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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

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Metadaten
Author of HS ReutlingenMedynskyi, 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
Year of Publication:2021
Page Number:6
First Page:171
Last Page:176
DDC classes:600 Technik
Open Access?:Ja
Licence (German):License Logo  Open Access