Algorithmic optimization of coal-fired boilers using energy consumption models

This article discusses approaches to modeling and optimizing the energy consumption of a coal-fired boiler house in order to increase its efficiency and reduce fuel costs. The main focus is on the use of mathematical models to calculate coal consumption and control thermal processes in the boiler room. The use of a genetic algorithm to optimize system parameters, such as the thermal insulation coefficient, the frequency of coal supplies and operating costs, allowed minimizing the total heating costs. During the study, a model was developed that takes into account external climatic conditions, heat loss through walls and windows, as well as the efficiency of boilers. Experimental results have shown that improving thermal insulation and adjusting the frequency of coal supplies significantly reduce operating costs, especially in low temperature conditions. The presented results confirm that the integration of energy management systems with optimization algorithms contributes to improving the efficiency of coal-fired boilers and reducing their impact on the environment. This model can be adapted for use in industrial facilities, which makes it a useful tool for enterprises seeking to reduce operating costs and increase environmental sustainability.