Photovoltaic Station based on ESP32 and Two-Axis Movement
Mechanism Controlled by Solar Tracking Algorithm for Rural Areas
EDU ESCALANTE1, RICARDO YAURI1,2
1Facultad de Ingeniería,
Universidad Tecnológica del Perú,
Lima,
PERÚ
2Universidad Nacional Mayor de San Marcos,
Lima,
PERÚ
Abstract: - Rural areas suffer from an energy deficiency due to their difficult access and low economic
conditions, which limits their development and quality of life. The conversion to renewable energies, such as
photovoltaic solar energy, emerges as a viable alternative to meet this need, but it is necessary to consider the
technical and economic challenges associated with its implementation to guarantee its long-term viability.
Research background highlights the potential of solar-powered home PV stations as a clean alternative to fossil
fuels in diverse climates such as Peru, where coastal regions can benefit from optimal charging infrastructure
due to high projected solar radiation. The research shows an autonomous control system integrated into a
photovoltaic station with solar tracking for which a validation prototype was developed. As a result, the
prototype of the autonomous control system with solar tracking demonstrated its effectiveness in capturing
energy and visual monitoring verified the dynamic adjustment to light conditions to optimize solar collection.
The main conclusion is that the implementation and remote monitoring of a photovoltaic station with two-axis
solar tracking demonstrated the viability of the technology in obtaining energy efficiently.
Key-Words: - photovoltaic station, ESP32, sun tracking, rural zones, remote monitoring, solar tracking, LDR.
Received: May 5, 2024. Revised: November 16, 2024. Accepted: December 4, 2024. Published: December 31, 2024.
1 Introduction
Currently, there is an energy deficiency in rural
areas or human settlements because they do not
have electricity due to remote or poorly accessible
areas. Furthermore, as they belong to areas of low
economic level, they are not considered in future
electrical planning, showing a lack of support from
the state added to the difficulty of access, the
investment in electrification, and the management of
uncontrolled zonal growth of the population, [1],
[2]. The lack of energy affects economic
development and the quality of life of people,
because there are limitations in areas such as health
and education, [3], [4]. The conversion of renewable
energy appears as a solution due to the absence of
electricity in the sectors, since they are inexhaustible
sources of energy, [5], [6]. With the use of
renewable energy, installation, operating, and
maintenance costs are reduced because photovoltaic
stations with solar panels can support some of the
basic services required by inhabitants of rural areas.
However, there is a related problem because these
systems must be placed over large areas of a region
to meet the needs since they need a clear area to
obtain sunlight. On the other hand, climate
variability and adverse atmospheric conditions can
reduce the efficiency of solar panels, [7], [8].
In the review of the literature, it was found that
many investigations seek to promote the acquisition
of a renewable energy system [9], based on the
design and implementation of a domestic
photovoltaic station, [10], [11]. For this reason, in
the context of countries with a diversity of climates,
such as Peru, optimal charging infrastructures are
implemented to supply energy considering that the
solar radiation projected for the year 2024 can
generate the equivalent of 398 MegaWatts [12],
[13]. For this reason, the rural areas of the coast of
Peru are an optimal place for the use of solar panels,
[14], [15].
In relation to the use of solar panels, some
papers describe the use of bifacial solar cells, which
increase energy generation in relation to the
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elevation of the module, [16], [17]. It is also
indicated that a stable relationship between charge
and energy consumed is increased with the use of
Lithium-Iron Phosphate batteries [18], [19], Lead-
Acid (Pb), ultracapacitors and Lithium-Ion
capacitor,s [20]. Also, there are different types of
energy charging techniques such as the application
of constant voltage or current, [21], [22] using in
some cases electronic curve plotting systems for
characterization and evaluation, [11], [23].
Regarding the efficiency of the solar panel with
a tracking system, the paper describes that it
increases its performance by dynamically
positioning its location perpendicular to the solar
radiation for which a control stage, light sensors,
and direction motors are used, [24], [25].
Furthermore, this control stage is integrated by a
management algorithm, which reduces power losses
by improving energy quality, [26], [27]. In some
research, techniques based on artificial intelligence
algorithms with MPTT and Shunt Active Parallel
Filter algorithms are used to optimize energy
capture, [28], [29].
On the other hand, web-based systems have
been developed using the Python OTSun library to
analyze solar collection devices and thermal
simulation as photovoltaics. Users can use the
application by installing it locally using Docker
containers or by accessing the server provided, [30],
[31]. In addition, other research highlights the
importance of real-time monitoring due to the
intermittent nature of solar energy and its focus on
key aspects such as computer boards, sensors,
and cloud platforms, concluding that Amazon Web
Services, [32].
Due to the aforementioned, the research
question arises: How can a photovoltaic station for
homes in rural areas be designed? It is for this
reason that this paper describes the design and
implementation of a photovoltaic station with a two-
axis solar tracking mechanism, for which it seeks to
adapt its design to rural locations, which have
exposure to the sun for most of the year. This station
is made up of solar panels, a battery for energy
storage, and a structure for the movement of the
panel. In this way, a sustainable alternative is
provided to meet the energy demands of
communities that have limited energy resources.
The paper is presented in sections
corresponding to the introduction; Section 2 of
materials and methods describes the methodology;
Section 3 shows the results; Section 4 focuses on the
discussion and finally, the conclusions.
2 Materials and Methods
The research describes an autonomous control
system integrated into a photovoltaic station with
solar tracking for which a validation prototype was
developed, in smaller size and power to demonstrate
the integration of the technologies.
Therefore, the following specific activities are
conducted: The components are defined, and the
scientific method is applied by evaluating the
interaction of the station processes through a block
diagram of the battery charge management stage,
the solar tracking process, and the ESP32 hardware
(Figure 1).
Fig. 1: General block diagram
On the other hand, the design of the electronic
circuit is shown in Figure 2, which covers the
aforementioned processes: battery management
(green box), which displays the solar panel, the
optocoupler and the battery with its Management
System (BMS), and the solar tracking (orange box),
whose devices are the switches such as switches, the
LDRs connected with their resistors and the
servomotors, connected to the ESP32 device, which
acts as the processing block (purple box).
2.1 System Architecture Components
The station uses an HFK-7.5V polycrystalline
photovoltaic solar cell because it is economical and
for commercial use, with an operating voltage
greater than 5V for battery charge management. In
addition, an LDR 5528 photoresistor (LDR) is used
for the acquisition of solar tracking data, comparing
the best position of the light in horizontal and
vertical directions.
The ESP32 development board that controls the
algorithm has a 32-bit processor and WiFi
connectivity and is programmed using the
ARDUINO IDE environment to manage sensor
data, power charging and actuator control. For
energy storage, a compact device with a BMS
system and 'Quick Charge 3' technology is used.
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DOI: 10.37394/232017.2024.15.21
Edu Escalante, Ricardo Yauri
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Finally, SG90 servomotors are used to move the
base horizontally and the solar panel vertically.
Fig. 2: Electronic diagram of the system
2.2 Electronic Circuit for Battery Charge
Management
Once the system components have been defined, the
design process of the energy management stage is
defined, which begins with the ADC module of the
ESP32, energy control with the switches, storage
with a battery, and regulation with the internal BMS
system. of the battery and the delivery of power to
other external components (Figure 3). The design
of the electronic circuit of the energy management
stage is shown in Figure 4, consisting of the solar
panel on the left side, the optocoupler in the upper
central part, the battery, the internal BMS system in
the lower central part, and the module ESP32 on the
right side.
Fig. 3: Block diagram for battery charge and
discharge management
Fig. 4: Electronic circuit for battery charge
management during discharge
The processes related to energy management are the
following:
Energy Acquisition. It converts solar energy
into electricity using the solar panel with the
support of the solar tracking system.
Energy Measurement. It is done through the
ESP32, which measures the battery voltage
through pin A1 connected to the positive side,
performing an analog-digital conversion.
Power Outage. It interrupts the flow of energy
from the solar panel to the battery when it is
100% charged, using the data obtained from the
ESP32. An optocoupler is used for this function.
Energy storage. The battery is constantly
charged while it is not 100% charged using the
regulator system. Adjust the battery charge from
4.4V to 5V.
Energy Discharge. The last process involves
discharging the battery through two ports: one
to charge the ESP32 device and another to
charge an additional device.
2.3 Control Algorithm for Solar Tracking
The operation diagram of the algorithm is shown in
Figure 5, where it begins with the process of
acquiring data from the sensors and the time until
the correct positioning of the solar panel facing the
sun. The algorithm that was implemented for this
project includes a library for the use of servomotors,
ADC functions, and a system interrupt in the
Arduino IDE program. The LDR sensors are
connected to bias resistors for light-intensity data
collection along with external switches that activate
the interrupt functions.
The algorithm performs data acquisition through
the LDRs using the ADC and the trigger signal
detection as an external switch. The trigger variables
are “pos” and “ps2”, which will take the angular
position data for the servomotors and the variables
“int1” and int2” to control the internal interrupt
function (Table 1). The libraries used to control the
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servomotor are in “ESP32Servo.h”, while “WiFi.h”
and “time.h” allow to initialize the Wi-Fi network.
Fig. 5: Block diagram of the control algorithm for
solar tracking
Table 1. Algorithm variables
Input variables
Transformed
variables
Activation
variables
Ldr_1
v_ldr1
int1
Ldr_2
v_ldr2
int2
Ldr_3
v_ldr3
pos
Ldr_4
v_ldr4
ps2
The mathematical model used for system
calibration is essential to ensure the accuracy and
efficiency of the solar tracking mechanism
operation. During the data acquisition process, the
voltages obtained from the photoresistors (LDR) are
calibrated because each one has different resistance
values. To do this, a set of equations is implemented
that directly relate the sensor signals to the
movement of the system in the four main directions:
up, down, left and right.
During the data acquisition process, the LDR
voltages are calibrated, they already have different
resistance values. Therefore, as a result, we have the
equations shown in Table 2 with respect to the
variable “v_ldr1” (equation 1), “v_ldr2” (equation
3), “v_ldr3” (equation 5) and “v_ldr4” (equation 7).
Subsequently, these values are transformed so that
they are related to the movement and directions up,
down, left and right, using the variables “prom_top”
(equation 2), “prom_bot” (equation 4), “prom_left”
(equation 6) and “prom_right” (equation 8).
Figure 6 shows the algorithm diagram for
transforming and updating the position variables of
the servomotors, which starts by reading the data in
four positions. Then, the difference between the
upper and lower values is evaluated by updating it
in 10 units, checking if its angle is greater than 90.
When it is less than 90 in the vertical position, it
rotates horizontally clockwise, however, the
opposite occurs when it is greater than 90. The
algorithm detects when the limits of the conditioned
values, which are configured for the rotation of the
servomotors, are exceeded, not taking negative
values or greater than 180 due to its working range.
Table 2. Calibration and transformation equations
Transformation equation
(eq. 2)
prom_top= (𝑣_𝑙𝑑𝑟1 +
𝑣_𝑙𝑑𝑟4)/20
(eq. 4)
prom_bot = (𝑣_𝑙𝑑𝑟2 +
𝑣_𝑙𝑑𝑟3)/20
(eq. 6)
prom_left = (𝑣_𝑙𝑑𝑟3 +
𝑣_𝑙𝑑𝑟4)/20
(eq. 8)
prom_right = (𝑣_𝑙𝑑𝑟1 +
𝑣_𝑙𝑑𝑟2)/20
Fig. 6: Position Variables Update Flowchart
2.4 Integration of System Components in the
Pilot Test Model
The assembly of the prototype model was conducted
(Figure 7), which is integrated by the prototype base
with the servomotor, energy stage, ESP32 device,
and mechanical structure for vertical and horizontal
movement.
Additionally, the photovoltaic panel is mounted
so that it can be oriented towards the sun, with
external cables to avoid entanglement during the
platform's rotation. Safety considerations, such as
overload protection, have been considered, ensuring
safe operation of the station.
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Fig. 7: System structure components
3 Results
This section describes the results related to the
integration of the components, the electronic circuit
developed for battery charging and the control of
solar tracking based on two axes focused on the
prototype. Figure 8 shows the integrated
components such as the battery, the ESP32 SoC that
controls the servomotor to perform the horizontal
movement of the platform, along with the LDRs and
the solar panel.
Fig. 8: Electronic components of the base and upper
part of the structure
To evaluate the energy supply behavior of the
photovoltaic station, battery load tests were
conducted in the circuit, conducting voltage
measurements to determine its behavior (Figure 9),
obtaining full load values of 4.08V (68% load).
(Figure 9 (a)) and current of 80.1 mA in series
(Figure 9 (b)), when the solar panel is positioned
horizontally directly to the sun (Table 3).
To monitor the data, the position and direction
of the solar cell location mechanisms, LDR data,
and servomotor status, an information visualization
stage was integrated using a ThingSpeak web
service, which provides an interface for remote
access. The ESP32 module sends this information
via the Internet to monitor widgets, using the HTTP
protocol, to display the LDR data, servomotor
status, and activation of the tracking system as seen
in Figure 10. This is done using the ThingSpeak
Platform which allows for monitoring real-time data
such as solar cell position, LDR data, and servo
motor status. Setup involves creating a channel,
generating API keys, and programming the ESP32
to send data at minimum 15 second intervals.
(a)
(b)
Fig. 9: Measurement tests of (a) voltage generation
and (b) current consumption
Table 3. Battery charge and voltage ratio
Battery charge
Voltage
1%
3.4 𝑉
25%
3.65 𝑉
50%
3.9 𝑉
100%
4.4 𝑉
4 Discussion
The selection of system components was
appropriate in relation to the choice of devices that
are adequately integrated at an electrical level in a
reduced space, which was validated in a pilot test.
The system components, such as the battery,
allowed the ESP32 SoC device and the servomotors
that perform the horizontal and vertical movement
to be adequately powered. In addition, the four LDR
sensors allow adequate sunlight detection, acting
automatically to modify the orientation of the
servomotors.
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Fig. 10: Measurement of LDR values: ADC Voltage
vs Time
In relation to the energy supply behavior, it was
verified that the solar panel turned out to be efficient
in converting solar energy into electrical energy,
generating an average current of 80mA during a
short-circuit measurement and managing it
effectively, guaranteeing optimal operation of the
prototype in the pilot test.
The integration of an information visualization
stage, using the ThingSpeak web service, allowed
effective monitoring of data related to the position
and direction of the solar cell location mechanisms
using the monitoring widgets. The generated graphs
adequately showed that the system operated
continuously 24 hours a day, optimizing the
obtaining of light for the solar panel during the
hours of greatest intensity, verifying the
visualization of the LDR data obtained for real-time
verification. Therefore, the system's ability to
dynamically adjust to lighting conditions is evident,
maximizing solar collection efficiency.
The tracking system is a contribution to solar
energy harvesting, making it cost-effective and
sustainable in rural settings, with the potential to
save energy and reduce dependence on non-
renewable sources. Despite its scalability, durability
in harsh conditions and internet availability are
barriers that could be overcome by rugged materials
and local connectivity solutions such as LoRa.
5 Conclusion
The implementation of a photovoltaic station was
conducted with a two-axis solar tracking mechanism
based on light-intensity sensors. In addition, the
successful integration of solar panels, an energy
charging system, and ESP32 control device was
validated. The appropriate components for the
construction of the system were identified in
relation to the limitations inherent to the
development of a pilot-scale prototype, checking the
energy generation necessary to charge the 3.7V
battery and power the device and sensors. The
remote Web monitoring application resulted in an
efficient way to determine the performance of the
system operation due to the ease and accessibility of
the information.
Compared to other solutions, the system
proposed in this work stands out for its simplicity
and efficiency in implementing solar tracking using
light sensors, in contrast to previous works that
employ more complex or expensive mechanisms
such as predictive algorithms or control systems.
Unlike these approaches, which require more robust
infrastructure and higher processing resources, this
solution focuses on maintaining energy efficiency
and accessibility in limited environments.
In future work, it is recommended that the
solution be evaluated on a scale of experimental
tests in the field and with a dedicated power stage
for servomotors, since it alters the proper calibration
of positioning and other devices. In addition, you
should consider using more solar panels of the same
voltage or others with greater power. Finally, for
greater solar tracking control, the use of an
algorithm based on fuzzy logic is suggested, since
environmental alterations that do not follow a
deterministic pattern could appear.
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WSEAS TRANSACTIONS on ELECTRONICS
DOI: 10.37394/232017.2024.15.21
Edu Escalante, Ricardo Yauri
E-ISSN: 2415-1513
202
Volume 15, 2024