STOCHASTIC-MODELS FOR POWER-GENERATION SYSTEM PRODUCTION COSTS

Production costing models are widely used in the electric power indust ry for the purpose of generation capacity expansion planning, fuel man agement, and operational planning. These models account for the load v ariation over time and generator outages. A widely used model, due to Baleriaux and Booth, yields a prediction of the expected production co sts and is based on the load duration curve and forced outage rate of the generating units. This paper highlights the fact that, in order to obtain a more detailed characterization of the probability distributi on of production costs beyond the expected value, a model involving th e stochastic processes underlying the generator outages is necessary. A stochastic model is considered as an enhancement to the traditional Baleriaux model. It is shown that Monte Carlo simulation can be routin ely used on the enhanced model to provide answers concerning the distr ibution of production costs. Monte Carlo methods avoid the problems as sociated with the complexity of the analytical methods. Numerical exam ples are given using the enhanced model where load is considered to be either a deterministic or stochastic time-varying function. An exampl e is given using decision analysis where a possible use of the more de tailed information on the probability distribution of production costs in generation system planning is illustrated.