Optimizing Industrial Energy Management: Advanced Simulators Enhanced With Machine Learning For Improved Forecast Accuracy

The aim is to face the problem of uncertainty of forecasting. It evaluated the integration of Artificial Intelligence (AI) into a simulator to improve its accuracy in the energy prediction, applied to industrial field. Firstly, a literature review on the main applications of AI into energy consumption forecasting was carried out. Then a case study has been taken and Random Forest has been applied to improve forecasting. The AI model improved accuracy of the prediction, being able to consider real-time data of weather and consumption. Therefore, AI has been proved to be successfully implementable for energy forecasting, in synergy with simulation.