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Reducing the energy consumption and CO2 emissions of energy intensive industries through decision support systems – An example of application to the steel industry

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  • Porzio, Giacomo Filippo
  • Fornai, Barbara
  • Amato, Alessandro
  • Matarese, Nicola
  • Vannucci, Marco
  • Chiappelli, Lisa
  • Colla, Valentina

Abstract

The management of process industries is becoming in the recent years more and more challenging, given the stringent environmental policies as well as raising energy costs and the always-present drive for profit. A way to help plant decision makers in their daily choices is to refer to decision-support tools, which can give advice on the best practices on how to operate a plant in order to reduce the energy consumption and the CO2 emissions keeping at the same time the costs under control. Such an approach can be useful in a variety of industries, particularly the most energy-intensive ones such as iron and steel industries. In this paper, an approach to the realisation of a software system, which allows to generate internal reports on the plant performances, as well as to simulate the plant behaviour in different scenarios, is described. The main production processes (coke plant, blast furnace, steel shop, hot rolling mill) are described and simulated focusing on the prediction of products flow rates and composition, energy consumption and GHGs (Greenhouse Gases) emissions in different operating conditions. The importance of a correct management of the CO2 within the plant is underlined, particularly with regard to the new EU Emission Trading System, which will be based on European benchmarks. The software tool is illustrated and a case study is included, which focuses on the simultaneous minimisation of the CO2 emissions and maximisation of the profit through an optimised management of the by-product gases. The results from the case study show a good potential for process improvement, by a reduction in the cost and environmental impact.

Suggested Citation

  • Porzio, Giacomo Filippo & Fornai, Barbara & Amato, Alessandro & Matarese, Nicola & Vannucci, Marco & Chiappelli, Lisa & Colla, Valentina, 2013. "Reducing the energy consumption and CO2 emissions of energy intensive industries through decision support systems – An example of application to the steel industry," Applied Energy, Elsevier, vol. 112(C), pages 818-833.
    • Handle: RePEc:eee:appene:v:112:y:2013:i:c:p:818-833
    DOI: 10.1016/j.apenergy.2013.05.005
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    References listed on IDEAS

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    1. Tanaka, Kanako, 2012. "A comparison study of EU and Japan methods to assess CO2 emission reduction and energy saving in the iron and steel industry," Energy Policy, Elsevier, vol. 51(C), pages 578-585.
    2. Kong, Haining & Qi, Ershi & Li, Hui & Li, Gang & Zhang, Xing, 2010. "An MILP model for optimization of byproduct gases in the integrated iron and steel plant," Applied Energy, Elsevier, vol. 87(7), pages 2156-2163, July.
    3. Tanaka, Kanako, 2008. "Assessment of energy efficiency performance measures in industry and their application for policy," Energy Policy, Elsevier, vol. 36(8), pages 2877-2892, August.
    4. Karlsson, Magnus, 2011. "The MIND method: A decision support for optimization of industrial energy systems - Principles and case studies," Applied Energy, Elsevier, vol. 88(3), pages 577-589, March.
    5. Arens, Marlene & Worrell, Ernst & Schleich, Joachim, 2012. "Energy intensity development of the German iron and steel industry between 1991 and 2007," Energy, Elsevier, vol. 45(1), pages 786-797.
    6. Fröhling, Magnus & Schwaderer, Frank & Bartusch, Hauke & Rentz, Otto, 2010. "Integrated planning of transportation and recycling for multiple plants based on process simulation," European Journal of Operational Research, Elsevier, vol. 207(2), pages 958-970, December.
    7. Thollander, Patrik & Mardan, Nawzad & Karlsson, Magnus, 2009. "Optimization as investment decision support in a Swedish medium-sized iron foundry - A move beyond traditional energy auditing," Applied Energy, Elsevier, vol. 86(4), pages 433-440, April.
    8. Carvalho, Monica & Lozano, Miguel A. & Serra, Luis M., 2012. "Multicriteria synthesis of trigeneration systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 91(1), pages 245-254.
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