Swarm Intelligence for Transmission System Control

Many areas related to power system transmission require solving one or more nonlinear optimization problems. While analytical methods might suffer from slow convergence and the curse of dimensionality, heuristics based swarm intelligence can be an efficient alternative. This paper highlights the application of swam intelligence techniques for solving some of the transmission system control problems.

[1]  Marco Dorigo,et al.  Optimization, Learning and Natural Algorithms , 1992 .

[2]  R.G. Harley,et al.  Multiple STATCOM Allocation and Sizing Using Particle Swarm Optimization , 2006, 2006 IEEE PES Power Systems Conference and Exposition.

[3]  Kevin M. Passino,et al.  Biomimicry of bacterial foraging for distributed optimization and control , 2002 .

[4]  R. Steele Optimization , 2005 .

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

[6]  G.K. Venayagamoorthy,et al.  Optimal control parameters for a UPFC in a multimachine using PSO , 2005, Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems.

[7]  Y.P. Lu,et al.  Swarm Intelligence for Optimal Reactive Power Dispatch , 2005, 2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific.

[8]  J.G. Vlachogiannis,et al.  Optimization of Power Systems based on Ant Colony System Algorithms: An Overview , 2005, Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems.

[9]  Wenxin Liu,et al.  Particle Swarm Optimization based Defensive Islanding of Large Scale Power System , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[10]  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.

[11]  H. F. Wang,et al.  Power system voltage control by multiple STATCOMs based on learning humoral immune response , 2002 .

[12]  Liqun Gao,et al.  Transmission network optimal planning using the particle swarm optimization method , 2005, 2005 International Conference on Machine Learning and Cybernetics.

[13]  G. K. Venayagamoorthy,et al.  Optimal Design of a SVC Controller Using a Small Population Based PSO , .

[14]  Salman Mohagheghi,et al.  Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems , 2008, IEEE Transactions on Evolutionary Computation.

[15]  Manuel López-Ibáñez,et al.  Ant colony optimization , 2010, GECCO '10.

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

[17]  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 .

[18]  D.G. Robinson Reliability analysis of bulk power systems using swarm intelligence , 2005, Annual Reliability and Maintainability Symposium, 2005. Proceedings..

[19]  Bo Zhao,et al.  A Survey on Application of Swarm Intelligence Computation to Electric Power System , 2006, 2006 6th World Congress on Intelligent Control and Automation.

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

[21]  Ji-Pyng Chiou,et al.  Ant direction hybrid differential evolution for solving large capacitor placement problems , 2004, IEEE Transactions on Power Systems.

[22]  J.G. Vlachogiannis,et al.  Determining generator contributions to transmission system using parallel vector evaluated particle swarm optimization , 2005, IEEE Transactions on Power Systems.

[23]  Sukumar Mishra,et al.  Hybrid least-square adaptive bacterial foraging strategy for harmonic estimation , 2005 .

[24]  Mark M. Millonas,et al.  Swarms, Phase Transitions, and Collective Intelligence , 1993, adap-org/9306002.