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Digitalization, Industry 4.0, Data, KPIs, Modelization and Forecast for Energy Production in Hydroelectric Power Plants: A Review

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  • Crescenzo Pepe

    (Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy)

  • Silvia Maria Zanoli

    (Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy)

Abstract

Intelligent water usage is required in order to target the challenging goals for 2030 and 2050. Hydroelectric power plants represent processes wherein water is exploited as a renewable resource and a source for energy production. Hydroelectric power plants usually include reservoirs, valves, gates, and energy production devices, e.g., turbines. In this context, monitoring and maintenance policies together with control and optimization strategies, at the different levels of the automation hierarchy, may represent strategic tools and drivers for energy efficiency improvement. Nowadays, these strategies rely on different basic concepts and elements, which must be assessed and investigated in order to provide a reliable background. This paper focuses on a review of the state of the art associated with these basic concepts and elements, i.e., digitalization, Industry 4.0, data, KPIs, modelization, and forecast.

Suggested Citation

  • Crescenzo Pepe & Silvia Maria Zanoli, 2024. "Digitalization, Industry 4.0, Data, KPIs, Modelization and Forecast for Energy Production in Hydroelectric Power Plants: A Review," Energies, MDPI, vol. 17(4), pages 1-35, February.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:4:p:941-:d:1340546
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    References listed on IDEAS

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    1. Muh, Erasmus & Tabet, Fouzi, 2019. "Comparative analysis of hybrid renewable energy systems for off-grid applications in Southern Cameroons," Renewable Energy, Elsevier, vol. 135(C), pages 41-54.
    2. Xiaoli Zhang & Yong Peng & Wei Xu & Bende Wang, 2019. "An Optimal Operation Model for Hydropower Stations Considering Inflow Forecasts with Different Lead-Times," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 173-188, January.
    3. Aslan, Yilmaz & Arslan, Oguz & Yasar, Celal, 2008. "A sensitivity analysis for the design of small-scale hydropower plant: Kayabogazi case study," Renewable Energy, Elsevier, vol. 33(4), pages 791-801.
    4. Jennifer Kreklow & Björn Tetzlaff & Gerald Kuhnt & Benjamin Burkhard, 2019. "A Rainfall Data Intercomparison Dataset of RADKLIM, RADOLAN, and Rain Gauge Data for Germany," Data, MDPI, vol. 4(3), pages 1-16, August.
    5. Aldemar Leguizamon-Perilla & Juan S. Rodriguez-Bernal & Laidi Moralez-Cruz & Nidia Isabel Farfán-Martinez & César Nieto-Londoño & Rafael E. Vásquez & Ana Escudero-Atehortua, 2023. "Digitalisation and Modernisation of Hydropower Operating Facilities to Support the Colombian Energy Mix Flexibility," Energies, MDPI, vol. 16(7), pages 1-17, March.
    6. Jessica B. Heluany & Ricardo Galvão, 2023. "IEC 62443 Standard for Hydro Power Plants," Energies, MDPI, vol. 16(3), pages 1-16, February.
    7. Jie Chen & François Brissette, 2015. "Combining Stochastic Weather Generation and Ensemble Weather Forecasts for Short-Term Streamflow Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(9), pages 3329-3342, July.
    8. Fernando Mainardi Fan & Dirk Schwanenberg & Rodolfo Alvarado & Alberto Assis dos Reis & Walter Collischonn & Steffi Naumman, 2016. "Performance of Deterministic and Probabilistic Hydrological Forecasts for the Short-Term Optimization of a Tropical Hydropower Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3609-3625, August.
    9. Augusto Cesar Campos de Souza Machado & Geraldo Lucio Tiago Filho & Thiago Modesto de Abreu & Francesco Facchini & Robson Francisco da Silva & Luiz Fernando Rodrigues Pinto, 2023. "Use of Balanced Scorecard (BSC) Performance Indicators for Small-Scale Hydropower Project Attractiveness Analysis," Energies, MDPI, vol. 16(18), pages 1-16, September.
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