台风灾害下考虑多元随机变量的分布式鲁棒优化调度

张 志; 郝俊聪; 产雪振; 杨 楠

引用本文:	张志,郝俊聪,产雪振,等.台风灾害下考虑多元随机变量的分布式鲁棒优化调度[J].电力系统保护与控制,2026,54(07):162-173.
	ZHANG Zhi,HAO Juncong,CHAN Xuezhen,et al.Distributed robust optimal scheduling considering multivariate random variables under typhoon disasters[J].Power System Protection and Control,2026,54(07):162-173

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台风灾害下考虑多元随机变量的分布式鲁棒优化调度
张志^1，2，郝俊聪³，产雪振⁴，杨楠³
1.新型电力系统运行与控制全国重点实验室(清华大学电机系)，北京 100084；2.国家电网有限公司，北京 100031； 3.梯级水电站运行与控制湖北省重点实验室(三峡大学)，湖北宜昌 443002；4.国网安徽省电力有限公司安庆供电公司，安徽安庆 246000

摘要:

为了应对台风等极端天气给电力系统安全稳定运行带来的严峻挑战，提出一种考虑多元随机变量的分布式鲁棒优化机组组合模型。首先，构建了面向台风灾害的新能源机组出力模型和电网设备故障概率模型；然后，建立了台风灾害下的min-max-min三层分布式鲁棒优化调度模型。在此基础上，考虑多元随机变量的影响，构建计及最恶劣故障和最可能故障的分布式鲁棒优化故障概率分布模糊集。最后，采用列与约束生成(column and constraint generation, C&CG)算法对模型进行求解，并基于改进IEEE118节点系统开展算例分析。结果表明，相比于传统经典鲁棒优化模型，所提方法能够最大程度上平衡电力系统的鲁棒性与经济性。

关键词: 台风灾害机组组合优化调度分布式鲁棒优化

DOI：10.19783/j.cnki.pspc.250716

分类号:

基金项目:智能电网国家科技重大专项(2030)资助(2025ZD 0807300)

Distributed robust optimal scheduling considering multivariate random variables under typhoon disasters

ZHANG Zhi^1,2, HAO Juncong³, CHAN Xuezhen⁴, YANG Nan

1. State Key Laboratory of Power System Operation and Control (Department of Electrical Engineering, Tsinghua University), Beijing 100084, China; 2. State Grid Corporation of China, Beijing 100031, China; 3. Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station (China Three Gorges University), Yichang 443002, China; 4. Anqing Power Supply Company of State Grid Anhui Electric Power Co., Ltd., Anqing 246000, China

Abstract:

To address the severe challenges posed by extreme weather events such as typhoons to the safe and stable operation of power systems, a distributed robust unit commitment model considering multivariate random variables is proposed in this paper. First, the output model of new energy units and the fault probability model of power grid equipment under typhoon disasters are constructed. Then, a three-layer min-max-min distributed robust optimal scheduling model under typhoon disasters is established. Based on this, considering the influence of multivariate random variables, a fuzzy set of fault probability distributions is developed, incorporating both the worst-case failures and the most probable failures. Finally, the model is solved using the column-and-constraint generation algorithm, and case studies are conducted on the improved IEEE118-bus system. Results show that, compared with traditional robust optimization models, the proposed method achieves a better balance between robustness and economic performance of the power system.

Key words: typhoon disaster unit commitment optimal scheduling distributed robust optimization

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