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Języki publikacji
Abstrakty
The static synchronous compensator (STATCOM) is the multipurpose FACTS device with the multiple input and multiple output system for the enhancement of its dynamic performance in power system. Based on artificial intelligence (AI) optimization technique, a novel controller is proposed for CSC based STATCOM. In this paper, the CSC based STATCOM is controlled by the LQR. But the best constant values for LQR controller's parameters are obtained laboriously through trial and error method, although time consuming. So the goal of this paper is to investigate the ability of AI techniques such as genetic algorithm (GA) and particle swarm optimization (PSO) methods to search the best values of LQR controller's parameters in a very short time with the desired criterion for the test system. Performances of the GA, PSO & ABC based LQR controllers are also compared. Applicability of the proposed scheme is demonstrated through simulation in MATLAB and the simulation results are shown an improvement in the input-output response of CSC-STATCOM.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
469--487
Opis fizyczny
Bibliogr. 22 poz., rys., tab., wz.
Twórcy
autor
- Department of Electrical Engineering Motilal Nehru N. I. T. Allahabad - 211004, India
autor
- Department of Electrical Engineering Motilal Nehru N. I. T. Allahabad - 211004, India
Bibliografia
- [1] Ulas Eminoglu, M. Hakan Hocaoglu, Tankut Yalcinoz, Transmission line shunt and series compensation with voltage sensitive loads. International Journal of Electrical Engineering Education 46(4): 354-369 (2009).
- [2] Ghosh A., Ledwich G.F., Power Quality Enhancement using Custom Power Devices. Kluwer Academic Publishers, Boston, USA (2002).
- [3] Moran L., Ziogas P., Joos G., Analysis and design of a three-phase synchronous solid-state Var compensator. IEEE Transactions Industry Application 25: 598-608 (1989).
- [4] Schauder M., Gernhardt, Stacey E., Operation of " 100MVAR TVA STATCON. IEEE Transactions Power Delivery 12: 1805-1811 (1997).
- [5] Hingorani N.G., Gyugyi L., Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems. IEEE Press, Piscataway, NJ, USA, pp. 132-133 (2000).
- [6] Gyugyi L., Application Characteristics of Converter-Based FACTS Controllers. Proceedings of International Conference on Power System Technology, Piscataway, NJ, USA 1: 391-396 (2000).
- [6] Han B., Moon S., Static synchronous compensator using thyristor PWM current source inverter. IEEE Transactions Power Delivery 15: 1285 (2000).
- [7] Gupta S., Tripathi R.K. (2010) Voltage Stability Improvement in Power Systems using FACTs Controllers: State-of-the-Art Review. IEEE International Conference on Power, Control and Embedded Systems (ICPCES), pp.1-8 (2010).
- [8] Shen D., Lehn P.W., Modeling, analysis, and control of a current source inverter-based STATCOM. IEEE Transactions Power Delivery 17: 248 (2002).
- [9] Kazearni M., Ye Y., Comparative evaluation of three-phase PWM voltage - and current-source converter topologies in FACTS applications. Proc. IEEE Power Eng. Soc. Summer Meeting 1: 473 (2002).
- [10] Bilgin H.F., Ermis M., Current source converter based STATCOM: Operating principles, design and field performance. Electric Power Systems Research 81(2): 478-487 (2011).
- [11] Wang H., Li F., Multivariable sampled regulators for the coordinated control of STATCOM ac and dc voltage. IEE Proceedings Generation, Transmission and Distribution 2(147): 93-/98 (2000).
- [12] Ali N., Amin V., An LQR/Pole Placement Controller Design for STATCOM. in Proc. Conf. Rec. IEEE CCC, pp.189-193 (2007).
- [13] Rao P., Crow M.L., Yang Z.P., STATCOM control for power system voltage control applications. IEEE Transactions Power Delivery 15(4): 1311-1317 (2000).
- [14] Warwick K., Ekwue A., Aggarwal R., Artificial Intelligence Techniques in Power Systems. Institution of Electrical Engineers, London (1997).
- [15] Shaheen H.I., Rashed G.I., Cheng S.J., Application and comparison of computational intelligence techniques for optimal location and parameter setting of UPFC. Engineering Applications of Artificial Intelligence 23: 203-216 (2010).
- [16] R. C. Eberhart and Y. H. Shi, Comparison between genetic algorithms and particle swarm optimization. Evolutionary Programming VII Lecture Notes in Computer Science (Springer), Volume 1447, pp 611-616, (1998).
- [17] Al-Saedi W., Lachowicz S.W., Habibi D., Bass O., Power flow control in grid-connected microgrid operation using particle swarm optimization under variable load conditions. International Journal of Electrical Power & Energy Systems 49(1): 76-85 (2013).
- [18] Katsuhiko Ogata, Modern Control Engineering. 5th Edition, Prentice Hall (2010).
- [19] Haupt R.L., Haupt S.E., Practical Genetic Algorithms. New York: Wiley (2004).
- [20] Shi Y.H., Eberhart R.C., A Modified Particle Swarm Optimizer. Proceeding of IEEE International Conference on Evolutionary Computation (ICEC'98), Anchorage, pp. 69-73 (1998).
- [21] Fajar Galih Indarko, Muhammad Abdillah et. al., Improvement of Dynamic Stability in Single Machine Infinite Bus (SMIB) using Linear Quadratic Regulator (LQR) based Artificial Bee Colony (ABC) Algorithm. Seminar on Applied Technology, Science, and ARTS 1st APTECS, 2009.
- [22] Haiquan Wang, Lei Liao, Dongyun Wang at al., Improved Artificial Bee Colony Algorithm and Its Application in LQR Controller Optimization. Hindawi Journal Mathematical Problems in Engineering 2014: 8 (2014).
Typ dokumentu
Bibliografia
Identyfikator YADDA
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