6th International Young Scientist Congress (IYSC-2020) and Workshop on Intellectual Property Rights. 10th International Science Congress (ISC-2020).  International E-publication: Publish Projects, Dissertation, Theses, Books, Souvenir, Conference Proceeding with ISBN.  International E-Bulletin: Information/News regarding: Academics and Research

Economic Dispatch Incorporating Wind Power Plant Using Modified Particle Swarm Optimization

Author Affiliations

  • 1Computer Engineering Department, Iran University of Science and Technology, Tehran, IRAN
  • 2 ECE Department, College of Engineering, University of Tehran, Tehran, IRAN

Res. J. Recent Sci., Volume 2, Issue (6), Pages 108-112, June,2 (2013)


This paper presents a new approach for Economic Dispatch (ED) problems incorporating wind power plant using Modified Particle Swarm Optimization (MPSO) method. As Wind Power Plant increases in power systems, its effects to conventional units should be analyzed. Also the total cost is dependent on wind speed in specific period of time. Therefore, the mathematical techniques are not appropriate to find the global optimum ED. In this paper, MPSO is proposed to deal with wind power plants in ED. To show efficiency of wind power plant in reducing total cost, different simulation scenarios with and without wind power production are simulated


  1. Yue C.D., Liu C.M. and Liou Eric M.L., A transition toward a sustainable energy future feasibility assessment and development strategies of wind power inTaiwan, Energy Policy, 29, 951–963 (2001)
  2. Hetzer J., Yu C., and Bhattarai K., An economic dispatch model incorporating wind power, IEEE Trans. Energy Convers, 23(2), 603–611 (2008)
  3. Seguro J.V. and Lambert T.W., Modern estimation of the parameters of the Weibull wind speed distribution for wind energy analysis, J. Wind Eng. Ind. Aerodyn., 85(1), 75–84 (2000)
  4. Kennedy J. and Eberhart R., Particle swarm optimization, Proceeding of IEEE Int. Conf. Neural Networks (ICNN’95), Perth, Australia, 1942–1948 (1995)
  5. Park J.B., Lee K.S., Shin J.R. and Lee K.Y, A particle swarm optimization for economic dispatch with nonsmooth cost functions, Power Systems, IEEETrans., 20(1), 34-42 (2005)
  6. Sinha N., Chakrabarti R., and Chattopadhyay P.K., Evolutionary programming techniques for economic load dispatch, IEEE Trans. Evol. Comput, 7(1), 83–94 (2003)
  7. Carta J.A., Ramirez P. and Velázquez S., A review of wind speed probability distributions used in wind energy analysis: Case studies in the canary islands, Renewable Sustainable Energy Rev., 13(5), 933–955 (2009)
  8. Leon-Garcia A., Probability, Statistics, and Random Processes for Electrical Engineering, 3rd Ed., Prentice Hall, (2008)
  9. Victoire T. and Jeyakumar V., A modified hybrid EP–SQP approach for dynamic dispatch with valve-point effect, Electr Power Energy Syst, 27, 594–601 (2005)
  10. Renewable Energy Organization of Iran, Available Online: http://www.suna.org.ir/home-en.html, (2011)