IoT-based solar power monitoring systems consist of several interconnected components that work together to provide comprehensive monitoring and control: Contact online >>
IoT-based solar power monitoring systems consist of several interconnected components that work together to provide comprehensive monitoring and control:
Energy demands are steadily increasing, leading to excessive consumption of fossil energy resources. Indeed, to meet the energy needs of today''s society, it is necessary to find more sustainable, effective and clean solutions for the environment. Among renewable energies sources, solar energy is considered the most fascinating source that could balance this gap between the consumption and the production, thanks to the remarkable decreasing in its cost and the advancement in this technology [1]. With modern monitoring and control systems, this technology become a reliable sources of energy [2].
Smart grids exploit the capability of information and communication technologies (ICT) to improve the sustainability, quality performance and balance of energy production and demand previsions, whereas reducing resources consumption. ICT also help smart grid to integrate renewable energies.
Internet of things (IoT) is playing a crucial role in the daily life of humans by enabling the connectivity of many physical devices through internet where the devices are intelligently linked together enabling new kinds of communication between things and people, and between things themselves to exchange the data for monitoring and controlling the devices from anywhere around the globe using the internet connection [3]. Additionally, The communication between machines or different devices is possible without human intervention using the IoT applications [4].
The idea behind IoT principle is to connect the sensors and devices of a special system on a common network through wired or wireless nodes. In general, IoT based wireless systems are widely chosen in order to avoid associated risks with wired systems. While keeping in mind the needs of near future, where every device will be smart, automated and connected via internet. For more details, authors in [3] have investigated some technical details that refer to the IoT enabling technologies, protocols, and applications. They have explained the link between the IoT technology and the other emerging technologies including cloud services, big data analytics and fog computing.
The purpose of PV monitoring systems is to offer continuously a clear information about various parameters, namely the energy potential, extracted energy, fault detection, historical analysis of the plant, and associated energy loss. Furthermore, the monitored data can be used for preventive maintenance, early detection of warning and evaluating the weather variations etc. [1, 5]. Many classifications of PV monitoring systems based on the internet technology, data acquisition systems used and monitoring system methods have overviewed in detail in [2].
The remote supervising technology could be used in numerous applications related to solar field, namely: Solar plants, solar stations for charging electric vehicles [6], micro grids [7] and solar street lights and so on. Also in many other vital applications such as the monitoring of the water quality [8], and the monitoring and control of solar thermal station with solar collector [9].
Since we are interested in photovoltaic part of the solar energy, we have studied the state of the art of wireless remote monitoring related to PV applications during the last decade. Starting by a comprehensive review on monitoring systems for photovoltaic plants; the communication and storage in data acquisition systems, challenges and opportunities in existing and futuristic systems have discussed in [1]. PV performance metrics was monitored and processed ubiquitously using cloud data logging with a LabVIEW based monitoring system was presented in many researches [10,11,12,13].
Researchers in [14] have elaborated a low cost IoT application based on embedded solar PV monitoring system using a GPRS module and a microcontroller to send the data measured. However, authors in [15] have reported a real-time monitoring of solar home systems based on Arduino microcontroller with 3G Connectivity. Whereas, a remote monitoring for solar photovoltaic systems in rural application using GSM voice channel have presented in [16].
An IoT-based experimental prototype for monitoring of photovoltaic arrays has been developed in [17]. Furthermore, a cost effective IoT technique in order to remotely supervise the maximum power point (MPP) of a photovoltaic system has described in [18].
A health monitoring system of a solar farm has been developed in [4], with a validation concept using eight solar panels to monitor the string voltage, string current, temperature and humidity. The system is controlled by CC3200 microcontroller with ARM Cortex-M4 architecture.
Since PV panels are sensitive to environmental parameters, specifically irradiance and temperature, the electric data, weather information are considered essential for analysing PV station state. This is why supervising the performance of every PV systems is very important [13, 19].
The rest of the paper is organized as follow: Sect. 2 presents the architecture of the proposed IoT based photovoltaic data monitoring. Section 3 presents the hardware and software of the designed system. Results are described in Section 4 and a discussion is investigated in Sect. 5.
Since the data needs to be collected, processed, stored and analyzed in an IoT setup, a low cost data pipeline for monitoring the electrical and environmental parameters in a photovoltaic station is designed in this work.
In the proposed monitoring system, the ESP32 DEVKIT V1 board acts as the microcontroller that acquires and processes the incoming data from various sensors, then it transmits the processed data to the cloud and servers via built-in Wi-Fi. Data communication occurs in two steps: The first step is the communication between sensors, and the controller via inter-integrated circuit protocol (I2C), then the second step is the communication between controller and the cloud service application via Wi-fi protocol.
The data collected by the various sensors is stored in the cloud (web server) or locally. The exchange is based on client and server requests. A client launches an HTTP request, and the server returns an answer. This protocol defines the communication between the different parts of the web. The bloc diagram of the proposed IoT solution that used to monitor photovoltaic plants, is illustrated in Fig. 1 bellow:
The experimental setup of the system hardware, drawn with fritzing software is illustrated in Fig. 2.
The experimental setup of the system
The developed experimental prototype consists mainly of the PV system including the battery, sensors and the dual core ESP32 controller (Figs. 3, 4, 5):
The PV panel used in the prototype
The current/voltage DC sensor INA219
The Luminosity sensor BH1750
The photovoltaic system in this experimental setup consists of three PV panels, a DC–DC Buck converter and a Lithium ion battery as a load.
The PV panels consist of a set of parallel and series PV cells that convert the sun light into DC electrical energy. Three small polycrystalline PV panels with a dimension of 115 mm × 85 mm are capable to generate 1.6 W of power and 12 V of voltage for each one, are used in this work.
To harvest the maximum of generated PV energy and reduce the power losses, a stage of adaptation is necessary. For this reason, a dc–dc converter is placed between the PV generator and the load to adjust the maximum power point MPP using an MPPT control [20]. Since a lithium ion battery is used as a load, an associated commercial regulator TP4056 that incorporates protection features is also used, but it is important to note that this regulator does not incorporate the MPPT algorithm in its features.
The Lithium-ion battery used in mobile phone applications, is employed as a load in this monitoring prototype. This battery of 3.7 V nominal voltage is protected by the regulator that controls the charging current (1A maximum). Besides, It is equipped with an overload protection circuit (charging stops at 4.3 V), an excessive discharge protection to avoid destruction of the battery, and an overcurrent detection at the battery output level to avoid the battery damage in case of a short circuit.
The measurement sensors network in the presented application involves three mean sensors that sense four physical signals: Current, Voltage, irradiation and temperature.
This a smart sensor that sense, makes also filtering and analog to digital conversion. INA219 sensor is a current and power sensor that gives the total power consumed by shunt load and gives respective reading in digital form. It can handle high side current measuring up to +26 V of voltage and up to 3.2A of current, even though it is powered with 3.3 or 5 V. It is equipped with an I2C bus, which makes it easy to retrieve measurements using a microcontroller. The essential characteristics of this sensor are listed in Table 1.
It is possible to check the rate of sunshine using the BH1750 according to different parameters: time of day, inclination, location, orientation, season BH1750 is a digital ambient light sensor integrated circuit, which considered as a lux meter that gives a wide range of measurement and high resolution (1–65535 lx). The BH1750 module communicates via the I2C bus with the ESP32 controller to transmit the measured data.
A Lux meter (in this work BH1750 sensor) measures the sunlight intensity in (lux) and the direct conversion of its value to irradiance value in (W/m2) is not possible since the nature of the measured parameter is different. But one of the important claims of this paper is using the fusion sensor principle to lower the cost of the instruments used to collect irradiation. Instead of using an expensive pyranometer, a software approximation is used based on data collected from both the BH1750 sensor and a calibrated pyranometer LP02 of the laboratory to estimate a relationship between the two measurements.
In this paper, the laboratory pyranomter is exploited to find the global luminous efficacy relationship. The global luminous efficacy is defined as the ratio of global illuminance and global irradiance [21, 22]. This relationship that is found a linear function, was deduced based on numerous physical measurements with both instruments approximately in the same time, then it was implemented in the software to convert the reading of the BH1750 sensor to irradiance.
The solar radiation sensor used to measure irradiance then extract this relationship is the pyranometer LP02, which complies with class C specifications of the IEC 61724-1 standard. This scientific instrument costs more than $600, and owing to this low-cost method, the irradiance measurement becomes possible with acceptable accuracy using an illuminance sensor that costs less than 10 $.
The sensor DHT11 is a low cost temperature and humidity sensor, which is widely used in embedded projects. Its temperature range is from 0 to 50 degrees Celsius with ± 2 degrees accuracy. DHT11 has good quality, fast response time and provides high stability. For temperature measurement, it has a thermistor embedded in it, which measure temperature. To ensure the accuracy of measurements, this sensor was also calibrated using another trustworthy thermometer.
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