Hybridizing cuckoo search algorithm with biogeography-based optimization for estimating photovoltaic model parameters

•Accurate and reliable identification of photovoltaic model parameters is important.•Biogeography-based heterogeneous cuckoo search (BHCS) algorithm is developed.•Heterogeneous cuckoo search and biogeography-based discovery are used.•Application to solve parameter estimation problems of different PV...

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Bibliographic Details
Published in:	Solar energy 2019-03, Vol.180, p.192-206
Main Authors:	Chen, Xu, Yu, Kunjie
Format:	Article
Language:	eng
Subjects:	Algorithms Biogeography Biogeography-based optimization Cuckoo search Exploitation Exploration Heuristic Heuristic methods Hybrid meta-heuristic Linearity Mathematical models Optimization Parameter estimation Parameter identification Photovoltaic cells Photovoltaic modeling Photovoltaics Search algorithms Solar cells
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Summary:	•Accurate and reliable identification of photovoltaic model parameters is important.•Biogeography-based heterogeneous cuckoo search (BHCS) algorithm is developed.•Heterogeneous cuckoo search and biogeography-based discovery are used.•Application to solve parameter estimation problems of different PV models.•BHCS shows a superior performance in terms of solution accuracy, robustness and convergence. Accurate estimation of model parameters plays a very important role in modeling solar photovoltaic (PV) systems. In the past decade, meta-heuristic algorithms (MHAs) have been used as promising methods for solving this problem. However, due to the non-linearity and multi-modality existed in the problem, many HMAs may present unsatisfactory performance due to their premature or slow convergence. Therefore, how to develop algorithms efficiently balancing the exploration and exploitation, and identify the PV model parameters accurately and reliably is still a big challenge. In this paper, to improve parameter estimation of solar photovoltaic models, we propose a hybrid meta-heuristic algorithm, called biogeography-based heterogeneous cuckoo search (BHCS) algorithm. Specifically, BHCS hybridizes cuckoo search (CS) and biogeography-based optimization (BBO) by employing two search strategies, namely heterogeneous cuckoo search and biogeography-based discovery. The cooperation of the two strategies helps BHCS achieve an efficient balance between exploration and exploitation. Furthermore, the proposed algorithm is applied to solve four parameters estimation problems of different photovoltaic models, including single diode model, double diode model and two PV panel modules. Experimental results demonstrate that BHCS has very competitive performance in terms of accuracy and reliability compared with CS, BBO and several other meta-heuristic algorithms.
ISSN:	0038-092X 1471-1257