NDLI: Generation of multivariate scenario trees to model stochasticity in power management

Content Provider	IEEE Xplore Digital Library
Author	Heitsch, H. Romisch, W.
Copyright Year	2005
Description	Author affiliation: Humboldt-Univ. Berlin, Berlin (Heitsch, H.; Romisch, W.)
Abstract	Modern electricity portfolio and risk management models represent multistage stochastic programs. The input of such programs consists in a finite set of scenarios having the form of a scenario tree. They model the probabilistic information on random data (electrical load, stream flows to hydro units, market prices of fuel and electricity). Since the corresponding deterministic equivalents of multistage stochastic programs are mostly large scale, one has to find significant tree-structured scenarios. Our approach to generate multivariate scenario trees is based on recursive deletion and bundling of scenarios out of some given (possibly large) scenario set originating from historical or simulated data. The procedure makes use of certain Monge-Kantorovich transportation distances for multivariate probability distributions. We report on computational results for generating load-inflow scenario trees based on realistic data of EDF Electricite de France.
Starting Page	1
Ending Page	7
File Size	759168
Page Count	7
File Format	PDF
ISBN	9785932080344
DOI	10.1109/PTC.2005.4524696
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-06-27
Publisher Place	Russia
Access Restriction	Subscribed
Rights Holder	Energy Systems Institute
Subject Keyword	Power generation Energy management Stochastic processes Load management Portfolios Risk management Fuels Large-scale systems Computational modeling Transportation scenario tree construction Stochastic programming power management scenario reduction
Content Type	Text
Resource Type	Article

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