Economic load dispatch using heuristic algorithms

Ramadevi Lingala, Abhinaya Bethina, P. V. R. Ramana Rao, K. Sumanth
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引用次数: 4

Abstract

With the growth of commercial world, the utilization of electrical energy is also increased. Due to this the need to install large amount of power generation to meet the increasing load has become the basic utility, which is quite complex to distribute the power among large number of units economically in less time. This intricacy made to develop the faster convergent techniques to large systems. Economic load dispatch is a basic tool in balancing the power among units with minimum cost. Henceforth the paper evaluates and demonstrates the ELD with transmission losses in three best optimization techniques called Genetic Algorithm, Particle Swarm Optimization and Cuckoo Search Optimization Techniques abstracted from optimization world. A comparative analysis of three methods is done for 62-bus Indian utility system and other higher order systems. The paper ensures that the cuckoo search optimization technique is the best for faster convergence as well as for better economical and as the system size increases CSO provides the vast economic difference i.e. best economical than other methods.
基于启发式算法的经济负荷调度
随着商业世界的发展,电能的利用率也在不断提高。因此,需要安装大量的发电设备来满足不断增加的负荷已成为基本的公用事业,而如何在短时间内经济地将电力分配给大量的机组是相当复杂的。这种复杂性使得开发更快速的大型系统收敛技术成为可能。经济负荷调度是实现机组间以最小成本实现电力平衡的基本手段。在此基础上,对遗传算法、粒子群算法和布谷鸟搜索算法这三种从优化世界中抽象出来的最优优化技术进行了评价和论证。对62总线印度公用事业系统和其他高阶系统进行了三种方法的比较分析。本文确定了布谷鸟搜索优化技术具有更快的收敛速度和更好的经济性,并且随着系统规模的增加,CSO提供了巨大的经济性差异,即与其他方法相比具有最佳经济性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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