Abstract：At present, most probabilistic load flow methods have only considered the uncertainties of loads and generators, without taking the network configuration uncertainties into account. A probabilistic load flow method considering network configuration uncertainties is proposed in this paper. The linear relationship between power injections and line flows is deduced, and that enables applying cumulants and Gram-Charlier expansion to compute the probabilistic distributions of the transmission line flows, instead of complex convolution calculations. Then compensation method and total probability theorem are combined to model the random variations of network configuration. This way, the cumulative distribution function (CDF) and probability density function (PDF) can be easily obtained considering the random factors of loads, generators and network configuration. The case studies of IEEE 39-node system and a practical system show that the uncertainties of network configuration remarkably effected the probabilistic distributions of state variables. Thus the proposed method can give planners more accurate and comprehensive information, and the comparison with Monte Carlo simulation (MCS) verifies its higher speed, high degree of accuracy and the prospects for practical application.
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2012, Vol. 27 
