• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Anderes
  4. Optimisation of physical and financial power purchase portfolios
 
  • Details
  • Full
Options
2002
Internet Contribution
Title

Optimisation of physical and financial power purchase portfolios

Abstract
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 Monte-Carlo-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 aversion 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 have been taken into account.
Author(s)
Spangardt, G.
Fraunhofer-Institut für Umwelt-, Sicherheits- und Energietechnik UMSICHT  
Lucht, M.
Fraunhofer-Institut für Umwelt-, Sicherheits- und Energietechnik UMSICHT  
Althaus, W.  
Fraunhofer-Institut für Umwelt-, Sicherheits- und Energietechnik UMSICHT  
Language
English
Fraunhofer-Institut für Umwelt-, Sicherheits- und Energietechnik UMSICHT  
Keyword(s)
  • electric utility

  • small and medium-sized business

  • demand for electricity

  • power trading

  • portfolio management

  • risk management

  • stochastic optimization (SO)

  • multicriteria optimization

  • modelling

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024