The proposed IoT-based distribution transformer condition monitoring system enables real-time monitoring of distribution transformers, identifying such deviations as overload conditions and overheating.

IoT technology collects and displays essential operational data locally on an LCD interface.
Additionally, this data is transmitted remotely to cloud platforms like Adafruit.io for analysis, allowing for proactive maintenance. The system’s architecture incorporates sensors interfaced with a microcontroller, ensuring seamless data acquisition and transmission. This system empowers utilities to optimize power distribution networks and enhance operational reliability cost-effectively.

Note: The LCD display is optional for local data monitoring. If it is not connected, data will still be displayed remotely on the IoT dashboard.

In the system design, the ACS712 current sensor detects the transformer’s current, and identifies overload conditions, while the DHT humidity and temperature sensor monitors the temperature of both the transformer and its surroundings. The ultrasonic sensor tracks the transformer’s oil level.
The Adafruit IO dashboard enables data monitoring on an IoT platform. The ESP32 board connects the system to a Wi-Fi network, sending data to the IoT dashboard. The authors’ prototype is shown in Fig. 1, and the required components are listed in the Bill of Materials table.

Fig. 1: IoT-Based Distribution Transformer Condition Monitoring System

Project Prerequisites: What You’ll Need to Get Started

The Arduino IDE is used to write the software, and the ESP32 board must be installed on the IDE. Follow the steps provided on the ESP website to add the ESP32 to the Arduino IDE. After installation, the libraries for the DHT sensor, ACS712 current sensor, and LCD display must be added via the Arduino Library manager.

MQTT and Adafruit IO are employed to display the data on the IoT dashboard. Sign in to an
Adafruit IO account and create an API by following the steps outlined by Adafruit IO.

For more information, visit:
https://io.adafruit.com/api/docs/#about-the-api-docs

Additional details can be found here:

https://cdn-learn.adafruit.com/downloads/pdf/adafruit-io.pdf

Code for Distribution Transformer Monitoring System

In the source code, begin by defining the pins for the sensors and LCD display, then include the necessary libraries. Configure the Wi-Fi SSID and password for the network near the transformer. Next, configure the Adafruit MQTT API as outlined earlier.

Fig. 2 illustrates how to configure the MQTT API in the code. Subsequently, define the LCD pins. The system uses an 8-bit data setup for the LCD. Fig. 3 demonstrates how to set the pins for both the LCD and sensors.

The code also contains functions for gathering sensor data and sending it to the Adafruit MQTT IO dashboard. Finally, select the appropriate board and port, and upload the code.

Fig. 2: Configuring the Adafruit MQTT API in code

Circuit Diagram for IoT-Based Distribution Transformer Condition Monitoring System

Fig. 4 presents the circuit diagram for the IoT-based distribution transformer condition monitoring system. It comprises the ESP32 board, DHT2 humidity sensor, HC-SR04 ultrasonic sensor, ACS712 current sensor, 16×2 LCD, and several other components.

Construction and Testing

To begin, upload the source code to the ESP32 board, then connect all components as shown in Fig. 4. Power the system for local data monitoring via the LCD. Fig. 5 displays local data on the LCD, while remote monitoring on the Adafruit dashboard shows real-time temperature and current data (see Fig. 6).

Fig. 5: Local data monitoring on the LCD

Fig. 6: Real-time temperature and current data on the dashboard

Fig. 7: Various load connection diagrams

For transformer testing, refer to Fig. 7, which outlines various load connection diagrams. The upper diagram shows the inductive load, the middle diagram shows a single resistive load, and the lower figure shows two resistive loads in parallel. Testing the transformer’s performance involves evaluating the three distinct load conditions. The authors’ prototypes are displayed in Figs 8 through 10 for the three conditions:

(a) An inductive load is applied to assess the transformer’s behavior under variable loads. The prototype is shown in Fig. 8.

Fig. 8: Inductive load testing of the transformer

(b) A single resistive load is connected. The corresponding prototype is shown in Fig. 9.

Fig. 9: Single resistive load testing of the transformer

Fig. 10: Two resistive loads for testing the transformer

(c) Two resistive loads are connected in parallel. The prototype is shown in Fig. 10.

As the load increases in each scenario, the current drawn from the transformer also rises, while the output voltage decreases due to the transformer’s internal impedance. This behavior is characteristic of transformers under load, where voltage regulation diminishes as the load current increases.

If the current exceeds the preset threshold of 1A, the system triggers an alert on Adafruit IO, signaling an overcurrent situation. This proactive alert helps prevent transformer damage and ensures timely interventions to maintain system reliability and safety.

Source: Electronics For You