Optimization of CHP operation taking into account the use of neural network technologies

Thermal power plants generate more than half of world's electric energy. The question of optimisation of thermal power plants is very relevant for the regions of Russia's Far East. This paper is dedicated to researching the possibilities of reducing loss of electric energy for steam condensation. An analysis of thermal power plant's operating modes was conducted in searching of ways to optimise them. Excessive steam generation was pointed out as a main drawback of thermal power plant's operation, it is not fully coordinated and often exceeds the needs of users in electricity and heat. The issue of reducing energy losses by analyzing the operating modes of the thermal power plant, the amount of electricity consumed and weather conditions depending on time is considered. The use of algorithms based on artificial neural networks to solve the problem of predicting the required amount of energy is proposed.