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Methods of Simulated Annealing and Particle Swarm Applied to the Optimization of Reactive Power Flow in Electric Power SystemsPIJARSKI, P. , KACEJKO, P. |
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Author keywords
optimization, heuristic algorithms, power systems, reactive power control, compensation
References keywords
power(12), optimization(7), systems(6), swarm(6), fuzzy(4), control(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2018-11-30
Volume 18, Issue 4, Year 2018, On page(s): 43 - 48
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.04005
Web of Science Accession Number: 000451843400005
SCOPUS ID: 85058812305
Abstract
Electric power system is characterized by relatively high demand for lagging reactive power. From the economic viewpoint, reactive power sources should be installed close to its demand. Optimal compensation should ensure minimal costs of the reactive power generation and transmission within the considered system. The optimization of activities related to reactive power compensation concerns the location and power of compensation devices. This is to optimize voltage levels and reactive power flows in the system. The article presents methods of simulated annealing and particle swarm applied to solve an optimization task of the reactive power flow. It has been assumed that active power losses in a power system are the objective function. |
References | | | Cited By «-- Click to see who has cited this paper |
[1] A. Meier, "Electric Power Systems: Conceptual Introduction", pp. 144-228, Wiley-IEEE Press, 2006.
[2] J. Machowski, J. Bialek, J. Bumby, "Power system dynamics stability and control", pp. 15-122, John Wiley & Sons, 2008. [3] L. L. Grigsby, "Power systems", pp. 46-56, CRC Press, 2012. [4] J. Zhu, "Optimization of Power System Operation", pp. 1-50, Wiley-IEEE Press, 2015. [5] W. Zhang, Y. Liu, "Multi-objective reactive power and voltage control based on fuzzy optimization strategy and fuzzy adaptive particle swarm," International Journal of Electrical Power & Energy Systems, vol. 30, no. 9, pp. 525-532, 2008. [CrossRef] [Web of Science Times Cited 151] [SCOPUS Times Cited 210] [6] C. Wang, G. Yao, X. Wang et al., "Reactive Power Optimization Based on Particle Swarm Optimization Algorithm in 10kV Distribution Network," Advances in Swarm Intelligence, vol. 6728, pp. 157-164, 2011. [CrossRef] [SCOPUS Times Cited 7] [7] A. Q. H. Badar, B. S. Umre,, A. S. Junghare, "Reactive power control using dynamic Particle Swarm Optimization for real power loss minimization," International Journal of Electrical Power & Energy Systems, vol. 41, no. 1, pp. 133-136, 2012. [CrossRef] [Web of Science Times Cited 95] [SCOPUS Times Cited 118] [8] S. Biswas, K. K. Manadal, N. Chakraborty, "Simulated Annealing Based Real Power Loss Minimization Aspect for a Large Power Network," Swarm, Evolutionary, and Memetic Computing, vol. 8297, pp. 345-353, 2013. [CrossRef] [SCOPUS Times Cited 1] [9] M. A. Abido, "Multiobjective Optimal VAR Dispatch Using Strength Pareto Evolutionary Algorithm," 2006 IEEE International Conference on Evolutionary Computation, Vancouver, pp. 16-21, 2006. [CrossRef] [Web of Science Times Cited 37] [10] M. S. Bazaraa, H. D. Sherali, C. M. Shetty, "Nonlinear Programming: Theory and Algorithms", pp. 1-313, Wiley, 2006. [11] Z. Michalewicz, D. B. Fogel, "How to Solve It. Modern Heuristics", pp. 145-487, Springer , 2004. [12] X.-S. Yang, "Nature-inspired metaheuristic algorithms", pp. 11-108, Luniver Press, 2010. [13] P. J. Braspenning, F. Thuijsman, A. J. M. M. Weijters, "Artificial Neural Networks: An Introduction to ANN Theory and Practice", pp.1-100, Springer, 1995. [14] W. Pedrycz, "Fuzzy control and fuzzy systems", pp. 1-78, John Wiley & Sons, 1996. [15] L. J. Fogel, Owens, A., J., M., J. Walsh, "Artificial Intelligence through Simulated Evolution", pp. 11-66, John Wiley & Sons, 1966. [16] S. Kirkpatrick, C. D. Gelatt, M. P. Vecchi, "Optimization by Simulated Annealing," Science, vol. 220, no. 4598, pp. 671-680, 1983. [CrossRef] [Web of Science Times Cited 28059] [SCOPUS Times Cited 34103] [17] H. Bersini, J. Varela, Francisco, "Hints for adaptive problem solving gleaned from immune networks," Parallel Problem Solving from Nature, vol. 496, pp. 343-354, 1990. [CrossRef] [SCOPUS Times Cited 95] [18] R. Eberhart, J. Kennedy, "A new optimizer using particle swarm theory," in MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science, pp. 39-43, IEEE, 1995. [CrossRef] [19] A. Colorni, M. Dorigo, V. Maniezzo, "Distributed Optimization by Ant Colonies," Appeared in Procedings of ECAL91, pp. 134-142, 1991. [20] F. Glover, "Tabu Search-Part I," ORSA Journal on Computing, vol.1, no. 3, pp. 190-206, 1989. [CrossRef] [21] D. T. Pham, A. Ghanbarzadeh, E. Koc et al., "The Bees Algorithm A Novel Tool for Complex Optimisation," Intelligent Production Machines and Systems, pp. 454-459, 2006, [CrossRef] [SCOPUS Times Cited 951] [22] X.-S. Yang, S. Deb, "Cuckoo Search via Levy flights," 2009 World Congress on Nature & Biologically Inspired Computing, pp. 210-214, 2009. [CrossRef] [Web of Science Times Cited 4772] [SCOPUS Times Cited 6469] [23] J. E. Freund, B. M. Perles, "Modern Elementary Statistics", pp. 43-93, Pearson, 2006. Web of Science® Citations for all references: 33,114 TCR SCOPUS® Citations for all references: 41,954 TCR Web of Science® Average Citations per reference: 1,380 ACR SCOPUS® Average Citations per reference: 1,748 ACR TCR = Total Citations for References / ACR = Average Citations per Reference We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more Citations for references updated on 2024-11-12 12:37 in 79 seconds. Note1: Web of Science® is a registered trademark of Clarivate Analytics. Note2: SCOPUS® is a registered trademark of Elsevier B.V. Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site. |
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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