Historical Process Data Based Energy Monitoring - Model Based Time-Series Segmentation to Determine Target Values

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 operati...

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Main Authors: J. Abonyi, T. Kulcsar, M. Balaton, L. Nagy
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2013-09-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/6104
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spelling doaj-2d6b12f235d342228a8205065d5356762021-02-21T21:03:54ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162013-09-013510.3303/CET1335155Historical Process Data Based Energy Monitoring - Model Based Time-Series Segmentation to Determine Target ValuesJ. AbonyiT. KulcsarM. BalatonL. NagyEnergy 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 data-driven 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.https://www.cetjournal.it/index.php/cet/article/view/6104
collection DOAJ
language English
format Article
sources DOAJ
author J. Abonyi
T. Kulcsar
M. Balaton
L. Nagy
spellingShingle J. Abonyi
T. Kulcsar
M. Balaton
L. Nagy
Historical Process Data Based Energy Monitoring - Model Based Time-Series Segmentation to Determine Target Values
Chemical Engineering Transactions
author_facet J. Abonyi
T. Kulcsar
M. Balaton
L. Nagy
author_sort J. Abonyi
title Historical Process Data Based Energy Monitoring - Model Based Time-Series Segmentation to Determine Target Values
title_short Historical Process Data Based Energy Monitoring - Model Based Time-Series Segmentation to Determine Target Values
title_full Historical Process Data Based Energy Monitoring - Model Based Time-Series Segmentation to Determine Target Values
title_fullStr Historical Process Data Based Energy Monitoring - Model Based Time-Series Segmentation to Determine Target Values
title_full_unstemmed Historical Process Data Based Energy Monitoring - Model Based Time-Series Segmentation to Determine Target Values
title_sort historical process data based energy monitoring - model based time-series segmentation to determine target values
publisher AIDIC Servizi S.r.l.
series Chemical Engineering Transactions
issn 2283-9216
publishDate 2013-09-01
description 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 data-driven 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.
url https://www.cetjournal.it/index.php/cet/article/view/6104
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AT tkulcsar historicalprocessdatabasedenergymonitoringmodelbasedtimeseriessegmentationtodeterminetargetvalues
AT mbalaton historicalprocessdatabasedenergymonitoringmodelbasedtimeseriessegmentationtodeterminetargetvalues
AT lnagy historicalprocessdatabasedenergymonitoringmodelbasedtimeseriessegmentationtodeterminetargetvalues
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