a b s t r a c tThe optimization of a location of redundant measurements under varying loads for steam boiler of a supercritical power unit using the generalized method of data reconciliation has been carried out. The method of weighted objectives has been applied as a method of optimization. This method reduce the weighted multi-criteria optimization task to task one-dimensional. Measurement values have been determined by numerical experiment and the Monte Carlo method for the designed redundant measurements system. For this purpose, a mathematical simulation model of a supercritical steam power unit with power rating of 900 MW in the Thermoflex program has been worked out. In the optimization calculations of location of redundant measurements as an objective functions minimizing the relative standard deviation of a boiler thermal capacity and maximizing the Kullback-Leibler divergence have been accepted. In the calculation the measurements were taken into account, which can be located in the water-steam system of the boiler and in the high-pressure heat recovery steam supercritical power unit. The results of calculations confirm the influence of the number of redundant measurements and places of their location in the thermal system of the boiler on the accepted criteria of optimization. Increasing the number of redundant measurements, in terms of the data reconciliation method, leads to decrease the relative standard deviation of the thermal capacity of the boiler and increase the value of KullbackLeibler divergence, i.e.; decrease the information entropy of the measuring system.
For the optimal location of an additional surplus measurements in the design of redundant measurements system, from data reconciliation point of view, of thermal processes, an information entropy has been applied. The relative entropy -Kullback-Leibler divergence, has been used. As a criterion of the optimal location of an additional surplus measurements in a system of measurements data, the minimum of the entropy information of reconciled measurements data has been assumed. Hence, the objective function in the described optimization task is maximum of the relative entropy -Kullback-Leibler divergence concerning sets of raw and reconciled measurements data. Simulation calculation with application of data reconciliation algorithm and Monte Carlo method concerning the influence of installation of the additional surplus measurements on decrease of entropy information of measurements after data validation have been carried out. The example calculations concerned the cross high-pressure heat regeneration system with cascade flow of condensate installed in 153 MW power unit equipped with cooler of steam are presented. Calculations for all variants of configurations of an additional surplus measurements in the analyzed thermal system have been done. Usefulness of the proposed Kullback-Leibler divergence as a objective function has been demonstrated.
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