Application of artificial neural networks for testing long-term energy policy targets

Highlights: • Analysis of European Union energy system using Artificial Neural Network is presented. • Based on key indicators, emissions of CO₂ in the year 2050 are estimated. • Influence of energy policy on energy trends is discussed. -- Abstract: The paper analyses a model of the EU energy system by means of artificial neural networks. This model is based on the prediction of CO₂ emissions until 2050 taking into account the current Energy Policy of the EU. The results show that artificial neural networks model this system very well and that this model has the ability to predict the behaviour of CO₂ emissions. This will also enable timely response and correction of energy and economic strategy by changing the value of the relevant indicators in order to achieve the ambitious planned reductions of CO₂ emissions by 2050. These plans are specified in the Energy Roadmap 2050 document of the European Commission from 2012 and promote economically cost-effective scenarios that will adapt the European Union's economy to the needs of environmental protection and the reduction of energy consumption. Several structures of Artificial Neural Networks were analysed in order to select the best one for modelling large energy systems. It was determined that the model with the Cascade Forward Back Propagation structure with numerous specific indicators can model such energy systems and predict of CO₂ emissions with acceptable accuracy.