Low-Carbon Economic Optimization of Integrated Energy Systems with Carnot Battery Considering Demand Response

This study addresses the issue of poor economic and environmental performance in traditional combined heat and power (CHP) systems due to insufficient flexibility in heat and electricity coupling. A multi-energy complementary integrated energy system (IES) optimization operation model, that includes a Carnot battery (CB), is proposed. In this model, demand response (DR) is categorized into price-based and substitution-based types, and a price-based DR model is established based on the price elasticity matrix. Additionally, a ladder carbon emission mechanism oriented towards IES is constructed, using the base-line method to allocate free carbon emission quotas for the system, and taking into account actual carbon emissions. The low-carbon optimization operation model aims to minimize energy purchase costs, carbon trading costs, and operational and maintenance costs. The effectiveness of the model is verified through simulation analysis of three typical cases, and the results indicate that the model can significantly reduce operating costs, decrease the rate of wind and solar power curtailment, enhance system revenue, and improve the flexibility and peak-shaving capability of CHP units. The integration of the CB and DR enhances the system's flexibility, optimizes the supply of electricity and heat, and improves the system's energy utilization efficiency, providing an effective strategy and tool for achieving low-carbon operation goals. Keywords-integrated energy systems, demand response, low-carbon operation,carnot battery

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Published
2024-12-13
DOI
https://doi.org/10.1109/icpes63746.2024.10856672
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.00

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Low-Carbon Economic Optimization of Integrated Energy Systems with Carnot Battery Considering Demand Response

Xiang Lin, Xiaoxun Zhu, Shiyuan Liu, Penghui Wang et al.
Smart Grid Energy Management
article

Low-Carbon Economic Optimization of Integrated Energy Systems with Carnot Battery Considering Demand Response

Xiang Lin, Xiaoxun Zhu, Shiyuan Liu, Penghui Wang, Baiyun Qian
article en

Abstract

This study addresses the issue of poor economic and environmental performance in traditional combined heat and power (CHP) systems due to insufficient flexibility in heat and electricity coupling. A multi-energy complementary integrated energy system (IES) optimization operation model, that includes a Carnot battery (CB), is proposed. In this model, demand response (DR) is categorized into price-based and substitution-based types, and a price-based DR model is established based on the price elasticity matrix. Additionally, a ladder carbon emission mechanism oriented towards IES is constructed, using the base-line method to allocate free carbon emission quotas for the system, and taking into account actual carbon emissions. The low-carbon optimization operation model aims to minimize energy purchase costs, carbon trading costs, and operational and maintenance costs. The effectiveness of the model is verified through simulation analysis of three typical cases, and the results indicate that the model can significantly reduce operating costs, decrease the rate of wind and solar power curtailment, enhance system revenue, and improve the flexibility and peak-shaving capability of CHP units. The integration of the CB and DR enhances the system's flexibility, optimizes the supply of electricity and heat, and improves the system's energy utilization efficiency, providing an effective strategy and tool for achieving low-carbon operation goals. Keywords-integrated energy systems, demand response, low-carbon operation,carnot battery

North China Electric Power University (CN), Inner Mongolia Electric Power (China) (CN)
Electric Power Research Institute
Affordable and clean energy
Openalex Percentile: Top 76%
Smart Grid Energy Management
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Low-Carbon Economic Optimization of Integrated Energy Systems with Carnot Battery Considering Demand Response — Xiang Lin, Xiaoxun Zhu, et al. · (2024) | TGRS Research Map | TGRS