Рассматривается задача оптимального распределения нагрузки между электроприводами вентиляторов в многосекционной установке охлаждения газа по критерию минимума энергозатрат на охлаждение. Задача оптимизации решается на базе полученной аналитической модели для температуры газа на выходе установки охлаждения. Модель учитывает взаимное влияние режимов работы всех вентиляторов установки. Разработана методика решения задачи оптимального распределения нагрузки между электроприводами вентиляторов для линеаризованной модели процесса с помощью процедуры целочисленного программирования. Методика оптимизации учитывает индивидуальные характеристики аппаратов. The problem of the optimal load distribution between electric drives of fans in a multi-section gas cooling unit is considered based on the minimum energy expenditure for cooling. The optimization problem is solved on the basis of the obtained analytical model for the gas temperature at the outlet of the cooling unit. The model takes into account the mutual infl uence of the operating modes of all fans of the installation. A technique for solving the problem of optimal load sharing between electric drives of fans for a linearized process model is developed using the procedure of integer programming. The optimization technique takes into account the individual characteristics of the devices.

The work is devoted to the development of a dynamic model of a waste heat boiler based on a recurrent neural network. The developed model can be used to create computer simulators for gas turbine plant operators, technologists and operating personnel. The object of modeling is presented as a complex thermodynamic system. The dynamic processes taking place inside the boiler are non-linear and interconnected. Changes in the technological parameters of the exhaust gases occur in ranges that do not allow to obtain an acceptable quality of the linearized model. Due of the difficulty of creating a mathematical description that takes into account the operation of the installation in different modes, recurrent neural networks were chosen to implement the simulation task. Based on the recurrent neural network, a dynamic model was synthesized that describes the change in the technological parameters of the waste heat boiler in the Power boost, Rated Load, Power reduction operating modes. The model output is the temperature of the network water behind the boiler. The created model takes into account the change in the water flow through the boiler, the change in the inlet water temperature, the increase and decrease in the temperature and pressure of the exhaust gas at the inlet of the waste heat boiler. In the formation of training and test samples for the neural network, archival trends obtained during the operation of the waste heat boiler were used. The article provides experimental data, a description of the stages of the synthesis of a neural network model, structural and graphic schemes, simulation results with explanations.

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