Approximate computation of the variance of electric power generation system production costs

Abstract The cost of producing electric power by a utility depends on the magnitude of demand, the loading sequence of the generators used to meet the demand, their variable costs and their availabilities. A Markovian model of the generation system together with a deterministic time-varying demand has been proposed to compute the mean and the variance of the production costs. The purpose of this paper is to demonstrate how the bivariate Gram-Charlier series approximation can be used to speedup the computation of the standard deviation. Numerical examples are given to demonstrate that this approximation is an effective computational tool for large systems.