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Damping low-frequency oscillations in a multi-machine power system using a fuzzy-multi-band power system stabilizer

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Synchronous generators are usually eguipped with power system stabilizers (PSS) to damp low-freguency oscillations. Among the various types of PSS, it has recently been demonstrated that the Multi-Band PSS (MB-PSS) has a better performance to handle all global, inter-area and local modes. However, the performance of this PSS may degrade since the power supply system is intrinsically non-linear and its operating conditions freguently change. This paper introduces a new design of MB-PSS based on Mamdani Fuzzy inference (Fuzzy-MB-PSS). Compared to the IEEE standard MB-PSS, the proposed stabilizer is more efficient owing to its ability to deal with oscillations at different operating points. The controller is tested on a power system benchmark under various disturbance conditions to prove its robustness and to demonstrate its superiority over conventional PSS and MB-PSS.
Rocznik
Strony
140--148
Opis fizyczny
Bibliogr. 22 poz., rys., tab., wykr.
Twórcy
  • Universite de Sousse, Ecole National d'Ingenieurs de Sousse, LATIS- Laboratory of Advanced Technology and Intelligent Systems, Sousse 4023, Tunisia
autor
  • Universite de Sousse, Ecole National d'Ingenieurs de Sousse, LATIS- Laboratory of Advanced Technology and Intelligent Systems, Sousse 4023, Tunisia
Bibliografia
  • [1] Sahu, P. R. Hota, P. k. & Panda, S. (2019). Modified whale optimization algorithm for coordinated design of fuzzy lead-Jag structure-based SSSC controller and power system stabilizer. International Transactions on Electrical Energy Systems, 29(4), e2797.
  • [2] Vakula, V.S. & Sudha, K.R. (2012). Design of differential evolution algorithm-based robust fuzzy logic power system stabiliser using minimum rule base. lET Generation, Transmission & Distribution, 6, 121-132.
  • [3] Essallah, S. Bouallegue, A. & Khedher, A. (2019). Integration of automatic voltage regulator and power system stabilizer: small-signal stability in DFIG-based wind farms. Journal of Modern Power Systems and Clean Energy, 7(5), 1115-1128.
  • [4] Hussein, T., Saad, M. S., Elshafei, AL. & Bahgat, A. (2010). Damping inter-area modes of oscillation using an adaptive fuzzy power system stabilizer. Electric Power Systems Research, 80(12), 1428-1436.
  • [5] Sebaa, K. & Boudour, M. (2007) Robust power system stabilizers design using multi objective genetic algorithm,in: IEEE Power Engineering Society General Meeting.
  • [6] Abdulkhader, H. K., Jacob,J. & Mathew, A. T. (2019). Robust type-2 fuzzy fractional order PID controller for dynamic stability enhancement of power system having RES based microgrid penetration. International Journal of Electrical Power & Energy Systems, 110, 357-371.
  • [7] Huerta, H., Loukianov, A.G. & Canedo, J.M. (2010). Decentralized sliding mode block control of multimachine power systems, Electrical Power and Energy Systems, 32, 1-11.
  • [8] Khodabakhshian, A. & Hemmati, R. (2012). Robust decentralized multi-machine power system stabilizer design using quantitative feedback theory. Electrical Power and Energy Systems, 41,112-119.
  • [9] Ramakrishna, G. & Malik,O.P. (2010). Adaptive PSS using a simple on-line identifier and linear pole-shift controller, Electrical Power and Energy Systems, 80, 406-416.
  • [10] Solimana, M., Elshafei, AL., Bendary,F. & Mans our,W. (2010). Robust decentralized PIDbased power system stabilizer design using an ILMI approach. Electrical Power and Energy Systems, 80, 1488-1497.
  • [11] Abd Elazim,S. M. & Ali, E. S. (2016). Optimal power system stabilizers design via cuckoo search algorithm. International Journal of Electrical Power & Energy Systems, 75, 99-107.
  • [12] Hussain, A.N. & Shri, S. H. (2018). Damping Improvement by Using Optimal Coordinated Design Based on PSS and TCSC Device. In 2018 Third Scientific Conference of Electrical Engineering (SCEE), 116-121.
  • [13] Krishan, R. & Verma, A. (2016). Robust tuning of power system stabilizers using hybrid intelligent algorithm. In 2016 IEEE Power and Energy Society General Meeting (PESGM), 1-5.
  • [14] Obaid, Z. A., Cipcigan, L. M. & M. T. Muhssin (2017). Power system oscillations and control: Classifications and PSSs' design methods: A review. Renewable and Sustainable Energy Reviews, 79, 839-849.
  • [15] Chaib, L., Choucha, A. & Arif, S. (2017). Optimal design and tuning of novel fractional order PID power system stabilizer using a new metaheuristic Bat algorithm. Ain Shams Engineering Journal, 8(2), 113-125.
  • [16] Kumara, K & Srinivasan, A. D. (2017). Design of optimal controllers for the power system stabilizer-Effect of operating conditions. In 2017 Second International Conference on Electrical,Computer and Communication Technologies (ICECCT), 1-6.
  • [17] Dasu, B. , Sivakumar, M. & Srinivasarao, R. (2019). Interconnected multi-machine power system stabilizer design using whale optimization algorithm. Protection and Control of Modern Power Systems, 4(1), 2.
  • [18] Jebali, M., Kahouli, 0., & Abdallah, H. H. (2017). Optimizing PSS parameters for a multi machine power system using genetic algorithm and neural network techniques. The International Journal of Advanced Manufacturing Technology, 90(9-12), 2669-2688.
  • [19] Ray, P. K., & al. (2019). A hybrid firefly-swarm optimized fractional order interval type-2 fuzzy PID-PSS for transient stability improvement. IEEE Transactions on Industry Applications, 55(6), 6486-6498.
  • [20] Rimorov,D. & al. (2016, July). Inter-area oscillation damping and primary frequency control of the New York state power grid with multi-functional multi-band power system stabilizers. In 2016 IEEE Power and Energy Society General Meeting (PESGM), pp. 1-5.
  • [21] Baghani, D. & Koochaki, A. (2016). Multi-machine power system optimized fuzzy stabilizer design by using cuckoo search algorithm. International Electrical Journal (IEEJ), v7(3), 2182-2187.
  • [22] Kundur, P. (1994). Power System Stability and Control. Mc-Graw Hill, USA.
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8e3b738f-a6fa-4dd3-985a-28abc5174af5
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