Application of Artificial Neural Networks for Predicting Energy Consumption of a Mining Enterprise

The problem of prediction electricity consumption remains relevant, especially for energy-intensive industrial enterprises with uneven loads, such as mining and processing complexes. Traditional methods of assessing energy consumption do not always consider dynamic changes in the load structure, including seasonal fluctuations, technological features, and operational factors. Inefficient management of active and reactive power can lead to network overload, increased transmission system losses, and reduced power quality. These factors directly affect the stability of electrical equipment, increasing the risk of emergency situations and additional operating costs.