@MASTERSTHESIS{delff09,
  author = {Philip Delff Andersen},
  title = {Optimal trading strategies for a wind-storage power system under
	market conditions},
isbn = {978-87-643-0555-5},
issn = {1601-233X},
  school = {Technical University of Denmark},
  year = {2009},
  abstract = {In this thesis a model of a system consisting of electric power
	
	production on wind turbines combined with 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.}
}