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

机译:不同惯性重量函数对粒子群优化算法的影响,解决经济负荷调度问题

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摘要

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:调度生成单位在植物的经济运营中起着宝贵的作用。经济负担调度问题(ELDPS)处理植物的这种经济运作。粒子群优化(PSO)技术变得更加流行,而不是解决ELDP。为了控制爆炸现象,在PSO算法中使用惯性重量(IW)。 IW可能是正常常数或时间变化功能。在本文中,六种不同的Iw即恒定,线性减少,自然指数策略1和2,用于解决IEEE 5,14和30个总线系统的ELDPS的随机和模拟退火。使用MATLAB编程的20个试运行计算最佳,最差平均值和其标准偏差成本。还检查了平均迭代和平均计算时间的数量。结果分析表明,用于IEEE-5总线系统的模拟退火IW以及用于IEEE-14总线系统的自然指数IW策略2和PSO算法中的IEEE-30总线系统的使用提供了更好的结果,计算时间较少。

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