Theory, Algorithms and Applications for Solar Panel MPP Tracking

Milea, Lucian; Zafiu, Adrian; Oltu, Orest; Dascălu, Maria-Iuliana

doi:10.5772/10337

Cited by 3 publications

(1 citation statement)

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“…Similar to the work of [9], in this paper a solar panel powers a mobile robot, but the main difference is that the panel on the robot of [9] has two motors to move it in the x-axis and y-axis [10]. The robot used in this work has a panel that moves in the φ-axis (spherical coordinates), and the adjustment of the panel position consists in operating this φ-axis motor and adjusting the position of the robot [11,12].…”

Section: Solar Tracking Approachesmentioning

confidence: 99%

Analysis of the Solar Tracking System for a Mobile Robot Prototype

Toginho¹,

Archela²,

Melo³

2020

Reliability and Ecological Aspects of Photovoltaic Modules

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Methods to detect the position of the sun and orientate a solar panel to its position are used in order to optimize the power generated. Two possible approaches are using light depending resistor (LDR) sensors, or using a GPS and equations that model the geometry between the Earth and the Sun. The main objective of this work is the proposal of a prototype system to optimize the harvesting of solar energy on photovoltaic panels. In this chapter, a mobile robot powered by a solar panel orientated by a LDR matrix and a GPS device was developed. The LDRs were used as the representation of vectors normal to a surface, where its sum resulted in the most lighted point. The GPS, in turn, provided location, date and time data, which were used in the calculations of the Sun's azimuth and zenith, used to orientate the panel. The obtained results show that an orientated photovoltaic panel has a better performance when compared to a static panel. Possibilities and opportunities of research tend to grow for the next years with many possible works to be done in the future, both in mobile robotics and in other systems powered by photovoltaic panels.

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Section: Solar Tracking Approachesmentioning

confidence: 99%