Artificial Intelligence in the Problems of Organizational Control and Planning of Electric Power Consumption in Oil Pipeline Transportation

Oil pipeline transportation is one of the significant power consumers. Currently, a single electric power market has been formed, which ensures strict control over its consumption. Any excess in or underdrawal of the actual power consumption compared to the planned figure is punished with fines. In this connection, the accuracy of planning the power consumption for oil transportation is a relevant problem. Artificial intelligence allows promptly and effectively solve complex problems in various areas. In this paper, the problem of building a neural network identification model for oil pipeline transportation has been considered. Solving problems using neural networks proceeds in several stages. First, identification models of the object under study are built, and then, the object’s behavior is studied and analyzed using the models built. Using the neural network model, the problems of organizational control and planning of electric power consumption in oil pipeline transportation have been considered. The models have been built and tested based on actual data. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.