On cointegration for modeling and forecasting wind power production
Applications
2020-10-16 v1
Abstract
This study evaluates the performance of cointegrated vector autoregressive (VAR) models for very short- and short-term wind power forecasting. Preliminary results for a German data set comprising six wind power production time series indicate that taking into account potential cointegrating relations between the individual series can improve forecasts at short-term time horizons.
Cite
@article{arxiv.2010.07857,
title = {On cointegration for modeling and forecasting wind power production},
author = {Florian Ziel and Antonia Arsova},
journal= {arXiv preprint arXiv:2010.07857},
year = {2020}
}