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Development of Probabilistic Power Flow Algorithm for Radial Distribution Systems with DG Using Analytical Approach

机译:解析法的分布式配电网概率潮流算法开发

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This paper studies a probability power-flow analysis radial distribution system (RDS) with photovoltaic (PV) DG utilizing an analytical approach. A combined cumulant and gram-chalier expansion are used to solve the analytical technique problem, cumulants are used to solve convolution problem and gram-chalier expansion is utilized to obtain the probability density function of the output variables. The uncertainties of DG and load demand are taken into consideration. To study the impact of DG in RDS, both solar irradiance random nature and load fluctuation are used as random variables. The developed technique is carried out on the standard IEEE 85-bus feeder using MATLAB M-Files. The obtained results prove that the DG improves the voltage profile and decrease the power losses of the test networks however the standard deviation of the system is increase.
机译:本文利用一种分析方法研究了光伏(PV)DG的概率潮流分析径向分布系统(RDS)。结合使用累积量和克-chaier展开来解决分析技术问题,使用累积量来解决卷积问题,并且利用克-chalier展开来获得输出变量的概率密度函数。 DG和负载需求的不确定性已考虑在内。为了研究DG对RDS的影响,将太阳辐照度随机性和负载波动均用作随机变量。所开发的技术是使用MATLAB M文件在标准IEEE 85总线进纸器上执行的。获得的结果证明,DG可以改善电压分布并减少测试网络的功率损耗,但是会增加系统的标准偏差。

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