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An accurate method for the PV model identification based on a genetic algorithm and the interior-point method
journal contribution
posted on 2023-06-09, 17:20 authored by Arash Moradinegade DizqahArash Moradinegade Dizqah, Alireza Maheri, Krishna BusawonDue 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.
History
Publication status
- Published
File Version
- Published version
Journal
Renewable EnergyISSN
0960-1481Publisher
ElsevierExternal DOI
Volume
72Page range
212-222Department affiliated with
- Engineering and Design Publications
Research groups affiliated with
- Dynamics, Control and Vehicle Research Group Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2019-03-21First Compliant Deposit (FCD) Date
2019-03-20Usage metrics
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