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REMOTELY MEASURING AND CONTROLLING SPECIFIC
PARAMETERS OF A PV MODULE VIA AN RF LINK
Ntombizanele Maqache
Central University of Technology, Free State, (South Africa).
E-mail: nsolfafa@cut.ac.za ORCID: https://orcid.org/0000-0001-9457-1573
Arthur James Swart
Central University of Technology, Free State, (South Africa).
E-mail: aswart@cut.ac.za ORCID: https://orcid.org/0000-0001-5906-2896
Recepción: 05/07/2021 Aceptación: 15/10/2021 Publicación: 14/12/2021
Citación sugerida:
Maqache, N., y Swart, A., J. (2021). Remotely measuring and controlling specic parameters of a PV module via an
RF link. 3C Tecnología. Glosas de innovación aplicadas a la pyme, 10(4), 103-129. https://doi.org/10.17993/3ctecno/2021.
v10n4e40.103-129
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ABSTRACT
The eciency of PV modules is aected by a number of factors, including installation parameters
and the module surface temperature. Installation parameters of PV modules focus primarily on the
tilt and orientation angles, which have to be considered for optimum output power. Furthermore, the
operating temperature of a PV module must be kept within certain limits, in order to obtain optimum
electrical energy eciency, depending on the module used. The purpose of this study was to measure
the instantaneous surface temperature, voltage and current of a remote PV module in order to monitor
its output power. An energy monitoring system was developed that received measurement data over an
RF link. The PC transceiver of the system featured a CC1101 RF transceiver connected to the PC via
an Arduino UNO, using a USB cable. The PV transceiver featured an Arduino Mega 2560, connected
to a CC1101 RF transceiver to make the ST board, which contained all the sensors of the system. In
addition, a graphical user interface was developed for sending and receiving measurements between the
PC transceiver and the PV transceiver. The PV module voltage and current data was veried using a
Fluke 115 DMM. The results showed a 4.9% error percentage for voltage measurements and a 3.9%
error percentage for current measurements. Furthermore, a 29-day period of data showed the surface
temperature to rise signicantly higher than the ambient temperature during the day, indicating that
there was considerable heating of the PV Module when there was solar radiation. The system could be
used to compare the eect of cooling the PV module on the output power as the orientation angle is
adjusted.
KEYWORDS
PV Module, Voltage, Current, Surface Temperature.
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1. INTRODUCTION
Fifty percent of the overall power consumption in the Information and Communication Technology
(ICT) eld is dedicated to telecommunication networks (Koutitas & Demestichas, 2010). In fact, research
has shown that a mobile base station uses an average of 36 000 kWh per year. The study included a
sample of 6 mobile base stations in the center of Italy for shelter, room and outdoor types (Spagnuolo et
al., 2015). The 2018 Telkom SA integrated report reects 563 055 930 kWh electricity consumption by
the telecommunications giant in South Africa (Telkom, 2018). In addition, a forecast study estimates that
communication technology will consume 51% of the world’s electricity in 2030 (Andrae & Edler, 2015).
This amplies the need for more renewable and sustainable sources of electricity.
Photovoltaic (PV) modules are devices that convert solar energy directly into electrical energy without
requiring mechanical energy and without producing greenhouse emissions. PV modules undergo
performance characterization in Standard Test Conditions (STC) by primarily measuring its voltage-
current (I-V) curve (Schwingsshackl et al., 2013). One study found that the operating temperature
plays a key role in the process of PV conversion (Swapnil, Jatin, & Bharath, 2013). In addition, the
aforementioned authors concluded that there is a linear dependence of electrical eciency, and thus
output power, of a PV module with regard to the operating temperature of a module. PV’s only convert
4-17% of the solar energy to electrical energy, the rest is converted to heat energy that is not used (Bai
et al., 2016). Solar radiation and other weather parameters, have an eect on a PV module’s operating
temperature, and as such on its Cell Temperature (Tc) (Swapnil et al., 2013). Ambient temperature (Ta) is
dened as the temperature of the air around the PV module (Bhattacharya, Chakraborty, & Pal, 2014;
Liu et al., 2015). The agreement across board is that the open-circuit voltage decreases considerably
(about 2.3 mV/C), while the short circuit current only decreases somewhat with increased PV module
temperature (Bai et al., 2016).
As such, eld measurements of the voltage and current of a PV module, allow more accurate data to
be collected for practical operating conditions that dier slightly from the Standard Test Conditions, in
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order to optimize the overall system performance. Researchers used a simple approach of a digital multi-
meter to measure the voltage and current in a study that increased the eciency of a PV module by 47%
using cooling (Peng, Herfatmanesh, & Liu, 2017). This approach is not an automated one and requires
one to physically save the measurements from the multi-meter. A more complex combination of super
capacitors, step-up and step-up converters were used to acquire voltage measurements in a study that
monitored PV modules using wireless sensor networks (Prieto et al., 2014). The aforementioned study
made use of ACS711 current sensors from Allegro, an 8-bit PIC microcontroller from Microchip for
processing and XBee PRO 802.15.4 for communication. The study was successful in obtaining real-time
measurements of PV modules for monitoring purposes. Alternatively, the voltage divider is a simpler and
cheaper method that has been used in PV monitoring systems to obtain voltage measurements eectively,
and in real-time (El Hammoumi et al., 2018; Kekre & Gawre, 2017). A variety of sensors have also been
used in PV monitoring systems to measure temperature (Atsu et al., 2020), which includes the LM35
and Pt-100 sensors. Alternatively, a thermographic camera can be used to measure the temperature
distribution over the module’s surface (Nedelchev & Zhivomirov, 2020), although it is again a manual
approach. An automatic PV module monitoring system was designed in Spain with a complex control
unit that connects a PV system physically to a computer to control the measuring circuit (Ortega et al.,
2018). This design proved to be both complex and expensive.
The monitoring system presented in this paper aims to be both a non-complex and cost-eective solution
as it eliminates physically connecting the PV module and the data recording system. The design and
development of a cost-eective remote measuring and monitoring system that will record the voltage,
current and surface temperature of a remote PV module via a Radio-Frequency (RF) link is contained
herein. Measuring these remote parameters instantaneously will allow eective monitoring in order to
maintain a high output power. The sections that follow will explore the sensing technologies used to
obtain measurements as well as the results obtained over a given period. The communication technology
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used to send and receive data to a remote PV module will also be presented. Lastly, this paper will show
the user interface used for the synergy of all the system parameters and controls.
2. SYSTEM DESIGN AND PRACTICAL SET-UP
The block diagram contained in Figure 1 shows the overall setup of the system design for remotely
measuring current, voltage and temperature. Block 1 is the Master Transceiver (MT) where the user can
see the real-time sensor data displayed on the PC that is sent from block 2 which is the Slave Transceiver
(ST) responsible for collecting data using a microcontroller. Block 3 shows all the parameters of the PV
module that are collected by the microcontroller.
When measurements are acquired from the PV module, there needs to be a method of processing and
saving the data for monitoring or analysis. Hence the need for a microcontroller where three options were
considered. Firstly, Rasberry Pi 3 model B+ is the latest release in the Rasberry Pi 3 range that makes
use of the Broadcom BCM2837B0 processor with 1.4 GHz operating speed. Although a RAM of 1Gb
makes it attractive, the drawback is that this board requires an external ADC, which will contribute to
the cost and complexity of the design (Rasberry Pi, 2018). Secondly, the BeagleBone Black incorporates
the TI Sitara AM3358 processor at the operating speed of 1GHz and 512Mb of RAM with six analog
input pins. This option is more expensive and more complex to implement. Lastly, the Arduino Uno is
based on the ATmega328 microcontroller, has 16 digital input / output pins, six analog inputs and a USB
connection. It was chosen for designing a data logger for a PV system for its simplicity and modularity,
in comparison with other boards (Arduino, 2018; Fuentes et al., 2014). The Arduino platforms allow for
easy learning and adaptation, because it is open ware, as such there are modules and libraries readily
available on the internet.
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PC FOR CONTROL
1. MASTER TRANSCEIVER
SERIAL OR
USB RF MODULE
R-F LINK
RF MODULE
2. SLAVE TRANSCEIVER
MICROCONTROLLER FOR CONTROL & DATA
TRANSFER
CURRENT SENSOR
3. PV MODULE SENSORS
VOLTAGE SENSOR TEMPERATURE
SENSOR
Figure 1. Block diagram of the practical set-up.
Source: own elaboration.
Wireless technology (the RF Link in Figure 1) is used to transfer information between two or more
points that are not physically connected to form wireless communication. Wireless technologies prove
useful when it comes to accessing data from a remote site that is without electricity or telephone lines.
Wireless communication can be achieved through either radio frequency, microwave or infrared. An RF
transceiver module is an integrated circuit that transmits and receives radio signals on a given carrier
frequency (433 MHz as an example). The CC1101 is an example of such a module. It has dierent
communication modes that can be changed by command. In addition, it can transmit over distances of
up to 500 m in open-air line of sight without any obstacles to absorb radio signals at a rate of about 600
kBps (Texas Instruments, 2018). The usefulness of RF modules in remote-sensing and control is widely
accepted in many industries. In wireless communication, power consumption is increased with bigger
communication distances. It is therefore required for wireless communication to consume minimal power
for remote sites. This is why RF modules are also widely used in renewable energy system monitoring, as
they have very low power consumption and also for their low-cost and wide open-air range capabilities
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(Kama et al., 2017). Added to these advantages, they eliminate the need for physical wiring between two
points that can complicate the installation of the energy monitoring system.
PV module sensors of Figure 1 include the voltage divider, the ACS712 and the DHT11. The voltage
divider is commonly used in PV data acquisition to obtain higher voltage measurements because it is
non-complex and inexpensive. The voltage divider is designed such that its output is proportional to the
input voltage and small enough to be processed by a microprocessor. For current measurements, Hall
Eect current transducers (LEM LA100-P, LA55p, Honeywell Microswitch CSLA1CF) have been used
to measure current for more complex PV applications (Belmili et al., 2010; Tina & Grasso, 2014). The
ACS712 has a precise proportional voltage provided by the low-oset, chopper-stabilized BiCMOS
Hall IC, which is programmed for accuracy after packaging (Allegro Microsystems, 2006). The DHT11
humidity and temperature sensor is a semiconductor thermometer device that is made up of a resistive
type humidity measurement component and an NTC temperature measurement component. It connects
to a microcontroller for excellent quality, fast response, anti-interference ability and cost-eectiveness
(D-Robotics, 2010). Their digital output can be connected to a microcontroller without complex circuitry,
which contributes to the overall cost of the setup.
2.1. THE GRAPHICAL USER INTERFACE (GUI)
The graphical user interface is used to connect the user (Master Transceiver) to the PV module sensors
(Slave Transceiver) using the RF link as shown in Figure 1. The GUI is designed using Visual Studio C#
with its purpose being for the end user of the system to visually see the data being sent from the ST or
to interact with the system. Figure 2 shows the GUI with numbered items that are used to illustrate its
functionality. The numbered items of the GUI are presented below with their functionality explained:
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1. Serial port settings to be selected by the user.
The serial port settings are obtained from combo boxes where the user selects the appropriate
port name, baud rate, parity, stop bits and handshake.
2. Tabs that can be selected to view dierent data representations.
The data grid sorts the data received into the 7 relative columns with the last column being the
time the measurements are received. The columns are named after the measurement reading
they collect; PV voltage, Battery voltage, Load voltage, PV current, Battery current, Load
current and Temperature. The data grid is displayed in the second tab of the GUI that is named
“Live table”. The third tab displays the chart representation of all the PV measurements, this
being the PV voltage vs time, PV current vs time, Temperature vs time and Power vs time. Tab
four and ve show the same charts (except for temperature) for the battery and the load.
3. The button used to turn on the water sprayer for 5 seconds at the PV module.
This functionality could be used to control the water sprayer used for cooling the PV module
when the surface temperature gets too high. When clicked, a signal is sent to the ST to activate
for 5 seconds.
4. Buttons used to move the PV module either left or right by 10° to adjust the orientation angle.
The orientation angle could be varied using these buttons to achieve the desired angle. When
these are clicked, a signal is sent to the ST to either extend or retract the actuator for a set
period.
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5. Displays the real time measurements as they are received from the ST.
Measurements received by the MT from the ST are displayed in this text box in rea-time and
loaded in the live table in the GUI.
6. Displays commands that are sent to the ST when buttons are clicked for the water sprayer and
actuator.
This enables the user to see the status of the control commands to avoid unwanted repetition.
7. The button that is used to send data to an excel sheet and save as a predetermined le name.
The export to Excel method is called after every 100 rows and when the user clicks the button.
When this is done, an Excel le is created named “ExportedFromDatGrid”. The le is saved to
the path specied that includes the day’s date and binary time format which ensures a unique
le name each time.
8. Buttons used to either start or stop serial communication between the MT and the ST.
Communication between the MT and the ST is initiated or terminated by these buttons, giving
the user control over when to start recording measurements.
9. Displays the real time orientation angle of the PV module.
This gauge displays the orientation angle of the PV module as it is adjusted either left or right
by the control commands.
2.2. MASTER TRANSCEIVER BOARD
The GUI uses the MT to interface the user at the PC with the measurement system at the PV module
(ST). The MT is responsible for receiving measurements and sending commands over the RF-link as well
as saving it on the PC. The MT board in Figure 3 is designed to plug into the Arduino UNO board that
connects to the PC using the USB port.
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Figure 3. Arduino and Master Transceiver.
Source: own elaboration.
It houses the CC1101 transceiver for wireless communication with the three LEDs indicating the
mode of the transceiver device; red being idle, green being receive data and yellow being transmit
data. The microcontroller was only used for the wireless communication; hence the Arduino Uno was
chosen because not many output pins were required for this function and for its simplicity, low cost and
modularity.
2.3. SLAVE TRANSCEIVER BOARD
The MT receives measurements of the PV module from the ST to display on the GUI. The ST board
(Figure 4) houses the second CC1101 and the three sensors on the PV module side. The Arduino Mega
that is used as the microcontroller has the same processing speed as the Arduino Uno with more RAM
(8 Kb) and I/O (54) pins allowing more data to be processed in and out by the microcontroller. This
transceiver board was developed as a shield for the microcontroller and connects it to the voltage,
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current and temperature sensors that obtain data from the PV module, battery and the load. This data
is transmitted to the MT board.
Figure 4. Slave Transceiver Board.
Source: own elaboration.
The measurements from the sensors are sent to the serial port of the Arduino Mega 2560. The
transmitting device, CC1101 transceiver RX and TX pins are connected to this Arduino’s serial port
0 at pin 0 and 1 respectively. This means that the measurements that are sent to the serial port of the
Arduino Mega 2560 are then transmitted by the CC1101 transceiver. When the Arduino Mega 2560 is
connected to a PC using a USB cable, terminal software can be used to display these measurements on
the serial port of the PC through the USB port. This feature might be used in environments that are not
remote and do not require wireless transmission.
2.4. SLAVE TRANSCEIVER SENSORS
Measurements are obtained using sensors connected on the ST board; they were designed to t onto
the Arduino Mega 2560 which processes the signals. Voltage dividers are used to obtain higher voltage
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measurements in a noncomplex and inexpensive manner, and are commonly used in PV data acquisition
(Tina & Grasso, 2014). The voltage divider is designed such that its output (VOUT) is proportional to the
input voltage (VPV) and small enough to be processed by a microprocessor. The output of the voltage
divider is calculated by:
(1)
Where VPV is the voltage from the PV modules (4 x SD ECO PLUS 10W PV modules connected in
parallel). The open circuit voltage (VOC) for these is 20.8 V and the short circuit current (ISC) is 0.78 A.
The Arduino Mega 2560 analog input pins can measure voltages from ground to 5 V, supplying these
pins with anything more will damage them. As such, voltage dividers are used to sense the voltages of the
PV module, battery and load, while fuses are used to protect the circuitry against any unwanted currents.
VOUT from these sensors is connected to the 3 analog pins of the Arduino Mega 2560 respectively. The
microcontroller then uses a programmed algorithm to process the voltage divider output and convert it
to a relative voltage.
Hall-eect current transducers have been used to measure current for more complex PV applications
(Tina & Grasso, 2014). The Allegro ACS712 sensor comprises a precise, low-oset, linear Hall sensor
circuit with a hall element. A precise, proportional voltage is provided by the low-oset, chopper-
stabilized BiCMOS Hall IC, which is programmed for accuracy after packaging (Allegro Microsystems,
2006). The analog input of the Arduino from the sensor is used in the formula below in order to arrive
to the current reading:
(2)
PinRead is the analog input, the 1023 is the 10-bit resolution of the ADC and the 5000 is the reference
voltage in mV. Because the oset of the current sensor is 2500 mV, it must be subtracted to arrive to the
actual current in mA.
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The DHT11 humidity and temperature sensor is a semiconductor thermometer device that is made up
of a resistive type humidity measurement component and an NTC (Negative Temperature Coecient)
temperature measurement component. It connects to a microcontroller for excellent quality, fast
response, anti-interference ability and cost-eectiveness (Gay, 2018). This digital sensor was used to
develop a humidity and temperature remote sensing system that was cost-eective and fast for real-time
operations (Randhir & Karhe, 2015). It can measure temperatures of up to 50°C with the accuracy of
+-2°C. The temperature sensor also connects to the ST board and gives real time temperature of the PV
module’s surface in Degrees Celsius (°C). As established in the previous section, the surface temperature
of the PV module is important to its eciency.
3. METHODOLOGY
The experimental set-up included the PV module, battery and 12 V LED ood light connected to a
programmable solar charge controller on a balcony of a building at the Central University of Technology,
Free State. The site is located in the city of Bloemfontein, South Africa where the latitude is -29.087 and
the longitude is 26.154. The PV voltage and current were measured between the charge controller and
the PV module. The battery voltage and current measurements were acquired between the battery and
the charge controller. The temperature is a measurement of the PV module surface temperature and
was obtained from the sensor that was attached to the back of the PV module. Measurement data was
acquired every 100 seconds from the ST via RF using the MT and saved to an MS Excel sheet using the
GUI. The data in MS Excel was analysed using Pivot Tables and then represented using line graphs.
The results of the PV voltage and current are presented below for a cloudy and sunny day in September,
as well as surface temperature measurements for a 29 day period in July and August of 2019. July and
August are winter months where temperatures have been seen to go below 0°C whereas September is
spring where warmer days can be found.
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4. RESULTS
4.1. RESULTS OF THE PV MODULE VOLTAGE AND CURRENT MEASUREMENTS
VERIFIED BY DMM
Experimental results are presented here for dierent weather conditions with the load connected. The
SD eco plus 10 W PV module was used with the rated parameters shown in Table 1 that are obtained
under Standard Testing Conditions (STC). Four of these modules were connected in parallel, giving the
expected parameters of Table 1.
Table 1. PV module parameters.
STC parameters for one PV module STC parameters for four PV modules in parallel
Imp (maximum power current) = 0.61 A Imp = 2.44 A
Vmp (maximum power voltage) = 16.5 V Vmp = 16.5 V
Isc (short circuit current) = 0.78 A Isc = 3.12 A
Voc (open circuit voltage) = 20.8 V Voc = 20.8 V
Peak Power = 10 W Peak Power=40 W
Source: own elaboration.
A Fluke 115 digital multimeter (DMM) was used to verify the voltage and current measurements from
the voltage divider and ACS712 sensors on the PV module transceiver. In Figure 5, a spreadsheet of
sensor measurements obtained from the PV module transceiver for 27 September 2019 is observed,
where a voltage and current reading was compared to a DMM voltage and current reading.
The accuracy of the voltage and current sensor measurements was evaluated by calculating the
percentage error between the sensor measurements and the DMM readings as follows:
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(3)
Figure 5. PV voltage and current measurements veried using a DMM.
Source: own elaboration.
The PV voltage of 13.69 V from the PV module transceiver and 13.05 V from the DMM were used in
equation 3 to give an error percentage of 4.9%. In addition, the error percentage for the current reading
was calculated using the PV current of 1.15 A from the PV module transceiver and 1.106 A from the
DMM, giving a value of 3.9%. A percentage error of between -10% and +10% has been found to be
acceptable for these type of measurements (Ertekin & Yaldiz, 2000).
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4.2. RESULTS OF THE PRACTICAL SETUP MEASUREMENTS OF PV VOLTAGE AND
CURRENT OVER SEVEN DAYS
Measurement data was acquired every 100 seconds from the ST via RF using the MT continually for
a period of seven days. The data stored by the GUI was processed using pivot tables and summarized
to hourly maximums. The daily PV voltage curve for the period above is presented in Figure 6 where
the voltage can be observed to be higher for the days where the load is switched o. The PV module
terminal voltage reaches 13.8 V when the load is on. When the load is switched o by the solar charge
controller, the battery then acts as a load and draws current from the PV module. The terminal voltage
the PV module, in this case, reaches is 15.44 V when the LED load is switched o and the battery is
charging. Both values of PV voltage are less than the rated maximum power voltage of 16.5 V, which
indicates that the process of measuring is satisfactory. Hourly maximum measurements of PV voltage for
24 September show a maximum of 12.76 V at 12 pm. Hourly maximum PV voltage for 27 September
show a maximum of 13.8 V at 10 am. The maximum terminal voltage of the PV module is less than the
rated maximum power voltage throughout the presented period.
Figure 6. Hourly maximum of PV voltage from 24 to 30 September 2019.
Source: own elaboration.
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Daily maximum PV current is presented in Figure 7 from 24 to 30 September. The diagram shows that
the maximum current recorded was less than the rated Imp = 2.44 A for the said period. The highest
maximum PV current is 2.43 A on 28 September and the lowest recorded maximum PV current 1.98
A on 29 September.
Figure 7. Hourly maximum of PV current from 24 to 30 September 2019.
Source: own elaboration.
Figure 8. Hourly maximum of PV current for 27 September 2019 (Sunny day).
Source: own elaboration.
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Figure 9. Hourly maximum of PV current for 29 September 2019 (Cloudy day).
Source: own elaboration.
A closer look at the daily performance shows hourly maximum PV currents for a sunny day on site
(Figure 8) and for a cloudy day (Figure 9). The measurements reect the maximum current drawn from
the PV module as 2.32 A at 11 am for the sunny day and 1.98 A at 11 am for a cloudy day. Both currents
are less than 2.44 A maximum power current of Table 1, suggesting that the measurement process is
satisfactory.
4.3. RESULTS OF THE PV MODULE SURFACE TEMPERATURE VERIFIED BY DMM
The measurements from the DHT11 sensor were veried using the Fluke 179 Digital Multimeter
(DMM). The sensor measurement of 34 °C in Figure 8 was judged against the DMM reading of 33.8 °C
and a percentage error calculated, using equation 3 arriving at an error percentage of 0.59%, indicating
that the measurements from the sensor are acceptable.
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Figure 10. PV module surface temperature measurements veried by DMM.
Source: own elaboration.
4.4. RESULTS OF THE PRACTICAL SETUP MEASUREMENT OF PV SURFACE
TEMPERATURE OVER 29 DAYS
Figure 11 reects hourly maximum PV surface temperature measurements for a cloudy day. The
maximum surface temperature for 29 September 2019 is recorded as 39°C at 09:00 am. Figure 12
reects hourly maximum PV surface temperature measurements for a sunny day. The maximum surface
temperature for 27 September 2019 is recorded as 54°C at 12:00 pm.
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Figure 11. Hourly maximum of PV module surface temperature for 29 September 2019 (Cloudy day).
Source: own elaboration.
Figure 12. Hourly maximum of PV module surface temperature for 27 September 2019 (Sunny day).
Source: own elaboration.
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PV surface temperature (TPV) data from the DHT11 sensor is presented in Figure 13, together with
the ambient temperature (Ta) data for Bloemfontein in South Africa, obtained from timeanddate.com
(Time and Date, 2020). The Ta data available from the website is given in maximum and minimum
for 00:00, 06:00, 12:00 and 18:00 for any required day. The available maximum and minimum Ta
was then captured and processed, using pivot tables where daily maximum and minimum Ta were
obtained. The TPV data was sampled every 100 seconds from 19 July to 16 August 2019, where the
highest surface temperature was recorded to be 55°C on 14 August. Pivot tables were used - due to the
sheer quantity of data that had to be analysed - to determine the hourly maximum and minimum TPV
values per day, and from those a daily maximum and minimum TPV was derived. Results indicate that
the surface temperature follows the same prole as the ambient temperature, suggesting reliability of the
measurements.
Figure 13. Ambient and PV surface temperature.
Source: own elaboration.
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5. CONCLUSIONS
Sensor measurements (voltage, current and temperature) were obtained from the remote ST and sent to
the MT using the CC1101 transceiver. The daily maximum of the voltage was recorded to be between
12.76 V and 15.44 for the said period, thereby not exceeding the rated Vmp of 16.5 V for these PV
modules. In addition, the PV current that was measured remotely for the same period, indicated more
current for a sunny day (2.32 A) than a cloudy day (1.98 A), both which are less than the rated Imp of 2.44
A. These results showed a 4.9% error percentage for voltage measurements and a 3.9% error percentage
for current measurements.
Temperature measurements were also taken remotely arriving at an error percentage of 0.59%, TPV was
observed to be signicantly higher than Ta during the day and more so around midday. An even wider
gap was seen in the two parameters on a sunny day, compared to a cloudy day, whereas at night, TPV and
Ta were evidently similar.
The research did not focus on the dierent types of PV modules, actuators or solenoid valves. The
inclusion of an energy regulator and storage system also did not form part of the research. This research
has unfolded possibilities of future studies that could contribute to the work of maintaining optimum
power of PV modules. This includes comparing the eect of cooling the PV module using a water sprayer
in relation to a change in the orientation angle on the output power of the module. Incorporating cloud
storage for monitoring of the output power and surface temperature from any location at any time can
also be considered for further research.
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