Energy monitoring systems calculate actual energy use, estimate energy needs at normal operation, track energy metrics, and highlight issues related to energy efficiency of process plants. Analysis of the Key Energy Indicators (KEIs) allows the comparison of operation strategies at different operating regimes. Based on the extracted knowledge realistic targets of KEI-s can be determined. The performance of datadriven targeting models depends on operating regimes determined by a complex set of process variables. Till now this modelling task is performed manually based on heuristic and subjective evaluation of the operation. We developed a goal-oriented time-series segmentation technique to automate the selection of proper dataset used for the identification of targeting models. With the proposed tool target-models for different operating regions can be automatically determined. The concept of the resulted energy monitoring system is demonstrated at Heavy Naphtha Hydrotreater and CCR Reforming Units of MOL Hungarian Oil and Gas Company.
ASJC Scopus subject areas
- Chemical Engineering(all)