Authors:
Akshay Raj, Ankur Kumar Gupta, Rupendra Kumar Pachauri, Vaibhav Sharma

Addresses:
Department of Electrical Engineering, IIMT University, Meerut, Uttar Pradesh, India. Department of Electrical Engineering, University of Petroleum and Energy Studies, Misraspatti, Uttarakhand, India.

Abstract:

Under partial shadowing (PS) circumstances, the solar array's photovoltaic cells become reversely biased and operate as a load. This can lead to hotspot issues, which can significantly reduce photovoltaic efficiency. In solar systems, the Perturb & Observe (MPPT) method is commonly employed; however, when both local and global maxima are present under PS circumstances, it is extremely difficult to identify the true maxima. Utilizing the Walrus optimization algorithm (WaOA), the study's innovative approach could significantly lower the solar PV system's efficiency. The suggested WaOA was used in the current study to track the GMPP under PS conditions and other meta-heuristic algorithms, including PSO, GWO, and ARO. We evaluate the performance of several solutions concerning GMPP tracking. Metaheuristic processes are evaluated in terms of their effectiveness, standard deviation (STD), rise time, mean, root mean square error (RMSE), and median. The benefits of the proposed strategy surpass the conventional P&O method when compared to the most popular metaheuristic algorithms, such as PSO, GWO, and ARO, in terms of accuracy, efficiency, and reduction in steady-state oscillations. The MPPT effectiveness of the suggested model is around 99.838%. It also has the best efficiency, a settling time of 1.83 seconds, and a mean power of roughly 662.6 W. Furthermore, the outcomes are cross-checked and verified on the prototype.

Keywords: Partial Shading; PV Systems; Metaheuristic Algorithms; Global Maximum Power Point; Walrus Optimization; Depletion of Natural Resources; Energy Sources; Maximum Power Tracking.

Received on: 14/02/2024, Revised on: 28/04/2024, Accepted on: 08/06/2024, Published on: 07/12/2024

DOI: 10.69888/FTSES.2024.000309

FMDB Transactions on Sustainable Energy Sequence, 2024 Vol. 2 No. 2, Pages: 88-101

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