Arduino Uno Wi-Fi DeMilitarized Zone-based monitoring of solar photovoltaic systems

Abstract

Due to global warming, governments around the world are focusing on renewable energy as the main source of energy. Gulf countries in particular, are focusing on solar energy due to its abundance and the gulf geolocation that allows the installation of ambitious solar photovoltaic (PV) energy systems and replace conventional power plants. In order to maximize energy extraction from the sun, solar power operators need to constantly monitor key solar PV parameters such as panel temperature, solar irradiation, voltage and current in order to detect abnormalities in the PV system operation and take the necessary actions to keep the PV system performance at its maximum. However, monitoring such parameters on-site is exhausting and expensive. Moreover, remote monitoring for solar PV systems is a more attractive solution once the data collection, processing and transmission become faster and less expensive. This paper describes the design of a low-cost remote monitoring system intended for off-grid solar PV systems. The designed remote monitoring system uses a combination of an Arduino Uno Wi-Fi demilitarized zone (DMZ) communication system with router-configured network sensors calibrated to fulfill the IEC-61,724 standards and it provides meteorological and electrical measurements with an error of 2% or less. There are four primary features of the proposed monitoring system. First, it combines the Arduino Uno Wi-Fi with a DMZ configuration in the router. Second, it complies with the minimum current, voltage, power, and PV-module temperature values set by the IEC-61,724 in such a way that the average error does not exceed the 4% threshold. Third, it provides an accuracy level of 98% for the meteorological and electrical parameters. This level of accuracy exceeds that of commercial data logging equipment. Finally, its total cost is less than $100, which is less than that of available commercial solar PV monitoring systems. Additional features include the ability to select the number of processed measurements per hour and innovative processing, display, and access schemes. These features enable the accessibility of the data from mobile phones and computers within the campus for teaching and experimentation purposes.