Skip to main content

Comparison of GSA and PSO-Based Optimization Techniques for the Optimal Placement of Series and Shunt FACTS Devices in a Power System

  • Conference paper
  • First Online:
Artificial Intelligence and Evolutionary Computations in Engineering Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 517))

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 299.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 379.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. 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).

    Google Scholar 

  2. Basu, M.: Optimal power flow with FACTS devices using differential evolution. Electrical Power and Energy Systems 30, 150–156 (2008).

    Google Scholar 

  3. 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).

    Google Scholar 

  4. 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).

    Google Scholar 

  5. 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).

    Google Scholar 

  6. 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).

    Google Scholar 

  7. 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).

    Google Scholar 

  8. Rashedi, E., Nezamabadi-pour, H., Saryazdi, S.: GSA: a gravitational search algorithm. Inf. Sc. 179(13), 2232–2248 (2009).

    Google Scholar 

  9. 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).

    Google Scholar 

  10. 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).

    Google Scholar 

  11. 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).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rajat Kumar Singh .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Nature Singapore Pte Ltd.

About this paper

Cite this paper

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

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-3174-8_33

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3173-1

  • Online ISBN: 978-981-10-3174-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics