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Title: 不确定环境下含云计算数据中心的电网韧性增强调度 = Resilience-enhanced scheduling of power system with cloud computing data centers under uncertainty
Authors: 赵天阳 Zhao, Tianyang
张华君 Zhang, Huajun
徐岩 Xu, Yan
王鹏 Wang, Peng
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Source: 赵天阳 Zhao, T., 张华君 Zhang, H., 徐岩 Xu, Y. & 王鹏 Wang, P. (2021). 不确定环境下含云计算数据中心的电网韧性增强调度 = Resilience-enhanced scheduling of power system with cloud computing data centers under uncertainty. 电力系统自动化 Automation of Electric Power Systems, 45(3), 49-57.
Journal: 电力系统自动化 Automation of Electric Power Systems
Abstract: 为解决飓风来临前路径不确定时输电线路随机故障等带来的难题,提出了适用于含云计算 数据中心的电网韧性增强日前调度策略,并将其构建为两阶段风险规避的分布鲁棒优化问题。以 飓风对输电线路的时空影响为出发点,采用蒙特卡洛模拟获得飓风路径不确定时线路的离散故障 集合,并构建基于L1 距离度量的分布鲁棒模糊集合。然后,在日前调度中,对机组和数据中心进行优化以平衡经济性和电网韧性,并采用追索问题量化其对日间调度的影响,形成两阶段优化问题。随后,对优化问题进行确定性转换与解耦求解。最后,以含4 个数据中心的IEEE-RTS 系统为测试算例,验证了所提韧性增强策略应对模糊不确定性的有效性。 To manage the possible transmission line failures under uncertain hurricane tracks before its advent, a day-ahead resilience-enhanced scheduling scheme is proposed for power systems with cloud computing data centers. The scheme is formulated as a two-stage risk aversion distributionally robust optimization problem. Considering the spatial and temporal impacts of hurricanes on transmission lines, a discrete line failure set is generated by the Monte-Carlo simulation scheme, in which the hurricane path uncertainty is considered. This set is further formulated as a distributionally robust ambiguity set using L1 norm distance. In the day-ahead scheduling, the generators and data centers are scheduled to balance the operational efficiency and resilience, considering the impacts of day-ahead scheduling on intra-day scheduling, which is formulated as a recourse problem, and resulting in a two-stage optimization problem. It is reformulated to its robust counterpart and solved by decomposition algorithms. Finally, simulations are conducted on a modified IEEE reliability test system with 4 data centers, and the results verify the effectiveness of the proposed resilience-enhanced strategy in addressing the ambiguity uncertainty.
ISSN: 1000-1026
DOI: 10.7500/AEPS20200509008
Rights: © 2021 The Author(s). All rights reserved. This paper was published in 电力系统自动化 Automation of Electric Power Systems and is made available with permission of The Author(s).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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