PV/Battery Water Pumping System Based on Firefly Optimizing Algorithm

  • Fethia HamidiaEmail author
  • Amel Abbadi
  • Mohamed Seghir Boucherit
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 62)


Since the beginning of the century, global energy consumption has been growing strongly in all regions of the world. It seems likely that energy consumption will continue to increase, as a result of economic growth on the one hand, and of the increase in per capita electricity consumption on the other, whatever the scenarios considered.

For this reason, renewable energies appear today and in the long term as the appropriate solution that covers this energy need by reducing the major disadvantage emitted by fossil and fissionable energies. This paper proposes in one hand, an artificial neural network controller to track the maximum power point and to get better performance mainly on variation of load and weather condition. In second hand, we added to our system a battery and voltage PID controller based on Firefly Algorithm FA to tune their parameter.


Induction motor PVG MPPT Battery Firefly algorithm 


  1. Boukhalafa, S., Bouchafaa, F.: Analysis and control of a further maximum power point (MPPT) of PV array. In: Proceedings of the 2nd International Conference on Systems and Control, Marrakech, Morocco, 20–22 June 2012Google Scholar
  2. Bouzeriaa, H., Fethaa, C., Bahib, T., Abadliab, I., Layateb, Z., Lekhchinec, S.: Fuzzy logic space vector direct torque control of PMSM for photovoltaic water pumping system. Energy Proc. 74, 760–771 (2015)CrossRefGoogle Scholar
  3. Wong, L.A., Shareef, H., Mohamed, A., Ibrahim, A.A.: Optimal battery sizing in photovoltaic based distributed generation using enhanced opposition-based firefly algorithm for voltage rise mitigation. Sci. World J. 2014, Article ID 752096, 11 p (2014). Hindawi Publishing CorporationGoogle Scholar
  4. Abouda, S., Nollet, F., Chaari, A., Essounbouli, N., Koubaa, Y.: Direct torque control of induction motor pumping system fed by a photovoltaic generator. In: International Conference on Control, Decision and Information Technologies (CoDit), pp. 404–408 (2013)Google Scholar
  5. Barazane, L., Kharzi, S., Malek, A., Larbès, C.: A sliding mode control associated to the field-oriented control of asynchronous motor supplied by photovoltaic solar energy. Rev. Energ. Renouv. 11(2), 317–327 (2008)Google Scholar
  6. Hamidia, F., Abbadi, A., Bocherit, M.S.: Maximum power point tracking of photovoltaic generation based on fuzzy logic. In: International Conference on Artificial Intelligence in Renewable Energetic Systems, IC-AIRES2017, Tipaza, Algeria (2017a)Google Scholar
  7. Hamidia, F., Abbadi, A., Bocherit, M.S.: Neuro-fuzzy logic controlled induction motor supplied with PVG. In: CGE10, EMP (2017b)Google Scholar
  8. Sundari, M.G., Rajaram, M., Balaraman, S.: Application of improved firefly algorithm for programmed PWM in multilevel inverter with adjustable DC sources. Appl. Soft Comput. 41, 169–179 (2016)CrossRefGoogle Scholar
  9. Nazarian, P., Hadidian-Moghaddam, M.J.: Optimal sizing of a stand-alone hybrid, power system using firefly algorithm. In: Proceedings of Eleventh The IIER International Conference, Singapore, 15th February 2015, pp. 93–97 (2015)Google Scholar
  10. Hemalatha, C., Rajkumar, M.V., Krishnan, G.V.: Simulation and analysis of MPPT control with modified firefly algorithm for photovoltaic system. Int. J. Innov. Stud. Sci. Eng. Technol. 2(11), 48–52 (2016)Google Scholar
  11. Solar Pumping (2017).

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Fethia Hamidia
    • 1
    Email author
  • Amel Abbadi
    • 1
  • Mohamed Seghir Boucherit
    • 2
  1. 1.LREA LaboratoryYahia Feres Medea UniversityMédéaAlgeria
  2. 2.LCP LaboratoryEcole National PolytechniqueHarrach, AlgiersAlgeria

Personalised recommendations