Probabilistic Forecasting Methods for System-Level Electricity Load Forecasting

TL;DR

This paper reviews various probabilistic load forecasting models for electricity systems, comparing short-term and long-term approaches, analyzing their advantages and disadvantages, and discussing future research directions.

Contribution

It provides a comprehensive comparison of probabilistic load forecasting models across different time horizons and highlights areas for future development.

Findings

Different models have unique advantages and disadvantages.

Probabilistic models improve uncertainty quantification in load forecasts.

Future research should focus on model comparability and integration.

Abstract

Load forecasts have become an integral part of energy security. Due to the various influencing factors that can be considered in such a forecast, there is also a wide range of models that attempt to integrate these parameters into a system in various ways. Due to the growing importance of probabilistic load forecast models, different approaches are presented in this analysis. The focus is on different models from the short-term sector. After that, another model from the long-term sector is presented. Then, the presented models are put in relation to each other and examined with reference to advantages and disadvantages. Afterwards, the presented papers are analyzed with focus on their comparability to each other. Finally, an outlook on further areas of development in the literature will be discussed.