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A New Improved Knowledge Based Cultural Algorithm for Reactive Power Planning

机译:一种新的基于知识的改进无功规划文化算法

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This paper proposes a novel hybrid method for the planning of reactive power problem (RPP). The objective of this paper is to determine the optimum investment required to satisfy suitable reactive power constraints for an acceptable performance level of a power system. Due to the discrete nature of reactive compensation devices, the given objective function leads to a nonlinear problem with combined (distinct and constant) variables. It is solved by a hybrid procedure, aiming to develop the best search features of an iterative algorithm. The performance of the proposed procedure is shown by presenting the numerical results obtained from its application to the IEEE 30-bus test network. The results obtained are compared with evolutionary programming (EP) and Broyden method to determine the efficacy of the proposed method.
机译:本文提出了一种用于规划无功功率问题的新型混合方法。本文的目的是确定在电力系统可接受的性能水平上满足适当的无功功率约束所需的最佳投资。由于无功补偿装置的离散特性,给定的目标函数会导致具有组合变量(离散变量和常数)的非线性问题。它是通过混合过程解决的,旨在开发迭代算法的最佳搜索功能。通过将从其应用程序获得的数值结果呈现给IEEE 30总线测试网络,可以证明所提出程序的性能。将获得的结果与进化规划(EP)和Broyden方法进行比较,以确定所提出方法的有效性。

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