Bees-algorithm for parameters identification of PV Models

Suliman, Fouad, Anayi, Fatih ORCID: https://orcid.org/0000-0001-8408-7673 and Packianather, Michael ORCID: https://orcid.org/0000-0002-9436-8206 2022. Bees-algorithm for parameters identification of PV Models. Presented at: 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), Greater Noida, India, 28-29 April 2022. Proceedings of 2nd International Conference on Advance Computing and Innovative Technologies in Engineering. IEEE, pp. 2219-2223. 10.1109/ICACITE53722.2022.9823446

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Abstract

An appropriate circuit model using a Bees Algorithm (BA) for predicting and evaluating photovoltaic (PV) module performance is developed. The BA simulation model is capable of computing the electrical parameters which are usually not supplied by manufacturers' datasheets with commercial PV modules. BA is employed here for the identification of optimum parameters of the PV module (photo-watt PWP201) for both single diode (SD), and double diode (DD) models. The photovoltaic module is tested using a standard PV characterization system to acquire current-voltage curves. Additionally, b experimental results from the I- V characteristic curves are used as the input parameters for the simulation. The results show that the simulation model can significantly reduce root mean square error of photovoltaic modules between the measured and calculated data. A comparative study of the simulation technique and other techniques from the literature demonstrates the functionality and applicability of the BA for PV systems. The novel technique also presents a promising feature for detecting faults which could be crucial for condition monitoring and fault diagnosis in future PV energy systems.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Engineering
Publisher:	IEEE
Last Modified:	30 Nov 2022 08:36
URI:	https://orca.cardiff.ac.uk/id/eprint/152045

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