High-Resolution Electricity Spot Price Forecast for the Danish Power Market

Sustainability

George Xydis¹  Jannik Schütz Roungkvist¹  Peter Enevoldsen¹ 

[1] Department of Business Development and Technology, Centre for Energy Technologies, Aarhus University, Aarhus BSS, Birk Centerpark 15, DK-7400 Herning, Denmark;

关键词: electricity spot price forecast;    power markets;    renewable energy;    wind power;    big data;   

DOI  :  10.3390/su12104267

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown