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Development of a Computational Tool for Measuring Organizational Competitiveness in the Photovoltaic Power Plants

Author

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  • Carmen B. Rosa

    (Pós-Graduação em Engenharia Elétrica, Federal University of Santa Maria (UFSM), 97105-900 Santa Maria, Brazil)

  • Graciele Rediske

    (Pós-Graduação em Engenharia de Produção, Federal University of Santa Maria (UFSM), 97105-900 Santa Maria, Brazil)

  • Paula D. Rigo

    (Pós-Graduação em Engenharia de Produção, Federal University of Santa Maria (UFSM), 97105-900 Santa Maria, Brazil)

  • João Francisco M. Wendt

    (Pós-Graduação em Engenharia de Produção, Federal University of Santa Maria (UFSM), 97105-900 Santa Maria, Brazil)

  • Leandro Michels

    (Pós-Graduação em Engenharia Elétrica, Federal University of Santa Maria (UFSM), 97105-900 Santa Maria, Brazil)

  • Julio Cezar M. Siluk

    (Pós-Graduação em Engenharia de Produção, Federal University of Santa Maria (UFSM), 97105-900 Santa Maria, Brazil)

Abstract

Photovoltaic (PV) power generation is embedded in a globally competitive environment. This characteristic forces PV power plants to perform most processes relevant for their competitiveness with maximum efficiency. From managers’ point of view, the evaluation of solar energy performance from installed plants is justified to indicate their level of organizational competitiveness, which supports the decision-making process. This manuscript purposes a computational tool that graphically presents the level of competitiveness of PV power plants units based on performance indicators. This tool was developed by using the Key Performance Indicators (KPIs) concept, which represents a set of measures focusing on the most critical aspects for the success of the organizations. The KPIs encompass four Fundamental Viewpoints (FV): Strategic Alliances, Solar Energy Monitoring, Management and Strategic Processes, and Power Generation Innovations. These four FVs were deployed on 26 Critical Success Factors (CSFs) and 39 KPIs. Sequentially, the tool was applied in four solar generation plants, where three presented an organizational competitiveness global level “potentially competitive”. The proposed computational tool allows managers to assess the degree of organization competitiveness as well as aid in prospecting of future scenarios and decision-making.

Suggested Citation

  • Carmen B. Rosa & Graciele Rediske & Paula D. Rigo & João Francisco M. Wendt & Leandro Michels & Julio Cezar M. Siluk, 2018. "Development of a Computational Tool for Measuring Organizational Competitiveness in the Photovoltaic Power Plants," Energies, MDPI, vol. 11(4), pages 1-13, April.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:867-:d:140091
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    1. J. C. Teo & Rodney H. G. Tan & V. H. Mok & Vigna K. Ramachandaramurthy & ChiaKwang Tan, 2018. "Impact of Partial Shading on the P-V Characteristics and the Maximum Power of a Photovoltaic String," Energies, MDPI, vol. 11(7), pages 1-22, July.
    2. Natália Gava Gastaldo & Graciele Rediske & Paula Donaduzzi Rigo & Carmen Brum Rosa & Leandro Michels & Julio Cezar Mairesse Siluk, 2019. "What is the Profile of the Investor in Household Solar Photovoltaic Energy Systems?," Energies, MDPI, vol. 12(23), pages 1-18, November.
    3. Ioan Aschilean & Gabriel Rasoi & Maria Simona Raboaca & Constantin Filote & Mihai Culcer, 2018. "Design and Concept of an Energy System Based on Renewable Sources for Greenhouse Sustainable Agriculture," Energies, MDPI, vol. 11(5), pages 1-12, May.
    4. 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).
    5. Felipe Moraes do Nascimento & Julio Cezar Mairesse Siluk & Fernando de Souza Savian & Taís Bisognin Garlet & José Renes Pinheiro & Carlos Ramos, 2020. "Factors for Measuring Photovoltaic Adoption from the Perspective of Operators," Sustainability, MDPI, vol. 12(8), pages 1-29, April.

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