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Economic load dispatch with the proposed GA algorithm for large scale system

机译:提出的GA算法在大型系统中进行经济负荷分配

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Economic load dispatch (ELD) have been applied to obtain optimal fuel cost of generating units. Genetic Algorithm (GA) is a global search technique based on principles inspired from the genetic and evolution mechanism observed in natural biological systems. This paper presents a novel stochastic Genetic Algorithm approach to solve the Economic Load Dispatch problem considering various generator constraints and also conserves an acceptable system performance in terms of limits on generator real and reactive power outputs bus voltages, shunt capacitors/reactors, transformers tap-setting and power flow of transmission lines. The ELD problem in a power system is to determine the optimal combination of power outputs for all generating units which will minimize the total fuel cost while satisfying all practical constraints. To show its efficiency and effectiveness, the proposed GA algorithm is applied to some types of ED problems containing non-smooth cost functions of 13 and 40 generating units systems (large scale systems). The experimental results show that the proposed GA approach is comparatively capable of obtaining higher quality solution.
机译:经济负荷分配(ELD)已被应用以获得发电机组的最佳燃料成本。遗传算法(GA)是一种全球搜索技术,它基于从自然生物系统中观察到的遗传和进化机制中获得启发的原理。本文提出了一种新颖的随机遗传算法方法来解决考虑各种发电机约束的经济负荷分配问题,并且在发电机有功和无功功率输出母线电压,并联电容器/电抗器,变压器抽头设置的限制方面,还可以保持可接受的系统性能和传输线的功率流。电力系统中的ELD问题是确定所有发电机组的功率输出的最佳组合,这将使总燃料成本最小化,同时满足所有实际约束。为了显示其效率和有效性,将所提出的GA算法应用于某些类型的ED问题,该问题包含13和40个发电机组系统(大型系统)的非平稳成本函数。实验结果表明,所提出的遗传算法相对能够获得更高质量的解。

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