基于粒子群算法的配电系统分布式风力发电布局优化

Muhammad Hasan Basri Paleba, Lesnanto Multa Putranto, S. P. Hadi
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引用次数: 3

摘要

分布式发电(DG)是一种利用小容量能源发电的系统,本文采用风能可再生能源发电,以减少化石燃料的使用。DG具有降低功率损耗和改善电压分布等功能。本研究确定了改进的IEEE 33总线测试系统中wind-DG的位置和尺寸。制定了功率损耗和电压偏差(VD)最小的优化程序。模拟了两种情况,分别有一个wind-DG和两个wind-DG位置。在MATLAB环境下,利用粒子群算法(PSO)进行了优化仿真。结果表明,该方法满足目标函数。总损耗在第一种情况下为2.459 MWh,在第二种情况下为2.209 MWh。最大VD值在总线18上,样品结果在03:00 am低负载和07:00 pm峰值负载,在03:00 am第一个场景值为0.040 pu,在第二个场景值为0.032 pu。然后在07:00 pm, VD值在第一个场景中为0.042 pu,在第二个场景中为0.035 pu。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Placement and Sizing Distributed Wind Generation Using Particle Swarm Optimization in Distribution System
Distributed Generation (DG) is a system of generating electricity from energy sources with small capacity, in this paper DG is generated from wind renewable energy source to reduce fossil fuel usage. DG has several functions such as power loss minimization and voltage profile improvement. In this study, location and size of wind-DG in the modified IEEE 33 bus test system were determined. Optimization procedure to minimize power loss and Voltage Deviation (VD) was formulated. There are two scenarios were simulated, there are one wind-DG and two wind-DG locations. The optimization was simulated using Particle Swarm Optimization (PSO) technique under MATLAB environment. The results were proven that the objective function satisfied. Furthermore, the total losses becomes 2.459 MWh in the first scenario and 2.209 MWh in the second scenario. Maximum VD value is on bus 18 with sample results in low load at 03:00 am and peak load at 07:00 pm, with a value 0.040 pu in the first scenario and 0.032 pu in the second scenario at 03:00 am. Then at 07:00 pm with a VD value 0.042 pu in the first scenario and 0.035 pu in second scenario.
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