Time-invariant maximum power point tracking (MPPT) methods, such as particle swarm optimization (PSO) and simulated annealing (SA), have been shown to be effective at locating the region of the global maximum power point (GMPP) in photovoltaic systems where partial shading conditions are observed. These techniques, however, are not effective in providing continuous tracking and identifying when a change in conditions warranting a new global search has occurred. In this article, the SA algorithm is combined with the conventional perturb and observe (P&O) technique in a hybrid MPPT method. This approach leverages the advantages of each technique. The technique is further enhanced by the integration of a novel sentry particle approach to identify when a change in the environmental conditions has occurred leading to a new global search being initiated. The simulation and experimental validations are provided and showed that the proposed technique with the sentry particle reinitialization outperforms both the SA and P&O-based MPPT algorithms by ensuring more consistent tracking to the GMPP.

Item Type:	Refereed Article
Keywords:	MPPT, photovoltaic, maximum power point trackers, cooling, simulated annealing, photovoltaic systems, complexity theory, schedules, hybrid power systems
Research Division:	Engineering
Research Group:	Electrical engineering
Research Field:	Photovoltaic power systems
Objective Division:	Energy
Objective Group:	Renewable energy
Objective Field:	Solar-photovoltaic energy
UTAS Author:	Lyden, S (Dr Sarah Lyden)
UTAS Author:	Galligan, H (Mr Harry Galligan)
ID Code:	143102
Year Published:	2020
Web of Science® Times Cited:	3
Deposited By:	Engineering
Deposited On:	2021-02-26
Last Modified:	2021-08-17
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