| Summary: | 碩士 === 明志科技大學 === 電機工程研究所 === 99 === This paper presents that a kind of algorithm based on Bio-cluster to solve the optimal power flow problems. The proposed approach is called particle swarm optimization. This method is mainly used to adjust the various control variables to find the optimal power flow solution, and can get a lower generation cost. In this paper, particle swarm optimization of adding the inertia weight and the constriction factor to make the particles more quickly and accurately obtain the global best, and the particle swarm optimization without losing speed and stability advantages of high. This article uses the IEEE-30 bus system for testing, by using three cases of simulation to check the proposed improved particle swarm optimization. These cases are to minimize the fuel case, piecewise quadratic cost curve, and piecewise quadratic cost curve with sine comparison, respectively. And with the references on the evolutionary programming and other improved particle swarm optimization for comparison, the results presented in this paper that the improved particle swarm optimization in the three simulations can really get a better global best and a lower cost. The fourth simulation is used to check if the number of particles in different optimal power flow solution problem arising from the differences and benefits. The simulation results show that an improved particle swarm optimization can indeed solve the problem of optimal power flow is a certain effectiveness and reliability.
Keyword: improved particle swarm optimization, optimal power flow, power system.
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