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IEEE International Conference on Power System Technology (POWERCON)

作者： Iwata, Sohei Fukuyama, Yoshikazu Meiji Univ Sch Interdisciplinary Math Sci Tokyo 101 Japan

ISBN: (纸本)9781467388481

This paper evaluates dependability of parallel differential evolutionary particle swarm optimization (DEEPSO) based voltage and reactive power control (Volt/Var Control: VVC). Considering large penetration of renewable energies and deregulated environment of power systems, VVC is required to realize faster computation to larger-scale problems and one of the solutions for the problem is applications of parallel and distributed computing. Since power system is one of the infrastructures of social community, not only fast computation, but also sustainable control (dependability) is strongly required for VVC. The simulation results with IEEE 118 bus systems indicate that parallel DEEPSO is superior to parallel PSO and parallel differential evolution (DE) from the dependability point of view.

关键词： Dependability parallel and distributed computing parallel differential evolutionary particle swarm optimization Voltage and reactive power control

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parallel Multipopulation differential evolutionary particle swarm optimization for Voltage and Reactive Power Control

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ELECTRICAL ENGINEERING IN JAPAN 2018年第3期204卷 31-40页

作者： Yoshida, Hotaka Fukuyama, Yoshikazu Meiji Univ Sch Interdiscipl Math Sci Dept Network Design Tokyo Japan Meiji Univ Tokyo Japan

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.

关键词： voltage and reactive power control parallel and distributed computing parallel differential evolutionary particle swarm optimization multipopulation

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parallel Multi-population differential evolutionary particle swarm optimization for Voltage and Reactive Power Control in Electric Power Systems 56

Parallel Multi-population Differential Evolutionary Particle...

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56th Annual Conference of the Society-of-Instrument-and-Control-Engineers-of-Japan (SICE)

作者： Yoshida, Hotaka Fukuyama, Yoshikazu Meiji Univ Sch Interdisciplinary Math Sci Tokyo Japan

ISBN: (纸本)9784907764579

This paper proposes parallel multi-population differential evolutionary particle swarm optimization (DEEPSO) for voltage and reactive power control in electric power systems. The problem can be formulated as a mixed integer nonlinear optimization problem and various evolutionary computation techniques such as differential evolutionary particle swarm optimization (DEEPSO) and differential evolution (DE) have been applied so far. However, since there is still room for improvement on solution quality, this paper applies parallel multi-population DEEPSO in order to improve solution quality. The proposed method is applied to IEEE 118 bus system. The simulation results show the appropriate number of sub-populations and migration intervals, and verify improvement of solution quality compared with the conventional parallel DEEPSO based method.

关键词： parallel differential evolutionary particle swarm optimization Multi-population Model Voltage and Reactive power control

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