Probabilistic Forecasting Methods for System-Level Electricity Load Forecasting
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 18 references that are in the map. First posted on arXiv 17 Oct 2022.
Builds on
5 of 18 references.
References · 5
- 2020Forecasting Daily Primary Three-Hour Net Load Ramps in the CAISO Systemcited by 2
- 2019Probabilistic Load Forecasting via Point Forecast Feature Integrationcited by 1
- 2020A Distributionally Robust Optimization Approach for Unit Commitment in Microgridscited by 1
- 2020Kullback-Leibler Divergence-Based Distributionally Robust Unit Commitment Under Net Load Uncertaintycited by 1
- 2020Quantification of the Impact of GHG Emissions on Unit Commitment in Microgridscited by 1
Built on by
Not cited yet.