Generation Planning including Distributed Generator under Uncertainty of Demand Growth

This paper addresses the problem of generation planning in the competitive power market with uncertainty of demand growth. The distributed generator (DG) is paid attention against a large-scale generator to correspond uncertain demand growth. Optimization consists in minimizing the average cost and hedging risk over the scenario trees of demand growth.

At first, based on the idea of Real Option, Dynamic Programming using the utility function is applied to generation planning. Utility functions can model investor's risk-return profile. The decisions in the first stage indicate that they are influenced by the type of utility functions and demand growth scenarios, and data of generators.

Next, Monte Carlo Simulation is applied to Brown motion model of demand growth. This model can increase the possible number of demand level. With this simulation, the case that the distributed generator has advantage against the large-scale generator is quantitatively discussed.