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多状态不确定性下的鲁棒机组组合:新模型与可扩展求解方法
Robust Unit Commitment With Multi-State Uncertainty: A Novel Formulation and Scalable Solution Method
| 作者 | Jikeng Lin · Zihang Zeng · Lingjie Liu · Guangyuan Zhu · Fushuan Wen |
| 期刊 | IEEE Transactions on Sustainable Energy |
| 出版日期 | 2025年6月 |
| 卷/期 | 第 17 卷 第 1 期 |
| 技术分类 | 系统并网技术 |
| 技术标签 | 调峰调频 弱电网并网 构网型GFM 模型预测控制MPC |
| 相关度评分 | ★★★★ 4.0 / 5.0 |
| 关键词 |
语言:
中文摘要
本文提出多状态不确定性集(MSUS)建模风电出力波动,结合条件分位数回归与马尔可夫链提升场景刻画精度;设计改进的不精确列约束生成法(II-C&CG)加速求解,显著降低保守性与计算耗时。
English Abstract
To mitigate the conservatism of scheduling schemes derived from the two-stage robust unit commitment model (TS-RUCM), this paper proposes a novel multi-state uncertainty set (MSUS) considering the uncertain wind power output (WPO). The MSUS formulates WPO uncertainties with higher resolution by introducing multiple discrete state values within the uncertain interval. Additionally, the MSUS limits extreme fluctuations of WPO uncertainties among state values through transition indicators embedded in multiple transition constraints. The state values and transition indicators are calculated using the conditional quantile regression technique and Markov chain analysis. This systematic and scientific approach allows the MSUS to effectively exclude low-probability WPO scenarios, thereby significantly mitigating the conservatism of the scheduling schemes. Moreover, to accelerate the computation of the TS-RUCM based on the MSUS, this paper proposes an improved inexact column and constraint generation (II-C&CG) method. The II-C&CG method employs an adaptive tolerance strategy and refined backtracking to solve master and subproblems inexactly while ensuring finite convergence, significantly reducing computational time. Case studies demonstrate the effectiveness and advantages of both the MSUS and the II-C&CG method.
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SunView 深度解读
该研究对阳光电源风光储协同调度与构网型储能系统(如PowerTitan、ST系列PCS)在弱电网/高比例新能源场景下的鲁棒运行具有直接支撑价值。MSUS可嵌入iSolarCloud智能云平台的日前-日内滚动优化模块,提升储能参与调峰调频的经济性与可靠性;II-C&CG算法可适配于阳光电源储能变流器本地化快速决策单元,增强构网型(GFM)模式下对风电波动的主动响应能力。建议在PowerStack光储融合系统中开展实证验证。