Title: Optimisation-based parameter estimation of photovoltaic modules

Authors: Mohamed A. Awadallah; Bala Venkatesh

Addresses: Centre for Urban Energy, Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3, Canada ' Centre for Urban Energy, Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3, Canada

Abstract: This paper presents a methodology for parameter estimation of photovoltaic (PV) modules based on global search and optimisation algorithms. A nonlinear optimisation problem is formulated to search the best set of equivalent circuit parameters which minimises a certain objective function. The objective function measures the discrepancy between computed and targeted performance. The proposed technique is flexible on the source of the targeted performance, which could be datasheet information or experimental measurements. The method is also flexible on the nature and number of sought parameters according to the equivalent circuit representation and available information. The nonlinear optimisation problem is solved using three different global search routines, namely, genetic algorithms (GA), particle swarm optimisation (PSO) and bacterial foraging (BF). Effectiveness of the proposed methodology is shown through three case studies on different PV modules of various ratings and manufacturers. The extracted parameters could accurately simulate the performance of PV modules under normal operation as well as low irradiance and partial shading conditions.

Keywords: photovoltaic modules; parameter estimation; optimisation.

DOI: 10.1504/IJIED.2018.090412

International Journal of Industrial Electronics and Drives, 2018 Vol.4 No.1, pp.33 - 43

Received: 14 Oct 2017
Accepted: 25 Oct 2017
Published online: 15 Mar 2018 *