Multi-stage low-carbon planning of an integrated energy system considering demand response

Frontiers in Energy Research

Energy Research

Jiajia Huan¹  Yusi Cheng²  Qiaoyi Ding²  Tao Yu² 

[1] Guangdong Power Grid Co., Ltd., Guangzhou, China;School of Electric Power Engineering, South China University of Technology, Guangzhou, China;

关键词: integrated energy systems;    multi-stage planning;    low-carbon planning;    data center;    demand response;   

DOI  :  10.3389/fenrg.2023.1259067

 received in 2023-07-15, accepted in 2023-08-14,  发布年份 2023

来源: Frontiers

【 摘 要 】

In the context of energy crisis, the development of low-carbon integrated energy systems has become a prominent research area. This article addresses the challenges posed by high energy consumption and emissions in integrated energy systems by proposing a multi-stage planning method for low-carbon integrated energy that considers load time transfer characteristics. The first step involves examining the time transfer characteristics of demand response and analyzing the economic benefits of integrated energy systems participating in the electricity–carbon market. Subsequently, a multi-stage green low-carbon planning model for the integrated energy system is constructed. To validate the effectiveness of the proposed model, actual calculation results are obtained. These results demonstrate that the demand response, specifically in data centers, can significantly reduce the operational costs of integrated energy systems. Furthermore, the multi-stage low-carbon planning approach is shown to be more reasonable and economically beneficial compared to single-stage planning. Overall, this research article provides insights into the development of low-carbon integrated energy systems within the context of energy crisis. By considering load time transfer characteristics and employing a multi-stage planning method, this article highlights the potential for reducing costs and improving the overall efficiency of integrated energy systems.

【 授权许可】

Unknown   
Copyright © 2023 Huan, Ding, Yu and Cheng.