Electrical and Meteorological Data Acquisition System of a Commercial and Domestic Microgrid for Monitoring PV Parameters

Abstract

This paper centers on the design and installation of a robust photovoltaic (PV)-based microgrid data acquisition system (DAS) that can monitor different PV systems simultaneously. The PV-based microgrid consists of three solar systems: off-grid, hybrid and grid-assisted systems, each with 3.8 kWp located at SolarWatt park, Fort Hare Institute of Technology (FHIT), South Africa. The designed DAS is achieved by assembling and connecting a set of sensors to measure and log electrical and meteorological parameters from each of the three power plants. Meteorological parameters use a CR1000 datalogger while the electrical output parameters use a DT80 data logger. Calibration was done by voltage signal conditioning which helps to reduce errors initiated by analogue signals. The designed DAS mainly assist in assessing the potential of solar energy of the microgrid power plant considering the energy needed in the remote community. Besides, the simultaneous monitoring of the three systems ensures that the outdoor operating conditions are the same while comparing the logged data. A variable day and a week, data were used to verify the reliability of the system. The back of the array temperature was observed to be 42.7 °C when solar irradiance was 1246 W/m2. The ambient temperature and relative humidity were obtained at 21.3 °C and 63.3%, respectively. The PV current in all three systems increases with the solar irradiance and is highest around midday. The results obtained show that the designed DAS is of great interest in PV system developments.

Solar Energy Resources and Photovoltaic Power Potential of an Underutilised Region: A Case of Alice, South Africa

“…Also, a three-phase Schneider IEM 3155 energy meter was used to monitor the inverter output voltage, power and energy. A Campbell Scientific CR1000 datalogger and AM16/32 multiplier were used for the solar resources and ambient air temperature observations [44].…”

Modeling and experimental analysis of battery charge controllers for comparing three off-grid photovoltaic power plants

“…(5) , the ampere-hour relationship reveals that the M-Molar battery current with load connection has the highest charges of -27.75 A at 13h30, whereas, for Hoppecke and Trojan systems, 12h00 were -18.51 and -25.23 A, respectively. Solar radiation and module temperature are the main influencing factors affecting PV power production [ 22 ]. PV current curve does not always follow the irradiance curve directly throughout the day as expected since the photo-generated current is directly proportional to solar irradiance [ 6 ].…”

“…The electrical data acquisition system performance measurements cover the PV module, charge controller, battery, and inverter current [ 22 ]. All the measurements sensors and devices were connected to a DT80 dataTaker accompanied by a CEM 20 channel expansion module, where data are stored and retrieved periodically.…”

Remote Monitoring of Energy Production and Efficiency Of an Off-Gridd Photovoltaic System

“…The conversion efficiency of photovoltaic cells represents their electricity flow in relation to the energy absorbed by the incident solar radiation (Mehmet and Furkan, 2011;Cristescu et al, 2017;Meyer et al, 2020). This is calculated by dividing the peak electric power of the cell expressed in W by the power density of the incident radiation when the maximum power is reached expressed in W/m 2 and at the cell surface expressed in m 2 :…”

“…By means of additional hardware equipment and software applications, remote monitoring can be performed directly through the local network or through the Internet (LTE, LoRa). In other papers that addressed the monitoring of PV systems, the authors used wireless systems (Andreoni et al, 2012) or data acquisition system (DAS) (Meyer et al, 2020) for remote monitoring and control for microgrid applications. In the first mentioned work, the authors present a flexible, robust and reliable measurement and control system based on wireless sensor network (WSN) architecture.…”