A new maximum power tracking in PV system during partially shaded conditions based on shuffled frog leap algorithm. Issue 3 (4th May 2017)

• Record Type: Journal Article
• Authors: Sridhar, R.; Jeevananthan, S.; Dash, S. S.; Vishnuram, Pradeep
• Is Part Of: Journal of experimental & theoretical artificial intelligence. Volume 29:Issue 3(2017)
• Page Start: 481
• Page End: 493
• Publication Date: 2017-05-04
• Subjects: Maximum power point tracking -- solar energy -- particle swarm optimisation -- shuffled frog leap algorithm -- differential evolution -- evolutionary algorithm; Artificial intelligence -- Periodicals; 006.3
• DOI: 10.1080/0952813X.2016.1186750
• Languages: English
• ISSNs: 0952-813X

Abstract

Abstract: Maximum Power Point Trackers (MPPTs) are power electronic conditioners used in photovoltaic (PV) system to ensure that PV structures feed maximum power for the given ambient temperature and sun's irradiation. When the PV panels are shaded by a fraction due to any environment hindrances then, conventional MPPT trackers may fail in tracking the appropriate peak power as there will be multi power peaks. In this work, a shuffled frog leap algorithm (SFLA) is proposed and it successfully identifies the global maximum power point among other local maxima. The SFLA MPPT is compared with a well-entrenched conventional perturb and observe (P&O) MPPT algorithm and a global search particle swarm optimisation (PSO) MPPT. The simulation results reveal that the proposed algorithm is highly advantageous than P&O, as it tracks nearly 30% more power for a given shading pattern. The credible nature of the proposed SFLA is ensured when it outplays PSO MPPT in convergence. The whole system is realised in MATLAB/Simulink environment.