An Approach for Estimating Lightning Current Parameters Using the Empirical Mode Decomposition Method

Area of Science:

• Electrical Engineering
• Atmospheric Physics
• Data Science

Background:

• Accurate lightning current parameters are essential for predicting transient voltages in power systems.
• Current standards recommend regional classification of lightning characteristics, but global uniformity is often assumed.
• There is a recognized need for improved methods in lightning current measurement and analysis.

Purpose of the Study:

• To describe a system for direct lightning current measurements.
• To analyze observed data and obtain statistical lightning parameters and correlations.
• To propose a novel method for classifying and analyzing lightning data using empirical mode decomposition (EMD).

Main Methods:

• Installation of a direct lightning current measurement system on Mount Lovćen.
• Statistical analysis of measured lightning data using Matlab.
• Application of empirical mode decomposition (EMD) for data classification and analysis.

Main Results:

• Acquisition of statistical data on key lightning parameters.
• Identification of correlations between different lightning parameters.
• Demonstration of a novel EMD-based approach for lightning data analysis.

Conclusions:

• The developed methodology allows for automated analysis of large lightning datasets.
• Lightning parameters can be expressed in probabilistic terms based on site-specific measurements.
• The EMD approach offers a promising tool for advancing lightning research and engineering applications.