Tools supporting wind energy trade in deregulated markets | Ulfar Linnet
| | Abstract | A large share of the wind energy produced in Scandinavia is sold at deregulated electricity markets. The main market, Elspot, is a day-ahead market where energy is sold up to 36 hours before delivery. Failure in delivering exactly the quantity which was sold results in a fine, called regulation cost. As wind energy comes from an uncontrollable energy source - the wind - producers can not always fulfil their sales obligations and must, therefore, often pay high regulation costs. In this thesis it is examined how producers can increase their profit by bidding on the market in such a way that the regulation cost is minimised. The methods developed rely on new production forecasts which provide better probabilistic information about the prediction uncertainty than many forecasting systems currently in use.
The problem is formulated in two different ways. One, originally presented by John B. Bremnes, where only a part of the market is included, gives a simple method that can be applied using only statistical tools. The other method is more
exible at the cost of complexity. It uses both statistics and stochastic programming. This method can be changed and applied in other markets with a structure different from that of the Scandinavian market, NordPool. | | Keywords | Electricity market, Wind energy, NordPool, Quantile Regression, Stochastic Programming | | Type | Master's thesis [Industrial collaboration] | | Year | 2005 | | Publisher | Informatics and Mathematical Modelling, Technical University of Denmark, DTU | | Address | Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby | | Series | IMM-Thesis-2005-56 | | Note | Supervised by Prof. Henrik Madsen, IMM, and Assoc. Prof. Henrik Aalborg Nielsen, IMM. | | Electronic version(s) | [pdf] [ps] | | BibTeX data | [bibtex] | | IMM Group(s) | Mathematical Statistics |
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