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Heuristic probabilistic power flow algorithm for microgrids operation and planning

机译:微电网运行与计划的启发式概率潮流算法

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摘要

One of the basic components of future distribution networks is renewable energy resources (RER). The uncertainty in power production of renewable resources such as wind and solar as well as load is another characteristic of such networks. Conventional power flow methods may not be suitable for active distribution networks such as microgrids. In this study, a heuristic load flow method considering the effects of intermittent behaviour of RERs and load is modelled in probabilistic load flow (PLF) algorithm. The method is suitable for both radial and weakly meshed distribution networks with RER for operation and planning of microgrids. Imperialist competitive algorithm (ICA) as heuristic-based optimisation algorithm is applied to solve the PLF. Based on PLF technique, calculated parameters of the system such as bus voltages and feeders’ current are extracted as random variables. A modified version of IEEE 33-bus test system with RER is used to evaluate efficiency and capability of the algorithm. Results are compared with Monte Carlo simulation method. The probability density function and cumulative distribution function (CDF) of some network variable are compared. Based on the results, the presented approach can solve the PLF problem regardless of the type of distribution network.
机译:未来配电网络的基本组成部分之一是可再生能源(RER)。可再生资源(如风能和太阳能)以及负荷的发电不确定性是此类网络的另一个特征。常规的潮流方法可能不适用于有源配电网,例如微电网。在这项研究中,在概率潮流(PLF)算法中建模了一种考虑RER间歇性行为和荷载影响的启发式潮流方法。该方法适用于带有RER的径向和弱网格配电网络,用于微电网的运行和规划。将帝国主义竞争算法(ICA)作为基于启发式的优化算法来求解PLF。基于PLF技术,系统的计算参数(例如母线电压和馈线电流)将作为随机变量提取。带有RER的IEEE 33总线测试系统的修改版本用于评估算法的效率和功能。将结果与蒙特卡洛模拟方法进行比较。比较了某些网络变量的概率密度函数和累积分布函数(CDF)。根据结果​​,无论配电网的类型如何,所提出的方法都可以解决PLF问题。

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