Collaborative planning method for integrated energy system based on improved compressed sensing algorithm
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.
Authors
- Xiaojun Zhu (ORCID: https://orcid.org/0000-0003-0931-2927)
- Chen Zhu (ORCID: https://orcid.org/0000-0002-3256-7330)
- Yinzhe Xie
- Qiong Wang (ORCID: https://orcid.org/0000-0002-3313-8263)
- Na Li (ORCID: https://orcid.org/0000-0003-2572-0955)
- Qingshan Wang (ORCID: https://orcid.org/0000-0003-4264-0180)
- Yan Li (ORCID: https://orcid.org/0009-0002-9931-719X)
Institutions
- Shanghai Electric (China) (CN)
- China Power Engineering Consulting Group (China) (CN)
Publication Details
- Journal
- International Journal of Global Energy Issues
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1504/ijgei.2025.147236
- Primary Topic
- Power Systems and Renewable Energy
- Type
- article
- Field-Weighted Citation Impact
- 0.00