## Beta 1

Title Optimal trading strategies for a wind-storage power system under market conditions
Author Andersen, Philip Hvidthøft Delff (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 2009
Abstract In this thesis, a model of a system consisting of electric power production on wind turbines combined with a storage device is developed. By use of Monte Carlo simulation, the operation of the system is optimised with respect to two different objective functions. One strategy is to maximise the expected revenue for the whole delivery period, the other is to minimise the expected regulation costs. Moreover, two different markets are considered, with different horizons and duration of the delivery periods. A passive operation strategy for the electrical energy storage is defined, and hence the delivery to the power net becomes a function of only the production and the issued contract at the market. Since the production is assumed to be uncontrollable, only the contract is left to optimise. Three different models of the electrical storage devices are being used. Hence, effects of all limited capacity, charging and discharging efficiencies, and limitations on charging and discharging speeds can be observed. For running the Monte Carlo Simulation, a non-linear estimate of the distribution of the future production for each relevant horizon by use of adaptive quantile regression with point forecasts as explanatory variable. From this, the interdependence of future production at different horizons are estimated. From these two estimates, the scenarios are simulated, and based on these the optimisation problems are solved. The simulations are run throughout all in all more than one year of data. The results of the optimisation strategies are not as good as expected, assumed because of too poor estimates of the distributions of the production. However, by use of simulations, a potential gain of the method can be estimated. This gain is expected to be realistic if a good model for prediction of the distributions is found. The results are very depending on optimisation strategy and storage model, and the obtained revenues are between -2% and 19% compared to when using the point predictions as contracts and the respective storage devices. Finally, different approaches to improve the method are discussed.
Series IMM-M.Sc.-2009-54
Fulltext
 Original PDF ep09_54_net.pdf (1.64 MB)
Admin Creation date: 2009-09-02    Update date: 2009-10-21    Source: dtu    ID: 249639    Original MXD