Multiple STATCOM Allocation and Sizing Using Particle Swarm Optimization

This study shows step by step the application of the particle swarm optimization (PSO) method to solve the problem of optimal allocation and sizing of multiple static compensators (STATCOM) in a medium size power network (45 bus system, part of the Brazilian power network). The PSO is proposed as an alternative methodology for traditional heuristic approaches and complicated mixed integer linear and non linear programming methods. Simulation results show the suitability of the PSO technique in finding multiple optimal solutions to the problem (Pareto front) with reasonable computational effort. As a part of this study, the optimal setting of PSO parameters is investigated and different power system load conditions are tested to determine the impact over the location and size of each STATCOM unit

[1]  Michael N. Vrahatis,et al.  Particle swarm optimization for integer programming , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[2]  Shuyuan Yang,et al.  A quantum particle swarm optimization , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[3]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[4]  H. Sasaki,et al.  A New Formulation for FACTS Allocation for Security Enhancement against Voltage Collapse , 2002, IEEE Power Engineering Review.

[5]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[6]  F. Milano,et al.  An open source power system analysis toolbox , 2005, 2006 IEEE Power Engineering Society General Meeting.

[7]  Joong-Rin Shin,et al.  A particle swarm optimization for economic dispatch with nonsmooth cost functions , 2005, IEEE Transactions on Power Systems.

[8]  Chao-Ming Huang,et al.  A particle swarm optimization to identifying the ARMAX model for short-term load forecasting , 2005, IEEE Transactions on Power Systems.

[9]  S. Kannan,et al.  Application and comparison of metaheuristic techniques to generation expansion planning problem , 2005, IEEE Transactions on Power Systems.

[10]  Laszlo Gyugyi,et al.  Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems , 1999 .

[11]  R.G. Harley,et al.  Optimal STATCOM Sizing and Placement Using Particle Swarn Optimization , 2006, 2006 IEEE/PES Transmission & Distribution Conference and Exposition: Latin America.

[12]  S. Gerbex,et al.  Optimal Location of Multi-Type FACTS Devices in a Power System by Means of Genetic Algorithms , 2001, IEEE Power Engineering Review.

[13]  Ronald G. Harley,et al.  Optimal Allocation of a STATCOM in a 45 Bus Section of the Brazilian Power System Using Particle Swarm Optimization , 2006 .

[14]  D.H. Werner,et al.  Particle swarm optimization versus genetic algorithms for phased array synthesis , 2004, IEEE Transactions on Antennas and Propagation.

[15]  Hiroyuki Mori,et al.  A parallel tabu search based method for determining optimal allocation of FACTS in power systems , 2000, PowerCon 2000. 2000 International Conference on Power System Technology. Proceedings (Cat. No.00EX409).

[16]  Peerapol Jirapong,et al.  Optimal allocation of FACTS devices to enhance total transfer capability using evolutionary programming , 2005, 2005 IEEE International Symposium on Circuits and Systems.

[17]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[18]  James Kennedy,et al.  The particle swarm: social adaptation of knowledge , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[19]  Rachid Cherkaoui,et al.  Optimal location of FACTS devices to enhance power system security , 2003, 2003 IEEE Bologna Power Tech Conference Proceedings,.

[20]  Georgios C. Stamtsis,et al.  Optimal choice and allocation of FACTS devices in deregulated electricity market using genetic algorithms , 2004, IEEE PES Power Systems Conference and Exposition, 2004..