Abstract
This paper proposes an approach to determine the optimal location of static var compensators (SVCs) in electric power systems in order to improve voltage profile and minimize active power losses. A multi-scenario framework that includes different load levels with different time periods is considered in this approach. The problem is formulated as a mixed-integer nonlinear programming problem using an optimal power flow (OPF). The SVC value and location are modeled as a variable susceptance inside the bus admittance matrix and as a binary decision variable, respectively. The problem is solved using the branch and bound algorithm associated with the OPF. Studies and simulations were conducted on the IEEE 118-bus test system considering variations in both the objective function and the amount of SVCs to be allocated. Analysis of results demonstrate that the performance of the power system can be effectively enhanced due to the optimal allocation of SVC equipment if considering different load levels with different time periods for the allocation of SVCs, rather than allocate the SVCs separately.
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References
Ambriz-Perez, H., Acha, E., & Fuerte-Esquivel, C. R. (2000). Advanced SVC models for Newton–Raphson load flow and Newton optimal power flow studies. IEEE Transactions on Power Systems, 15(1), 129–136.
Berrouk, F., & Bounaya, K. (2018). Optimal power flow for multi-FACTS power system using hybrid PSO–PS algorithms. Journal of Control, Automation and Electrical Systems, 29, 177–191. https://doi.org/10.1007/s40313-017-0362-7.
Byrd, R. H., Nocedal, J., & Waltz, R. A. (2006). Knitro: An integrated package for nonlinear optimization. In G. Di Pillo & M. Roma (Eds.), Large-scale nonlinear optimization. Nonconvex optimization and its applications (Vol. 83). Boston: Springer.
Chang, Y. S. (2012). Multi-objective optimal SVC installation for power system loading margin improvement. IEEE Transactions on Power Systems, 27(2), 984–992.
Dommel, H. W., & Tinney, W. F. (1968). Optimal power flow solutions. IEEE Transactions on Power Apparatus and Systems, PAS–87(10), 1866–1876.
Duan, C., Fang, W., Jiang, L., & Niu, S. (2016). FACTS devices allocation via sparse optimization. IEEE Transactions on Power Systems, 31(2), 1308–1319.
Eghbal, M., Yorino, N., Zoka, Y., & El-Araby, E. E. (2008). Application and comparison of metaheuristic techniques to reactive power planning problem. IEEJ Transactions on Electrical and Electronic Engineering, 3, 721–730.
Fourer, R., Gay, D. M., & Kernighan, B. W. (2003). AMPL: A modeling language for mathematical programming. Pacific Grove: Brooks/Cole-Thomson Learning.
Gerbex, S., Cherkaoui, R., & Germond, A. J. (2001). Optimal location of multi-type FACTS devices in a power system by means of genetic algorithms. IEEE Transactions on Power Systems, 13(3), 537–544.
Granville, S. (1994). Optimal reactive dispatch through interior point methods. IEEE Transactions on Power Systems, 9(1), 136–146.
Group ISSCW. (1994). Static VAr compensator models for power flow and dynamic performance simulation. IEEE Transactions on Power Systems, 9(1), 229–240.
Hingorani, N. G., & Gyugyi, L. (2000). Understanding FACTS: Concepts and technology of flexible AC transmission systems. New York: IEEE Press.
Hoji, E. S., Padilha-Feltrin, A., & Contreras, J. (2012). Reactive control for transmission overload relief based on sensitivity analysis and cooperative game theory. IEEE Transactions on Power Systems, 27(3), 1192–1203.
Kannan, S., Slochanal, S. M. R., & Padhy, N. P. (2005). Application and comparison of metaheuristic techniques to generation expansion planning problem. IEEE Transactions on Power Systems, 20(1), 466–475.
Khator, S. K., & Leung, L. C. (1997). Power distribution planning: A review of model and issues. IEEE Transactions on Power Systems, 12(3), 1151–1159.
Maza-Ortega, J. M., Acha, E., García, S., & Gómez-Expósito, A. (2017). Overview of power electronics technology and applications in power generation transmission and distribution. Journal of Modern Power Systems and Clean Energy, 5(4), 499–514. https://doi.org/10.1007/s40565-017-0308-x.
Mínguez, R., Milano, F., Zárate-Miñano, R., & Conejo, A. J. (2007). Optimal network placement of SVC devices. IEEE Transactions on Power Systems, 22(4), 1851–1860.
Phan, D. T. (2012). Lagrangian duality and branch-and-bound algorithms for optimal power flow. Operations Research, 60, 275–285.
Rajarman, R., Alvarado, F., Maniaci, A., Camfield, R., & Jalali, S. (1998). Determination of location and amount of series compensation to increase power transfer capability. IEEE Transactions on Power Systems, 13(2), 294–300.
Sun, D. I., Ashley, B., Brewer, B., Hughes, A., & Tinney, W. F. (1984). Optimal power flow by Newton approach. IEEE Transactions on Power Apparatus and Systems, PAS–103(10), 2864–2880.
Wibowo, R. S., Yorino, N., Eghbal, M., Zoka, Y., & Sasaki, Y. (2011). FACTS devices allocation with control coordination considering congestion relief and voltage stability. IEEE Transactions on Power Systems, 26(4), 2302–2310.
Acknowledgements
The authors acknowledge financial support from FAPESP under Grant 2014/14361-8, CNPq under Grant 306243/2014-8 and FAPERJ under Grants E-26/202886/2017, E-26/101953/2012 and E-26/110400/2014.
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Belati, E.A., Nascimento, C.F., de Faria, H. et al. Allocation of Static Var Compensator in Electric Power Systems Considering Different Load Levels. J Control Autom Electr Syst 30, 1–8 (2019). https://doi.org/10.1007/s40313-018-00421-2
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DOI: https://doi.org/10.1007/s40313-018-00421-2