DocumentCode :
703687
Title :
Parameter extraction of solar PV double diode model using artificial immune system
Author :
Jacob, Basil ; Balasubramanian, Karthik ; Babu, Thanikanti Sudhakar ; Rajasekar, N.
Author_Institution :
Sch. of Electr. Eng., VIT Univ., Vellore, India
fYear :
2015
fDate :
19-21 Feb. 2015
Firstpage :
1
Lastpage :
5
Abstract :
In this paper, a meta-heuristics algorithm based artificial immune system (AIS) is used for solar PV parameter estimation. A new objective function based on derivative of maximum power with respect to voltage for solar double diode model is proposed. For performance evaluation and validation of the proposed approach using AIS, the results are compared with Genetic algorithm (GA) and particle swarm optimization (PSO) for two different PV modules. The results prove that the proposed approach with AIS outperforms GA and PSO in terms of convergence speed and objective function value for both PV modules. The proposed formulation with AIS can be used for parameter extraction of panel with different make/models.
Keywords :
artificial immune systems; diodes; genetic algorithms; parameter estimation; particle swarm optimisation; performance evaluation; photovoltaic power systems; solar power stations; AIS; GA; PSO; artificial immune system; genetic algorithm; metaheuristics algorithm; parameter extraction; particle swarm optimization; performance evaluation; solar PV double diode model; solar PV parameter estimation; Biological system modeling; Genetic algorithms; Immune system; Linear programming; Mathematical model; Parameter extraction; Photovoltaic cells; Artificial Immune System (AIS); Genetic Algorithm (GA); Parameter extraction; Particle Swarm Optimization (PSO); double diode model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, Informatics, Communication and Energy Systems (SPICES), 2015 IEEE International Conference on
Conference_Location :
Kozhikode
Type :
conf
DOI :
10.1109/SPICES.2015.7091390
Filename :
7091390
Link To Document :
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