Chance-Constrained AC Optimal Power Flow for Unbalanced Distribution Grids
Chance-Constrained AC Optimal Power Flow for Unbalanced Distribution Grids
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DOI：
10.48550/arxiv.2207.09520
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发表时间：
2022-07
期刊：
影响因子：
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通讯作者：
Kshitij Girigoudar;Ashley M. Hou;Line A. Roald
中科院分区：
文献类型：
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作者：
Kshitij Girigoudar;Ashley M. Hou;Line A. Roald
- 分布式能源（DER）的日益普及导致运行条件不断变化，这需要配电网运营商进行有效管理。太阳能光伏（PV）系统等DER的间歇性以及负荷预测误差不仅增加了电网的不确定性，而且还带来了重大的电能质量挑战，如电压不平衡和电压幅值违规。本文利用机会约束优化方法来减少不确定性对分布式电网运行的影响。首先提出了配电网机会约束最优功率潮流（CC-OPF）问题，并讨论了一种基于约束收紧的重构方法，该方法不需要对三相交流功率潮流方程进行任何近似或松弛。然后，我们提出了两个迭代求解算法能够有效地解决重新制定。在案例研究中，这两种算法的性能进行了分析，通过运行模拟IEEE 13总线测试馈线使用真实的PV和负载测量数据。仿真结果表明，这两种方法都能够加强机会约束的样本内和样本外的评价。
—The growing penetration of distributed energy re- sources (DERs) is leading to continually changing operating conditions, which need to be managed efficiently by distribution grid operators. The intermittent nature of DERs such as solar photovoltaic (PV) systems as well as load forecasting errors not only increase uncertainty in the grid, but also pose significant power quality challenges such as voltage unbalance and voltage magnitude violations. This paper leverages a chance-constrained optimization approach to reduce the impact of uncertainty on dis- tribution grid operation. We first present the chance-constrained optimal power flow (CC-OPF) problem for distribution grids and discuss a reformulation based on constraint tightening that does not require any approximations or relaxations of the three-phase AC power flow equations. We then propose two iterative solution algorithms capable of efficiently solving the reformulation. In the case studies, the performance of both algorithms is analyzed by running simulations on the IEEE 13-bus test feeder using real PV and load measurement data. The simulation results indicate that both methods are able to enforce the chance constraints in in- and out-of-sample evaluations.