Security Constrained Optimal Power Flow with Distributionally Robust Chance Constraints
Security Constrained Optimal Power Flow with Distributionally Robust Chance Constraints
复制标题
具有分布鲁棒机会约束的安全约束最优潮流
DOI：
10.1109/tpwrs.2015.2407363
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
G. Andersson
中科院分区：
文献类型：
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作者：
Line A. Roald;F. Oldewurtel;Bart P. G. Van Parys;G. Andersson
随着可再生能源投入量的不断增加和市场的开放，电力系统运行中的不确定性增加。为了捕捉运行计划中波动的影响，我们将不确定输入的预测误差建模为随机变量，并利用机会约束建立了安全约束的最优潮流。机会约束限制了违反技术约束的可能性，例如发电和输电限制，但需要易于处理的重新表述。在这篇文章中，我们讨论了机会约束的不同解析形式，基于一组给定的关于预测误差分布的假设。特别是，我们讨论了不假设正态分布的重构，并允许仅给出均值向量和协方差矩阵的解析重构。我们以IEEE118节点系统为例，基于来自欧洲系统的实际数据来说明我们的方法。从经验违约率和运行成本两个方面对不同的重构方案进行了比较，从而为最优潮流设置下最合适的重构方案提供了建议。对于大量不确定性源，可以观察到，即使注入功率不是正态分布，线路潮流和发电机出力的分布也可以接近正态分布。
The growing amount of fluctuating renewable infeeds and market liberalization increases uncertainty in power system operation. To capture the influence of fluctuations in operational planning, we model the forecast errors of the uncertain in-feeds as random variables and formulate a security constrained optimal power flow using chance constraints. The chance constraints limit the probability of violations of technical constraints, such as generation and transmission limits, but require a tractable reformulation. In this paper, we discuss different analytical reformulations of the chance constraints, based on a given set of assumptions concerning the forecast error distributions. In particular, we discuss reformulations that do not assume a normal distribution, and admit an analytical reformulation given only a mean vector and covariance matrix. We illustrate our method with a case study of the IEEE 118 bus system, based on real data from the European system. The different reformulations are compared in terms of both achieved empirical violation probability and operational cost, which allows us to provide a suggestion for the most appropriate reformulation in an optimal power flow setting. For a large number of uncertainty sources, it is observed that the distributions of the line flows and generator outputs can be close to normal, even though the power injections are not normally distributed.