Optimisation of solar photovoltaic (PV) parameters using meta-heuristics
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TECHNICAL PAPER
Optimisation of solar photovoltaic (PV) parameters using metaheuristics Valentine Obiora1 • Chitta Saha1 • Ammar Al Bazi1 • Koushik Guha2 Received: 2 October 2020 / Accepted: 10 October 2020 Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract This paper presents a critical analysis of the meta-heuristic techniques used in various researches on the optimisation of photovoltaic (PV) parameters, which involves the use of different algorithms in order to extract and improve these parameters from the single diode model (SDM), double diode model (DDM) and three diode model (TDM) respectively. The modelling parameters such as the photon current, saturation current, the series and parallel resistances are investigated to understand the optimum value. It will also equate the results of datasheet values from PV manufactures with experiment values obtained from PV module measurements. The meta-heuristics techniques to be considered include genetic algorithm (GA), particle swarm optimisation (PSO), harmony search (HS), flower pollination algorithm (FPA), simulated annealing (SA), teaching learning based optimisation (TLBO), and other different hybrid solutions to optimize the convergence speed. Root mean square error (RMSE) is used as a performance indicator of each meta-heuristic technique. These optimisation techniques are utilised in extracting the parameters of a 5 W polycrystalline panel at standard testing conditions. The results presented in this paper compared the performances of the mentioned meta-heuristics on the single, double and triple diode models respectively.
1 Introduction There exist global concerns regarding the utilisation of non-renewable energy sources such as fossil fuels. These concerns have to do with the immediate combustion of fossil fuel in generation. This combustion has led to serious environmental impacts such as climate change which is a worldwide concern. This motivates to investigate alternative sources of energy including renewables such as solar photovoltaic (PV), wind energy etc. Solar PV has shown & Valentine Obiora [email protected] Chitta Saha [email protected] Ammar Al Bazi [email protected] Koushik Guha [email protected] 1
School of Computing, Electronics and Mathematics, Coventry University, Priory Street, Coventry CV1 2JH, UK
2
Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Assam, Silchar 788010, India
the superior potential for the replacement of petroleum derivatives to meet the energy demand in many countries worldwide, as it has no moving parts and has little negative impact on the environment. However, due to the high cost of the modules and intermittent availability of solar energy, it is necessary to develop an accurate model of the PV system, especially the modules (Ishaque et al. 2011). The efficiency and maximum power point of the solar PV vary with temperature and irradiation. It is crucial to give the right value
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