Sensor Fusion and State Estimation of IoT Enabled Wind Energy Conversion System.

Area of Science:

• Engineering
• Computer Science
• Renewable Energy Systems

Background:

• Renewable energy, particularly wind power, is increasingly critical.
• Wind turbines require reliable sensor data transmission for monitoring and maintenance.
• Existing wireless communication methods face challenges in industrial IoT environments.

Purpose of the Study:

• To propose an Internet of Things (IoT) based communication framework for reliable data transfer from wind turbines.
• To enhance the integration and utilization of data from multiple sensors on wind turbines.
• To improve the accuracy of wind turbine state prediction and monitoring.

Main Methods:

• Development of an IoT communication framework utilizing repeat-accumulate coded communication.
• Implementation of a sensor fusion algorithm to integrate multi-sensor observations.
• Consideration of unpredictable wireless channel characteristics in the communication design.

Main Results:

• The proposed scheme accurately predicts the operational state of wind turbines.
• The system demonstrates superior performance compared to traditional estimation schemes.
• Repeat-accumulate coding significantly enhances communication reliability.

Conclusions:

• The developed IoT framework ensures reliable wireless communication for wind farms.
• The fusion algorithm effectively leverages multi-sensor data for precise state estimation.
• This approach offers a robust solution for wind turbine monitoring and maintenance.