Stochastic economic dispatch scheme with distributed loads using group search optimizer

Mengshi Li, Y. Hu, T. Ji, P. Wu
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Abstract

This paper proposed an economic dispatch scheme based on stochastic frame. Compared with conventional dispatch, the stochastic dispatch fully considers the variation of distributed load variations in the grid between dispatch intervals. The objective function of the stochastic dispatch scheme aims to minimize the distribution of fuel cost rather than a single value. Due to the stochastic analysis, the computational complexity of proposed method is also significantly increased. Therefore, this research adopts a animal behavior inspired algorithm, Group Search Optimizer (GSO) to solve the stochastic dispatch. The simulation studies are taken on the IEEE 30-bus system with uncertain load. The comparison between the results achieved using the proposed method and GA and PSO is presented to demonstrate the merits of GSO.
基于群搜索优化器的分布式负荷随机经济调度方案
提出了一种基于随机框架的经济调度方案。与常规调度相比,随机调度充分考虑了调度区间内电网内分布负荷的变化。随机调度方案的目标函数是最小化燃料成本的分布,而不是单个值。由于随机分析,该方法的计算复杂度也显著增加。因此,本研究采用一种启发动物行为的算法——群体搜索优化器(GSO)来解决随机调度问题。对具有不确定负载的IEEE 30总线系统进行了仿真研究。将该方法与遗传算法和粒子群算法的结果进行了比较,证明了粒子群算法的优越性。
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