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Non-Convex Power Plant Modelling in Energy Optimization

Simo Makkonen, Risto Lahdelma, Non-Convex Power Plant Modelling in Energy Optimization. European Journal of Operational Research 171(3), 1113–1126, 2006.

Abstract:

The European electricity market has been deregulated recently. This means that energy companies must optimise
power generation considering the rapidly fluctuating price on the spot market. Optimisation has also become more dif-
ficult. New production technologies, such as gas turbines (GT), combined heat and power generation (CHP), and combined
steam and gas cycles (CSG) require non-convex models. Risk analysis through stochastic simulation requires
solving a large number of models rapidly. These factors have created a need for more versatile and efficient decision-
support tools for energy companies.
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We formulate the decision-problem of a power company as a large mixed integer programming (MIP) model. To
make the model manageable we compose the model hierarchically from modular components. To speed up the optimisation
procedure, we decompose the problem into hourly sub-problems, and develop a customised Branch-and-Bound
algorithm for solving the sub-problems efficiently. We demonstrate the use of the model with a real-life application.

BibTeX entry:

@ARTICLE{jMaLa06a,
  title = {Non-Convex Power Plant Modelling in Energy Optimization},
  author = {Makkonen, Simo and Lahdelma, Risto},
  journal = {European Journal of Operational Research},
  volume = {171},
  number = {3},
  publisher = {Elsevier},
  pages = {1113–1126},
  year = {2006},
  keywords = {Energy management; Deregulation; Energy market; Optimisation; Mixed integer programming},
}

Belongs to TUCS Research Unit(s): Algorithmics and Computational Intelligence Group (ACI)

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