High-Accuracy Harmonic Source Localization in Transmission Networks Using Voltage Difference Features and Random Forest

This paper proposes a harmonic source localization method for power systems, combining voltage difference features with a random forest classifier. The method captures harmonic propagation patterns and optimizes network topology handling to ensure accurate and efficient identification across various configurations. Validated on IEEE standard transmission networks, it achieves high accuracy and scalability. While effective in transmission systems, distribution networks pose challenges due to complex topologies and high impedance. Future enhancements will focus on advanced feature engineering, data augmentation, and real-time processing to improve adaptability in diverse power system environments.