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Energy Optimization of Industrial Steam Boiler using Energy Performance Indicator

Author

Listed:
  • Guillermo Valencia Ochoa

    (Mechanical Engineering Program, Faculty of Engineering, Grupo de Investigaci n en Gesti n Eficiente de la Energia-ka , Universidad del Atl ntico, Carrera 30 N mero 8-49, Puerto Colombia 081007, Atl ntico, Colombia,)

  • Jhan Piero Rojas

    (Faculty of Engineering, Universidad Francisco de Paula Santander, #0-a Avenida Gran Colombia No. 12E-96, C cuta, Norte de Santander, Colombia.)

  • Juan Campos Avella

    (Mechanical Engineering Program, Faculty of Engineering, Grupo de Investigaci n en Gesti n Eficiente de la Energia-ka , Universidad del Atl ntico, Carrera 30 N mero 8-49, Puerto Colombia 081007, Atl ntico, Colombia,)

Abstract

This article shows the application of an energy management system and the calculation of energy efficiency indicators to a pyrotubular boiler, following the guidelines of the ISO50001 standard. The actual energy consumption indicators, the theoretical consumption index, the energy baseline and the efficiency index 100 were evaluated based on gas consumption and steam production data. As for the savings measure, a 20% reduction in gas consumption can be achieved by reducing the operational variability equivalent to 186,633 m3/month, thereby achieving a monthly savings of $70,920,717 COP and a large reduction in natural gas equivalent to a reduction in CO2 emissions (1,318,739.05 kg CO2/month). Also, the purges currently recorded in the boiler are higher than the recommended value for this equipment, and the excess air released varies between 6% and 11%, increasing the losses due to sensible heat. Three main implementations were applied to improve the energy performance of the steam boiler. The first saving implementation was the reduction of the generation pressure from 250 to 180 psig, achieving a lower gas temperature with a reduction of heat losses from the boiler, pipes and steam leakage losses, achieving a saving of 2% of the average natural gas consumption. The second implementation was the automation of the boiler purges, in accordance with the recommended value UNE-9075/85, achieving a total saving of 0.66%, and the third measurement allows on-line correction of the combustion air by direct measurement of O2, which maintains the measured oxygen value at 3%, which is the recommended value. With this practical and novel method energy performance indicator on the boiler, was increased the performance of the equipment, as well as the production costs and environmental impact reduction.

Suggested Citation

  • Guillermo Valencia Ochoa & Jhan Piero Rojas & Juan Campos Avella, 2019. "Energy Optimization of Industrial Steam Boiler using Energy Performance Indicator," International Journal of Energy Economics and Policy, Econjournals, vol. 9(6), pages 109-117.
  • Handle: RePEc:eco:journ2:2019-06-14
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    References listed on IDEAS

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    1. Shen, Bo & Han, Yafeng & Price, Lynn & Lu, Hongyou & Liu, Manzhi, 2017. "Techno-economic evaluation of strategies for addressing energy and environmental challenges of industrial boilers in China," Energy, Elsevier, vol. 118(C), pages 526-533.
    2. Habib, Mohammad Ahsan & Hasanuzzaman, M. & Hosenuzzaman, M. & Salman, Asif & Mehadi, Md Riyad, 2016. "Energy consumption, energy saving and emission reduction of a garment industrial building in Bangladesh," Energy, Elsevier, vol. 112(C), pages 91-100.
    3. Meschede, Henning & Dunkelberg, Heiko & Stöhr, Fabian & Peesel, Ron-Hendrik & Hesselbach, Jens, 2017. "Assessment of probabilistic distributed factors influencing renewable energy supply for hotels using Monte-Carlo methods," Energy, Elsevier, vol. 128(C), pages 86-100.
    4. Feng, Tian-tian & Yang, Yi-sheng & Xie, Shi-yan & Dong, Jun & Ding, Luo, 2017. "Economic drivers of greenhouse gas emissions in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 996-1006.
    5. May, Gökan & Barletta, Ilaria & Stahl, Bojan & Taisch, Marco, 2015. "Energy management in production: A novel method to develop key performance indicators for improving energy efficiency," Applied Energy, Elsevier, vol. 149(C), pages 46-61.
    6. Mecrow, B.C. & Jack, A.G., 2008. "Efficiency trends in electric machines and drives," Energy Policy, Elsevier, vol. 36(12), pages 4336-4341, December.
    7. Barma, M.C. & Saidur, R. & Rahman, S.M.A. & Allouhi, A. & Akash, B.A. & Sait, Sadiq M., 2017. "A review on boilers energy use, energy savings, and emissions reductions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 970-983.
    8. Nikula, Riku-Pekka & Ruusunen, Mika & Leiviskä, Kauko, 2016. "Data-driven framework for boiler performance monitoring," Applied Energy, Elsevier, vol. 183(C), pages 1374-1388.
    9. Arens, M. & Worrell, E., 2014. "Diffusion of energy efficient technologies in the German steel industry and their impact on energy consumption," Energy, Elsevier, vol. 73(C), pages 968-977.
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    More about this item

    Keywords

    Energy Optimization; Steam Boiler; Energy Performance Indicator; ISO 50001 Standard.;
    All these keywords.

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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