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Stochastic Models and Algorithms for the Optimal Operation of a Dispersed Generation System under Uncertainty

In: Mathematics – Key Technology for the Future

Author

Listed:
  • Edmund Handschin

    (University of Dortmund, Institute of Energy Systems and Energy Economics)

  • Frederike Neise

    (University of Duisburg-Essen, Department of Mathematics)

  • Hendrik Neumann

    (University of Dortmund, Institute of Energy Systems and Energy Economics)

  • Rüdiger Schultz

    (University of Duisburg-Essen, Department of Mathematics)

Abstract

Due to the impending renewal of generation capacities and present decisions concerning energy policy, dispersed generation systems become more and more important. The optimal operation of such a system and corresponding trading activities are substantially influenced by uncertainty and require powerful optimization techniques. We present expectation-based as well as risk-averse stochastic mixedinteger linear optimization models using risk measures and dominance constraints. Two case studies show the benefit of stochastic optimization in power generation and the superiority of tailored solution methods over standard solvers.

Suggested Citation

  • Edmund Handschin & Frederike Neise & Hendrik Neumann & Rüdiger Schultz, 2008. "Stochastic Models and Algorithms for the Optimal Operation of a Dispersed Generation System under Uncertainty," Springer Books, in: Hans-Joachim Krebs & Willi Jäger (ed.), Mathematics – Key Technology for the Future, pages 205-233, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-77203-3_15
    DOI: 10.1007/978-3-540-77203-3_15
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