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Firefly Algorithm for Economic Power Dispatching With Pollutants Emission

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  • Latifa DEKHICI
  • Khaled BELKADI
  • Pierre BORNE

Abstract

Bio-inspired algorithms become among the most powerful algorithms for optimization. In this paper, we intend to provide one of the recent bio-inspired metaheuristic which is the Firefly Algorithm (FF) to optimize power dispatching. For evaluation, we adapt the particle swarm optimization to the problem in the same way as the firefly algorithm. The application is done in an IEEE-14 and on two thermal plant networks. In one of the examples, we neglect power loss and pollutant emissions. The comparison with the particle swarm optimization (PSO), demonstrate the efficiency of firefly algorithm to reach the best cost in less than one second.

Suggested Citation

  • Latifa DEKHICI & Khaled BELKADI & Pierre BORNE, 2012. "Firefly Algorithm for Economic Power Dispatching With Pollutants Emission," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 16(2), pages 45-57.
    • Handle: RePEc:aes:infoec:v:16:y:2012:i:2:p:45-57
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    References listed on IDEAS

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    1. Garcia-Gonzalez, Javier & Parrilla, Ernesto & Mateo, Alicia, 2007. "Risk-averse profit-based optimal scheduling of a hydro-chain in the day-ahead electricity market," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1354-1369, September.
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    1. Faisal Tariq & Salem Alelyani & Ghulam Abbas & Ayman Qahmash & Mohammad Rashid Hussain, 2020. "Solving Renewables-Integrated Economic Load Dispatch Problem by Variant of Metaheuristic Bat-Inspired Algorithm," Energies, MDPI, vol. 13(23), pages 1-36, November.

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