Probabilistic available delivery capability assessment of general distribution network with renewables

Hao Sheng, Xiaozhe Wang
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引用次数: 2

Abstract

Rapid increase of renewable energy sources and electric vehicles in utility distribution feeders introduces more and more uncertainties. To investigate how such uncertainties may affect the available delivery capability (ADC) of the distribution network, it is imperative to employ a probabilistic analysis framework. In this paper, a formulation for probabilistic ADC incorporating renewable generators and load variations is proposed; a computationally efficient method to solve the probabilistic ADC is presented, which combines the up-to-date sparse polynomial chaos expansion (PCE) and the continuation method. A numerical example in the IEEE 13 node test feeder is given to demonstrate the accuracy and efficiency of the proposed method.
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可再生能源配电网的概率可用输电能力评估
可再生能源和电动汽车在公用事业馈线中的快速增长带来了越来越多的不确定性。调查这些不确定性可能如何影响可用的交付能力(ADC)的分销网络,必须采用概率分析框架。本文提出了一种考虑可再生发电机组和负荷变化的概率ADC公式;将稀疏多项式混沌展开(PCE)与延拓方法相结合,提出了一种计算效率高的概率ADC求解方法。最后以IEEE 13节点试验馈线为例,验证了该方法的准确性和有效性。
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