Open AccessCharacteristics Performance Prediction of PV Panel Using Cuckoo Search Algorithm
Author(s) -
Ibtisam A. Hasan,
Mohammed Saeed Jawad,
Basma Abdullah
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/518/3/032033
Subject(s) - cuckoo search , mean squared error , correlation coefficient , algorithm , correlation , computer science , wind speed , mathematics , statistics , meteorology , particle swarm optimization , physics , geometry
This paper focuses on prediction and evaluation the correlation factors of PV panel characteristics in order to determine the implicit correlation forms for the efficiency and temperature of the system under Iraq climate conditions. Implicit correlation forms consisted on the ambient temperature, solar radiation, wind speed and humidity. Cuckoo search algorithm was employed as an intelligent optimization method to predict the correlation factors of each variable under different evaluation method which are, mean square error (MSE), integrate absolute error (IAE) and integrate square error (ISE). The results appeared that the proposed method was succeeded to predict both of the PV panel temperature and efficiency with MSE evaluation method compared with other methods. Where, the lowest MSE was recorded lower the 1 % for each characteristic.