An improved optimization technique for estimation of solar photovoltaic parameters

Derick, Mathew, Rani, C., Rajesh, M., Farrag, Mohamed, Wang, Yue and Busawon, Krishna (2017) An improved optimization technique for estimation of solar photovoltaic parameters. Solar Energy, 157. pp. 116-124. ISSN 0038-092X

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The nonlinear current vs voltage (I-V) characteristics of solar PV make its modelling difficult. Optimization techniques are the best tool for identifying the parameters of nonlinear models. Even though, there are different optimization techniques used for parameter estimation of solar PV, still the best optimized results are not achieved to date. In this paper, Wind Driven Optimization (WDO) technique is proposed as the new method for identifying the parameters of solar PV. The accuracy and convergence time of the proposed method is compared with results of Pattern Search (PS), Genetic Algorithm (GA), and Simulated Annealing (SA) for single diode and double diode models of solar PV. Furthermore, for performance validation, the parameters obtained through WDO are compared with hybrid Bee Pollinator Flower Pollination Algorithm (BPFPA), Flower Pollination Algorithm (FPA), Generalized Oppositional Teaching Learning Based Optimization (GOTLBO), Artificial Bee Swarm Optimization (ABSO), and Harmony Search (HS). The obtained results clearly reveal that WDO algorithm can provide accurate optimized values with less number of iterations at different environmental conditions. Therefore, the WDO can be recommended as the best optimization algorithm for parameter estimation of solar PV.

Item Type: Article
Uncontrolled Keywords: Double diode model, Genetic algorithm, Pattern search, Simulated annealing, Wind driven optimization
Subjects: H800 Chemical, Process and Energy Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Becky Skoyles
Date Deposited: 06 Oct 2017 08:42
Last Modified: 12 Oct 2019 19:45

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