The deregulation of the European power market brings new sales prospects for the power-suppliers as well as an appreciable increase of entrepreneurial risks. In order to handle the novel price- and volume-risks the optimisation of decisionmaking under uncertain boundary conditions is of essential interest. The former task of resource management in energy-supply was the minimisation of costs for the fulfilment of a foreseeable power-request at long-ranging conditions of pricing. Now a multicriterial optimisation problem arises: simultaneous minimisation of cost and risk. In the last years a number of power-exchanges have been established, where power is physically traded day-ahead and derivatively as future contracts. Furthermore financial power-derivatives like Options, Caps, Floors or Swaps are traded bilateral in the so called over-the-counter market. A serious question is how to use different physical contracts and financial derivatives in an optimal way to protect a power purchase portfolio against market risks. Facing this question a multicriterial linear stochastic optimisation model has been developed. It is based on scenarios for the market price, generated by montecarlo-simulation that uses a mean-reversion market model calibrated for the German power spot-market. The different optimisation criteria are merged into a single objective by a weighted summation. Individual risk is considered by the coefficients of the weighted sum. The model is adapted to resolvability by Benders-Decomposition in a way that even a larger number of optimisations with different coefficients of the weighted sum can be solved in acceptable time giving an idea of the shape of the efficiency-frontier. Nevertheless all important microeconomic features of the portfolio-components are modelled.
Fraunhofer Institut für Umwelt-, Sicherheits- und Energietechnik UMSICHT Osterfelder Str. 3 46047 Oberhausen Germany. Appeared in: Central European Journal of Operations Research CEJOR 11/2003