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Probabilistic security-constrained AC optimal power flow

机译:概率安全受限的交流电流

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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:我们提出了一个概率框架,用于设计具有波动电源的系统的N-1安全调度。这可以在各种最佳功率流相关的应用中使用,但在这项工作中,我们展示了我们对现日的规划问题的方法。我们在概率的N-1安全性上延长了我们的早期工作,以融入凸交流最优功率流量放松的最近结果。问题是制定的机会限制凸面;要处理机会约束,我们遵循基于随机和鲁棒优化的组合的算法。我们还通过引入强加对自动电压调节(AVR)设定点的应急控制的矫正方案来增强系统的可控性。该方案允许我们继承关于系统约束满足的先验概率保证,与AVR设定点恒定的基本情况不同。为了说明所提出的安全约束的交流最佳功率流的性能,我们使用蒙特卡罗模拟将其与基于直流电流的配方进行比较,并表明它导致与AVR设定点恒定的情况下的操作成本降低。

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