Parameter Estimation of Photovoltaic Models via Cuckoo Search | Zendy

Jieming Ma | Zendy; T. O. Ting | Zendy; Ka Lok Man | Zendy; Nan Zhang | Zendy; Sheng-Uei Guan | Zendy; Prudence W. H. Wong | Zendy

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Parameter Estimation of Photovoltaic Models via Cuckoo Search

Author(s) -

Jieming Ma,

T. O. Ting,

Ka Lok Man,

Nan Zhang,

Sheng-Uei Guan,

Prudence W. H. Wong

Publication year - 2013

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2013/362619

Subject(s) - cuckoo search , photovoltaic system , cuckoo , mean squared error , computer science , algorithm , value (mathematics) , statistics , mathematics , machine learning , particle swarm optimization , engineering , biology , zoology , electrical engineering

Since conventional methods are incapable of estimating the parameters of Photovoltaic (PV) models with high accuracy, bioinspired algorithms have attracted significant attention in the last decade. Cuckoo Search (CS) is invented based on the inspiration of brood parasitic behavior of some cuckoo species in combination with the Lévy flight behavior. In this paper, a CS-based parameter estimation method is proposed to extract the parameters of single-diode models for commercial PV generators. Simulation results and experimental data show that the CS algorithm is capable of obtaining all the parameters with extremely high accuracy, depicted by a low Root-Mean-Squared-Error (RMSE) value. The proposed method outperforms other algorithms applied in this study

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