An investigation of reactive power planning based on chance constrained programming
An investigation of reactive power planning based on chance constrained programming
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DOI：
10.1016/j.ijepes.2006.09.008
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发表时间：
2007-11
影响因子：
5.2
通讯作者：
Ning Yang;C. Yu;F. Wen;C. Chung
中科院分区：
文献类型：
--
作者：
Ning Yang;C. Yu;F. Wen;C. Chung
电力供应行业的放松管制给无功规划问题带来了许多新的挑战。虽然这个问题已经得到了广泛的研究，现有的标准优化模型和方法并没有提供很好的解决方案，特别是在竞争激烈的电力市场环境中，许多因素是不确定的。在此背景下，本文提出了一种基于机会约束规划的无功规划新方法，该方法考虑了不确定性因素。首先，在假设发电机出力和负荷需求可以被建模为指定的概率分布的情况下，制定随机优化模型。然后，提出了一种方法来解决优化问题，使用蒙特卡罗模拟方法和遗传算法。最后，通过一个案例研究来说明所提出的模型和方法的有效性和基本特征。
Deregulation in the electricity supply industry has brought many new challenges to the problem of reactive power planning. Although the problem has been extensively studied, available standard optimization models and methods do not offer good solutions to this problem, especially in a competitive electricity market environment where many factors are uncertain. Given this background, a novel method for reactive power planning based on chance constrained programming is presented in this paper, with uncertain factors taken into account. A stochastic optimization model is first formulated under the presumption that the generator outputs and load demands can be modeled as specified probability distributions. A method is then presented for solving the optimization problem using the Monte Carlo simulation method and genetic algorithm. Finally, a case study is used to illustrate the validity and essential features of the proposed model and methodology.