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

Dizqah, Arash, 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]
Preview
PDF
2014_RE_AD.pdf - Accepted Version

Download (775kB) | Preview
Official URL: http://dx.doi.org/10.1016/j.renene.2014.07.014

Abstract

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
Subjects: H100 General Engineering
H300 Mechanical Engineering
Department: Faculties > Engineering and Environment > Mechanical and Construction Engineering
Depositing User: Ay Okpokam
Date Deposited: 10 Jul 2014 14:19
Last Modified: 14 May 2017 10:21
URI: http://nrl.northumbria.ac.uk/id/eprint/17090

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics


Policies: NRL Policies | NRL University Deposit Policy | NRL Deposit Licence