Optimal scheduling method for multi-regional integrated energy system based on dynamic robust optimization algorithm and bi-level Stackelberg model

Bo Zhou; Erchao Li; Wenjing Liang

doi:10.1016/j.gloei.2024.11.018

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Optimal scheduling method for multi-regional integrated energy system based on dynamic robust optimization algorithm and bi-level Stackelberg model

Clean Energy | 更新时间：2025-09-24

- Optimal scheduling method for multi-regional integrated energy system based on dynamic robust optimization algorithm and bi-level Stackelberg model
- Optimal scheduling method for multi-regional integrated energy system based on dynamic robust optimization algorithm and bi-level Stackelberg model
- 全球能源互联网(英文) 2025年8卷第3期
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- DOI：10.1016/j.gloei.2024.11.018
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- 纸质出版日期：2025
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Optimal scheduling method for multi-regional integrated energy system based on dynamic robust optimization algorithm and bi-level Stackelberg model[J]. 全球能源互联网(英文), 2025,8(3).

Bo Zhou, Erchao Li, Wenjing Liang. Optimal scheduling method for multi-regional integrated energy system based on dynamic robust optimization algorithm and bi-level Stackelberg model[J]. Global energy interconnection, 2025, 8(3).
Optimal scheduling method for multi-regional integrated energy system based on dynamic robust optimization algorithm and bi-level Stackelberg model[J]. 全球能源互联网(英文), 2025,8(3). DOI： 10.1016/j.gloei.2024.11.018.

Bo Zhou, Erchao Li, Wenjing Liang. Optimal scheduling method for multi-regional integrated energy system based on dynamic robust optimization algorithm and bi-level Stackelberg model[J]. Global energy interconnection, 2025, 8(3). DOI： 10.1016/j.gloei.2024.11.018.

摘要

Abstract

In this study

we construct a bi-level optimization model based on the Stackelberg game and propose a robust optimization algorithm for solving the bi-level model

assuming an actual situation with several participants in energy trading.Firstly

the energy trading process is analyzed between each subject based on the establishment of the operation framework of multi-agent participation in energy trading.Secondly

the optimal operation model of each energy trading agent is established to develop a bi-level game model including each energy participant.Finally

a combination algorithm of improved robust optimization over time(ROOT)and CPLEX is proposed to solve the established game model.The experimental results indicate that under different fitness thresholds

the robust optimization results of the proposed algorithm are increased by 56.91%and 68.54%

respectively.The established bi-level game model effectively balances the benefits of different energy trading entities.The proposed algorithm proposed can increase the income of each participant in the game by an average of 8.59 %.

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