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An efficient DSE using conditional multivariate complex Gaussian distribution
Journal article   Peer reviewed

An efficient DSE using conditional multivariate complex Gaussian distribution

A. Arefi, G. Ledwich and B. Behi
IEEE Transactions on Smart Grid, Vol.6(4), pp.2147-2156
2015
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Abstract

This paper presents an efficient noniterative method for distribution state estimation using conditional multivariate complex Gaussian distribution (CMCGD). In the proposed method, the mean and standard deviation (SD) of the state variables is obtained in one step considering load uncertainties, measurement errors, and load correlations. In this method, first the bus voltages, branch currents, and injection currents are represented by MCGD using direct load flow and a linear transformation. Then, the mean and SD of bus voltages, or other states, are calculated using CMCGD and estimation of variance method. The mean and SD of pseudo measurements, as well as spatial correlations between pseudo measurements, are modeled based on the historical data for different levels of load duration curve. The proposed method can handle load uncertainties without using time-consuming approaches such as Monte Carlo. Simulation results of two case studies, six-bus, and a realistic 747-bus distribution network show the effectiveness of the proposed method in terms of speed, accuracy, and quality against the conventional approach.

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Citation topics
4 Electrical Engineering, Electronics & Computer Science
4.18 Power Systems & Electric Vehicles
4.18.472 Power System Stability
Web Of Science research areas
Engineering, Electrical & Electronic
ESI research areas
Engineering
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