Skip to main content

Krill Herd Algorithm for Solution of Economic Dispatch with Valve-Point Loading Effect

  • Conference paper
  • First Online:
Applications of Computing, Automation and Wireless Systems in Electrical Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 553))

Abstract

The article presents a novel bio-inspired Krill Herd (KH) algorithm to solve economic dispatch problems. KH algorithm is based on crowding behavior of the krill individuals and achieves a near global optimum solution by using three main actives. The proposed algorithm is tested by considering three and six generating unit systems on different loads on objective function. The attained results have proved that the KH algorithm provides remarkable results as compared with the other optimization algorithms reported in the literature.

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 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
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. Reid GF, Hasdorff L (1973) Economic dispatch using quadratic programming. IEEE Trans Power Syst 92:2015–2023

    Article  Google Scholar 

  2. El-Keib J, Ma H, Hart JL (1994) Environmentally constrained economic dispatch using the Lagrangian relaxation method. IEEE Trans Power Syst 30(4):1723–1729

    Article  Google Scholar 

  3. Chen CL, Wang S (1993) Branch-and-bound scheduling for thermal generating units. IEEE Trans Energy Convers 8(2):184–189

    Article  Google Scholar 

  4. Fanshel S, Lynes ES (1964) Economic power generation using linear programming. IEEE Trans Power Apparatus Syst 83(4):347–356

    Article  Google Scholar 

  5. Wood J, Wollenberg BF (1984) Power generation, operation, and control, 2nd edn. Wiley

    Google Scholar 

  6. Walters DE, Sheble GB (1993) Genetic algorithm solution of economic dispatch with valve point loading. IEEE Trans Power Syst 8(3):1352–1332

    Article  Google Scholar 

  7. Jong Bae P, Song LK, Rin SJ, Lee KY (2005) A particle swarm optimization for economic dispatch with non-smooth cost functions. IEEE Trans Power Syst 20(1):34–42

    Article  Google Scholar 

  8. Pothiya S, Ngamroo S, Kongprawechnon W (2008) Application of multiple tabu search algorithm to solve dynamic economic dispatch considering generator constraints. Energy Convers Manage 49(4):506–516

    Article  Google Scholar 

  9. Coelho LDC, Mariani VC (2006) Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve point effect. IEEE Trans Power Syst 21(3):989–996

    Google Scholar 

  10. Nidul S, Chakrabarti R, Chattopadhyay PK (2003) Evolutionary programming techniques for economic load dispatch. IEEE Trans Evol Comput 7(1):83–94

    Article  Google Scholar 

  11. Pereira-Neto A, Unsihuay C, Saavedra OR (2005) Efficient evolutionary strategy optimization procedure to solve the nonconvex economic dispatch problem with generator constraints. IET Gener Transm Distrib 152(5):653–660

    Article  Google Scholar 

  12. Abro AG, Mohamad-Saleh J (2013) Enhanced probability-selection artificial bee colony algorithm for economic load dispatch: a comprehensive analysis. Eng Optim 46(10):1315–1330

    Article  Google Scholar 

  13. Coelho LDS, Mariani VC (2009) An improved harmony search algorithm for power economic load dispatch. Energy Convers Manage 50(10):2522–2526

    Article  Google Scholar 

  14. Yang XS, Hosseinib SSS, Gandomic AH (2012) Firefly algorithm for solving non-convex economic dispatch problems with valve loading effect. Appl Soft Comput 12(3):1180–1186

    Article  Google Scholar 

  15. Naveen P, Chandel AK, Vedik B, Topwal T (2016) Economic dispatch with valve point effect using symbiotic organisms search algorithm. In: Proceedings of international conference on energy efficient technologies for sustainability (ICEETS), pp 430–435

    Google Scholar 

  16. Gandomi AH, Alavi AH (2012) Krill herd: a new bio-inspired optimization algorithm. Commun Nonlinear Sci Numer Simul 17(12):4831–4845

    Article  MathSciNet  Google Scholar 

  17. Pulluri H, Naresh R, Sharma V (2017) Application of stud krill herd algorithm for solution of optimal power problems. Int Trans Electr Energy Syst 27(6). https://doi.org/10.1002/etep.2316

    Article  Google Scholar 

  18. Pulluri H, Naresh R, Sharma V (2017) A solution network based on stud krill herd algorithm for optimal power flow problems. Soft Comput 22(1). https://doi.org/10.1007/s00500-016-2319-3

    Article  Google Scholar 

  19. Gai-Ge W, Amir HG, Amir HA, Guo-Sheng H (2014) Hybrid krill herd algorithm with differential evolution for global numerical optimization. Neural Comput Appl 25:297–308

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Preeti .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Pulluri, H., Goutham Kumar, N., Mohan Rao, U., Preeti, Kumar, M.G. (2019). Krill Herd Algorithm for Solution of Economic Dispatch with Valve-Point Loading Effect. In: Mishra, S., Sood, Y., Tomar, A. (eds) Applications of Computing, Automation and Wireless Systems in Electrical Engineering. Lecture Notes in Electrical Engineering, vol 553. Springer, Singapore. https://doi.org/10.1007/978-981-13-6772-4_33

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-6772-4_33

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6771-7

  • Online ISBN: 978-981-13-6772-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics