Dstatcom allocation in the distribution system considering load uncertainty

In this paper, a new stochastic structure is described to model the uncertainty effect of the active and reactive loads in the DSTATCOM allocation and sizing problem. The proposed technique has 2m+1 point estimate method (PEM) to trap the uncertainty associated with the expected error of the loads. The objectives are minimization of the total active power losses which diminish the voltage deviation of the buses. Other than that, a new optimization algorithm based on the bat algorithm (BA) is presented to search the problem space globally. Also, the idea of interactive fuzzy satisfying method is applied in the multi- objective formulation to provide a proper balance between the optimization of the objective functions. In the end, the proposed method is tested on the 69-bus IEEE distribution system to validate its feasibility and effective performance.

[1]  I. Wasiak,et al.  Application of DSTATCOM compensators for mitigation of power quality disturbances in low voltage grid with distributed generation , 2007, 2007 9th International Conference on Electrical Power Quality and Utilisation.

[2]  Chan-Nan Lu,et al.  Two-point estimate method for quantifying transfer capability uncertainty , 2005, IEEE Transactions on Power Systems.

[3]  Taher Niknam,et al.  Optimal operation management of fuel cell/wind/photovoltaic power sources connected to distribution networks , 2011 .

[4]  Arindam Ghosh,et al.  A flexible DSTATCOM operating in voltage or current control mode , 2002 .

[5]  Ali Maroosi,et al.  Application of shuffled frog-leaping algorithm on clustering , 2009 .

[6]  Loi Lei Lai,et al.  Application of evolutionary programming to reactive power planning-comparison with nonlinear programming approach , 1997 .

[7]  Xin-She Yang,et al.  Bat algorithm for multi-objective optimisation , 2011, Int. J. Bio Inspired Comput..

[8]  D. Das A fuzzy multiobjective approach for network reconfiguration of distribution systems , 2006, IEEE Transactions on Power Delivery.

[9]  G. Carpinelli,et al.  Point estimate schemes for probabilistic three-phase load flow , 2010 .

[10]  R. Romero,et al.  Optimal Capacitor Placement in Radial Distribution Networks , 2001, IEEE Power Engineering Review.

[11]  Saeed Jazebi,et al.  DSTATCOM allocation in distribution networks considering reconfiguration using differential evolution algorithm , 2011 .

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

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

[14]  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.

[15]  M. E. Baran,et al.  Optimal capacitor placement on radial distribution systems , 1989 .

[16]  R.C. Degeneff,et al.  Security constrained optimization: an added dimension in utility systems optimal power flow , 1988, IEEE Computer Applications in Power.

[17]  Taher Niknam,et al.  Considering uncertainty in the multi-objective stochastic capacitor allocation problem using a novel self adaptive modification approach , 2013 .

[18]  Thanatchai Kulworawanichpong,et al.  Distribution Voltage Regulation Under Three- Phase Fault by Using D-STATCOM , 2008 .

[19]  Abdollah Kavousi-Fard,et al.  A new hybrid correction method for short-term load forecasting based on ARIMA, SVR and CSA , 2013, J. Exp. Theor. Artif. Intell..

[20]  Taher Niknam,et al.  Scenario-based multiobjective distribution feeder reconfiguration considering wind power using adaptive modified particle swarm optimisation , 2012 .

[21]  Abdollah Kavousi-Fard A new fuzzy-based feature selection and hybrid TLA–ANN modelling for short-term load forecasting , 2013, J. Exp. Theor. Artif. Intell..

[22]  Abdollah Kavousi-Fard,et al.  Considering uncertainty in the optimal energy management of renewable micro-grids including storage devices , 2013 .

[23]  Taher Niknam,et al.  Application of honey-bee mating optimization on state estimation of a power distribution system including distributed generators , 2008 .

[24]  Abdollah Kavousi-Fard,et al.  Reliability enhancement using optimal distribution feeder reconfiguration , 2013, Neurocomputing.

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

[26]  Taher Niknam,et al.  A novel hybrid particle swarm optimization for economic dispatch with valve-point loading effects , 2011 .

[27]  Taher Niknam,et al.  Distribution feeder reconfiguration considering fuel cell/wind/photovoltaic power plants , 2012 .

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

[29]  Chan-Nan Lu,et al.  Two-point estimate method for quantifying transfer capability uncertainty , 2005 .

[30]  Taher Niknam,et al.  An efficient hybrid evolutionary algorithm based on PSO and HBMO algorithms for multi-objective Distribution Feeder Reconfiguration , 2009 .