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Probabilistic security-constrained AC optimal power flow

机译:概率安全受限的交流最优潮流

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We propose a probabilistic framework for designing an N-1 secure dispatch for systems with fluctuating power sources. This could be used in various optimal power flow related applications, however in this work, we demonstrate our approach for a day-ahead planning problem. We extend our earlier work on probabilistic N-1 security, to incorporate recent results on convex AC optimal power flow relaxations. The problem is formulated as a chance constrained convex program; to deal with the chance constraint we follow an algorithm based on a combination of randomized and robust optimization. We also enhance the controllability of the system by introducing a corrective scheme that imposes post-contingency control of the Automatic Voltage Regulation (AVR) set-point. This scheme allows us to inherit a priori probabilistic guarantees regarding the satisfaction of the system constraints, unlike the base case where the AVR set-points are constant. To illustrate the performance of the proposed security-constrained AC optimal power flow we compare it against a DC power flow based formulation using Monte Carlo simulations, and show that it results to lower operational cost compared to the case where the AVR set-points are constant.
机译:我们提出一个概率框架,为电源波动的系统设计N-1安全调度。这可以用于各种与最佳潮流相关的应用中,但是在这项工作中,我们演示了解决日前计划问题的方法。我们扩展了关于概率N-1安全性的早期工作,以结合凸AC最优潮流松弛的最新结果。该问题被公式化为机会约束凸程序;为了处理机会约束,我们遵循一种基于随机优化和鲁棒优化相结合的算法。我们还通过引入一种校正方案来增强系统的可控制性,该方案对自动电压调节(AVR)设定点进行事后控制。与AVR设定点恒定的基本情况不同,此方案使我们能够继承有关系统约束满足的先验概率保证。为了说明所建议的受安全约束的交流最优功率流的性能,我们将其与使用蒙特卡洛模拟的基于直流功率流的公式进行了比较,并表明与AVR设定点恒定的情况相比,它可降低运营成本。

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