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Title Forecasting of Electricity Prices Accounting for Wind Power Predictions
Author Jónsson, Tryggvi (Mathematical Statistics, Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Supervisor Madsen, Henrik (Mathematical Statistics, Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Pinson, Pierre (Mathematical Statistics, Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Institution Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark
Thesis level Master's thesis
Year 2008
Abstract For players in deregulated energy markets such as Nord Pool and EEX, price forecasts are paramount when it comes to designing bidding strategies and are an important aid in production planning. In addition, price forecasts can be of great value for grid operators who are responsible for keeping the grid in balance. It is a known fact that electricity prices on Nord Pool’s spot market are, in the long run, mainly influenced by the level of water in the reservoirs of the Norwegian and Swedish hydropower plants. However, changes in the water level happen slowly and are therefore not a matter of great relevance when forecasts are made for the prices at the Nord Pool spot market on a relatively short horizon. In this thesis, the effects of predicted wind power production on the spot prices in Nord Pool’sWestern Danish price area (DK-1) are investigated. Moreover, ways of including the predicted wind power production in a forecasting model not only for the mean spot price in DK-1, but also the full distribution of the prices, are explored. It turns out that the effects of forecasted wind power production on the spot price is substantial and even more effects can be found with small modifications. The forecasting model constructed consists of three mains parts. The first part accounts for the effects of external factors on the prices while the second one is a dynamic model of the spot prices that accounts for the effects found be the first model. The final layer adds valuable information about the uncertainty or the distribution of the prices. Combined these models give reliable non-parametric description to the full distribution of the spot prices. Given the result of this thesis, it is very likely that the same methodology will give good results when forecasting the prices on other electricity pools. It is expected that the approach will be highly beneficial both for pools where wind power penetration is relatively high, and for markets with other characteristics, such as regulation markets.
Series IMM-M.Sc.-2008-43
Fulltext
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Admin Creation date: 2008-05-30    Update date: 2011-02-09    Source: dtu    ID: 220562    Original MXD