Commenced in January 2007
Paper Count: 30184
Multiple Power Flow Solutions Using Particle Swarm Optimization with Embedded Local Search Technique
Abstract:Particle Swarm Optimization (PSO) with elite PSO parameters has been developed for power flow analysis under practical constrained situations. Multiple solutions of the power flow problem are useful in voltage stability assessment of power system. A method of determination of multiple power flow solutions is presented using a hybrid of Particle Swarm Optimization (PSO) and local search technique. The unique and innovative learning factors of the PSO algorithm are formulated depending upon the node power mismatch values to be highly adaptive with the power flow problems. The local search is applied on the pbest solution obtained by the PSO algorithm in each iteration. The proposed algorithm performs reliably and provides multiple solutions when applied on standard and illconditioned systems. The test results show that the performances of the proposed algorithm under critical conditions are better than the conventional methods.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1328628Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1401
 C.A. Silva, J.M.C. Sousa, T.A. Runkler, "Rescheduling and optimization of logistic processes using GA and ACO", Engineering Applications of Artificial Intelligence, Volume 21, Issue 3, April 2008, Pages 343-352.
 Li Liu, Wenxin Liu, David A. Cartes, "Particle swarm optimizationbased parameter identification applied to permanent magnet synchronous motors", Engineering Applications of Artificial Intelligence, Volume 21, Issue 7, October 2008, Pages 1092-1100.
 S. Ghosh, D. Kundu, K. Suresh, S. Das and A. Abraham, An Adaptive Particle Swarm Optimizer with Balanced Explorative and Exploitative Behaviors, 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, IEEE Computer Society Press, USA, 2008.
 N. Samal, A. Konar, S. Das and A. Abraham, A Closed Loop Stability Analysis and Parameter Selection of the Particle Swarm Optimization Dynamics for Faster Convergence, IEEE Congress in Evolutionary Computation, CEC 2007, IEEE press, USA, ISBN 1-4244-1340-0, pp. 1769-1776, 2007.
 Del Valle Y., Venayagamoorthy G.K., Mohagheghi S., Hernandez J.-C., Harley R.G., "Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems", IEEE Transactions on Evolutionary Computation, Volume 12, Issue 2, April 2008 Page(s):171 - 195.
 Emad Elbeltagi, Tarek Hegazy, Donald Grierson, "Comparison among five evolutionary-based optimization algorithms", Advanced Engineering Informatics, Volume 19, Issue 1, January 2005, Pages 43- 53.
 P.K. Modi, S.P. Singh, J.D. Sharma, "Loadability margin calculation of power system with SVC using artificial neural network", Engineering Applications of Artificial Intelligence, Volume 18, Issue 6, September 2005, Pages 695-703.
 M. A. Abido, "Optimal Power Flow Using Particle Swarm Optimization", international journal of Electrical Power & Energy Systems, vol. 24, pp 563-571, 2002.
 Kit Po Wong, "Solving power system optimization problems using simulated annealing", Engineering Applications of Artificial Intelligence, Volume 8, Issue 6, December 1995, Pages 665-670.
 S. Chakrabarti, B. Jeyasurya, "Generation rescheduling using ANNbased computation of parameter sensitivities of the voltage stability margin", Engineering Applications of Artificial Intelligence, Volume 21, Issue 8, December 2008, Pages 1164-1169.
 Wong K. P., Li A., and Law M.Y., "Development of constrained Genetic algorithm load flow method", IEE Proc.-Gener. Transm. Distrib., March 1997, Vol. 144, No. 2, pp. 91-99.
 Abido M.A., "Optimal design of power-system stabilizers using particle swarm optimization", IEEE Transactions on Energy Conversion, September 2002, Vol. 17, No. 3, pp. 406-413.
 Ting T.O., Rao M.V.C., Loo, C.K., "A novel approach for unit commitment problem via an effective hybrid particle swarm optimization", IEEE Transaction on Power Systems, Feb. 2006, Vol. 21, No. 1, pp. 411 - 418.
 Lingfeng Wang, Chanan Singh, "Reserve-constrained multiarea environmental/economic dispatch based on particle swarm optimization with local search", Engineering Applications of Artificial Intelligence, In Press, Corrected Proof, Available online 11 October 2008.
 M. Senthil Arumugam, M.V.C. Rao, "On the improved performances of the particle swarm optimization algorithms with adaptive parameters, cross-over operators and root mean square (RMS) variants for computing optimal control of a class of hybrid systems", Applied Soft Computing, 8 (2008), pages 324-336.
 Sidhartha Panda, Narayana Prasad Padhy, "Comparison of particle swarm optimization and genetic algorithm for FACTS-based controller design", Applied Soft Computing, In Press, Corrected Proof, Available online 26 October 2007.
 Fukuyama Y., and Yoshida H., "A Particle Swarm Optimization for Reactive Power and Voltage Control in Electrical Power Systems", Proc. of 2001 Congress on Evolutionary Computation, May 2001, Vol. 1, pp. 87-93.
 Eberhart R.C., and Kennedy J, "A new optimizer using particle swarm theory", Proc. of Sixth International Symposium on Micro Machine and Human Science (Nagoya, Japan), IEEE Service Centre, Piscataway, NJ, 1995, pp. 39-43.
 Tinney W.F., and Hart C.E., "Power flow solution by Newton-s method", IEEE Trans. Power Apparatus & Systems, Vol. PAS-86, pp. 1449-1456, Nov. 1967.
 Stott B., and Alsac O., "Fast decoupled load flow", IEEE Trans. Power Apparatus & Systems, Vol. PAS-93, pp. 859-869, May/June 1974.
 Van Amerongan R. A. M., "A General purpose version of the fast decoupled load flow", IEEE Trans. Power System, Vol. 4, pp. 760-770, May 1989.
 V. Ajjarapu, and C. Christy, "The continuation power flow: A Tool For Steady State Voltage Stability Analysis", IEEE Trans. Power Syst. PS-7 (1992) 416-423.
 Ferreira L.A.F.M., De Jesus C.M.S.C., "Local Network Power Flow Analysis: An Accuracy Level Comparison for Two Sets of Equations", Power Systems, IEEE Transactions on, Page(s): 1624-1629, Volume: 21 Issue: 4 Nov. 2006.
 De Leon F., "Discussion of "A new preconditioned conjugate gradient power flow", Power Systems, IEEE Transactions on, Volume: 18 Issue: 4 Nov. 2003.
 Li S.-H., Chiang H.-D., "Nonlinear predictors and hybrid corrector for fast continuation power flow", Generation, Transmission & Distribution, IET, Page(s): 341-354, Volume: 2 Issue: 3 May 2008.
 Tamura Y., Mori H., and Iwamoto, "Relationship between voltage instability and multiple load flow solutions in electric power systems", IEEE Transaction on Power App. And Sys., May 1983, Vol. PAS-102, pp. 1115-1123.
 Yorino Y., Harada S., and Kitagawa M., "Use of multiple load flow solutions to approximate closest loadability limit", Bulk Power System Voltage Phenomena III Conference, Davos, Switzerland, Aug. 1994.
 Overbye T. J., and Klump R. P., "Effective calculation of power system low-voltage solutions", IEEE Transaction on Power Systems, February 1996, Vol. 11, No. 1, pp. 75-82.
 Salam F. M. A., Ni L., Guo S., and Sun X., "Parallel processing for the load flow of power systems: the approach and applications", Proc. 28th CDC,Tampa, Florida, Dec. 1989, pp. 2173-2178.
 Iba K., Suzuki H., Egawa M., and Watanabe T., "A method finding a pair of multiple load flow solutions in bulk power systems", IEEE Transaction on Power Systems, May 1990, Vol. 5, No. 2.
 Ma W., and Thorp J.S., "An efficient algorithm to locate all the load flow solutions", IEEE Trans. PWRS, Aug. 1993, Vol. 8, No. 3, pp. 1077-1083.
 Zhigang W., Zhang Y. et. Al, "A new method to calculate multiple power flow solutions", conference on advances in power system control, operation and management, 2000, APSCOM-00, 2000 international, Nov. 2000, Vol 2, 30 oct.-1st, pp-491-495.
 Xu W. and wang Y., "The existence of multiple power flow solutions in unbalanced three phase circuits", power engineering review, IEEE, Dec 2002, Vol 22, Issue 12.
 Eberhart R.C., and Shi Y., "Comparing inertia weights and constriction factors in particle swarm optimization", Proc. of CEC 2000.