DocumentCode :
3486539
Title :
Mean-risk optimization of electricity portfolios using multiperiod polyhedral risk measures
Author :
Eichhorn, Andreas ; Römisch, Werner ; Wegner, Isabel
Author_Institution :
Humboldt-Univ. Berlin, Berlin
fYear :
2005
fDate :
27-30 June 2005
Firstpage :
1
Lastpage :
7
Abstract :
We present an applied mathematical model with stochastic input data for mean-risk optimization of electricity portfolios containing electricity futures as well as several components to satisfy a stochastic electricity demand: electricity spot market, two different types of supply contracts offered by a large power producer, and a combined heat and power production facility with limited capacity. Stochasticity enters the model via uncertain electricity demand, heat demand, spot prices, and future prices. The model is set up as a decision support system for a municipal power utility (price taker) and considers a medium term optimization horizon of one year in hourly discretization. The objective is to maximize the expected overall revenue and, simultaneously, to minimize risk in terms of multiperiod risk measures. Such risk measures take into account intermediate cash values in order to avoid uncertainty and liquidity problems at any time. We compare the effect of different multiperiod risk measures taken from the class of polyhedral risk measures which was suggested in our earlier work.
Keywords :
contracts; investment; load forecasting; power markets; power system economics; risk management; combined heat production facility; decision support system; electricity portfolios; electricity spot market; heat demand; mean-risk optimization; multiperiod polyhedral risk measures; municipal power utility; polyhedral risk measures; power production facility; power supply contracts; stochastic electricity demand; uncertain electricity demand; Cogeneration; Contracts; Decision support systems; Electric variables measurement; Mathematical model; Portfolios; Power system modeling; Production facilities; Resistance heating; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Tech, 2005 IEEE Russia
Conference_Location :
St. Petersburg
Print_ISBN :
978-5-93208-034-4
Electronic_ISBN :
978-5-93208-034-4
Type :
conf
DOI :
10.1109/PTC.2005.4524674
Filename :
4524674
Link To Document :
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