Department of Business Development and Technology

High-resolution electricity spot price forecast for the Danish power market

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High-resolution electricity spot price forecast for the Danish power market. / Roungkvist, Jannik Schütz ; Enevoldsen, Peter; Xydis, Georgios.

In: Sustainability, Vol. 12, No. 10, 4267, 2020.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

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Roungkvist, Jannik Schütz ; Enevoldsen, Peter ; Xydis, Georgios. / High-resolution electricity spot price forecast for the Danish power market. In: Sustainability. 2020 ; Vol. 12, No. 10.

Bibtex

@article{9fe5cb058f5c4f8e8c7e24118a520a30,
title = "High-resolution electricity spot price forecast for the Danish power market",
abstract = "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.",
keywords = "Big data, Electricity spot price forecast, Power markets, Renewable energy, Wind power",
author = "Roungkvist, {Jannik Sch{\"u}tz} and Peter Enevoldsen and Georgios Xydis",
year = "2020",
doi = "10.3390/su12104267",
language = "English",
volume = "12",
journal = "Sustainability",
issn = "2071-1050",
publisher = "MDPI AG",
number = "10",

}

RIS

TY - JOUR

T1 - High-resolution electricity spot price forecast for the Danish power market

AU - Roungkvist, Jannik Schütz

AU - Enevoldsen, Peter

AU - Xydis, Georgios

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

KW - Big data

KW - Electricity spot price forecast

KW - Power markets

KW - Renewable energy

KW - Wind power

UR - http://www.scopus.com/inward/record.url?scp=85085640077&partnerID=8YFLogxK

U2 - 10.3390/su12104267

DO - 10.3390/su12104267

M3 - Journal article

AN - SCOPUS:85085640077

VL - 12

JO - Sustainability

JF - Sustainability

SN - 2071-1050

IS - 10

M1 - 4267

ER -