi-objective low-carbon economic dispatch model for power grid operators, aiming to minimize the system’s total operating cost, the total direct carbon emissions of the power grid, and the disparity in regional carbon emissions. In the lower layer, a low-carbon economic dispatch model for load aggregators is established to minimize the total cost for load aggregators. To obtain the dynamic carbon emission factor signal, a complex power flow tracking method that considers the power supply path is proposed, and a carbon flow tracking model is established. NSGA-II is used to obtain the Pareto optimal frontier set for the upper model, and the ‘optimal’ scheme is determined based on the fuzzy satisfaction decision. The example analysis demonstrates that the interactive carbon reduction effect under the guidance of dual signals is the most effective. This approach fully exploits the carbon reduction potential of the flexible load, enhancing both the economic efficiency and low-carbon operation of the system.

Keywords: regional power grid; dynamic carbon emission factor; dual demand response of electricity and carbon; multi-objective bi-level optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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