ROBUST DESIGN OF POWER SYSTEM STABILIZER FOR A SINGLE GENERATOR-INFINITE BUS POWER SYSTEM
Mots-clés :
Power system stabilizer (PSS), Genetic algorithm (GA), Fuzzy proportional–integral–derivative, PSS controller design (FPID-PSS)Résumé
In interconnected power system stability is influenced by oscillations. The safe functioning of these systems depends on the damping of these oscillations. The development of the damping controllers is a constraint-based on a multimodal optimization problem. The use of conventional optimization methods is relatively difficult. In this paper, a power system stabilizer that generates an additional control signal for the excitation system provides the improvement of the stability of the Single Machine Infinite Bus System (SMIB). To overcome the disadvantages of conventional power system stabilizers (CPSS), a PSS controller is designed. The structure of a conventional controller PID is used, where the gains are adapted online based on parameter estimation using fuzzy gain scheduling. A genetic algorithm (GA) is used to determine the range of the controller parameters. The simulation results show the high performance of the proposed controller, to improve the stability of the power system compared to conventional PSS.
Références
(1) M. A. Hannan, N.N. Islam, M. Azah, M.S.H. Lipu, P.J.Ker, M.M. Rashid, H. Shareef, Artificial intelligent based damping controller optimization for the multi-machine power system, IEEE Access, 6, pp. 39574–39594 (2018).
(2) Y. Peng, Q. Chen, W. Sun, M. Kashif, A Disturbance-rejection Power Stabilizer for Power System Based-on Internal Model Control Framework, 37th Chinese Control Conference (CCC), IEEE, pp. 714–719 (2018).
(3) S. Ekinci, B. Hekimoğlu, E. Uysal, Kidney-inspired algorithm for determination of PID power system stabilizer parameters, Journal of polytechnic., 22, 2, pp. 453-460 (2019).
(4) Z.A. Obaid, L. M. Cipcigan, M. T. Muhssin, Power system oscillations and control: Classifications and PSSs’ design methods: A review, Renewable and Sustainable Energy Reviews, 79, pp. 839–849 (2017).
(5) P. Dey, A. Bhattacharya, J. Datta, P. Das, Small signal stability improvement of large, interconnected power systems using power system stabilizer, 2nd International Conference for Convergence in Technology (I2CT), IEEE, pp. 753–760 (2017).
(6) H. Wang, W. Du, Analysis and Damping, Control of Power System Low-frequency Oscillations, New York: Springer, 2016.
(7) J. Usmana, M. W. Mustafaa, G. Aliyua, B. U. Musab, Coordinated AVR-PSS for Transient Stability Using Modified Particle Swarm Optimization., Jurnal Teknologi -Sciences & Engineering., 67, 3, pp. 9–16, Malaysia, 2014.
(8) P. W. Sauer, M. A. Pai, J. H. Chow, Power System Dynamics and Stability, p. 223, JohnWiley & Sons Ltd, 2018.
(9) S. Ekinci, B. Hekimoğlu, E. Uysal, Modeling, simulation, and optimal design of power system stabilizers using ABC algorithm, Turkish Journal of Electrical Engineering & Computer Sciences, 24, 3, pp. 1532-1546 (2016).
(10) K. Sundareswaran, S. Razia Begum, Genetic Tuning of a Power System Stabilizer, European Transactions on Electrical Power, 14, 3, pp. 151–160 (2004).
(11) H. Labdelaoui, F. Boudjema, D. Boukhetala, Multiobjective optimal design of dual-input power system stabilizer using genetic algorithms, Rev. Roum. Sci. Techn.-Électrotechn. et Énerg., 62, 1, pp. 93–97, 2017.
(12) A. Boulayoune, C. Guerroudj, R. Saou, L. Moreau, M. Zaim, Optimisation par essaim de particule et algorithmegénétique d’une machine à inversion de flux, Rev. Roum. Sci. Techn.-Électrotechn.et Énerg., 62, 1, pp. 19–24, (2017).
(13) Z. Zhen-Yu, T. Masayoshi, I. Satoru, Fuzzy gain scheduling of PID controllers, IEEE Transactions on Systems, Man, and Cybernetics, 23, 5, pp. 1392–1398 (1993).
(14) M.M. Pedram, H. Seifi, F.M.G. Tomescu, Extended Algorithm of a Fuzzy-set Based Power-system Stabilizer with Genetic Algorithm Timing, European Transactions on Electrical Power, 7, 3, pp. 205–210 (1997).
