Skip to main content

Reactive Power Optimization Using Firefly Algorithm

  • Conference paper
  • First Online:
Power Electronics and Renewable Energy Systems

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 326))

Abstract

This paper presents a Firefly algorithm to minimize the real power losses and to improve the voltage profile. This problem is a nonlinear combinatorial optimization with constraints. Newton-Raphson method of power flow is used in conjunction with Firefly algorithm to obtain the optimal values of the control variables. The control variables for this problem are the Generator bus voltages, Transformer Tap positions and the MVAR at the capacitor Banks. The performance of the proposed algorithm has been demonstrated with the IEEE 30-bus system. The algorithm used in this problem is compared to another nature-inspired metaheuristic algorithm (PSO). The simulated result shows improved results both in terms of convergence time and reduction of real power loss.

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 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover 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. Venkatesh B, Sadasivam G, Abdullah M (1999) Khan fuzzy logic based successive L.P. method for reactive power optimization. Electr Mach Power Syst 27:1141–1160

    Article  Google Scholar 

  2. Sayed MAH El, Abdel-Rahman TM, Mansour MO Fast quadratic programming approach for large scale reactive power optimization

    Google Scholar 

  3. Iha K (1994) Reactive power optimization by genetic algorithm. IEEE Trans Power Syst 9(2), Mitsubishi Electric Corp., Kobe, Japan

    Google Scholar 

  4. Bhagwan Das D, Patvardhan C (2002) Reactive power dispatch with a hybrid stochastic search technique. Electrl Power Energy Syst 24:731–736

    Article  Google Scholar 

  5. Lenin K, Mohan MR (2006) Ant colony search algorithm for optimal reactive power optimization Serbian. J Electr Eng 3(1):77–88

    Google Scholar 

  6. Shunmugalatha A, Raja Slochanal SMR (2008) Application of hybrid multiagent-based particle Swarm optimization to optimal reactive power dispatch. Electr Power Compon Syst 36:788–800

    Article  Google Scholar 

  7. Bhattacharya B, Goswami SK (2007) Reactive power optimization through evolutionary techniques: a comparative study of the GA, DE and PSO algorithms. Intell Autom Soft Comput 13(4):453–461

    Article  Google Scholar 

  8. Varadarajan M, Swarup KS (2008) Differential evolution approach for optimal reactive power dispatch. Appl Soft Comput 8:1549–1561

    Article  Google Scholar 

  9. Bhattacharya A, Chattopadhyay PK (2010) Solution of optimal reactive power flow using biogeography-based optimization. Int J Electr Electron Eng 4:8

    Google Scholar 

  10. Khazali AH, Kalantar M (2011) Optimal reactive power dispatch based on harmony search algorithm. Electr Power Energy Syst 33:684–692

    Article  Google Scholar 

  11. Mandal B, Roy PK (2013) Optimal reactive power dispatch using quasi-oppositional teaching learning based optimization. Electr Power Energy Syst 53:123–134

    Article  Google Scholar 

  12. Yang X-S Firefly algorithms for multimodal optimization

    Google Scholar 

  13. Yang X-S Nature inspired meta-heuristic algorithms. Luniver press

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to G. Kannan .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer India

About this paper

Cite this paper

Kannan, G., Padma Subramanian, D., Udaya Shankar, R.T. (2015). Reactive Power Optimization Using Firefly Algorithm. In: Kamalakannan, C., Suresh, L., Dash, S., Panigrahi, B. (eds) Power Electronics and Renewable Energy Systems. Lecture Notes in Electrical Engineering, vol 326. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2119-7_9

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-2119-7_9

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2118-0

  • Online ISBN: 978-81-322-2119-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics