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Multiple matrix rank constrained optimization for optimal power flow over large scale transmission networks

机译:多矩阵秩约束优化,用于大规模传输网络上的最佳功率流

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The optimal power flow (OPF) problem for power transmission networks is an NP-hard optimization problem with numerous quadratic equality and indefinite quadratic inequality constraints on bus voltages. The existing nonlinear solvers often fail in yielding a feasible solution. In this paper, we follow our previously developed nonsmooth optimization approach to address this difficult large-scale OPF problem, which is an iterative process to generate a sequence of improved solutions that converge to an optimal solution. Each iteration calls an SDP of a moderate dimension. Intensive simulations for OPF over networks with a large number of buses are provided to demonstrate the efficiency of our approach.
机译:输电网络的最优潮流(OPF)问题是一个NP-hard优化问题,对总线电压具有许多二次等式和不确定的二次不等式约束。现有的非线性求解器通常无法产生可行的解决方案。在本文中,我们遵循先前开发的非平滑优化方法来解决这一难题,即大规模OPF问题,这是一个迭代过程,可生成一系列收敛于最优解的改进解。每次迭代都会调用一个中等尺寸的SDP。通过具有大量总线的网络对OPF进行了深入的仿真,以证明我们的方法的效率。

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