FACTS location and size for reactive power system compensation through the multi-objective optimization

• Autorzy: Belazzoug M. , Boudour M. , Sebaa K.
• Języki publikacji: EN

Abstrakty

EN

The problem of the FACTS (Flexible Alternative Current Transmission System Devices) location and size for reactive power system compensation through the multi-objective optimization is presented in this paper. A new technique is proposed for the optimal setting, dimension and design of two kinds of FACTS namely: Static Volt Ampere reactive (VAR) Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC) handling the minimization of transmission losses in electrical network. Using the proposed scheme, the type, the location and the rating of FACTS devices are optimized simultaneously. The problem to solve is multi criteria under constraints related to the load flow equations, the voltages, the transformer turn ratios, the active and reactive productions and the compensation devices. Its solution requires the the advanced algorithms to be applied. Thus, we propose an approach based on the evolutionary algorithms (EA) to solve multi-criterion problem. It is similar to the NSGA-II method (Ellitist Non Dominated Sorting Genetic Algorithm). The Pareto front is obtained for continuous, discrete and multiple of five MVArs (Mega Volt Ampere reactive) of compensator devices for the IEEE 57-bus test system (IEEE bus test is a standard network).

Słowa kluczowe

EN

reactive dispatch; multi-objective optimization; NSGA-II; SVC; TCSC; FACTS

• Wydawca: Polish Academy of Sciences, Committee of Automatic Control and Robotics
• Czasopismo: Archives of Control Sciences
• Rocznik: 2010
• Tom: Vol. 20, no. 4
• Strony: 473--489
• Opis fizyczny: Bibliogr. 19 poz., rys., wzory

Twórcy

autor

Belazzoug M.

autor

Boudour M.

autor

Sebaa K.

• Department of Electronic L. A. B. S. E.T., University of Saad Dahleb Road of Soumaa - Blida (Algeria),

Bibliografia

• [1] IEEE/CIGRE’ (Institute of Electrical and Electronic Engineers / Conseil International des Grands Réseaux Électriques) FACTS overview. Special issue, TP108, IEEE Service Center, Oiscataway, NJ, 1995.
• [2] N. G. HINGORANI and L. GYUGYI: Understanding FACTS, Concepts and technology of flexible AC transmission systems. IEEE Press, 2000.
• [3] Y. B. SONG and A.T. JOHNS: Applications of fuzzy logic in power systems. III. Example applications. Power Engineering J., 13(2), (1999), 97-103.
• [4] K. DEB: Evolutionary algorithms for multi-criterion optimization in engineering design. Evolutionary Algorithms in Engineering and Computer Science, Charter 8, 1999, 135-161.
• [5] C. FONSECA: Multiobjective genetic algorithms with application to control engineering problems. PhD Thesis, Department of Automatic Control and Systems Engineering, The University of Sheffild, September, 1995.
• [6] J. HORN, N. NAFPLIOTIS and D.E. GOLDBERG: A niched Pareto genetic algorithm for multi-objectives optimization. Proc. of the First IEEE Conf. on Evolutionary Computation, IEEE World Congress on Computational Intelligence, 1 (1994), 82-87.
• [7] M. A. ABIDO: A niched Pareto genetic algorithm for multi objectives environmental / economic dispatch. Electrical Power and Energy Systems, (2003), 97-105.
• [8] H. ALEXANDRE, F. DIAS and J. A. DE VASCONCELOS: Multiobjective genetic algorithms applied to solve optimization problems. IEEE Trans. Magnetics, 38(2), (2002), 1133-1136.
• [9] E. ZITZLER and L. THIELE: An evolutionary algorithm for multi-objectives optimization: The strength Pareto approach. TIK-Report no. 43, 1998.
• [10] E. ZITZLER, M. LAUMANNS and L. THIELE: SPEA2: Improving the strength Pareto evolutionary algorithm. TIK-Report no. 103, 2001.
• [11] W. YAN, S. LU and D.C. YU: A novel optimal reactive power dispatch metod based on an improved hybrid evolutionary programming technique. IEEE Trans. Power Systems, 19(2), (2004).
• [12] T. BOUKTIR and L. SLIMANI: Optimal power flow of the algerian electrical network using an ant colony optimization method. Leonardo J. of Sciences, 6 (2005), 43-57.
• [13] M. O. MANSOUR and T.M. ABDEL-RAHMAN: Non-linear VAR optimization using decomposition and coordination. IEEE Trans. Power Apparat. Systems, 103(2), (1984), 246-255.
• [14] I. P. ABRIL and J. A. GONZÁLEZ: VAR compensation by sequential quadratic programming. IEEE Trans. Power Systems, 18(1), (2003), 36-41.
• [15] Y. T. HSIAO, H. D. CHIANG, C.C. LIU and Y.L. CHEN: A vomputer package for optimal multi-objective VAR planning in large scale power systems. IEEE Trans. Power Systems, 9(2), (1994), 668-676.
• [16] J. T. MA, and L. L. LAI: Evolutionary programming approach to reactive power planning. IEE Proc. - Gener. Transm. Distrib., 143(4), (1996), 365-370.
• [17] A. FARAG, S. AL-BAIYAT and T.C. CHENG: Economic load dispatch multiobjectives optimization procedures using linear programming techniques. IDEE Trans. Power Systems, 10(2), (1995), 731-738.
• [18] M. BELAZZOUG, M. BOUDOUR and A. HELLAL: New reactive power sources dispatch applied to the IEEE 57 nodes. The Int. J. for Computation and Mathematics in Electrical and Electronic Engineering, 27(5), (2008), 1192-1211.
• [19] E. ACHA and C. FUERTE ESQUIVEL: FACTS, modelling and simulation in power network. John Wiley & Sons Ltd., England, 2004.