Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Forecasting Uncertainty Intervals for Return Period of Extreme Daily Electricity Consumption

Domaine:

environment and energy
Créateur:
Kat
Éditeur:
Eco
Hôte:
The use of extreme value theory (EVT) is usually aimed at quantifying the asymptotic behaviour of extreme quantiles. The generalised Pareto distribution (GPD) with peaks-over-threshold (POT) approach is applied to bootstrap uncertainty intervals for the return periods of extreme daily electricity consumption in South Africa. The leeway of extremes on daily electricity consumption studied here is the impetus behind this study. To examine the effect of a time-based and extreme non-stationary trend in a dataset, a non-stationary GPD is cast-off in computing the shape parameter and, this resulted in the establishment of a type III GPD known as a Weibull class for the South African electricity sector. Results of this study revealed a non-stationary trend with a prediction power of 89.6% for the winter season and 85.65% non-winter season. This means that EVT provides a robust basis for statistical modelling of extreme values. Furthermore, a base for future researchers for conducting studies on emerging markets, more specifically in the South African context has also been contributed.

Visit

doi.org

Similaires

Forecasting Uncertainty Intervals for Return Period of Extreme Daily Electricity Consumption التنبؤ بفترات عدم اليقين لفترة عودة الاستهلاك اليومي الشديد للكهرباء Prévision des intervalles d'incertitude pour la période de retour de la consommation quotidienne extrême d'électricité Intervalos de incertidumbre de previsión para el período de retorno del consumo diario extremo de electricidadPrediction intervals for electricity load forecasting using neural networksDaily electricity demand forecasting in South AfricaForecasting electricity consumption by aggregating specialized expertsModelling the Hourly Consumption of Electricity during Period of Power CrisisEstimation of the Probability of Earthquakes Return Period in Zimbabwe Using Gumbel’s Extreme Value Theory Method

Forecasting Uncertainty Intervals for Return Period of Extreme Daily Electricity Consumption التنبؤ بفترات عدم اليقين لفترة عودة الاستهلاك اليومي الشديد للكهرباء Prévision des intervalles d'incertitude pour la période de retour de la consommation quotidienne extrême d'électricité Intervalos de incertidumbre de previsión para el período de retorno del consumo diario extremo de electricidad

The use of extreme value theory (EVT) is usually aimed at quantifying the asymptotic behaviour of ex

Prediction intervals for electricity load forecasting using neural networks

Most of the research in time series is concerned with point forecasting. In this paper we focus on i

Daily electricity demand forecasting in South Africa

Forecasting electricity consumption by aggregating specialized experts

We consider the setting of sequential prediction of arbitrary sequences based on specialized experts

Modelling the Hourly Consumption of Electricity during Period of Power Crisis

In this paper, we capture the dynamic behaviour of hourly consumption of electricity during the peri

Estimation of the Probability of Earthquakes Return Period in Zimbabwe Using Gumbel’s Extreme Value Theory Method

Using Gumbel's extreme value theory method, this study looked into the probability of the largest ea