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Energy optimization of Multiple Stage Evaporator system using Water Cycle Algorithm.

Drishti Yadav1, Om Prakash Verma1

  • 1Department of Instrumentation and Control Engineering, Dr. B. R. Ambedkar National Institute of Technology Jalandhar, India-144011.

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Summary

Optimizing paper mill black liquor concentration using a novel Water Cycle Algorithm improves energy efficiency. This hybrid model enhances steam economy by 52.84% and reduces steam consumption by 28.13%.

Keywords:
BiofuelComputing methodologyEnergyEnergy economicsEnergy optimizationEnergy saving strategiesEnergy sustainabilityMultiple Stage EvaporatorRenewable energy resourcesSteam consumptionSteam economyWater Cycle Algorithm

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Area of Science:

  • Chemical Engineering
  • Energy Engineering
  • Biomass Valorization

Background:

  • Black liquor, a byproduct of paper production, is a significant biomass energy resource.
  • Concentrating black liquor via Multiple Stage Evaporators is highly energy-intensive.
  • Improving the energy efficiency of these evaporators is crucial for sustainability.

Purpose of the Study:

  • To develop a non-linear model for a Heptads' stage Multiple Stage Evaporator.
  • To optimize evaporator performance using energy-saving strategies.
  • To enhance the energy efficiency of black liquor concentration.

Main Methods:

  • Non-linear modeling and simulation of a backward feed Multiple Stage Evaporator.
  • Application of the Water Cycle Algorithm (WCA) for optimization.
  • Integration of energy-saving strategies: steam-split, feed-split, and feed-preheating.

Main Results:

  • The Water Cycle Algorithm effectively identified optimal operating parameters.
  • A hybrid model combining all energy-saving strategies achieved the best performance.
  • Optimized Steam Economy: 7.092; Optimized Steam Consumption: 1.919 kg/s.

Conclusions:

  • The hybrid energy-saving strategy significantly enhances evaporator performance.
  • The optimized model shows a 52.84% improvement in Steam Economy and a 28.13% reduction in Steam Consumption compared to real plant data.
  • This approach offers substantial energy savings and improved sustainability in the pulp and paper industry.