Energy monitoring of process systems: time-series segmentation-based targeting models

Abstract

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 key energy indicators (KEIs) allows the comparison of process efficiency at different operating regimes. Based on the extracted knowledge realistic targets of KEIs can be determined. The performance of data-driven targeting models depends on how effective the operating regimes are characterized. Till now this modeling task is performed manually based on heuristic and subjective evaluation of the operation. A goal-oriented time-series segmentation technique has been developed to automate the selection of proper data used for the identification of targeting models. With the proposed novel segmentation algorithm targeting-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.