Research Area:  Metaheuristic Computing

Abstract:

Maximum power-point-tracking techniques applied for partially shaded photovoltaic array yield maximum power output via operating the panel at its most efficient voltage. Considering the noticeable issues existing with the available methods, including steady-state oscillations, poor tracking capability and complex procedures, a new bioinspired Spotted-Hyena Optimizer (SHO) is proposed. It follows simple implementation steps, and does not require additional controller-parameter tuning to track the optimal power point. To validate the versatility of the proposed method, the SHO algorithm is applied to track the maximum power of different string arrangements under six partial-shade conditions. Further, to authenticate SHO’s methods, its results are compared with perturb-and-observe (P&O), and particle-swarm-optimization (PSO) methods. As a result of its implementation, it is observed that the tracking speed of SHO towards the global convergence for four patterns under 4S2P are 0.34 s, 0.24 s, 0.2 s, and 0.3 s, which is far less than the PSO and P&O methods. Further, to demonstrate its suitability, a hardware prototype is built and tested for various operating conditions. The experimental results are in good agreement with the simulated values.

Keywords:  
maximum power point tracking
optimization
partial shading
perturb-and-observe algorithm
photovoltaic array
solar energy

Author(s) Name:  Ezhilmaran Ranganathan, Rajasekar Natarajan

Publisher name:  MDPI

DOI:  10.3390/en15082850

Volume Information:  15(8), 2850

Paper Link:   https://www.mdpi.com/1996-1073/15/8/2850