Parameters extraction of photovoltaic module for long-term prediction using Artifical Bee Colony optimization
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessRestricted access - publisher's policy
In this paper, a heuristic optimization approach based on Artificial Bee Colony (ABC) algorithm is applied to the extraction of the five electrical parameters of a photovoltaic (PV) module. The proposed approach has several interesting features such as no prior knowledge of the physical system and its convergence is not dependent on the initial conditions. The extracted parameters have been tested against several static IV characteristics of different PV modules from different manufacturers. In order to assess the effectiveness of the extracted parameters, a dynamic model based maximum power point has been used and compared to real measurements data of a grid connected system located in the Centre de Developpement des Energies Renouvelables (CDER) in Algiers. In addition, comparison of the proposed ABC algorithm with some wellknown heuristic algorithms such as, Particle Swarm Optimization (PSO) and Differential Evolution (DE), has given better results in terms of local minimum avoidance and accuracy.
CitationGaroudja, E., Kara, K., Chouder, A., Silvestre, S. Parameters extraction of photovoltaic module for long-term prediction using Artifical Bee Colony optimization. A: International Conference on Control, Engineering & Information Technology. "3rd International Conference on Control, Engineering & Information Technology (CEIT 2015): 25-27 May 2015: Tlemcen, Algeria". Tlecmen: Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 1-6.