Maximum Loadability of Meshed Networks: A Sequential Convex Optimization Approach

Danman Wu, Libin Yang, Wei Wei, Laijun Chen, M. Lotfi, J. Catalão
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引用次数: 2

Abstract

In power system static security analysis, it often requires to calculate continuous power flow from a certain load condition to a bifurcation point along a given direction, which is referred to as the maximum loadability problem. This paper proposes a convex optimization method for maximum loadability problem over meshed power grids based on the semidefinite relaxation approach. Because the objective is to maximize the load increasing distance, convex relaxation model is generally inexact, unlike the situation in cost-minimum optimal power flow problem. Inspired by the rank penalty method, this paper proposes an iterative procedure to retrieve the maximum loadability. The convex quadratic term representing the penalty on the rank of matrix variable is updated in each iteration based on the latest solution. In order to expedite convergence, generator reactive power is also included in the objective function, which has been reported in literature. Numeric tests on some small-scale systems validate its effectiveness. Any sparsity-exploration and acceleration techniques for semidefinite programming can improve the efficiency of the proposed approach.
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网格网络的最大可加载性:一种顺序凸优化方法
在电力系统静态安全分析中,往往需要计算从某一负荷状态到某一给定方向的分岔点的连续潮流,称为最大负荷问题。基于半定松弛法,提出了一种求解网格最大负荷问题的凸优化方法。由于目标是使负荷增加距离最大化,凸松弛模型通常不精确,不像成本最小的最优潮流问题。受秩罚法的启发,本文提出了一种获取最大负载性的迭代方法。在每次迭代中,基于最新的解更新表示矩阵变量秩惩罚的凸二次项。为了加快收敛速度,在目标函数中也加入了发电机无功功率,已有文献报道。在一些小型系统上的数值试验验证了该方法的有效性。任何用于半定规划的稀疏性探索和加速技术都可以提高所提出方法的效率。
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