학술논문

Detection and Assessment of Power Quality Disturbance in Varriable Distributed Energy Resources using Variational Mode Decomposition
Document Type
Conference
Source
2023 IEEE 3rd International Conference on Smart Technologies for Power, Energy and Control (STPEC) Smart Technologies for Power, Energy and Control (STPEC), 2023 IEEE 3rd International Conference on. :1-6 Dec, 2023
Subject
Aerospace
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Simulation
Power quality
Mathematical models
Frequency estimation
Real-time systems
Power electronics
Task analysis
VMD
sag
swell
harmonics
Language
Abstract
The assessment of power quality related disturbance has been a significant challenge due to enhanced usages of electronic equipment. Considering the fact that majority of power electronic equipment’s performance are susceptible to voltage and frequency variation and is also dependent on the quality of supplied power, the tools for adequately identifying presence of any power quality related disturbance in grid becomes indispensable. Catering to this vital aspect of power quality assessment, in this work, we propound a variational mode decomposition(VMD) enabled classifier, to effectually detect and categorize power quality disturbances. VMD acts by decomposing the signal into several modes that carry the signature of disturbances. Different types of events like SAG, SWELL and Interruption would have different magnitude signature in different modes of VMD. The primary mode i.e. Model has been observed to contain the signature pertaining to the disturbance leading to power quality issues, thus we have utilized Mode 1 for classifying the such disturbances. In order identify other disturbances we utilize other modes of VMD. The mathematical modeling and simulation are carried out to validate the method. The test system has been modeled to generate the data set and generated data set has been stored using PSCAD/EMTDC.