Finding optimal location of FACTS device for dynamic Reactive Power compensation using Genetic Algorithm and Particle Swarm Optimisation (PSO)

• Autorzy: Pavleka Josip , Nikolovski Srete , Stojkov Marinko

Identyfikatory

DOI

10.15199/48.2019.08.21

Warianty tytułu

PL

Optymalna lokalizacja FACTS do dynamicznej kompensacji mocy biernej z wykorzystaniem algorytmu genetycznego

• Języki publikacji: EN

Abstrakty

EN

This paper presents advantage of using a FACTS device for dynamic Reactive Power compensation. Simulation model was built in MATLAB Simulink software to prove mathematical constraints. Determination of the most favourable location and size of the compensation devices from the aspect of losses, power quality, costs are calculated as a fitness function developed by genetic algorithm. Optimisation was done by Particle swarm optimization (PSO). Finally, cut convergence time and significant potential of usage such type of PSO optimisation method for determination of future investments are shown. This algorithm is tested to determine optimal location of FACTS device in railway application, instead of the methods and algorithms in transmission or distribution power system used until now.

PL

W artykule zaprezentowano korzyści ze stosowanie FACTS do dynamicznej kompensacji mocy biernej. Symulacje miały na celu określenie najlepszego położenia i roz,miaru urządzeń kompensujących z punktu widzenia jakości energii i kosztów. Zastosowano algorytm genetyczny PSO do optymalizacji i analizy przyszłych inwestycji.

Słowa kluczowe

EN

FACTS; reactive power compensation; genetic algorithm; particle swarm optimisation; determination of optimal location

PL

FACTS; kompensacja mocy biernej; algorytm genetyczny; optymalna lokalizacja

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2019
• Tom: R. 95, nr 8
• Strony: 86--91
• Opis fizyczny: Bibliogr. 15 poz., rys., tab.

Twórcy

autor

Pavleka Josip

• HEP-Distribution System Operator Ltd., Zagreb, Croatia

autor

Nikolovski Srete

• Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Croatia

autor

Stojkov Marinko

• Mechanical Engineering Faculty in Slavonski Brod, Croatia

Bibliografia

• [1] R. Benabid, M. Boudour, M.A. Abido, Optimal location and setting of SVC and TCSC devices using non-dominated sorting Particle Swarm Optimization, Electric Power Systems Research, 79 (2009), pp. 1668-1677
• [2] Saravanan, S.M.R. Slochanal, P. Venkatesh, P.S. Abraham, Application of PSO technique for optimal location of FACTS devices considering system loadability and cost of installation” Power Engineering Conference, 2 (2005), pp. 716-721
• [3] M. Saravanan, S. Mary Raja Slochanal, P. Venkatesh, J. Prince Stephen Abraham, Application of particle swarm optimization technique for optimal location of FACTS devices considering cost of installation and system loadability, Electric Power Systems Research, 77 (2007), pp. 276-283
• [4] J. Aghaei, M. Gitizadeh, M. Kaji, Placement and operation strategy of FACTS devices using optimal continuous power flow, Scientia Iranica, 19 (6) (December 2012), pp. 1683-1690
• [5] E. Ghahremani, I. Kamwa, Optimal placement of multiple-type FACTS devices to maximize power system loadability using a generic graphical user interface, IEEE Trans Power Syst, 28 (2) (2013), pp. 764-778
• [6] A. Lashkar Ara, A. Kazemi, S.A. Nabavi Niaki, Multiobjective optimal location of FACTS shunt-series controllers for power system operation planning IEEE TRANS Power Del, 27 (2) (2012), pp. 481-490
• [7] S. Gerbex, R. Cherkaoui, A.J. Germond, Optimal location of multi-type FACTS devices in a power system by means of genetic algorithms, IEEE Transactions on Power Systems, 16 (3) (2001), pp. 537-544
• [8] A. Deihimi, H. Javaheri, A fuzzy multi-objective multi-case genetic-based optimization for allocation of FACTS devices to improve system static security, power loss and transmission line voltage profiles, International Review of Electrical Engineering (IREE), 5 (4) (2010), pp. 1616-1626
• [9] B. Singh, V. Mukherjee, P. Tiwari, A survey on impact assessment of DG and FACTS controllers in power systems, Renew. Sustain. Energy Rev, 42 (2015), pp. 846-882
• [10] M.H. Moradi, M. Abedini, A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems, Int. J. Electr. Power Energy Syst, 34 (2012), pp. 66-74
• [11] S. Devi, M. Geethanjali, Optimal location and sizing determination of Distributed Generation and DSTATCOM using Particle Swarm Optimization algorithm, Int. J. Electr. Power Energy Syst, 62 (2014), pp. 562-57
• [12] Samimi A., Golkar M.A., A Novel Method for Optimal Placement of STATCOM in Distribution Networks Using Sensitivity Analysis by DIgSILENT Software, Asia-Pacific Power and Energy Engineering Conference, (2011),1-5 (Electrical Review), ISSN 0033-2097, R. 88 NR 1a/2012
• [13] Lakdja, F., Gherbi, F.Z., Zidi, S. A., OPF including TCSC devices using FACTS program software, Przegląd Elektrotechniczny 2012, R. 88, nr. 11a, p. 161-165
• [14] Eslami M., Shareef H., Mohamed A., Application of Artificial Intelligent Techniques in PSS design: A survey of the stateofthe-art methods, Przegląd Elektrotechniczny (Electr. Rev.) 87(2011) No. 4. 188-197
• [15] J. Kennedy, R. Eberhart, Particle swarm optimization, Proceedings of ICNN'95 - International Conference on Neural Networks, 27 Nov.-1 Dec. 1995

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019)