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Parallel Multipopulation Differential Evolutionary Particle Swarm Optimization for Voltage and Reactive Power Control
Authors:HOTAKA YOSHIDA  YOSHIKAZU FUKUYAMA
Affiliation:Meiji University, Japan
Abstract:This paper presents parallel multipopulation differential evolutionary particle swarm optimization (DEEPSO) for voltage and reactive power control (VQC). The problem can be formulated as a mixed integer nonlinear optimization problem and various evolutionary computation techniques have been applied to the problem including PSO, differential evolution (DE), and DEEPSO. Since VQC is one of the online controls, speed‐up of computation is required. Moreover, there is still room for improvement in solution quality. This paper applies parallel multipopulation DEEPSO in order to speed up the calculation and improve solution quality. The proposed method is applied to IEEE 30, 57, and 118 bus systems. The results indicate that the proposed method can realize fast computation and minimize more active power losses than the conventional evolutionary computation techniques.
Keywords:voltage and reactive power control  parallel and distributed computing  parallel differential evolutionary particle swarm optimization  multipopulation
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