Abstract
This paper presents the application of gravitational search algorithm (GSA) and particle swarm optimization (PSO)-based approach along with multiple FACTS (flexible AC transmission system) devices for the economic operation of an interconnected power system under different loading condition. Two different types of FACTS devices such as static Var compensator (SVC) and thyristor-controlled series capacitor (TCSC) are used in this paper. The location of the FACTS devices is obtained by the reactive power flow in the transmission lines. The reactive loading of the system have been increased from the base value to 110 and 120% of base reactive loading. Finally, results have been compared between both the techniques in terms of minimization of active power loss and operating cost.
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References
Hingorani, N.G., Gyugyi, L.: Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems. The institute of Electrical and Electronics Engineers, New York (2000).
Basu, M.: Optimal power flow with FACTS devices using differential evolution. Electrical Power and Energy Systems 30, 150–156 (2008).
Chung, T.S., Ge, S.: Optimal power flow incorporating FACTS devices and power flow control constraints. In: IEEE Conference, vol. 98, pp. 415–419 (1998).
Acha E., Ambriz-Perez H., Fuerte-Esquivel, C.R.: Advanced SVC Models for Newton-Raphson Load Flow and Newton Optimal Power Flow Studies. IEEE Transactions on Power Systems, 15(1), 129–136 (2000).
Bhattacharyya, B., Goswami, S.K., Bansal, R.C.: Loss Sensitivity Approach in Evolutionary Algorithms for Reactive Power Planning. Electric Power Components and Systems 37(3), 287–299 (2009).
Bhattacharyya, B., Goswami, S.K., Gupta, V.K.: Particle swarm intelligence based allocation of FACTS controller for the increased load ability of power system. Int. J. Electr. Eng. Inform 4(4) (2012).
Fukuyama, Y., Tahyama, S., Yoshida, H., Kawata, K., Nahnishi, Y.: A particle swarm optimization for reactive power and voltage control considering voltage security assessment. IEEE IRons. on Power Systems, 1232–1239 (2000).
Rashedi, E., Nezamabadi-pour, H., Saryazdi, S.: GSA: a gravitational search algorithm. Inf. Sc. 179(13), 2232–2248 (2009).
Ippolito, L., Cortiglia, A.L., Petrocelli, M.: Optimal allocation of FACTS devices by using multi-objective optimal power flow and genetic algorithms. Int. J. Emerg. Elect. Power Syst. 7(2) (2006).
Mirjalili, S., MohdHashim, S.Z.: A new Hybrid PSOGSA Algorithm for Function Optimization. In: IEEE International Conference on Computer and Information and Application (ICCIA), 374–377 (2010).
Bhattacharyya, B., Kumar, S., Gupta, V.K.: Enhancement of Power System Loadability with FACTS Devices. Journal of The Institution of Engineers (India): Series B 95(2), 113–120 (2014).
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Singh, R.K., Gupta, V.K. (2017). Comparison of GSA and PSO-Based Optimization Techniques for the Optimal Placement of Series and Shunt FACTS Devices in a Power System. In: Dash, S., Vijayakumar, K., Panigrahi, B., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-10-3174-8_33
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DOI: https://doi.org/10.1007/978-981-10-3174-8_33
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