An improved technique for identification of mathematical model parameters of thermal power equipment and assessment of its performance

Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences, Irkutsk, Russia

vitaliy@yandex.ru

Abstract

The problems of state estimation of thermal power system operation and identification of mathematical model parameters have not been acceptably solved due to the complexity of studied objects and their mathematical models, and the lack of effective methods, algorithms and computer programs to solve the required mathematical problems. The results of solving the indicated problems are of importance as such, and play a great part in the qualitative solution to the problems of thermal power equipment control, e.g., the problems of optimal load dispatch among thermal power plant units and optimal control of thermal power equipment operation conditions. The paper describes a technique improved by the author for identification (adjustment, verification) of mathematical model parameters for complex thermal power equipment. The technique allows us to more effectively detect gross errors in measurements of control parameters used for identification of the mathematical model of the studied equipment, to evaluate correctness and rectify errors in the mathematical model construction, and to improve identification accuracy. An improved technique for identification of mathematical model parameters was tested on a detailed mathematical model of the present-day 225 MW generating unit that was constructed by the author. The paper presents results of solving the identification problem of mathematical model parameters of a generating unit and an example of the optimization calculation of the real operation condition in order to reduce specific fuel consumption for electricity generation. In addition, the paper discusses an issue of assessing the identification accuracy of mathematical model parameters of thermal power equipment that depends on the accuracy of measurements of control parameters used to adjust the model, as well as on the correctness of the mathematical model construction and the calculation technique applied.