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Title: Natural Gas Energy Flow Quality() Uncertainty Estimation Using Monte Carlo Simulation Method.
Author: Hoi Yeung, Christos E. Papadopoulos
Source: Flomeko 2000
Year Published: 2000
Abstract: In the natural gas market, open access along with gas brokering and marketing has resulted in multiple gas contracts through one physical measuring point. Accurate metering of natural gas has become more important than ever as de-regulation subjects pipeline companies to competition. A more competitive market is driving the need for real-time accurate electronic flow measurement. Modern electronic natural gas metering systems (ENGMS) introduced additional, though necessary, complexity in the estimation and verification of the reported results. Additionally, it becomes more and more important to be able to verify these results. The application of Monte Carlo simulation as a combined energy flow measurement uncertainty estimation method seems to offer specific advantages over the more complex, traditional uncertainty estimation methods while at the same time fully conforms with the method of the ISO/GUM, the authoritative document for uncertainty evaluation. Since Monte Carlo simulation relies on randomness, it seems to capture more naturally and more related to the underlying physics of measurement uncertainty. Typical comparisons of estimated uncertainties by the model and the conventional method (RSS) have been carried out. In general the Monte Carlo method gives slightly higher estimated uncertainties. This is due to the fact that the simplified conventional methods inevitably neglect correlations between the variables.

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