Fluctuation analysis of high frequency electric power load in the Czech Republic

TL;DR

This study analyzes high-frequency electric power load data in the Czech Republic, revealing 1/f noise, persistent behavior, and non-Gaussian distribution characteristics through advanced fluctuation analysis methods.

Contribution

It introduces an improved MFDFA method combined with Fourier transform to analyze stochastic power load components with high resolution datasets.

Findings

Presence of 1/f noise in power load data

Persistent behavior in fluctuations

Non-Gaussian skewed distribution with heavy tails

Abstract

We analyze the electric power load in the Czech Republic (CR) which exhibits a seasonality as well as other oscillations typical for European countries. Moreover, we detect 1/f noise property of electrical power load with extra additional peaks that allows to separate it into a deterministic and stochastic part. We then focus on the analysis of the stochastic part using improved Multi-fractal Detrended Fluctuation Analysis method (MFDFA) to investigate power load datasets with a minute resolution. Extracting the noise part of the signal by using Fourier transform allows us to apply this method to obtain the fluctuation function and to estimate the generalized Hurst exponent together with the correlated Hurst exponent, its improvement for the non-Gaussian datasets. The results exhibit a strong presence of persistent behaviour and the dataset is characterized by a non-Gaussian skewed distribution. There are also indications for the presence of the probability distribution that has heavier tail than the Gaussian distribution.