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基于混合整数补救的输电与储能系统最小最大后悔鲁棒协同规划
Minimax Regret Robust Co-Planning of Transmission and Energy Storage Systems With Mixed Integer Recourse
| 作者 | Ehsan Barkom · Hossein Saber · Moein Moeini-Aghtaie · Mehdi Ehsan · Mohammad Shahidehpour |
| 期刊 | IEEE Transactions on Sustainable Energy |
| 出版日期 | 2025年3月 |
| 技术分类 | 储能系统技术 |
| 技术标签 | 储能系统 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | 可再生能源 输电与储能系统 极小极大后悔鲁棒协同规划模型 不确定性 求解策略 |
语言:
中文摘要
可再生能源的间歇性与不确定性给电力系统安全高效运行带来新挑战。本文提出一种从中心规划视角出发的输电与储能系统最小最大后悔鲁棒协同规划模型,考虑未来负荷峰值增长的多面体不确定集,并通过内部场景分析处理风电扩容不确定性。模型采用混合整数补救策略,确保投资决策的鲁棒性,并量化所有可能场景下的最大后悔值。通过重构为标准min-max-min形式,并设计基于改进嵌套列与约束生成的五层求解策略,有效应对线路与储能单元二元变量带来的复杂性。仿真验证了模型的可行性、实用性与有效性。
English Abstract
The growing penetration of renewable energy sources, with intermittent and uncertain nature, brings new challenges to the secure and efficient operation of power systems. Expanding transmission networks and utilizing energy storage (ES) have been introduced as effective solutions to address these challenges. This paper presents a minimax regret robust co-planning model with mixed integer recourse for transmission and ES systems, designed from the perspective of a central planner. The model considers a polyhedral uncertainty set for future peak load growth, while uncertainties in wind farm expansion are addressed through internal scenario analysis. This approach will guarantee the robustness of investment decisions and provide the central planner with a clear picture of the maximum regret among all possible scenarios. Furthermore, the proposed minimax regret framework facilitates strategic planning for ES installation after the resolution of long-term uncertainties. In this paper, we reformulate the model into a standard min-max-min problem, in which the maximization level is only over uncertainties. Subsequently, a five-level solution strategy based on a modified nested column and constraint generation decomposition technique is represented to deal with the intractability and complexity of the problem caused by binary variables of transmission lines and ES blocks. The model is finally evaluated through comprehensive simulation studies to verify its tractability, practicality, and effectiveness.
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SunView 深度解读
该输电储能协同规划技术对阳光电源PowerTitan大型储能系统及ESS集成方案具有重要应用价值。文章提出的最小最大后悔鲁棒优化模型可直接应用于阳光电源储能系统的容量配置与选址决策,特别是在面对可再生能源不确定性时,混合整数补救策略能优化ST系列储能变流器的投资部署方案。五层求解算法可集成至iSolarCloud云平台,为大规模储能项目提供智能规划工具,量化投资风险并降低最大后悔值。该方法结合阳光电源构网型GFM控制技术,可提升储能系统在电网侧的调度灵活性与经济性,为源网荷储一体化项目提供科学决策支持。