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Jannik Schütz Roungkvist
MHI Vestas Offshore Wind Aarhus Denmark

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Journal article
Published: 22 May 2020 in Sustainability
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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.

ACS Style

Jannik Schütz Roungkvist; Peter Enevoldsen; George Xydis. High-Resolution Electricity Spot Price Forecast for the Danish Power Market. Sustainability 2020, 12, 4267 .

AMA Style

Jannik Schütz Roungkvist, Peter Enevoldsen, George Xydis. High-Resolution Electricity Spot Price Forecast for the Danish Power Market. Sustainability. 2020; 12 (10):4267.

Chicago/Turabian Style

Jannik Schütz Roungkvist; Peter Enevoldsen; George Xydis. 2020. "High-Resolution Electricity Spot Price Forecast for the Danish Power Market." Sustainability 12, no. 10: 4267.

Review
Published: 14 January 2020 in Journal of Forecasting
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The intermittency of the wind has been reported to serve significant challenges to power and grid systems, which intensifies with increasing penetration levels. Accurate wind forecasting can mitigate these challenges and help integrating more wind power into the grid. A range of studies have presented algorithms to forecast the wind in terms of wind speeds and wind power generation across different time‐scales. However, the classification of time‐scales vary significant across the different studies 2010 to 2014. The time‐scale is important, in order to specify which methodology to use when, as well to unite future research, data requirements, etc. This study proposes a generic statement on how to classify the time‐scales, and further presents the different applications of these forecasts across the entire wind power value chain.

ACS Style

Jannik Schütz Roungkvist; Peter Enevoldsen. Timescale classification in wind forecasting: A review of the state‐of‐the‐art. Journal of Forecasting 2020, 39, 757 -768.

AMA Style

Jannik Schütz Roungkvist, Peter Enevoldsen. Timescale classification in wind forecasting: A review of the state‐of‐the‐art. Journal of Forecasting. 2020; 39 (5):757-768.

Chicago/Turabian Style

Jannik Schütz Roungkvist; Peter Enevoldsen. 2020. "Timescale classification in wind forecasting: A review of the state‐of‐the‐art." Journal of Forecasting 39, no. 5: 757-768.