Teaching Learning-Based Optimization Approach for Optimal Estimation of Power and Temperature of Photovoltaic Technologies
| International Journal of Electrical and Electronics Engineering |
| © 2023 by SSRG - IJEEE Journal |
| Volume 10 Issue 9 |
| Year of Publication : 2023 |
| Authors : Krupali Kanekar, Prakash Burade, Dhiraj Magare |
10.14445/23488379/IJEEE-V10I9P120
How to Cite?
Krupali Kanekar, Prakash Burade, Dhiraj Magare, "Teaching Learning-Based Optimization Approach for Optimal Estimation of Power and Temperature of Photovoltaic Technologies," SSRG International Journal of Electrical and Electronics Engineering, vol. 10, no. 9, pp. 213-220, 2023. Crossref, https://doi.org/10.14445/23488379/IJEEE-V10I9P120
Abstract:
The operating temperature throughout the Photovoltaic (PV) module has a greater impact on the environmental performance of the PV module as it affects the module's output power. Amorphous Silicon (a-Si) and Hetero-junction with Intrinsic Thin layer (HIT) PV modules, which are placed at the National Institute of Solar Energy (NISE), Gurgaon site in India, are the two PV technologies covered by this work. It describes a new method for estimating the effects of module temperature on seasonal performance variation. For the first time in this research project, estimates of the outcomes have been made based on a method for identifying new coefficients at the site by taking into account the same reported module temperature model format, then finding the RMSE of predicted temperature using Teaching Learning-Based Optimization (TLBO) method. This estimation is also used to boost the performance of PV modules. The calculation of the module temperature model coefficients and Root Mean Square Error (RMSE) for the two technologies are also presented here. Additionally, the PV module temperature model's efficiency and output power were estimated. The RMSE between anticipated and measured power and the percentage power departure from the Standard Test Condition (STC) were assessed. HIT module was the better performing PV technology than a-Si at the NISE site when comparing the parameters of the two distinct PV technology modules in terms of efficiency and output power. The performance evaluation of solar plants around the world can benefit from the methodology outlined in this paper.
Keywords:
Photovoltaic, Amorphous silicon, Hetero-junction with an intrinsic thin layer, Teaching Learning Based Optimization, Root Mean Square Error, Power.
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