@article{DAI2025, 
author = {WenHan DAI and XueWei WANG},
title = {Analysis of the time-frequency domain features of photovoltaic new energy metering signals},
year = {2025},
journal = {Journal of Beijing University of Chemical Technology (Natural Science Edition)},
volume = {52},
number = {2},
pages = {65-75},
keywords = {photovoltaic new energy, time-frequency domain features, feature extraction, eigenvector matrix},
url = {https://www.sciopen.com/article/10.13543/j.bhxbzr.2025.02.008},
doi = {10.13543/j.bhxbzr.2025.02.008},
abstract = {The output of photovoltaic new energy generation has complex dynamic features, which leads to inaccurate energy measurements. In order to explore the features of photovoltaic new energy power generation, a new energy measurement signal matrix was first established, and an unequally spaced interval STFT algorithm was then proposed based on the finite coverage theorem. A time-frequency domain data representation model was then constructed to represent the real and imaginary parts of the time-frequency domain information of the three-phase voltage and current of the energy measurement signal. This leads to a feature matrix which represents the important features in the time-frequency domain. Finally, important time-frequency domain features of photovoltaic new energy signals were extracted, providing a theoretical basis for determining the time-frequency domain feature parameters of the experimental signal for energy meter error testing.}
}