Knowledge-Based Sensors for Controlling A High-Concentration Photovoltaic Tracker

Abstract

To reduce the cost of generated electrical energy, high-concentration photovoltaic systems have been proposed to reduce the amount of semiconductor material needed by concentrating sunlight using lenses and mirrors. Due to the concentration of energy, the use of tracker or pointing systems is necessary in order to obtain the desired amount of electrical energy. However, a high degree of inaccuracy and imprecision is observed in the real installation of concentration photovoltaic systems. The main objective of this work is to design a knowledge-based controller for a high-concentration photovoltaic system (HCPV) tracker. The methodology proposed consists of using fuzzy rule-based systems (FRBS) and to implement the controller in a real system by means of Internet of Things (IoT) technologies. FRBS have demonstrated correct adaptation to problems having a high degree of inaccuracy and uncertainty, and IoT technology allows use of constrained resource devices, cloud computer architecture, and a platform to store and monitor the data obtained. As a result, two knowledge-based controllers are presented in this paper: the first based on a pointing device and the second based on the measure of the electrical current generated, which showed the best performance in the experiments carried out. New factors that increase imprecision and uncertainty in HCPV solar tracker installations are presented in the experiments carried out in the real installation.

Evaluation of control strategies applied in small-scale photovoltaic solar tracking systems: a review

“…However, it requires a solar sensor, which can be affected by meteorological disturbances and diffuse irradiance, so it can be said that its operation depends on meteorological alterations [38]. The solar location is limited to the field vision of the sensor and most of the sensors applied in this technique do not have a linear response to different temperature and radiation levels [41] [49].…”

A Knowledge-Based Battery Controller for IoT Devices

“…In [35], the authors presented different studies related to forecasting, control, energy management, fault location, modeling, energy generation prediction, anomaly detection, and MPTT algorithms. A high-concentration PV tracker controlled by an FRBS system executed in a constrained resource microcontroller and monitored by an IoT system is presented in [36].…”

Development and performance test of a novel solar tracking sensor

“…With the application of four LDRs, a two-axis tracking system based on Wheatstone bridge circuit without a microcontroller is proposed [11]. And on this base, the LDR arrangements and algorithm have been improved for greater detection range and higher detection accuracy, such as four quadrants and six quadrants by using the partition plate [12,13]. At the same time, in order to reduce the effect of diffuse radiation, a sun sensor with infrared and linear polarizing optical filters was proposed [14].…”