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Impact of different inertia weight functions on particle swarm optimization algorithm to resolve economic load dispatch problems

机译:不同惯性权函数对粒子群算法求解经济负荷分配问题的影响

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Dispatching generation units plays a valuable role in the economic operation of the plant. The Economic Load Dispatch Problems (ELDPs) deal with such economic operation of the plant. The Particle swarm optimization (PSO) technique becomes much more popular than other to resolve ELDPs. To control explosion phenomenon, Inertia Weight (IW) is used in the PSO algorithm. The IW may be a positive constant or a time varying function. In this article six different IW namely constant, linearly decreasing, natural exponent strategy 1 and 2, random and simulated annealing are used in PSO algorithm to resolve ELDPs of IEEE 5, 14 and 30 bus systems. The best, worst, average and their standard deviation costs are calculated for 20 trial runs using MATLAB programming. The average numbers of iteration and average computational time have been also examined. The analysis of results shows that the use of simulated annealing IW for IEEE-5 bus system and the use of natural exponent IW strategy 2 for IEEE-14 bus system and IEEE-30 bus systems in PSO algorithm provide better result with less computational time.
机译:发电部门的调度在工厂的经济运行中发挥了重要作用。经济负荷分配问题(ELDP)处理工厂的这种经济运行。粒子群优化(PSO)技术比其他解决ELDP的方法更为普及。为了控制爆炸现象,PSO算法中使用了惯性权重(IW)。 IW可以是正常数或时变函数。在本文中,六个不同的IW,即恒定,线性递减,自然指数策略1和2,在PSO算法中使用随机退火和模拟退火来解析IEEE 5、14和30总线系统的ELDP。使用MATLAB编程计算20次试运行的最佳,最差,平均及其标准偏差成本。还检查了平均迭代次数和平均计算时间。结果分析表明,在PSO算法中将模拟退火IW用于IEEE-5总线系统,并将自然指数IW策略2用于IEEE-14总线系统和IEEE-30总线系统,可提供更好的结果,且计算时间更少。

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