Electricity price forecasting at Virtual Power Plant Neckar-Alb
- This paper describes the analysis of day-ahead power market data from the European Power Exchange (EPEX) SPOT over a period of 17 months till October 2020 and the forecasting model for electricity prices. High volatility of the DE-LU (Germany and Luxembourg) power market in order to improve the planning of the bidding strategy and maximize benefits was reflected. Forecasting models based on the Autoregressive Integrated Moving Average (ARIMA) approach and artificial neural networks are developed to predict Day-Ahead prices up to a week ahead. Models are built for a virtual power plant Neckar-Alb and will be used as a part of an optimization tool for the operationtimetable of connected distributed energy devices
| Author of HS Reutlingen | Medynskyi, Anton; Truckenmüller, Frank; Tugarinov, Petr |
|---|---|
| URN: | urn:nbn:de:bsz:rt2-opus4-31100 |
| URL: | https://www.hs-nordhausen.de/fileadmin/daten/fb_ing/inret/PDFs/tagungsband_retcon21_web_aa3__1_.pdf |
| ISBN: | 978-3-940820-17-4 |
| Erschienen in: | RETCon 2021 - Tagungsband der 4 Regenerative Energietechnik Konferenz, 18-19 February 2021, Nordhausen |
| Publisher: | Hochschule Nordhausen |
| Place of publication: | Nordhausen |
| Editor: | Viktor Wesselak |
| Document Type: | Conference proceeding |
| Language: | English |
| Publication year: | 2021 |
| Page Number: | 6 |
| First Page: | 171 |
| Last Page: | 176 |
| DDC classes: | 600 Technik |
| Open access?: | Ja |
| Licence (German): |  Open Access |
