Energy Efficiency Analysis of the Refining Unit in Thermo-Mechanical Pulp Mill

Behnam Talebjedi*, Timo Laukkanen, Henrik Holmberg, Esa Vakkilainen, Sanna Syri

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)
184 Downloads (Pure)

Abstract

A refining model is developed to analyses the refining process's energy efficiency based on the refining variables. A simulation model is obtained for longer-term refining energy analysis by further developing the MATLAB Thermo-Mechanical Pulping Simulink toolbox. This model is utilized to predict two essential variables for refining energy efficiency calculation: refining motor-load and generated steam. The conventional variable for presenting refining energy efficiency is refining specific energy consumption (RSEC), which is the ratio of the refining motor load to throughput and does not consider the share of recovered energy from the refining produced steam. In this study, a new variable, corrected refining specific energy consumption (CRSEC), is introduced and practiced for better representation of the refining energy efficiency. In the calculation process of the CRSEC, recovered energy from the refining generated steam is considered useful energy. The developed model results in 160% and 78.75% improvement in simulation model determination coefficient and error, respectively. Utilizing the developed model and hourly district heating demand for CRSEC calculation, results prove a 22% annual average difference between CRSEC and RSEC. Findings confirm that the wintertime refining energy efficiency is 27% higher due to higher recovered energy in the heat recovery unit compared to summertime.

Original languageEnglish
Article number1664
Number of pages18
JournalEnergies
Volume14
Issue number6
DOIs
Publication statusPublished - 17 Mar 2021
MoE publication typeA1 Journal article-refereed

Keywords

  • thermo-mechanical pulping
  • district heating
  • pulping energy efficiency
  • refining energy efficiency
  • data analysis

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