THE USE OF ASH FROM THERMAL POWER PLANT DUMPS IN THE PRODUCTION OF PORTLAND CEMENT

The article considers a technical solution for the introduction of pozzolan additives into the cement after grinding clinker. Such additives are the fly ash of the CHP and ash from the ash dump. The use of ash in the composition of cement reduces its cost and energy intensity of its production

Development of methodology and measures to ensure the reliability of energy systems equipment

THE PURPOSE: The article presents the results of the development of a methodology for the design calculation of reliability and changes in the level of reliability of energy systems, taking into account the influence of control actions based on statistical methods of collection, analysis and models of experimental data processing.METHODS: The system analysis and generalization of experimental data on technological failures of the main equipment of thermal power plants were used in the calculation assessment.RESULTS: The objective function of controlling the reliability parameters of the thermal power plant power equipment is proposed. The approbation of the presented objective control function was performed, which showed the adequacy of the results obtained to assess the reliability of the main nodes and elements of the TPP power equipment.CONCLUSION: The results of the conducted studies show that when determining reliability indicators, it is necessary to take into account the actual technical condition of individual elements and resource-determining functional units of thermal power plant power equipment. The results obtained can be used to develop a methodology for evaluating control actions for calculating the output control parameters and a mathematical model for changing the output characteristics of TPP steam turbines in terms of heat and electric energy generation, as well as at the stage of developing design documentation for the creation of structural elements and practical recommendations in order to extend the service life of power equipment generating systems based on digital technologies.

Application of machine learning to predict the thermal power plant process condition

This paper deals with the development of an algorithm for predicting thermal power plant process variables. The input data are described, and the data cleaning algorithm is presented along with the Python frameworks used. The employed machine learning model is discussed, and the results are presented.