Improvement on state formulation, stratification and estimation in Monte Carlo production cost simulation [for power system planning]

A computer algorithm designed for power system Monte Carlo production cost simulation is described. The design seeks to enhance the precision of production cost estimation at a reduced computation time compared with the existing approach. The algorithm has three major computer steps: (i) to formulate a state population according to the uptime/downtime of the generating unit, hence to simulate generation availability; (ii) to stratify this population by a mathematical rule and draw sample states out of each stratum; and (iii) to estimate the population mean of unit commitment production costs by the rank statistics of the sample. The stratification rule aims to remove any judgemental input and to render the stratification process entirely mechanistic. The estimator, given by rank statistics of the sample, can avoid identification of the regression model and thus save computation time. The algorithm has been evaluated and compared numerically with the existing approach. Hence, the effectiveness on precision improvement is demonstrated