Effectiveness of antithetic sampling and stratified sampling in Monte Carlo chronological production cost modeling (power systems)

• Published in: IEEE transactions on power systems Vol. 6; no. 2; pp. 669 - 675
• Main Authors: Marnay, C., Strauss, T.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: New York, NY IEEE 01-05-1991; Institute of Electrical and Electronics Engineers
• Subjects: Applied sciences; Capacity planning; Costing; Costs; Electrical engineering. Electrical power engineering; Electrical power engineering; Exact sciences and technology; Monte Carlo methods; Operation. Load control. Reliability; Power networks and lines; Power system reliability; Power system simulation; Predictive models; Production planning; Production systems; Sampling methods; Monte Carlo method; Energy cost; Electrical network; Power production; Estimation; Econometric model; Planning; Sampling; Marginal cost
• ISSN: 0885-8950; 1558-0679
• DOI: 10.1109/59.76711

Sampling error detracts from the usefulness of estimates of mean hourly marginal cost produced by Monte Carlo chronological production cost models. Variance reduction techniques commonly used in other Monte Carlo simulation applications can significantly improve the precision of estimates. Two such techniques, antithetic sampling and stratified sampling, are tested for a fictitious system. The number of iterations needed to reach a precision target falls significantly. The estimated savings in total computing time could exceed 50% for a full one-year forecast. Both techniques are easily implemented and should be used in Monte Carlo production costing efforts to estimate hourly marginal cost.< >