تقرير
Probabilistic Forecasting of Day-Ahead Electricity Prices and their Volatility with LSTMs
| العنوان: | Probabilistic Forecasting of Day-Ahead Electricity Prices and their Volatility with LSTMs |
|---|---|
| المؤلفون: | Trebbien, Julius, Pütz, Sebastian, Schäfer, Benjamin, Nygård, Heidi S., Gorjão, Leonardo Rydin, Witthaut, Dirk |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science Physics (Other) |
| مصطلحات موضوعية: | Computer Science - Machine Learning, Physics - Data Analysis, Statistics and Probability, Physics - Physics and Society |
| الوصف: | Accurate forecasts of electricity prices are crucial for the management of electric power systems and the development of smart applications. European electricity prices have risen substantially and became highly volatile after the Russian invasion of Ukraine, challenging established forecasting methods. Here, we present a Long Short-Term Memory (LSTM) model for the German-Luxembourg day-ahead electricity prices addressing these challenges. The recurrent structure of the LSTM allows the model to adapt to trends, while the joint prediction of both mean and standard deviation enables a probabilistic prediction. Using a physics-inspired approach - superstatistics - to derive an explanation for the statistics of prices, we show that the LSTM model faithfully reproduces both prices and their volatility. Comment: 5 pages, 1 figure |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2310.03339 |
| رقم الأكسشن: | edsarx.2310.03339 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |