Collaborative optimization of regional integrated energy system with multiple energy storage
•A collaborative optimization method for multiple energy storage systems is proposed.•A dual-population coevolution multi-objective optimization algorithm is introduced.•Relative entropy is integrated into traditional objective decision-making methods.•The optimization with different energy storage...
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| Vydané v: | Applied thermal engineering Ročník 276; s. 126969 |
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| Hlavní autori: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Elsevier Ltd
01.10.2025
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| Predmet: | |
| ISSN: | 1359-4311 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | •A collaborative optimization method for multiple energy storage systems is proposed.•A dual-population coevolution multi-objective optimization algorithm is introduced.•Relative entropy is integrated into traditional objective decision-making methods.•The optimization with different energy storage configurations is analyzed.
Energy storage technologies play a crucial role in optimizing the resource utilization of energy systems, both spatially and temporally. To address the complexities involved in configuring and operating regional integrated energy systems with multiple energy storage, this work proposes an effective multi-objective collaborative optimization strategy. Firstly, a regional integrated energy system model incorporating various energy storage technologies was constructed. Next, a dual-population multi-objective optimization algorithm, combining the advantages of different optimization algorithms, was designed to optimize three key dimensions: economic performance, environmental impact, and energy efficiency. An improved solution set optimization method, based on the relative entropy theory, was then applied to identify the optimal solution. The impact of different energy storage strategies on system performance and collaborative optimization outcomes was analyzed. The results demonstrate that the proposed strategy significantly improves system performance, achieving balanced optimization across multiple dimensions, with specific improvements of 32.5 % in economic performance, 53.6 % in environmental impact reduction, and 133.9 % in energy efficiency. This approach provides an effective framework for optimizing energy storage cooperation, enhancing the overall performance of integrated energy systems. The strategy is scalable to other energy systems and offers valuable insights for energy policy and technological innovation. |
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| ISSN: | 1359-4311 |
| DOI: | 10.1016/j.applthermaleng.2025.126969 |