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Optimal capacitor placement using deterministic and genetic algorithms

机译:使用确定性和遗传算法进行最佳电容器展示

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A procedure for solving the power capacitor placement problem is presented. The objective is to determine the minimum investment required to satisfy suitable reactive constraints. Due to the discrete nature of reactive compensation devices, optimal capacitor placement leads to a nonlinear programming problem with mixed (discrete and continuous) variables. It is solved with an iterative algorithm based on successive linearizations of the original nonlinear model. The mixed integer linear programming problem to be solved at each iteration of the procedure is tackled by applying both a deterministic method (branch and bound) and genetic algorithm techniques. A hybrid procedure, aiming to exploit the best features of both algorithms is also considered. The proposed procedures are tested and compared with reference to a small CIGRE system and two actual networks derived from the Italian transmission and distribution system.
机译:提出了一种解决电力电容器放置问题的过程。目标是确定满足合适的反应限制所需的最低投资。由于反应补偿装置的离散性,最佳电容器放置导致混合(离散和连续)变量的非线性编程问题。基于原始非线性模型的连续线性化,用迭代算法解决了它。通过应用确定性方法(分支和绑定)和遗传算法技术来解决在过程的每次迭代时求解的混合整数线性编程问题。旨在利用两种算法的最佳特征的混合过程也被考虑。该提出的程序是测试的,并参考小型CIGRE系统和来自意大利传输系统的两种实际网络进行比较。

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