One of the most important challenges in fluid mechanics, gas dynamics, and hydraulic machinery fields is measuring the flow velocity with high accuracy. It is more important in large systems; such as thermal power stations, large scale power generations, and combined cycle power plants. The exact estimation of the measurement uncertainty inflow velocity is extremely important in evaluating the accuracy of the measurement. This work describes the problem of estimating measurement uncertainty when there are two or more dominant components of the uncertainty budget. . Two methods, analytical and numerical methods are used to study the comparative analysis for the results of determining the expanded uncertainty of measurement using two methods: analytical method and the numerical method. The analytical method uses the law of uncertainty propagation and is based on the estimation of uncertainty values of type A and B, while the numerical technique depends on the evaluation of measured samples by the Monte Carlo method using a random number generator. The aim of this article is to show the Monte Carlo method as an alternative way to determine the distribution of individual components of the measurement uncertainty budget. Also, the measurement of liquid flow velocity by an ultrasonic method has been analyzed, which is commonly used due to high measurement accuracy and non-invasiveness. Due to the complexity of the equation defining the measured flow velocity, determining the measurement uncertainty is not an easy task.
Optimal unit commitment scheduling of thermal power system based on the Monte Carlo method.