Probabilistic load flow incorporating generator reactive power limit violations with spline based reconstruction method

Abstract The increase in the penetration of intermittent generation and uncertainty in load patterns calls for the need to include these uncertainties in the conventional power flow programs. Consideration of the generator reactive power limit violation is an essential aspect in load flow studies for planning. In this paper, a probabilistic load flow method is proposed in which the violation of the reactive power limits of the generators are adequately represented. The seven point estimate method along with the spline based reconstruction technique is proposed for constructing the probability density function of the resulting multimodal distributions. The proposed load flow method has been tested on the IEEE-118 bus and IEEE-300 bus test systems for unimodal and multimodal load distributions, with and without correlation, and the accuracy of the results has been validated by comparing these results with those obtained by Monte Carlo simulation studies. Further, the effect of slack bus power limits has also been studied in this work.

[1]  Barbara Borkowska,et al.  Probabilistic Load Flow , 1974 .

[2]  C. Crawford,et al.  Probabilistic Load Flow Modeling Comparing Maximum Entropy and Gram-Charlier Probability Density Function Reconstructions , 2013, IEEE Transactions on Power Systems.

[3]  Julio Usaola,et al.  Probabilistic load flow with correlated wind power injections , 2010 .

[4]  Antonio J. Conejo,et al.  Probabilistic power flow with correlated wind sources , 2010 .

[5]  Julio Usaola Probabilistic load flow with wind production uncertainty using cumulants and Cornish–Fisher expansion , 2009 .

[6]  J. Morales,et al.  Point Estimate Schemes to Solve the Probabilistic Power Flow , 2007, IEEE Transactions on Power Systems.

[7]  A. Feijoo,et al.  Probabilistic Load Flow Including Wind Power Generation , 2011, IEEE Transactions on Power Systems.

[8]  J.H. Zhang,et al.  Probabilistic Load Flow Evaluation With Hybrid Latin Hypercube Sampling and Cholesky Decomposition , 2009, IEEE Transactions on Power Systems.

[9]  R D Zimmerman,et al.  MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education , 2011, IEEE Transactions on Power Systems.

[10]  Ronald N. Allan,et al.  Probabilistic analysis of power flows , 1974 .

[11]  Chun-Lien Su,et al.  Probabilistic load-flow computation using point estimate method , 2005 .

[12]  George J. Anders,et al.  Probability Concepts in Electric Power Systems , 1990 .

[13]  Volker John,et al.  Techniques for the reconstruction of a distribution from a finite number of its moments , 2007 .

[14]  Ronald N. Allan,et al.  Probabilistic a.c. load flow , 1976 .

[15]  A. C. Miller,et al.  Discrete Approximations of Probability Distributions , 1983 .

[16]  Yue Yuan,et al.  Probabilistic load flow computation of a power system containing wind farms using the method of combined cumulants and Gram-Charlier expansion , 2011 .

[17]  S.T. Lee,et al.  Probabilistic load flow computation using the method of combined cumulants and Gram-Charlier expansion , 2004, IEEE Transactions on Power Systems.

[18]  Colin Rose,et al.  mathStatica: Mathematical Statistics with Mathematica , 2002, COMPSTAT.

[19]  K. Tomsovic,et al.  Slack bus treatment in load flow solutions with uncertain nodal powers , 2004, 2004 International Conference on Probabilistic Methods Applied to Power Systems.

[20]  Yonghua Song,et al.  Modern Power Systems Analysis , 2008 .

[21]  J. Usaola Probabilistic load flow in systems with wind generation , 2009 .