Optimal Allocation and Sizing of Active Power Line Conditioners Using a New Particle Swarm Optimization-based Approach

Abstract Optimal allocation and sizing of active power line conditioners in a distribution network is a discrete and non-linear problem. Heuristic-based optimization methods are reliable approaches for solving these types of problems, particularly for a large-scale distribution network. However, the optimization parameters in heuristic methods can influence the final solution significantly so that if these parameters are selected improperly, the risk of trapping in local minima may be remarkable. In this article, a new method—modified particle swarm optimization—is proposed for optimal planning of active power line conditioners in a distribution network that is polluted by non-linear loads. In this method, external particle swarm optimization is used to determine the main particle swarm optimization parameters accurately. To validate the performance of the proposed method, a 6-bus and the IEEE 18-bus test systems are employed. Different scenarios are studied, and the results are compared with those obtained by other optimization methods, such as conventional particle swarm optimization, genetic algorithm, and discrete non-linear programming. The results illustrate higher accuracy of the proposed modified particle swarm optimization and its applicability for solving discrete and non-linear problems, such as active power line conditioner planning.

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