Introduction

This project focuses on developing an integrated system for monitoring and controlling power transformers in real time. The system continuously measures critical transformer parameters including voltage (within 180-250V operating range), current load, temperature, and power consumption. Using the ESP32 microcontroller, the system connects to Firebase cloud for remote data access and implements automated protection through relay-based load isolation when over/under-voltage conditions or temperature thresholds (50°C) are detected. LED indicators and buzzer alerts provide immediate local notification of abnormal operating conditions.

System Overview

Aim and Objectives

Aim:
Design and develop an integrated IoT-based transformer monitoring and control system for real-time health assessment and automated protection.

Objectives:

• Monitor transformer voltage, current, power, and energy consumption using PZEM-004T.
• Track transformer core temperature using MCP9808 precision temperature sensor.
• Implement automated load isolation via relay for over/under-voltage protection (180-250V range).
• Provide visual and audible alerts for abnormal operating conditions.
• Log all transformer data to Firebase for remote monitoring and historical analysis.
• Display real-time transformer status on a 20x4 LCD.

Features & Deliverables

• Voltage Monitoring: Continuous voltage tracking with safe operating range (180-250V) and automatic protection.
• Temperature Protection: MCP9808 precision sensor with 50°C threshold for overheating detection.
• Automated Load Isolation: Relay-based disconnection for over/under-voltage and overtemperature conditions.
• Power Monitoring: Real-time current, power, and energy consumption tracking via PZEM-004T.
• Cloud Dashboard: Firebase integration for remote monitoring, data logging, and trend analysis.
• Local Alerts: LED indicators for voltage and temperature status, buzzer for critical conditions.
• LCD Status Display: 20x4 LCD provides comprehensive local transformer status information.

Process / Methodology

Hardware Assembly

Components: ESP32, PZEM-004T v3.0, MCP9808 Temperature Sensor, 20x4 LCD (I2C), Relay Module, Voltage/Temperature LEDs, Buzzer, Power Supply.

• Integrated PZEM-004T for transformer electrical parameter measurement.
• Connected MCP9808 via I2C for high-precision temperature monitoring.
• Configured relay for automated load disconnection during fault conditions.

Software Development

• Developed firmware with voltage range monitoring (180V low, 250V high thresholds).
• Implemented temperature monitoring with 50°C protection threshold.
• Programmed WiFi connectivity and Firebase data synchronization routines.
• Created LCD display routines for real-time transformer status visualization.

Testing & Calibration

• Validated voltage threshold detection and relay response time.
• Tested temperature sensor accuracy against calibrated thermometer.
• Verified cloud data logging reliability under various load conditions.

Challenges & Solutions

• Challenge: Accurate voltage threshold detection without false triggers from transient spikes.
  Solution: Implemented moving average filtering and debounce timing for reliable threshold detection.
• Challenge: WiFi connectivity in industrial electrical environments with EMI interference.
  Solution: Used shielded connections and implemented robust WiFi reconnection logic.
• Challenge: Relay switching under load conditions.
  Solution: Selected appropriately rated relay modules with arc suppression for safe load switching.

Results & Impact

• Protection: Successfully detected and responded to all simulated over/under-voltage conditions.
• Monitoring: Provided continuous real-time data locally on LCD and remotely via Firebase.
• Prevention: Temperature monitoring enabled early detection of transformer overheating scenarios.
• Data Insights: Cloud-stored historical data supported informed maintenance scheduling decisions.

Future Enhancements

• Add oil level monitoring for transformer oil-cooled systems.
• Implement predictive maintenance algorithms using historical data trends.
• Develop SMS/email alert system for critical transformer faults.
• Expand to multi-transformer monitoring with centralized dashboard.

Demonstration / Access

• GitHub Repository: Coming soon
• Live Demonstration Video: Coming soon

Thank You for Visiting My Portfolio

I sincerely appreciate you taking the time to explore my portfolio and learn about my work and expertise. If you have any questions or wish to discuss potential collaborations, please feel free to reach out via the Contact section.

Best regards,
Damilare Lekan, Adekeye.