WWTF - Wiener Wissenschafts, Forschungs- und Technologiefonds



Simulation based stochastic Optimisation Methods for Risk Management in Liberalized Energy Markets


September 2005 - September 2007
Responsible project manager

Univ. Prof. Dr. G. Ch. Pflug

University of Vienna
Department of Statistics and Decision Support Systems
Universitätsstrasse 5
A-1010 Wien - Vienna

Phone: +43 - 1- 42 77 386 30
E-mail: georg.pflug@univie.ac.at
Research associates

Mag. Dr. R. Hochreiter
Phone: +43 -1 - 42 77 386 20
E-mail: ronald.hochreiter@univie.ac.at
Mag. N. Wozabal
E-mail: nancy.mathew@univie.ac.at
Mag. D. Wozabal
Phone: +43 - 1 - 42 77 386 60
E-mail: david.wozabal@univie.ac.at
Nikola Broussev
Phone: +43 - 1 - 42 77 386 16
E-mail: nikola.broussev@univie.ac.at

Univ. Prof. Dr. R. Haas

Vienna University of Technology
Institute of Energy Economics
Gusshausstrasse 25-29/373-2
A-1040 Wien - Vienna

Phone: +43-1-58801-37352
E-mail: haas@eeg.tuwien.ac.at

Univ. Prof. Dr. N. Nakicenovic

Vienna University of Technology
Institute of Energy Economics

Phone: +43-1-58801-37350
E-mail: naki@eeg.tuwien.ac.at
Research associates

Dr. Ing. H. Auer

Phone: +43-1-58801-37357
E-mail: auer@eeg.tuwien.ac.at
Dipl.-Ing. Ch. Redl
Phone: +43-1-58801-37368
E-mail: redl@eeg.tuwien.ac.at

Univ. Prof. Dr. W. Römisch
Humboldt University of Berlin
Department of Mathematics
Unter den Linden 6
10099 Berlin Germany

Phone: +49 (0)30 - 2093 2561
E-mail: romisch@mathematik.hu-berlin.de
Research associates
Dipl.-Math. I. Wegner-Specht Phone: +49 (0)30 - 2093 2624
E-mail: isabel@mathematik.hu-berlin.de
Dipl.-Math. A. Eichhorn
Phone: +49 (0)30 - 2093 2624
E-mail: eichhorn@mathematik.hu-berlin.de
Dipl.-Math. H. Heitsch
Phone: +49 (0)30 - 2093 2624
E-mail: heitsch@mathematik.hu-berlin.de
Dipl. -Math. Christian Küchler
+49 - (0)30 - 2093 5445 (office)
E-mail: ckuechler@math.hu-berlin.de
Dipl.-Math. S. Vigerske
Phone: +49 (0)30 - 2093 5445

Industrial cooperation APT
Supported by

WWTF - Wiener Wissenschafts, Forschungs- und Technologiefonds

Project summary

This project aims at developing mathematical methods for optimal risk management for energy producers and traders in liberalized energy markets. The deregulation of energy markets results in an increased need for methods of short and medium term decision making under the uncertainty of future demands, costs, prices and capacities. In an integrated view, production decisions as well as risk hedging decisions will be modelled simultaneously. Modern hedging instruments like forwards, swaps and options can be used in an optimal mix of risk management tools to avoid high volatilities and financial disaster. The mathematics behind the optimal decision making under uncertainty involves new methods of multiperiod stochastic optimisation and combined simulation / optimisation algorithms.

Scientific objectives

The objective of this project is to develop mathematical tools for supporting decision making under uncertainty in energy markets. As a case study, the Austrian energy system will be modelled. In particular, the decision problem of a wholesaler and the decision problem of a producer of renewable energy will be considered.
The general theme is decision making under uncertainty. The objective is to develop stochastic optimisation methods suitable for the joint consideration of the production side and the trading side. This integrative view requires the consideration of multiperiod, stochastic dynamic mixed integer problems of considerable size. There are in principle two ways of algorithmic solutions of such problems: the approximation by a deterministic program or the use of simulation/optimisation interleaved methods. In particular, gradient estimation methods for iterative interleaved simulation/optimisation methods will be studied and implemented. Stochastic gradient estimation plays also an important role in risk hedging methods, since a well hedged portfolio has small sensitivity w.r.t the drivers of uncertainty. An interleaved simulation/optimisation method is also the stochastic branch and bound method, which will be compared to Lagrangian decomposition. The success of the application depends heavily on interdisciplinary cooperation with the experts on energy markets from the TU Wien. This group will conduct an empirical study on the Austrian energy market and develop an economic model, which serves as the basis for the risk management and optimal decision model. With the help of employed computer scientists, code will be developed for solving multiperiod, stochastic dynamic mixed integer problems. This code will allow traders and producers to effectively manage their risk by creating a optimal portfolio of production, delivering contracts and financial instruments as options, swaps, futures and alike. A major objective is to bring theory, algorithms and implementations to such a level, that in a midterm perspective, it will be used by produces and traders to manage their portfolio and limit their risks. The benefit of the development is less price fluctuations and less volatility, leading to more stable and predictable market.


A joint photograph


Georg Pflug, Nikola Broussev: Vortrag UNI (pdf)

Nikola Broussev: Vortrag TU (pdf)

Georg Pflug, Nikola Broussev: Paper (pdf)

Römisch/Wegner-Specht: wwtf-literatur (pdf)

Reinhard Haas/Christian Redl: wwtf-literatur-v2 (pdf)

Jack King: electricity-price-modelling-references (pdf)

Jack King: Nov 30, 2005 Report (HTML)

Römisch/Wegner-Specht/Ch. Küchler: wwtf_modellbeschreibung_3 (pdf)

General References

Jack King: Further References