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不确定环境下含云计算数据中心的电网韧性增强调度
作者:
作者单位:

1.南洋理工大学能源研究院,新加坡 639798;2.南洋理工大学电气与电子工程学院,新加坡 639798

摘要:

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。

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作者简介:

赵天阳(1989—),男,博士,主要研究方向:能源系统韧性、电力系统优化运行。E-mail:zhaoty@ntu.edu.sg
张华君(1985—),女,博士,主要研究方向:电力系统可靠性、电力系统韧性。E-mail:huajun.zhang@ntu.edu.sg
徐岩(1985—),男,通信作者,博士,主要研究方向:电力系统稳定、优化和数据分析。E-mail:xuyan@ntu.edu.sg


Resilience-Enhanced Scheduling of Power System with Cloud Computing Data Centers Under Uncertainty
Author:
Affiliation:

1.Energy Research Institute, Nanyang Technological University, Singapore 639798, Singapore;2.School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore

Abstract:

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.

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Foundation:
引用本文
[1]赵天阳,张华君,徐岩,等.不确定环境下含云计算数据中心的电网韧性增强调度[J].电力系统自动化,2021,45(3):49-57. DOI:10.7500/AEPS20200509008.
ZHAO Tianyang, ZHANG Huajun, XU Yan, et al. Resilience-Enhanced Scheduling of Power System with Cloud Computing Data Centers Under Uncertainty[J]. Automation of Electric Power Systems, 2021, 45(3):49-57. DOI:10.7500/AEPS20200509008.
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  • 收稿日期:2020-05-09
  • 最后修改日期:2020-07-20
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  • 在线发布日期: 2021-02-03
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