Article ID: | iaor2007754 |
Country: | Netherlands |
Volume: | 171 |
Issue: | 3 |
Start Page Number: | 1113 |
End Page Number: | 1126 |
Publication Date: | Jun 2006 |
Journal: | European Journal of Operational Research |
Authors: | Lahdelma Risto, Makkonen Simo |
Keywords: | programming: integer |
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 difficult. 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. 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.