Application of the Detrended Fluctuation Analysis (DFA) method in short or long-range correlations in wind time series of Apodi-RN municipality

Abstract

This article aims to investigate short and long-range persistent and anti-persistent correlations in wind time series data from the municipality of Apodi in the state of Rio Grande do Norte, Brazil. The study employs a statistical method known as Detrended Fluctuation Analysis (DFA) to analyze wind correlations. Renewable energies, particularly wind energy, have been steadily growing as a major energy source used in various countries to power residences, factories, and businesses. Due to its clean, natural attributes and minimal environmental impact compared to other polluting energy sources, wind energy has garnered significant interest from the scientific community. In this context, there is a need to develop technologies capable of assessing wind potential. Statistical methods are employed to analyze wind speed time series, with the objective of quantifying, predicting, and forecasting wind speeds in a specific region. The methodological approach includes a literature review of relevant scientific works, and the DFA application involves three stages: data collection, tabulation, and corrections using software such as R, Geogebra, Excel, among others. The results indicate that wind speed exhibits no anti-persistent correlation or uncorrelated behavior (white noise), but rather persistent correlations, suggesting that high wind speeds are more likely to be followed by high wind speeds.