Czasopismo | PRZEGLĄD ELEKTROTECHNICZNY | Rocznik 2019 - zeszyt 8

Power Loss Minimization by Voltage Transformer Turns Ratio Selection based on Particle Swarm Optimization

Minimalizacja strat mocy w transformatorze przez dobór stosunku zwojów z wykorzystaniem algorytmu PSO

10.15199/48.2019.08.28

nr katalogowy: 121598
10.15199/48.2019.08.28

Streszczenie

The research considers the optimization of the taps position of voltage transformers to minimize power loss. The Particle Swarm Optimization algorithm is implemented to this optimization problem. The advantage of this algorithm is the ability to adapt to an optimization problem. It was found out that the Particle Swarm Optimization algorithm is more productive than the greedy heuristic algorithm based on the division of this optimization problem into subtasks. Also, the paper studied the influence of particle velocity restriction on the efficiency of the algorithm.

Abstract

W pracy analizowano metode optymalizacji strat transformatora przez dobór stosunku uzwojeń. Do tego celu wykorzystano algorytm genetyczny PSO. Porównano prace układu z innymi algorytmami adaptacyjnymi.

Słowa kluczowe

Keywords

Bibliografia

[1] Quevedo J., Cazakevicius F.E., Beltrame R.C., Analysis and Design of an Electronic On-Load Tap Changer Distribution Transformer for Automatic Voltage Regulation, IEEE Transactions on Industrial Electronics, 64 (2017), No. 1, 883- 894.
[2] Tengku J., Mohamed A., Shareef H., A review on voltage control methods for active distribution networks, Przeglad Elektrotechniczny, 88 (2012), nr. 6,304-312.
[3] Robbins B.A., Zhu H., Domínguez-García A.D., Optimal Tap Setting of Voltage Regulation Transformers in Unbalanced Distribution Systems, IEEE Transactions on Power Systems, 31 (2016), No. 1, 256-267.
[4] Huang S., Pillai J.R., Liserre M., Bak-Jensen B., Improving photovoltaic and electric vehicle penetration in distribution grids with smart transformer, Innovative Smart Grid Technologies Europe (ISGT EUROPE), 6-9 Oct. 2013. doi: 10.1109/ISGTEurope.2013.6695282. PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 95 NR 8/2019 131
[5] Kekatos V., Zhang L., Giannakis G.B., Baldick R., Voltage Regulation Algorithms for Multiphase Power Distribution Grids, IEEE Transactions on Power Systems, 31 (2016), No. 5, 3913-3923.
[6] Manusov V.Z., S idork in Y.M., Methods of optimization of transformer coefficients, Regimes of electrical network and systems, Novosibirsk, 1974, 51-56.
[7] Spatti D.H., Da Silva I.N., Usida W.F., Flauzino R.A., Fuzzy Control System for Voltage Regulation In Power Transformers, IEEE Latin America Transactions, 8 (2010), No. 1, 51-57.
[8] Zhmak E. I., Manusov V.Z., Substantiation of the principle of fuzzy voltage regulation by means of transformers with voltage regulation, Power engineering, Novosibirsk, 2002, 32-34.
[9] Kel ler J.M., L iu D., Fogel D.B., Collective Intelligence and Other Extensions of Evolutionary Computation, Wiley-IEEE Press, 2016, 400 p. doi: 10.1002/9781119214403.ch13.
[10] Verayiah R., Mohamed A., Shareef H., Abidin I. Z., Under Voltage Load Shedding Scheme Using Meta-heuristic Optimization Methods, Przeglad Elektrotechniczny 90 (2014), nr. 11, 162-168.
[ 1 1 ] Zhu Y. Tang X., Overview of swarm intelligence, Computer Application and System Modeling, 9 (2010), 400-409. doi: 10.1109/ICCASM.2010.5623005.
[12] Manusov, V., Matrenin, P., Kokin, S., Swarm intelligence algorithms for the problem of the optimal placement and operation control of reactive power sources into power grids, International Journal of Design & Nature and Ecodynamics, 12 (2017), No. 1, 101-112. doi: 10.1109/EPE.2017.7967231.
[ 1 3 ] Mantawy A.H., Abdel-Magid Y. L., Selim S.Z., Integrating Genetic Algorithms, Tabu Search, and Simulated Annealing for the Unit Commitment Problem, IEEE Transactions on Power Systems, 14 (1999), No. 3, 829-836.
[14] Der vani D., Rosel yn J.P., Genetic algorithm based reactive power dispatch for voltage stability improvement, International Journal of Electrical Power & Energy Systems, 32 (2010), No. 10, 1151-1156.
[15] Ebeed M., Kamel S., Youssef A-R., Optimal Integration of D-STATCOM in RDS by a Novel Optimization Technique, 2018 Twentieth International Middle East Power Systems Conference (MEPCON), 18-20 Dec. 2018, doi: 10.1109/MEPCON.2018.8635167.
[16] Mendoza G.E., Vacas V.M., Ferreira N.R., Optimal Capacitor Allocation and Sizing in Distribution Networks Using Particle Swarm Optimization Algorithm, 2018 Workshop on Communication Networks and Power Systems (WCNPS), 7-9 Nov. 2018, doi: 10.1109/WCNPS.2018.8604320.
[17] Karmakar N., Bhattacharyya B., A memory based meta-heuristic optimizer for optimal VAr management in power transmission system, 2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), 2-4 Nov. 2018, doi: 10.1109/UPCON.2018.8597118.
[18] Hao L., Wang G., Song P., Hu Q., Voltage Control Method Based on Coordinative Optimization of User Energy Saving and Power Loss Reduction in Distribution Network, 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2), 20-22 Oct. 2018, doi: 10.1109/EI2.2018.8582185.
[19] Kanata S., Gibson H.M., Maulidevi N.U., Optimization of Reactive Power and Voltage Control in Power System Using Hybrid Artificial Neural Network and Particle Swarm Optimization, 2018 2nd International Conference on Applied Electromagnetic Technology (AEMT), 9-12 April 2018, doi: 10.1109/AEMT.2018.8572408.
[ 20] Li D. , He Q. , A Version of Cooperative Multi-Swarm PSO Using Electoral Mechanism to Solve Hybrid Flow Shop Scheduling Problem, Przeglad Elektrotechniczny, 88(2012), 22- 26.
[ 21] Mat renin P.V., Sekaev V.G., Particle Swarm optimization with velocity restriction and evolutionary parameters selection for scheduling problem, Control and Communications (SIBCON), 2015 International Siberian Conference, 2015. doi: 10.1109/SIBCON.2015.
[22] Karimyan P., Abedi M., Hosseinian S.H., Khatami R., Stochastic approach to represent distributed energy resources in the form of a virtual power plant in energy and reserve markets, IET Generation, Transmission & Distribution, 10 (2016), No. 8, 1792-1804.
[23] Jamian J.J., Mustafa M.W., Mokhlis H., Baharudin M.A., A New Particle Swarm Optimization Technique in Optimizing Size of Distributed Generation, International Journal of Electrical and Computer Engineering, 1 (2012), No. 1, 137-146.
[24] Eberhart R., Shi Y., Kennedy J., Swarm Intelligence, Morgan Kaufmann, 2001, 512 p.
[25] Eberhar t R.C., Shi Y., Particle swarm optimization: developments, applications and resources, Congress on Evolutionary Computation, 1 (2001), doi: 10.1109/CEC.2001.934374.
[26] Pedersen M., Chippereld A., Simplifying Particle Swarm Optimization, Applied Soft Computing, 10 (2010), No. 2, 618- 628. doi: 10.1016/j.asoc.2009.08.029.
[27] Wolper t D.H., Mac ready W.G., No Free Lunch Theorems for Optimization, IEEE Transactions on Evolutionary Computation, 1 (1997), 67-82.

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