Adaptive sun tracking algorithm for incident energy maximization and efficiency improvement of PV panels
Raghuram Ranganathan,
Wasfy Mikhael,
Nasser Kutkut and
Issa Batarseh
Renewable Energy, 2011, vol. 36, issue 10, 2623-2626
Abstract:
In recent times, sun tracking systems are being increasingly employed to enhance the efficiency of photovoltaic panels by constantly tracking the elevation and azimuth angles of the sun. In this paper, a novel adaptive digital signal processing and control algorithm is presented that optimizes the overall PV system output power by adjusting the position angles of the solar panel on both the elevation and azimuth axes. Since the proposed approach is adaptive in nature, the optimal position angles for the solar panel are iteratively computed using the adaptive gradient ascent method, until the incident solar radiation, and hence the output power is maximized. Furthermore, a Taylor’s series approximation is employed for generating a unique optimal position angle increment/decrement at each iteration. Simulation results show that the proposed technique demonstrates fast convergence and excellent tracking accuracy at all times of the day.
Keywords: Sun tracking; Adaptive control; Signal processing (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148110002673
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:36:y:2011:i:10:p:2623-2626
DOI: 10.1016/j.renene.2010.06.011
Access Statistics for this article
Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides
More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().