Forecasting Intra-Hour Imbalances in Electric Power Systems
Abstract
Keeping the electricity production in balance with the actual demand is becoming a difficult and expensive task in spite of an involvement of experienced human operators. This is due to the increasing complexity of the electric power grid system with the intermittent renewable production as one of the contributors. A beforehand information about an occurring imbalance can help the transmission system operator to adjust the production plans, and thus ensure a high security of supply by reducing the use of costly balancing reserves, and consequently reduce undesirable fluctuations of the 50 Hz power system frequency. In this paper, we introduce the relatively new problem of an intra-hour imbalance forecasting for the transmission system operator (TSO). We focus on the use case of the Norwegian TSO, Statnett. We present a complementary imbalance forecasting tool that is able to support the TSO in determining the trend of future imbalances, and show the potential to proactively alleviate imbalances with a higher accuracy compared to the contemporary solution.
Cite
Text
Salem et al. "Forecasting Intra-Hour Imbalances in Electric Power Systems." AAAI Conference on Artificial Intelligence, 2019. doi:10.1609/AAAI.V33I01.33019595Markdown
[Salem et al. "Forecasting Intra-Hour Imbalances in Electric Power Systems." AAAI Conference on Artificial Intelligence, 2019.](https://mlanthology.org/aaai/2019/salem2019aaai-forecasting/) doi:10.1609/AAAI.V33I01.33019595BibTeX
@inproceedings{salem2019aaai-forecasting,
title = {{Forecasting Intra-Hour Imbalances in Electric Power Systems}},
author = {Salem, Tárik S. and Kathuria, Karan and Ramampiaro, Heri and Langseth, Helge},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2019},
pages = {9595-9600},
doi = {10.1609/AAAI.V33I01.33019595},
url = {https://mlanthology.org/aaai/2019/salem2019aaai-forecasting/}
}