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Energy modeling framework for optimizing heat recovery in a seasonal food processing facility

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  • Legorburu, Gabriel
  • Smith, Amanda D.

Abstract

Societal, cultural and economic factors are driving food processors to reduce energy consumed per unit mass of food. This presents a unique problem because time variant batch processing using low to medium grade heat is common in food production facilities. Heat recovery methods may be implemented by food processors to reduce energy consumption; however, temporal variance in the process and utility flow require the development of a robust, easily implemented energy model to accurately determine system effectiveness and economic incentive. A bottom-up modular computational framework is proposed to model the energy consumption of a cannery. The model predicts that the cannery will require 612 kJ gas/kg product produced, which is within the ranges provided in previous literature. Results show that adding a globally optimized indirect heat recovery system will reduce the gas consumption by 6% annually. The proposed framework, used here to represent a cannery, may be adapted to many different types of food processing facilities. With a clear picture of energy consumption by device, and the ability to predict the impact of process modification or heat recovery, plant-level energy usage for food processing may be significantly reduced.

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  • Legorburu, Gabriel & Smith, Amanda D., 2018. "Energy modeling framework for optimizing heat recovery in a seasonal food processing facility," Applied Energy, Elsevier, vol. 229(C), pages 151-162.
    • Handle: RePEc:eee:appene:v:229:y:2018:i:c:p:151-162
    DOI: 10.1016/j.apenergy.2018.07.097
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    References listed on IDEAS

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