TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Medynskyi, Anton
A1  - Truckenmüller, Frank
A1  - Tugarinov, Petr
ED  - Wesselak, Viktor
T1  - Electricity price forecasting at Virtual Power Plant Neckar-Alb
T2  - RETCon 2021 - Tagungsband der 4 Regenerative Energietechnik Konferenz, 18-19 February 2021, Nordhausen
N2  - 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
Y1  - 2021
U6  - https://nbn-resolving.org/urn:nbn:de:bsz:rt2-opus4-31100
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:rt2-opus4-31100
UR  - https://www.hs-nordhausen.de/fileadmin/daten/fb_ing/inret/PDFs/tagungsband_retcon21_web_aa3__1_.pdf
SN  - 978-3-940820-17-4
SB  - 978-3-940820-17-4
SP  - 171
EP  - 176
S1  - 6
PB  - Hochschule Nordhausen
CY  - Nordhausen
ER  -