Collaborative planning method for integrated energy system based on improved compressed sensing algorithm
Yan Li,
Xiaojun Zhu,
Qingshan Wang,
Qiong Wang,
Na Li,
Yinzhe Xie and
Zhu Chen
International Journal of Global Energy Issues, 2025, vol. 47, issue 4/5, 452-465
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. (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijgeni:v:47:y:2025:i:4/5:p:452-465
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