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Reactive power optimization of electric power system incorporating wind power based on Parallel Immune Particle Swarm Optimization

机译:基于并行免疫粒子群算法的风电电力系统无功优化

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This paper aims at the characteristics of reactive power optimization of the electric power system with the wind farm; proposing a new method for reactive power optimization on the entire power grid which uses the Parallel Immune Particle Swarm Optimization. It uses integer and real number hybrid encoding, improves the efficiency of compiling. And it combines the continuous and discrete particle swarm optimization, and introduces immune operators to improve the convergence precision. IEEE-14 and IEEE-30 system simulation examples show that the new method has better global convergence ability, faster convergence rate and higher accuracy.
机译:本文针对具有风电场的电力系统无功优化的特点。提出了一种使用并行免疫粒子群优化技术对整个电网进行无功优化的新方法。它使用整数和实数混合编码,提高了编译效率。它结合了连续和离散粒子群优化算法,并引入了免疫算子以提高收敛精度。 IEEE-14和IEEE-30系统仿真实例表明,该新方法具有更好的全局收敛能力,更快的收敛速度和更高的精度。

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