Wind Energy Monitoring and Control System - Electronic Engineering Guide
1. Introduction
This project involves designing a Wind Energy Monitoring and Control System that tracks power generation from a wind turbine, monitors key electrical and environmental parameters, and controls load management to optimize energy usage.
2. Objectives
• Monitor voltage, current, and power output from wind
turbines.
• Log and transmit data for remote monitoring.
• Implement control mechanisms to divert or store excess power.
• Provide real-time display and data analytics.
3. Components Required
• Arduino Uno / ESP32
• Voltage Sensor (e.g., ZMPT101B)
• Current Sensor (e.g., ACS712)
• Wind Speed Sensor (Anemometer)
• LCD Display (16x2 or OLED)
• SD Card Module or IoT Module (ESP8266/ESP32)
• Relay Module
• Battery Bank or Load Resistor
• Resistors, Wires, Breadboard
4. System Overview
The system continuously reads electrical signals and environmental conditions from the wind turbine setup. It calculates generated power and logs this data locally or transmits it to an IoT cloud platform for visualization and control.
5. Working Principle
The voltage and current sensors measure output parameters. Using these values, real-time power is calculated. Anemometers track wind speed. The system can control output loads through relays based on energy generation levels.
6. Circuit Design and Microcontroller Interface
• Voltage sensor → Analog pin (A0) of Arduino
• Current sensor → Analog pin (A1)
• Wind sensor → Digital or analog pin (based on type)
• Relay → Digital output pin (D7)
• LCD/OLED display → I2C or direct GPIO interface
• SD Card or Wi-Fi Module for data logging
7. Sensor Integration and Data Acquisition
Sensors are calibrated to ensure accurate readings. Data from sensors is sampled at regular intervals, filtered, and used to compute power using the formula: Power = Voltage × Current.
8. Control System Design
Relay modules are controlled based on energy output to either divert excess energy to storage, activate load resistors, or trigger alerts. The control logic ensures safe and efficient operation.
9. Data Logging and IoT Connectivity
Data can be stored locally using an SD card module or uploaded to IoT platforms like ThingSpeak or Blynk using ESP8266/ESP32. This enables remote access, analytics, and visualization of wind energy performance.
10. Software and Code Structure
• Initialize sensors and display
• Read voltage and current periodically
• Compute and display power
• Control relays based on thresholds
• Log or transmit data
• Loop execution with timing control
11. Power Supply Considerations
• Use voltage regulators or buck converters to power the
Arduino from turbine output or battery.
• Isolate relay and sensor power from MCU where necessary.
• Ensure surge protection and overcurrent safety.
12. Applications
• Small-scale wind farms
• Remote off-grid wind energy systems
• Hybrid renewable energy systems
• Educational prototypes for green energy research
13. Limitations and Future Enhancements
• Measurement accuracy depends on sensor quality.
• Environmental variations can affect performance.
• Future upgrades: AI-based predictive control, GSM alerts, cloud dashboard
integration, battery management systems.
14. Conclusion
This system demonstrates the effective use of embedded electronics and IoT to monitor and control wind energy systems. It offers a modular and scalable framework suitable for academic, experimental, and practical applications.