Artificial neural network in day-ahead electricity load forecasting for large steel factory

The growing competitiveness of goods on the market forces a violent searching for methods reducing the production costs. The cost of electrical energy is one of the components of these costs. In many cases, in addition to the cost of feedstock, this is a decisive cost. One of the methods allowing minimizing this cost may be the hourly forecasting of energy consumption, as well as purchasing the energy from the Energy Market. The paper presents the program for day-ahead electricity load forecasting for the large steelworks plant.