Seasonal signal analysis of distribution lines in smart grids via Hilbert-Huang transform

The increase of grid-connected renewable energy sources represents a hot topic for the operation and management of a smart grid, because the power injected into the grid by the most of them is unpredictable. Some constraints depend on the environmental condition, while some others depend on the need to guarantee stability, security and power quality of the grid. This implies that the power signals of distribution lines having distributed generators are typically a-periodic, non-stationary and nonlinear. Thus, mathematical tools usually adopted to analyze the electrical behavior of a distribution line can be inaccurate and reductive. This paper compares the seasons-based results obtained by applying the Fast Fourier Transform (FFT) and the Hilbert-Huang Transform (HHT) to the active and reactive powers of three different distribution lines belonging to a smart grid, highlighting remarkable differences. That analysis shows that the HHT is able to extract more accurate information than the FFT.