A novel method for modeling of photovoltaic modules based on arithmetic optimization algorithm and cuckoo search

Abstract

A quick, precise, and dependable parameters obtaining of photovoltaic is an important task to evaluate, simulate, and control photovoltaic systems. Accordingly, several numerical, analytical, and meta-heuristic approaches were proposed for the purpose of the estimation of the photovoltaic models’ parameters according to data obtained experimentally. A novel method depending on the hybridization of arithmetic optimization algorithm along with cuckoo search (AOACS) is utilized in the present work for obtaining parameters related to single-diode PV module depending on data obtained experimentally according to several climate conditions. The reliability of the newly introduced AOACS to maintain equilibrium between exploitation and exploration throughout the evolution process is one of its main benefits. The findings exhibit the AOACS beats some approaches that have been widely published in previous studies in terms of preciseness, steadiness, as well as the rate of convergence under diverse statistical criteria. The proposed method exhibits root mean square error (RMSE) and average absolute error (AAE) values lower than alternative approaches by about 72% and 50%, respectively.