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首页> 外文期刊>Control of Network Systems, IEEE Transactions on >Worst-Case Load Shedding in Electric Power Networks
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Worst-Case Load Shedding in Electric Power Networks

机译:电力网络中最坏情况的甩负荷

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摘要

We consider the worst-case load-shedding problem in electric power networks where a number of transmission lines are to be taken out of service. The objective is to identify a prespecified number of line outages that lead to the maximum interruption of power generation and load at the transmission level, subject to the active power-flow model, the load and generation capacity of the buses, and the phase-angle limit across the transmission lines. For this nonlinear model with binary constraints, we show that all decision variables are separable except for the nonlinear power-flow equations. We develop an iterative decomposition algorithm, which converts the worst-case load-shedding problem into a sequence of small subproblems. We show that the subproblems are either convex problems that can be solved efficiently or nonconvex problems that have closed-form solutions. Consequently, our approach is scalable for large networks. Furthermore, we prove convergence of our algorithm to a critical point, and the objective value is guaranteed to decrease throughout the iterations. Numerical experiments with IEEE test cases demonstrate the effectiveness of the developed approach.
机译:我们考虑在电力网络中最坏的情况下的甩负荷问题,在该网络中,许多传输线将被停用。目的是确定预定数量的线路中断,这些中断将导致最大程度地中断传输级别上的发电和负载,这取决于活动的功率流模型,总线的负载和发电量以及相角跨传输线的限制。对于具有二元约束的非线性模型,我们表明除非线性潮流方程之外,所有决策变量都是可分离的。我们开发了一种迭代分解算法,该算法将最坏情况下的甩负荷问题转换为一系列小的子问题。我们表明,子问题要么是可以有效解决的凸问题,要么是具有封闭形式解的非凸问题。因此,我们的方法可扩展到大型网络。此外,我们证明了算法收敛到临界点,并且保证了目标值在整个迭代过程中都会减小。 IEEE测试案例的数值实验证明了该方法的有效性。

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