Title: Collaborative planning method for integrated energy system based on improved compressed sensing algorithm

Authors: Yan Li; Xiaojun Zhu; Qingshan Wang; Qiong Wang; Na Li; Yinzhe Xie; Zhu Chen

Addresses: State Grid Jiangsu Electric Power Design Consulting Co., Ltd., Nanjing, Jiangsu Province, China; State Grid Jiangsu Electric Power Co., Ltd., Economic Research Institute, Nanjing, Jiangsu Province, China ' State Grid Jiangsu Electric Power Design Consulting Co., Ltd., Nanjing, Jiangsu Province, China; State Grid Jiangsu Electric Power Co., Ltd., Economic Research Institute, Nanjing, Jiangsu Province, China ' State Grid Jiangsu Electric Power Design Consulting Co., Ltd., Nanjing, Jiangsu Province, China; State Grid Jiangsu Electric Power Co., Ltd., Economic Research Institute, Nanjing, Jiangsu Province, China ' State Grid Jiangsu Electric Power Design Consulting Co., Ltd., Nanjing, Jiangsu Province, China; State Grid Jiangsu Electric Power Co., Ltd., Economic Research Institute, Nanjing, Jiangsu Province, China ' East China Electric Power Design Institute of China Power Engineering Consulting Group, Huangpu District, Shanghai, China ' East China Electric Power Design Institute of China Power Engineering Consulting Group, Huangpu District, Shanghai, China ' East China Electric Power Design Institute of China Power Engineering Consulting Group, Huangpu District, Shanghai, China

Abstract: Aiming at the problems of high-energy cost, high-energy consumption and environmental pollution in existing methods, a collaborative planning method for integrated energy systems based on improved compressed sensing algorithm is proposed. Build a comprehensive energy system architecture that includes modules for energy production, storage and conversion, transmission and distribution, consumption and management. Establish a collaborative planning mathematical model based on the characteristics of the architecture, set three objective functions: total energy consumption, total cost and total pollutant emissions, and set corresponding energy consumption, cost and environmental protection constraints. The improved compressed sensing algorithm is used for the integrated energy system collaborative planning, and the optimal solution is output, which is the optimal integrated energy system collaborative planning scheme. The experimental results show that the proposed method effectively reduces energy costs and energy consumption, and significantly reduces carbon dioxide emissions, indicating that the proposed method has practical value.

Keywords: improved compressed sensing algorithm; integrated energy system; search for updates; constraint condition.

DOI: 10.1504/IJGEI.2025.147236

International Journal of Global Energy Issues, 2025 Vol.47 No.4/5, pp.452 - 465

Received: 30 May 2023
Accepted: 22 Nov 2023
Published online: 14 Jul 2025 *

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