Research on Integrated Energy System Data Set Monitoring System Based on RPA Process Automation Technology

Integrated energy system integration is an important technical measure to realize energy saving, emission reduction and energy saving. Loads in energy systems tend to vary non-linearly within a specific period. Aiming at the automatic control technology of RPA process, this paper uses Kalman filter to forecast the short-term comprehensive load of energy. In this paper, the model is used to make short-term forecast of energy comprehensive load. It shows that this method is better than Kalman filter in prediction accuracy. MATLAB simulation results show that this method can open a new path for short-term load forecasting of energy systems.