Stochastic generation expansion planning by means of stochastic dynamic programming

Most generation expansion planning tools do not model uncertainties in important variables such as energy demand and prices of energy carriers together with the dynamics of the system. A method for handling these uncertainties in generation expansion problems is described. The method is based on stochastic dynamic programming. As the uncertain variables are modeled by Markov chains they give a natural year-to-year dependence of the variables. This modeling makes it possible to describe the connection between investment decisions, time, construction periods, and uncertainty. The importance of modeling these connections is demonstrated by a realistic example.