Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review
Final published version, 517 KB, PDF document
Final published version
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.
Original language | English |
---|---|
Article number | 4267 |
Journal | Sustainability |
Volume | 12 |
Issue | 10 |
Number of pages | 19 |
ISSN | 2071-1050 |
DOIs | |
Publication status | Published - 2020 |
See relations at Aarhus University Citationformats
ID: 188560796