Non-convex power plant modelling in energy optimisation

The European electricity market has been deregulated recently. This means that energy companies must optimize power generation considering the rapidly fluctuating price on the spot market. Optimisation has also become more difficult. Novel 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 subproblems, and apply a customised Branch-and-Bound algorithm for solving the sub-problems efficiently. We demonstrate the use of the model with a real-life application.