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research-article

A Solar Tracking System based on Solar Time for Integrated with Photovoltaic Systems

[+] Author and Article Information
Luiz A. S. Ferreira

MSc Candidate, Department of Communications, University of Campinas
luizfer@decom.fee.unicamp.br

Hermes José Loschi

PhD Candidate, Department of Communications, University of Campinas
hermes@decom.fee.unicamp.br

Abel Alejandro Duenas Rodriguez

PhD Candidate, Department of Communications, University of Campinas
duenas@decom.fee.unicamp.br

Yuzo Iano

PhD, Full Professor, Department of Communications, University of Campinas
yuzo@decom.fee.unicamp.br

Douglas do Nascimento

MSc Candidate, Department of Communications, University of Campinas
eng.douglas.a@ieee.org

1Corresponding author.

ASME doi:10.1115/1.4039094 History: Received May 16, 2017; Revised November 10, 2017

Abstract

The performance of photovoltaic systems is highly influenced by the tilt angle of photovoltaic (PV) modules and the incidence of global solar irradiance, which may change the solar to electrical conversion efficiency. Some authors have addressed these uncertainties arising from photovoltaic solar generation by using mechanisms and methods in which solar tracking systems are integrated to photovoltaic systems. Since the advent of the Internet of Things, this solar tracking strategy has yet to meet the requirements of scalable distributed power systems that can seamlessly support the photovoltaic solar generation, mainly for remote monitoring and control. In this context, this manuscript aims at developing a prospective study devoted to examine fundamental concepts to implement solar tracking algorithms based on local solar time by using embedded technology from the Internet of Things platform. Preliminary results evidenced an improvement of up to 38% in power generation performance for algorithm-driven PV modules compared to fixed PV modules.

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