Low-Carbon Optimization Scheduling for Systems Considering Carbon Responsibility Allocation and Electric Vehicle Demand Response

Bin Qian, Houpeng Hu, Jianlin Tang (), Yanhong Xiao, Xiaoming Lin and Zerui Chen
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Bin Qian: CSG Electric Power Research Institute, Guangzhou 510000, China
Houpeng Hu: Guizhou Power Grid Co., Ltd., Guizhou 550000, China
Jianlin Tang: CSG Electric Power Research Institute, Guangzhou 510000, China
Yanhong Xiao: Guizhou Power Grid Co., Ltd., Guizhou 550000, China
Xiaoming Lin: CSG Electric Power Research Institute, Guangzhou 510000, China
Zerui Chen: Guizhou Power Grid Co., Ltd., Guizhou 550000, China

Sustainability, 2025, vol. 17, issue 10, 1-22

Abstract: To achieve low carbon emissions in the power system and contribute to economic growth, a low-carbon optimization scheduling strategy for a power system, considering carbon responsibility sharing and electric vehicle demand response, is proposed based on the establishment of a flexible-load model guided by carbon potential. Firstly, utilizing the principle of proportional sharing to track carbon emission flow and establish a carbon emission flow model. Secondly, based on the Shapley value carbon responsibility allocation method, the reasonable range of carbon responsibility on each load side is calculated, and a hierarchical carbon price is established. A load aggregator demand response carbon emission model is established using the node carbon potential, and a dual-layer optimization scheduling model for the power system based on the node carbon potential demand response is constructed. The upper layer of the model is the optimal economic dispatch of the power grid operator, and the lower layer is the demand response economic dispatch of the load aggregator. Through numerical verification, the carbon trading model takes into account the system’s carbon emissions and overall operating costs while balancing the system’s low-carbon and economic aspects.

Keywords: carbon emission flow; demand response; electric vehicles; carbon responsibility allocation; low-carbon scheduling (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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