Effectiveness of optimum stratified sampling in Monte Carlo chronological CO2 emission pollutants of generation system modeling

This paper presents a combined Monte Carlo and stratified-sampling method to better estimate CO₂ emissions for generation systems. This design seeks to enhance the precision of CO₂ emission pollutants in generation system estimation, while reducing computation time. The techniques included are optimum stratified sampling and proportional estimate. The optimum stratification rule aims to remove any judgmental input and to render the stratification process entirely mechanistic. The estimator, provided by proportional statistics of the sample, can avoid identification of the regression model and thus save computation time. Hence, the effectiveness on precision improvement is demonstrated in this paper