粒子群优化在经济负荷调度问题中的应用

M. Sudhakaran, P. Ajay-D-Vimal Raj, T. G. Palanivelu
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引用次数: 42

摘要

针对经济负荷调度问题,提出了一种高效、可靠的粒子群优化方法。粒子群算法是通过对一个简化的社会系统的仿真而发展起来的,在解的精度和计算时间方面,它在求解连续非线性优化问题方面具有鲁棒性,优于其他算法。将该算法应用于三台机组和六台机组热电厂系统的ELD,并推广到其中一台机组为联合循环热电厂的三台机组系统。将所提出的PSO方法与传统方法和遗传算法进行了性能比较,结果表明该方法是可靠的,可以在不同的中心负荷调度中心有效地替代目前采用的传统方法。结果对比表明,所提出的粒子群算法确实能够在较短的计算时间内有效地获得高质量的ELD问题解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Particle Swarm Optimization for Economic Load Dispatch Problems
This paper presents an efficient and reliable particle swarm optimization (PSO) method for the economic load dispatch (ELD) problems. The PSO method was developed through the simulation of a simplified social system and has been found to be robust in solving continuous nonlinear optimization problems in terms of accuracy of the solution and computation time and it can out perform other algorithms. The proposed algorithm is applied for the ELD of three unit & six unit thermal plant systems and extended to three plant system in which one plant is combined cycle co-generation plant. The performance of the proposed PSO method is compared with the conventional method and genetic algorithm method and it is observed that this method is reliable and may replace effectively the conventional practices presently performed in different central load dispatch centers. The comparison of results shows that the proposed PSO method was indeed capable of obtaining higher quality solutions efficiently for ELD problems within less computation time.
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