Load forecasting has become one of the major areas of research in electrical engineering,
and most traditional forecasting models and artificial intelligence techniques have been tried …

Publisher Summary The class of stochastic volatility (SV) models has its roots in both,
mathematical finance and financial econometrics. In fact, several variations of SV models …

The volatility of financial returns changes over time and, for the last thirty years, Generalized
Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal …

An innovations state space modeling framework is introduced for forecasting complex
seasonal time series such as those with multiple seasonal periods, high-frequency …

The coronavirus disease 2019 (COVID-19) pandemic has urged many governments in the
world to enforce a strict lockdown where all nonessential businesses are closed and citizens …

In recent years, a large amount of literature has evolved on the use of artificial neural
networks (ANNs) for electric load forecasting. ANNs are particularly appealing because of …

We address the optimal energy storage management and sizing problem in the presence of
renewable energy and dynamic pricing associated with electricity from the grid. We …

Short-term load forecasts are needed for the efficient management of power systems.
Although weather-based modeling is common, univariate models can be useful when the …

This paper provides a review of some of the main methodological issues and techniques
which have become innovative in addressing the problem of forecasting daily loads and …

This paper studies the forecasting abilities of a battery of univariate models on hourly
electricity spot prices, using data from the Leipzig Power Exchange. The specifications …