Optimal parameter assessment of Solar Photovoltaic module equivalent circuit using a novel enhanced hybrid GWO-SCA algorithm

Abstract

Solar Photovoltaic (PV) modules provide a reliable and clean electricity source that can suit various applications. Based on the quality and type of crystals, the PV modules are classified as monocrystalline, polycrystalline, and thin film. The improvements on different solar PV modules can be made efficiently with accurate mathematical models, which requires extracting its parameters. This paper suggests a novel enhanced hybrid grey wolf optimizer-sine cosine algorithm (EHGWOSCA) to extract solar PV module parameters. The recommended algorithm is validated on CEC-C06 2019 benchmark functions which contain ten standard functions. The PV module parameter extraction is performed on different kinds of PV modules, namely, monocrystalline type Shell CS6K280M, polycrystalline type Shell S75, and thin-film type Shell ST40. Two well-known models of PV modules are considered with a requirement of 5 parameters and 7 parameters extraction. The proposed algorithm is implemented by minimizing the sum of squared errors at open circuit point, short circuit point, and maximum power point (MPP). The results obtained show that in the Monocrystalline model using the proposed hybrid approach with single diode model, an error is 1.0718E−15, and it is further reduced to 1.3229E−16 with the double diode model. The proposed EHGWOSCA Error in the Polycrystalline model with double diode is 6.1594E−19, and the Thin-film model error is 2.91E−22. The effectiveness of the proposed approach is verified by comparative analysis with other methods available in the literature.

Keywords

• Solar PV module
• Parameter extraction
• Double diode model
• Grey wolf optimizer
• Sine–cosine algorithm