An accurate method for the PV model identification based on a genetic algorithm and the interior-point method

Dizqah, Arash M, Maheri, Alireza and Busawon, Krishna (2014) An accurate method for the PV model identification based on a genetic algorithm and the interior-point method. Renewable Energy, 72. pp. 212-222. ISSN 0960-1481

[img] PDF (For REF only) - Published Version
Restricted to SRO admin only

Download (1MB)


Due to the PV module simulation requirements as well as recent applications of model-based controllers, the accurate photovoltaic (PV) model identification method is becoming essential to reduce the PV power losses effectively. The classical PV model identification methods use the manufacturers provided maximum power point (MPP) at the standard test condition (STC). However, the nominal operating cell temperature (NOCT) is the more practical condition and it is shown that the extracted model is not well suited to it. The proposed method in this paper estimates an accurate equivalent electrical circuit for the PV modules using both the STC and NOCT information provided by manufacturers. A multi-objective global optimization problem is formulated using only the main equation of the PV module at these two conditions that restrains the errors due to employing the experimental temperature coefficients. A novel combination of a genetic algorithm (GA) and the interior-point method (IPM) allows the proposed method to be fast and accurate regardless the PV technology. It is shown that the overall error, which is defined by the sum of the MPP errors of both the STC and the NOCT conditions, is improved by a factor between 5.1% and 31% depending on the PV technology.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Research Centres and Groups: Dynamics, Control and Vehicle Research Group
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA0168 Systems engineering
T Technology > TJ Mechanical engineering and machinery > TJ0807 Renewable energy sources > TJ0810 Solar energy
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3001 Distribution or transmission of electric power
Depositing User: Arash Moradinegade Dizqah
Date Deposited: 21 Mar 2019 11:15
Last Modified: 01 Jul 2019 18:15

View download statistics for this item

📧 Request an update