PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Application of artificial intelligent techniques in PSS design: a survey of the state-of-the-art methods

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
PL
Wykorzystanie technik sztucznej inteligencji przy projektowaniu systemów stabilizacji mocy systemu energetycznego
Języki publikacji
EN
Abstrakty
EN
Power system stabilizers (PSSs) are the most well known and efficient devices to damp the power system oscillations caused by interruptions. Low frequency oscillation problems are very difficult to solve because power systems are very large, complex and geographically distributed. Hence, it is necessary to employ most efficient optimization methods to take full advantages in simplifying the problem and its implementation. These optimization methodologies and techniques are widely diverse and have been the subject of ongoing enhancements over the years. This paper presents a survey of literature on the various optimization methods applied to solve the PSS problems.
PL
System stabilizacji mocy PSS jest powszechnie stosowaną i skuteczną metodą tłumienia oscylacji spowodowanych przerwaniami. Oscylacje niskiej częstotliwości są trudne do eliminacji ze względu na ich złożoność i rozległość przestrzenną. Dlatego warto poszukiwać skutecznych metod optymalizacji metody PSS. Artykuł przedstawia metody optymalizacji wykorzystujące sztuczną inteligencję.
Rocznik
Strony
188--197
Opis fizyczny
Bibliogr. 118 poz., rys.
Twórcy
autor
autor
autor
  • Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia, mahdiyeh_eslami@yahoo.com
Bibliografia
  • [1] Segal R., Sharma A., Kothari M., A self-tuning power system stabilizer based on artificial neural network. Int. J. Elect. Power Energy Syst, 26(2004) No. 6, 423-430.
  • [2] Talaat H.E.A., Abdennour A., Al-Sulaiman A.A., Design and experimental investigation of a decentralized GA-optimized neuro-fuzzy power system stabilizer. Int. J. Elect. Power Energy Syst, 32(2010) No. 7, 751-759.
  • [3] Kundur P., Klein M., Rogers G., Zywno M., Application of power system stabilizers for enhancement of overall system stability. IEEE Trans. Power Syst, 4 (2002) No. 2, 614-626.
  • [4] Cai L.Erlich I., Simultaneous coordinated tuning of PSS and FACTS damping controllers in large power systems. IEEE Trans. Power Syst., 20(2005) No. 1, 294-300.
  • [5] Abido M., A novel approach to conventional power system stabilizer design using tabu search. Int. J. Elect. Power Energy Syst, 21 (1999) No. 6, 443-454.
  • [6] Abido M. Thyristor Controlled Phase Shifter Based Stabilizer Design using Simulated Annealing Algorithm. in International Conference on Electric Power Engineering. 1999. Hungary
  • [7] Wang S., Chiou J., Liu C, Parameters tuning of power system stabilizers using improved ant direction hybrid differential evolution. Int. J. Elect. Power Energy Syst, 31 (2009) No. 1, 34-42.
  • [8] Wu D., Huang T., Yang G., Yang Y., Guo W., Lin Z., Wen F. Optimal parameter coordination of power system stabilizers in multi-machine power systems employing Harmony Search. In 8th International Conference on Advances in Power System Control, Operation and Management. 2010.
  • [9] Abido M., Abdel-Magid Y., Optimal design of power system stabilizers using evolutionary programming. IEEE Trans. Energy Convers., 17(2002) No. 4, 429-436.
  • [10] Mishra S., Tripathy M., Nanda J., Multi-machine power system stabilizer design by rule based bacteria foraging. Electr. Power Syst.Res., 77(2007) No. 12, 1595-1607.
  • [11] Abdel-Magid Y.L., Abido M.A., Optimal multiobjective design of robust power system stabilizers using genetic algorithms. IEEE Trans. Power Syst, 18(2003) No. 3, 1125-1132.
  • [12] Abido M., Optimal design of power-system stabilizers using particle swarm optimization. IEEE Trans. Energy Convers., 17 (2002) No. 3, 406-413.
  • [13] Eslami M., Shareef H., Mohamed A., Tuning of power system stabilizers using particle swarm optimization with passive congregation. International Journal of the Physical Sciences., 17(2010) No. 5, 2658-2663
  • [14] Eslami M., Shareef H., Mohamed A., Damping of Power System Oscillations Using Genetic Algorithm and Particle Swarm Optimization. International Review of Electrical Engineering, 6(2010) No.5, 2745-2753.
  • [15] McCarthy J. Programs with common sense. 1958: Proceedings of the Symposium of the National Physics Laboratory, Her Majesty's Stationery Office, London, UK
  • [16] Wasserman P., Meyer-Arendt J., Neural computing, theory and practice. Applied Optics, 29(1990) No. 2503.
  • [17] Pillutla S., Keyhani A., Power system stabilization based on modular neural network architecture. Int. J. Elect. Power Energy Syst, 19(1997) No. 6, 411-418.
  • [18] Hosseinzadeh N., Kalam A., A hierarchical neural network adaptive power system stabilizer. Int. J. Elect. Power Energy Syst, 19(1999) No. 1, 28-33.
  • [19] Shamsollahi P., Malik O., Design of a neural adaptive power system stabilizer using dynamie back-propagation method. Int. J. Elect. Power Energy Syst., 22(2000) No. 1, 29-34.
  • [20] Shamsollahi P., Malik O., An adaptive power system stabilizer using on-line trained neural networks. IEEE Trans. Energy Convers., 12(2002) No. 4, 382-387.
  • [21] Tsoukalas L., Uhrig R., Fuzzy and neural approaches in engineering. 1996: John Wiley & Sons, Inc. NY, USA.
  • [22] Abido M., Abdel-Magid Y., Adaptive tuning of power system stabilizers using radial basis funetion networks. Electr. Power Syst. Res., 49 (1999) No. 1, 21-29.
  • [23] Segal R., Kothari M., Madnani S., Radial basis function (RBF) network adaptive power system stabilizer. IEEE Trans. Power Syst, 15(2002) No. 2, 722-727.
  • [24] Senjyu T., Morishima Y., Yamashita T., Uezato K., Fujita H., Recurrent neural network supplementary stabilization controller for automatic voltage regulator and governor. Electr, Power Compon. Syst, 31 (2003) No. 7, 693-707.
  • [25] Chaturvedi D., Malik O., Generalized neuron-based PSS and adaptive PSS. Control Eng. Practice, 13(2005) No. 12, 1507- 1514.
  • [26] Chaturvedi D., Malik O., Generalized neuron-based adaptive PSS for multimachine environment. IEEE Trans. Power Syst, 20(2005) No. 1, 358-366.
  • [27] Chaturvedi D., Malik O., Experimental studies of a generalized neuron based adaptive power system stabilizer. Soft Comput, 11 (2007) No. 2, 149-155.
  • [28] Chaturvedi D., Malik O., Kalra P. Generalised neuron-based adaptive power system stabiliser. IEE Proceedings Generation, transmission and Distribution 2004.
  • [29] Chaturvedi D., Malik O., Neurofuzzy power system stabilizer. IEEE Trans. Energy Convers., 23 (2008) No. 3, 887-894.
  • [30] Barreiros J., Ferreira A., Tavares-da-Costa C., A neural power system stabilizer trained using local linear controllers in a gain-scheduling scheme. Int. J. Elect. Power Energy Syst., 27 (2005) No. 7, 473-479.
  • [31] Ping H., Kewen W., Chitong T., Xiaoyan B., Studies of the improvement of probabilistic PSSs by using the single neuron model. Int. J. Elect. Power Energy Syst, 29 (2007) No. 3, 217-221.
  • [32] Ray S.,Venayagamoorthy G., A wide area measurement based neurocontrol for generation excitation systems. Eng. Appl. Artif. Intell., 22(2009) No. 3, 473-481.
  • [33] Zadeh L, Fuzzy sets*. Information and control, 8 (1965) No. 3, 338-353.
  • [34] Pal S.,Mandal D., Fuzzy Logic and Approximate Reasoning: An Overview. J. Institution of Electronics and Telecommunication Engineers, (1991) No. 548-559.
  • [35] El-Hawary M., Electric power applications of fuzzy systems. 1998: Wiley-IEEE Press.
  • [36] El-Sherbiny M., Sharaf A., El-Saady G., Ibrahim E., A novel fuzzy state feedback controller for power system stabilization. Electr. Power Syst. Res., 39(1996) No. 1, 61-65.
  • [37] Lakshmi P., Abdullah Khan M., Design of a robust power system stabilizer using fuzzy logic for a multi-machine power system. Electr. Power Syst. Res., 47(1998) No. 1, 39-46.
  • [38] Mitra P., Chowdhury S., Chowdhury S., Pal S., Lahiri R., Song Y. Performance of A Fuzzy Power System Stabilizer With Tie Line Active Power Deviation Feedback. in IEEE Power Systems Conference and Exposition, 2007.
  • [39] Dash P., Liew A., Mishra B., An adaptive PID stabilizer for power systems using fuzzy logie. Electr. Power Syst. Res., 44 (1998) No. 3, 213-222.
  • [40] Kvasov D., Menniti D., Pinnarelli A., Sergeyev Y., Sorrentino N., Tuning fuzzy power-system stabilizers in multi-machine systems by global optimization algońthms based on efficient domain partitions. Electr. Power Syst. Res., 78(2008) No. 7, 1217-1229.
  • [41] Lu J., Nahrir M., Pierre D., A fuzzy logic-based adaptive power system stabilizer for multi-machine systems. Electr. Power Syst. Res., 60(2001) No. 2, 115-121.
  • [42] Abdelazim T., Malik O., Power system stabilizer based on model reference adaptive fuzzy control. Electr, Power Compon. Syst, 33(2005) No. 9, 985-998.
  • [43] Hossein-Zadeh N., Kalam A., An indirect adaptive fuzzy-logic power system stabiliser. Int. J. Elect. Power Energy Syst, 24 (2002) No. 10, 837-842
  • [44] Elshafei A., El-Metwally K., Shaltout A., A variable-structure adaptive fuzzy-logic stabilizer for single and multi-machine power systems. Control Eng. Practice, 13(2005) No. 4, 413-423.
  • [45] Lie T., Sharaf A., An adaptive fuzzy logie power system stabilizer. Electr. Power Syst. Res., 38(1996) No. 1, 75-81.
  • [46] Soliman M., Elshafei A., Bendary F., Mansour W., LMI static output-feedback design of fuzzy power system stabilizers. Expert Syst. Appl., 36(2009) No. 3, 6817-6825.
  • [47] Soliman M., Elshafei A., Bendary F., Mansour W., Robust decentralized PID-based power system stabilizer design using an ILMI approach. Electr. Power Syst. Res., 80 (2010) No. 12, 1488-1497.
  • [48] Kim S., Kwon S., Moon Y., Low-order robust power system stabilizer for single-machine systems: an LMI approach. Int. J. Elect. Power Energy Syst, 8(2010) No. 3, 556-563.
  • [49] Dou C., Jia Q., Jin S., Bo Z., Delay-independent decentralized stabilizer design for large interconnected power systems based on WAMS. Int. J. Elect. Power Energy Syst, 29 (2007) No. 10, 775-782.
  • [50] Dou C., Jia Q., Jin S., Bo Z., Robust controller design for large interconnected power systems with model uncertainties based on wide-area measurement. Electr. Eng., 90 (2008) No. 4, 265-273.
  • [51] Dou C., Zhang X., Guo S., Mao C., Delay-independent excitation control for uncertain large power systems using wide-area measurement signals. / Int. J. Elect. Power Energy Syst., 32(2010) No. 3, 210-217.
  • [52] Ramirez-Gonzalez M., Malik O., Self-tuned Power System Stabilizer Based on a Simple Fuzzy Logic Controller. Electr, Power Compon. Syst, 38(2010) No. 4, 407-423.
  • [53] Glover F.,Marti R., Tabu search. Metaheuristic Procedures for Training Neutral Networks, (2006) No. 53-69.
  • [54] Rayward V., Osman I., Reeves C, Smith G., Modern heuristic search methods. 1996: John Wiley & Sons, England.
  • [55] Abido M., Abdel-Magid Y., Eigenvalue assignments in multimachine power systems using tabu search algorithm. Comput Electr. Eng., 28(2002) No. 6, 527-545.
  • [56] Abido M., Abdel-Magid Y., Robust design of electrical power-based stabilizers using tabu search. 2001, IEEE, Power Engineering Society Summer Meeting: Vancouver, BC Canada p. 1573-1578.
  • [57] Abido M., Abdel-Magid Y., Robust design of multimachne power system stabilisers using tabu search algorithm, in Generation, Transmission and Distribution. 2000, IET. p. 387- 394.
  • [58] Abido M., Abdel-Magid Y., A tabu search based approach to power system stability enhancement via excitation and static phase shifter control. Electr. Power Syst. Res., 52 (1999) No. 2, 133-143.
  • [59] Ngamroo I., An optimization technique of robust load frequency stabilizer for superconducting magnetic energy storage. Enegy Conv. Manag., 46(2005) No. 18-19, 3060-3090.
  • [60] Kirkpatrick S., Optimization by simulated annealing: Quantitative studies. Journal of Stat. Phys., 34 (1984) No. 5, 975-986.
  • [61] Cerny V., Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm. J. optim. Theory appl., 45(1985) No. 1, 41-51.
  • [62] Abido M., An efficient heuhstic optimization technique for robust power system stabilizer design. Electr. Power Syst. Res., 58(2001) No. 2, 53-62.
  • [63] Abido M., Pole placement technique for PSS and TCSC-based stabilizer design using simulated annealing. Int. J. Elect. Power Energy Syst, 22(2000) No. 543-554.
  • [64] Abido M., Simulated annealing based approach to PSS and FACTS based stabilizer tuning. Int. J. Elect. Power Energy Syst, 22 (2000) No. 4, 247-258.
  • [65] Abido M., Robust design of multimachine power system stabilizers using simulated annealing. IEEE Trans. Energy Convers., 15(2002) No. 3, 297-304.
  • [66] Colorni A., Dorigo M., Maniezzo V. Distributed optimization by ant colonies. 1992.
  • [67] Dorigo M., Optimization, learning and natural algorithms. Unpublished doctoral dissertation, Politecnico di Milano, Dipartimento di Elettronica, Italy, (1992).
  • [68] Passino K., Biomimicry of bacterial foraging for distributed optimization and control. Control Systems Magazine, IEEE, 22 (2002) No. 3, 52-67.
  • [69] Ghoshal S.P., Chatterjee A., Mukherjee V., Bio-inspired fuzzy logic based tuning of power system stabilizer. Expert Syst. Appl., 36(2009) No. 5, 9281-9292.
  • [70] Goldberg D., Genetic algorithms in search, optimization, and machine learning. 1989: Addison-wesley.
  • [71] Do Bomfim A., Taranto G., Falcao D., Simultaneous tuning of power system damping controllers using genetic algorithms IEEE Trans. Power Syst, 15(2002) No. 1, 163-169.
  • [72] Hasanovic A., Feliachi A. Genetic algorithm based inter-area oscillation damping controller design using MATLAB. in IEEE Power Engineering Society Summer Meeting. 2007. IL, USA
  • [73] Sebaa K., Boudour M., Optimal locations and tuning of robust power system stabilizer using genetic algorithms. Electr. Power Syst. Res., 79(2009) No. 2, 406-416.
  • [74] Sebaa K., Gue guen H., Boudour M., Mixed integer non-linear programming via the cross-entropy approach for power system stabilisers location and tuning. Generation, Transmission & Distribution, IET, 4(2010) No. 8, 928-939.
  • [75] Hongesombut K., Dechanupaprittha S., Mitani Y., Ngamroo I., Robust power system stabilizer tuning based on multiobjective design using hierarchical and parallel micro genetic algorithm 2005: IEEE Int Conf Power Syst Technol, p. 402-407.
  • [76] Abdel-Magid Y., Dawoud M. Tuning of power system stabilizers using genetic algorithms. Electr. Power Syst. Res., 39(1996) No. 2, 137-143.
  • [77] Abido M., Abdel-Magid Y., A genetic-based power system stabilizer. Electr, Power Compon. Syst, 26 (1998) No. 6 559-571.
  • [78] Abido M.A., Parameter optimization of multimachine power system stabilizers using genetic local search. Int. J. Elect. Power Energy Syst, 23(2001) No. 8, 785-794.
  • [79] Abido M.A., Abdel-Magid Y.L., Coordinated design of a PSS and an SVC-based controller to enhance power system stability. Int. J. Elect. Power Energy Syst, 25 (2003) No. 9, 695-704.
  • [80] Abdel-Magid Y.L., Abido M.A., Robust coordinated design of excitation and TCSC-based stabilizers using genetic algorithms. Electr. Power Syst. Res., 69 (2004) No. 2-3, 129- 141.
  • [81] Panda S., Ardil C., Real-coded genetic algorithm for robust power system stabilizer design. International J. Electr. Comput. Syst. Eng., 2(2008) No. 1, 6-14.
  • [82] Panda S., Patidar N., Singh R., Simultaneous Tuning of Static Var Compensator and Power System Stabilizer Employing Real-Coded Genetic Algorithm. International J. Electr. Power Energy Syst. Eng, 1 (2008) No. 240-247.
  • [83] Kennedy J., Eberhart R. Particle swarm optimization. 1995: Perth, Australia.
  • [84] Shi Y., Eberhart R. A modified particle swarm optimizer. In IEEE World Congress on Computational Intelligence, 2002, pp. 69-73.
  • [85] El-Zonkoly A., Optimal tuning of power systems stabilizers and AVR gains using particle swarm optimization. Expert Syst. Appl., 31(2006) No. 3, 551-557.
  • [86] El-Zonkoly A., Khalil A., Ahmied N., Optimal tunning of lead-lag and fuzzy logie power system stabilizers using particle swarm optimization. Expert Syst. Appl., 36(2009) No. 2, 2097-2106.
  • [87] Shayeghi H., Shayanfar H., Safari A., Aghmasheh R., A robust PSSs design using PSO in a multi-machine environment. Energy Conv. Manag., 51 (2010) No. 4, 696-702.
  • [88] Shayeghi H., Safari A., Shayanfar H., Multimachine power system stabilizers design using PSO algorithm. Int. J. Electr. Power Energy Syst. Eng., 1(2008) No. 4, 226-233.
  • [89] Panda S.,Padhy N., Robust power system stabilizer design using particle swarm optimization technique. Int. J. Electr. Syst. Sci. Eng., 1 (2008) No. 1, 1-8.
  • [90] Shayeghi H., Shayanfar H., Jalilzadeh S., Safari A., Multimachine power system stabilizers design using chaotic optimization algorithm. Energy Conv. Manag., 51 (2010) No. 7, 1572-1580.
  • [91] Djukanovic M., Dobrijevic Milan S., Djorde M., Coordinated stabilizing control for the exciter and governor loops using fuzzy set theory and neural nets. Int. J. Elect. Power Energy Syst.s, 19(1997) No. 8, 489-499.
  • [92] Sharaf A., Lie T., A neuro-fuzzy hybrid power system stabilizer. Electr. Power Syst. Res., 30(1994) No. 1, 17-23.
  • [93] Abido M., Abdel-Magid Y., A fuzzy basis function network based power system stabilizer for generator excitation control. Electr. Power Syst. Res., 49(1999) No. 1, 11-19.
  • [94] Abido M., Abdel-Magid Y., A hybrid neuro-fuzzy power system stabilizer for multimachine power systems. IEEE Trans. Power Syst, 13(2002) No. 4, 1323-1330.
  • [95] Ramirez-Gonzalez M., Malik O., Power system stabilizer design using an online adaptive neurofuzzy controller with adaptive input link weights. IEEE Trans. Energy Convers., 23 (2008) No. 3, 914-922.
  • [96] Afzalian A., Linkens D., Training of neurofuzzy power system stabilisers using genetic algorithms. Int. J. Elect. Power Energy Syst, 22(2000) No. 2, 93-102.
  • [97] Awadallah M., Soliman H., A Neuro-fuzzy Adaptive Power System Stabilizer Using Genetic Algorithms. Electr, Power Compon. Syst, 37(2009) No. 2, 158-173.
  • [98] Fraile-Ardanuy J., Zufiria P., Design and comparison of adaptive power system stabilizers based on neural fuzzy networks and genetic algorithms. Neurocomputing, 70 (2007) No. 16-18, 2902-2912.
  • [99] Mahabuba A., Khan M., Small signal stability enhancement of a multi machine power system using robust and adaptive fuzzy neural network based power system stabilizer. Eur. Trans. Electr. Power, 19(2009) No. 7, 978-1001.
  • [100] Cheng Y., Elangovan S., Enhanced power system stabilizer via integrated tabu-fuzzy knowledge based controller. Int. J. Elect. Power Energy Syst, 25(2003) No. 7, 543-550.
  • [101] Malik O., Amalgamation of adaptive control and Al techniques: applications to generator excitation control. Annual Reviews in Control, 28(2004) No. 1, 97-106.
  • [102] Hwang G., Kim D., Lee J., An Y., Design of fuzzy power system stabilizer using adaptive evolutionary algorithm. Eng. Appl. Artifi. Intell., 21 (2008) No. 1, 86-96.
  • [103] Mukherjee V., Ghoshal S., Intelligent particle swarm optimized fuzzy PID controller for AVR system. Electr. Power Syst. Res., 77(2007) No. 12, 1689-1698.
  • [104] Caner M., Umurkan N., Tokat S., Ustun S., Determination of optimal hierarchical fuzzy controller parameters according to loading condition with ANN. Expert Syst. Appl., 34 (2008) No. 4, 2650-2655.
  • [105] Hussein T., Saad M., Elshafei A., Bahgat A., Damping inter- area modes of oscillation using an adaptive fuzzy power system stabilizer. Electr. Power Syst. Res., 80(2010) No. 12, 1428-1436.
  • [106] Hussein T., Saad M., Elshafei A., Bahgat A., Robust adaptive fuzzy logie power system stabilizer. Expert Syst. Appl., 36 (2009) No. 10, 12104-12112.
  • [107] Shayeghi H., Jalili A., Shayanfar H., Multi-stage fuzzy load frequency control using PSO. Energy Conv. Manag., 49 (2008) No. 10, 2570-2580.
  • [108] Zhang S., Luo F., An improved simple adaptive control applied to power system stabilizer. IEEE Trans. Power Electr., 24 (2009) No. 2, 369-375.
  • [109] Bhattacharya K., Kothari M., Nanda J., Aldeen M., Kalam A., Tuning of power system stabilizers in multi-machine systems using ise technique. Electr. Power Syst. Res., 46 (1998) No. 2, 119-131.
  • [110] Cai L., Erlich I., Robust power system stabilizer design using particle swarm optimization technique. IEEE Trans. Power Syst, 20(2005) No. 1, 294-300
  • [111] Abido M., Robust Design of Power System Stabilizers for Multimachine Power Systems Using Differential Evolution. Comput. Intell. Power Eng., 302(2010) No. 1-18.
  • [112] Yassami H., Darabi A., Rafiei S., Power system stabilizer design using Strength Pareto multi-objective optimization approach. Electr. Power Syst. Res., 80 (2010) No. 7, 838-846.
  • [113] Kashki M., Abdel-Magid Y., Abido M., Parameter optimization of multimachine power system conventional stabilizers using CDCARLA method. Int. J. Elect. Power Energy Syst., 32 (2010) No. 5, 498-506.
  • [114] Jiang Z., Design of a nonlinear power system stabilizer using synergetic control theory. Electr. Power Syst. Res., 79 (2009) No. 6, 855-862.
  • [115] Rigatos G., Siano P., Design of robust electric power system stabilizers using Kharitonov's theorem. Mathematics and Computers in Simulation, Article in Press (2010) No.
  • [116] Li T., Wu M., He Y., Lyapunov-Krasovskii functional based power system stability analysis in environment of WAMS. J. Cent. South Univ. Technol., 17(2010) No. 4, 801-806.
  • [117] de Oliveira R., Ramos R., Bretas N., An algorithm for computerized automatic tuning of power system stabilizers. Control Eng. Practice, 18(2010) No. 1, 45-54.
  • [118] Simoes Costa A., Freitas F., Pena H., Power system stabilizer design via structurally constrained optimal control. Electr. Power Syst. Res., 33(1995) No. 1, 33-40.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPS1-0044-0086
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.