Probabilistic power flow with correlated wind sources

A probabilistic power flow model that takes into account spatially correlated power sources and loads is proposed. It is particularly appropriate to assess the impact of intermittent generators such as wind power ones on a power network. The proposed model is solved using an extended point estimate method that accounts for dependencies among the input random variables (i.e. loads and power sources). The proposed probabilistic power flow model is illustrated through 24-bus and 118-bus case studies. Finally, conclusions are duly drawn.

[1]  Chun-Lien Su.  Probabilistic load-flow computation using point estimate method , 2005, IEEE Transactions on Power Systems.

[2]  H. Hong.  An efficient point estimate method for probabilistic analysis , 1998 .

[3]  E. Rosenblueth.  Point estimates for probability moments. , 1975, Proceedings of the National Academy of Sciences of the United States of America.

[4]  M. Harr.  Probabilistic estimates for multivariate analyses , 1989 .

[5]  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.

[6]  Emilio Rosenblueth,et al.  Two-point estimates in probabilities , 1981 .

[7]  Christina W. Tsai,et al.  Evaluation of Probabilistic Point Estimate Methods in Uncertainty Analysis for Environmental Engineering Applications , 2005 .

[8]  R.N. Allan,et al.  Evaluation Methods and Accuracy in Probabilistic Load Flow Solutions , 1981, IEEE Transactions on Power Apparatus and Systems.

[9]  Roy Billinton,et al.  Considering wind speed correlation of WECS in reliability evaluation using the time-shifting technique , 2009 .

[10]  R.N. Allan,et al.  Probabilistic Load Flow Considering Dependence Between Input Nodal Powers , 1984, IEEE Transactions on Power Apparatus and Systems.

[11]  J.F. Dopazo,et al.  Stochastic load flows , 1975, IEEE Transactions on Power Apparatus and Systems.

[12]  Tharam S. Dillon,et al.  Stochastic power flow using cumulants and Von Mises functions , 1986 .

[13]  R. Billinton,et al.  Considering load-carrying capability and wind speed correlation of WECS in generation adequacy assessment , 2006, IEEE Transactions on Energy Conversion.

[14]  Mohammad Shahidehpour,et al.  The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee , 1999 .

[15]  Roy Billinton,et al.  Effect of bus load uncertainty and correlation in composite system adequacy evaluation , 1991 .

[16]  Kumaraswamy Ponnambalam,et al.  Probabilistic optimal power flow , 1998, Conference Proceedings. IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.98TH8341).

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

[18]  J. Hammersley.  SIMULATION AND THE MONTE CARLO METHOD , 1982 .

[19]  A. Zervos,et al.  Wind power development in Europe , 2001, Proc. IEEE.

[20]  Yonghua Song,et al.  Load Flow Analysis , 2008 .

[21]  Antonio J. Conejo,et al.  A methodology to generate statistically dependent wind speed scenarios , 2010 .

[22]  João Tomé Saraiva,et al.  Fuzzy Load Flow-New Algorithms Incorporating Uncertain Generation and Load Representation , 1990 .

[23]  Ronald N. Allan,et al.  Probabilistic techniques in AC load flow analysis , 1977 .

[24]  A. Kiureghian,et al.  Multivariate distribution models with prescribed marginals and covariances , 1986 .

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