The information so collected is disseminated to the stakeholders using the existing internet network and the data can be accessed anywhere in the world from the website.
Solar energy is received on earth in the form of heat and light from the sun, and that is harnessed using a variety of techniques. Solar PV is the most sought after renewable energy technology in the present day. Solar PV applications: grid connected as well as off-grid systems are increasing but their installation is widely spread. Observing the output of the PV system when required is extremely important if the PV plant is a part of the local micro grid or a smart grid. Physical systems, which encompasses technologies such as smart grids, smart homes etc., is nothing but Internet of Things (IoT), augmented with sensors and actuators. In this work, PV panel condition is monitored using sensors and the acquired information is made accessible to the PV plant operator through IoT. Observing the plant or panel conditions from a remote location without having geographical barriers has several advantages. Experts estimate that IoT will consist of almost 50 billion objects by 2020.
Apart from large scale power plants, roof top PV generation is increasing as private households are opting for captive generation through static PV arrays on account of renewable energy policies and attractive incentive schemes. So, a low cost PV energy monitoring system with remote monitoring feature is useful in identifying the problems, energy yield assessment and load management. In this work, a PV output monitoring technique using a microcontroller and an integrated Wi-Fi module is developed.
A brief description of the hardware components used in the experimental work is given in this section. The total cost of the Sensors, the Ardiuno board and the Wi-Fi device used in this work is close to `800. The specimen chosen is a 30 Watt-peak PV panel having open circuit voltage of 21 Volt and a short circuit current of 1.6 and maximum voltage 18.75 Volt. The other components for the experimental work are selected by considering the maximum ratings of the PV panel. The PV panel circuit is closed through a rheostat.
Temperature Sensor - LM 35
LM35 is a precision IC temperature sensor with its output proportional to the temperature (in oC). The sensor circuitry is in a sealed packing, therefore it is not subjected to oxidation and corrosion due to external factors. LM35 temperature sensor measures temperature more accurately than thermistor. It possesses low self-heating and does not cause more than 0.1oC temperature rises in still air. The operating temperature range is from -55°C to 150°C. The output voltage varies by 10 mV in response to every oC rise/fall in temperature, and, its scale factor is 0.01V/ oC.
Current Sensor- ACS712
The Allegro ACS712 current sensor is based on the principle of Hall-effect. This sensor with a full scale value of 5 A is used in this work, which produces output voltage of 185 mV/A and the measurement range is -5 Amperes to +5 Amperes.
Voltage Sense Circuit
A simple voltage divider circuit, which consists of two resistors R1 = 66 kO and R2 = 12 kO connected across the PV voltage to be sensed. The fraction of the PV panel input voltage that appears across R2 (12kO) resistor is given to the Arduino board, which will never exceed 5 Volt.
The Arduino Uno board based on the ATmega328P is used in this work. The output of the temperature sensor, current sensor and the voltage divider circuit are connected to A0, A2 and A3 input pins of the Arduino board respectively. The Rx and Tx pins of the board are connected to Tx and Rx of the ESP8266 Wi-Fi module. Arduino is powered through a USB connector. The power supplies to the sensor ICs (temperature and current) and the Wi-Fi module is given through Arduino board.
Wi-Fi Module ESP8266
A highly integrated chip ESP8266 is used in this work and it occupies a small PCB area. Its cost is low. It offers a complete and self-contained Wi-Fi networking solution, allowing it to host applications. It serves as a Wi-Fi adapter; wireless internet access can be added to any development board based design with simple connections.
The code written in Arduino IDE software is uploaded. Then board reads the input at pins A0, A1, A3. A channel is created in "ThingSpeak.com" which can be accessed by a login identity (Username and Password). The Wi-Fi module is activated. Four linked fields are created to send the observed values of temperature, voltage, current and power. Power is computed as the product of voltage and current. The values are sent to the respective fields by the microcontroller using serial communication through ESP8266 and the Wi-Fi device. The experimental set up is shown in Figure 1. The electrical connection diagram is shown in Figure 2. The remaining input pins of the Arduino microcontroller can either be utilized for capturing other signals such as irradiation, wind speed etc or monitor temperature, voltage and current of another PV panel or PV array.
Results and Discussion
The value of each field is displayed in the channel created. The minimum time delay/interval between two values of a field is 15 seconds. However, it can be set to desired time interval by adjusting the delay in the code. The graphical display of the physical quantities Field1 - temperature of the PV module in oC, Field 2 - Voltage of the PV module in Volt, Field 3-Current of the PV module in Ampere and Field 4 û Power in Watt as observed at every 30 seconds is shown in Figure 3. The voltage and current were also measured using digital meters, showed the same values as displayed on the channel.
Monitoring of PV output is critical for fault identification and assessment of performance. A PV plant monitoring system based on IoT is developed. The monitoring system is shown to operate successfully. The information is disseminated to the stakeholders using the existing internet network and the data can be accessed anywhere in the world from the website. The monitoring technique developed is a low-cost solution which can be adapted for rooftop PV systems as well as large PV plants.
Authors: Padmavathi K., Vemanna K., B.Rashmia , Mahesha and Padmanabhan R., Department of Electrical and Electronics Engineering, BMS College of Engineering, Bengaluru, India
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