High-Resolution Electricity Spot Price Forecast for the Danish Power Market
Department of Business Development and Technology, Centre for Energy Technologies, Aarhus University, Aarhus BSS, Birk Centerpark 15, DK-7400 Herning, Denmark
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Sustainability 2020, 12(10), 4267; https://doi.org/10.3390/su12104267
Received: 13 April 2020 / Revised: 5 May 2020 / Accepted: 20 May 2020 / Published: 22 May 2020
(This article belongs to the Special Issue Sustainable and Renewable Energy Systems)
Energy markets with a high penetration of renewables are more likely to be challenged by price variations or volatility, which is partly due to the stochastic nature of renewable energy. The Danish electricity market (DK1) is a great example of such a market, as 49% of the power production in DK1 is based on wind power, conclusively challenging the electricity spot price forecast for the Danish power market. The energy industry and academia have tried to find the best practices for spot price forecasting in Denmark, by introducing everything from linear models to sophisticated machine-learning approaches. This paper presents a linear model for price forecasting—based on electricity consumption, thermal power production, wind production and previous electricity prices—to estimate long-term electricity prices in electricity markets with a high wind penetration levels, to help utilities and asset owners to develop risk management strategies and for asset valuation.
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MDPI and ACS Style
Schütz Roungkvist, J.; Enevoldsen, P.; Xydis, G. High-Resolution Electricity Spot Price Forecast for the Danish Power Market. Sustainability 2020, 12, 4267. https://doi.org/10.3390/su12104267
AMA Style
Schütz Roungkvist J, Enevoldsen P, Xydis G. High-Resolution Electricity Spot Price Forecast for the Danish Power Market. Sustainability. 2020; 12(10):4267. https://doi.org/10.3390/su12104267
Chicago/Turabian StyleSchütz Roungkvist, Jannik, Peter Enevoldsen, and George Xydis. 2020. "High-Resolution Electricity Spot Price Forecast for the Danish Power Market" Sustainability 12, no. 10: 4267. https://doi.org/10.3390/su12104267
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