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Energy audit model based on a performance evaluation system

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  • Zanardo, Rafael Petri
  • Siluk, Julio Cezar Mairesse
  • de Souza Savian, Fernando
  • Schneider, Paulo Smith

Abstract

Brazil has one of the highest electricity costs in the world, aggravating one of the lowest rates of development in energy efficiency. This context impairs the competitiveness of the Brazilian industrial sector, which consumes approximately one-third of all electricity generated in the country. The researchers aimed to propose a model to diagnose the level of energy performance in companies of the industrial sector, using concepts of evaluation of organizational performance and multicriteria approach to decision support. The model was developed based on Key Performance Indicators, organized in a hierarchical structure. Six Fundamental Points of View were listed, which were deployed in 58 Critical Success Factors, selected from the recurrences identified in the theoretical framework. The influence level of each indicator in the analysis was performed through the Analytic Hierarchy Process prioritization. In order to evaluate the interaction of performance indicators indices in the modeling, software for data processing and reporting was developed. The modeling was submitted to tests in an industry, returning in its evaluation phase an index that represents its energy performance, thus allowing the discussion of the results obtained. Subsequently, adequacy actions were proposed to simulate the possible gains of performance obtained through the adoption of strategic actions.

Suggested Citation

  • Zanardo, Rafael Petri & Siluk, Julio Cezar Mairesse & de Souza Savian, Fernando & Schneider, Paulo Smith, 2018. "Energy audit model based on a performance evaluation system," Energy, Elsevier, vol. 154(C), pages 544-552.
    • Handle: RePEc:eee:energy:v:154:y:2018:i:c:p:544-552
    DOI: 10.1016/j.energy.2018.04.179
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    Cited by:

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    2. Eduardo Correia & Rodrigo Calili & José Francisco Pessanha & Maria Fatima Almeida, 2023. "Definition of Regulatory Targets for Electricity Non-Technical Losses: Proposition of an Automatic Model-Selection Technique for Panel Data Regressions," Energies, MDPI, vol. 16(6), pages 1-22, March.
    3. Rediske, Graciele & Siluk, Julio Cezar M. & Michels, Leandro & Rigo, Paula D. & Rosa, Carmen B. & Cugler, Gilberto, 2020. "Multi-criteria decision-making model for assessment of large photovoltaic farms in Brazil," Energy, Elsevier, vol. 197(C).
    4. Savian, Fernando de Souza & Siluk, Julio Cezar Mairesse & Garlet, Taís Bisognin & do Nascimento, Felipe Moraes & Pinheiro, José Renes & Vale, Zita, 2021. "Non-technical losses: A systematic contemporary article review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    5. Komang Adi Kurniawan Saputra & Bambang Subroto & Aulia Fuad Rahman & Erwin Saraswati, 2022. "Eco-Efficiency and Energy Audit to Improve Environmental Performance: An Empirical Study of Hotels in Bali-Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 12(6), pages 175-182, November.
    6. Fernando de Souza Savian & Julio Cezar Mairesse Siluk & Tai s Bisognin Garlet & Felipe Moraes do Nascimento & Jose Renes Pinheiro & Zita Vale, 2022. "Non-technical Losses in Brazil: Overview, Challenges, and Directions for Identification and Mitigation," International Journal of Energy Economics and Policy, Econjournals, vol. 12(3), pages 93-107, May.
    7. Rosa, Carmen B. & Wendt, João Francisco M. & Chaves, Daniel M.S. & Thomasi, Virginia & Michels, Leandro & Siluk, Julio Cezar M., 2020. "Mathematical modeling for the measurement of the competitiveness index of Brazil south urban sectors for installation of photovoltaic systems," Energy Policy, Elsevier, vol. 136(C).
    8. de Oliveira Ventura, Lucas & Melo, Joel D. & Padilha-Feltrin, Antonio & Fernández-Gutiérrez, Juan Pablo & Sánchez Zuleta, Carmen C. & Piedrahita Escobar, Carlos César, 2020. "A new way for comparing solutions to non-technical electricity losses in South America," Utilities Policy, Elsevier, vol. 67(C).
    9. Trianni, Andrea & Cagno, Enrico & Accordini, Davide, 2019. "Energy efficiency measures in electric motors systems: A novel classification highlighting specific implications in their adoption," Applied Energy, Elsevier, vol. 252(C), pages 1-1.

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