Low-Carbon Demand Response Strategy for Park-Level Integrated Energy Systems Based on Typical Electricity–Carbon Coupling Scenarios

This paper addresses the low-carbon operation of integrated energy systems (PIESs) by proposing a carbon-aware demand response strategy with synergistic participation from consumers and energy storage. Initially, two typical scenarios—“electricity–carbon peak alignment” and “electricity–carbon peak misalignment”—are generated based on uncertainties in renewable generation and load profiles. These scenarios aim to characterise the coupling relationship between electricity and carbon emissions, providing a contextual basis for guiding responsive behaviours of consumers and storage systems. Subsequently, a carbon emission flow model incorporating energy conversion and storage is developed to quantify the carbon emission impacts of both consumers and energy storage units. Furthermore, a carbon-aware demand response strategy is formulated using dynamic carbon signals, coupled with an assessment model for carbon reduction benefits. Experimental validation across both scenarios demonstrates the efficacy of the proposed strategy in promoting low-carbon PIES operation. Compared to traditional electricity demand response, the proposed low-carbon demand response strategy enhances carbon emission reduction by 21.5% under the “electricity–carbon peak alignment” scenario, and this reduction even doubles under the “electricity–carbon peak misalignment” scenario. Additionally, the integration of energy storage for response increases the park’s average carbon reduction by 15%. This demonstrates that the strategy proposed in this paper significantly improves the park’s capability for carbon emission reduction.

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Journal
Processes
Published
2025-11-07
DOI
https://doi.org/10.3390/pr13113606
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Low-Carbon Demand Response Strategy for Park-Level Integrated Energy Systems Based on Typical Electricity–Carbon Coupling Scenarios

Zhe Chen, Zhixin Fu, Hao Wang, Haixin Wu et al.
Processes
Integrated Energy Systems Optimization
article

Low-Carbon Demand Response Strategy for Park-Level Integrated Energy Systems Based on Typical Electricity–Carbon Coupling Scenarios

Zhe Chen, Zhixin Fu, Hao Wang, Haixin Wu, Yongyong Jia, Zhou Jian-hua
article en

Abstract

This paper addresses the low-carbon operation of integrated energy systems (PIESs) by proposing a carbon-aware demand response strategy with synergistic participation from consumers and energy storage. Initially, two typical scenarios—“electricity–carbon peak alignment” and “electricity–carbon peak misalignment”—are generated based on uncertainties in renewable generation and load profiles. These scenarios aim to characterise the coupling relationship between electricity and carbon emissions, providing a contextual basis for guiding responsive behaviours of consumers and storage systems. Subsequently, a carbon emission flow model incorporating energy conversion and storage is developed to quantify the carbon emission impacts of both consumers and energy storage units. Furthermore, a carbon-aware demand response strategy is formulated using dynamic carbon signals, coupled with an assessment model for carbon reduction benefits. Experimental validation across both scenarios demonstrates the efficacy of the proposed strategy in promoting low-carbon PIES operation. Compared to traditional electricity demand response, the proposed low-carbon demand response strategy enhances carbon emission reduction by 21.5% under the “electricity–carbon peak alignment” scenario, and this reduction even doubles under the “electricity–carbon peak misalignment” scenario. Additionally, the integration of energy storage for response increases the park’s average carbon reduction by 15%. This demonstrates that the strategy proposed in this paper significantly improves the park’s capability for carbon emission reduction.

ProcessesVol. 13(11)
Hohai University (CN), Shanghai Electric (China) (CN)
Electric Power Research Institute, Science and Technology Project of State Grid, State Grid Jiangsu Electric Power
Openalex Percentile: Top 67%
Integrated Energy Systems Optimization
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