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Unsupervised grouping of industrial electricity demand profiles: Synthetic profiles for demand-side management applications

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  • Valdes, Javier
  • Masip Macia, Yunesky
  • Dorner, Wolfgang
  • Ramirez Camargo, Luis

Abstract

Demand side management is a promising alternative to offer flexibility to power systems with high shares of variable renewable energy sources. Numerous industries possess large demand side management potentials but accounting for them in energy system analysis and modelling is restricted by the availability of their demand data, which are usually confidential. In this study, a methodology to synthetize anonymized hourly electricity consumption profiles for industries and to calculate their flexibility potential is proposed. This combines different partitioning and hierarchical clustering analysis techniques with regression analysis. The methodology is applied to three case studies in Chile: two pulp and paper industry plants and one food industry plant. A significant hourly, daily and annual flexibility potential is found for the three cases (15%–75%). Moreover, the resulting demand profiles share the same statistical characteristics as the measured profiles but can be used in modelling exercises without confidentiality issues.

Suggested Citation

  • Valdes, Javier & Masip Macia, Yunesky & Dorner, Wolfgang & Ramirez Camargo, Luis, 2021. "Unsupervised grouping of industrial electricity demand profiles: Synthetic profiles for demand-side management applications," Energy, Elsevier, vol. 215(PA).
    • Handle: RePEc:eee:energy:v:215:y:2021:i:pa:s0360544220320697
    DOI: 10.1016/j.energy.2020.118962
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    as
    1. Valdés Lucas, Javier Noel & Escribano Francés, Gonzalo & San Martín González, Enrique, 2016. "Energy security and renewable energy deployment in the EU: Liaisons Dangereuses or Virtuous Circle?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 1032-1046.
    2. Yilmaz, S. & Chambers, J. & Patel, M.K., 2019. "Comparison of clustering approaches for domestic electricity load profile characterisation - Implications for demand side management," Energy, Elsevier, vol. 180(C), pages 665-677.
    3. Helin, Kristo & Käki, Anssi & Zakeri, Behnam & Lahdelma, Risto & Syri, Sanna, 2017. "Economic potential of industrial demand side management in pulp and paper industry," Energy, Elsevier, vol. 141(C), pages 1681-1694.
    4. Gils, Hans Christian, 2014. "Assessment of the theoretical demand response potential in Europe," Energy, Elsevier, vol. 67(C), pages 1-18.
    5. Lamidi, Rasaq. O. & Jiang, L. & Pathare, Pankaj B. & Wang, Y.D. & Roskilly, A.P., 2019. "Recent advances in sustainable drying of agricultural produce: A review," Applied Energy, Elsevier, vol. 233, pages 367-385.
    6. Torriti, Jacopo & Hassan, Mohamed G. & Leach, Matthew, 2010. "Demand response experience in Europe: Policies, programmes and implementation," Energy, Elsevier, vol. 35(4), pages 1575-1583.
    7. Valdes, Javier & Poque González, Axel Bastián & Masip Macia, Yunesky & Dorner, Wolfgang & Ramirez Camargo, Luis, 2020. "Unveiling the potential for combined heat and power in Chilean industry - A policy perspective," Energy Policy, Elsevier, vol. 140(C).
    8. McLoughlin, Fintan & Duffy, Aidan & Conlon, Michael, 2013. "Evaluation of time series techniques to characterise domestic electricity demand," Energy, Elsevier, vol. 50(C), pages 120-130.
    9. Luo, Xing & Zhu, Xu & Lim, Eng Gee, 2019. "A parametric bootstrap algorithm for cluster number determination of load pattern categorization," Energy, Elsevier, vol. 180(C), pages 50-60.
    10. Yilmaz, S. & Weber, S. & Patel, M.K., 2019. "Who is sensitive to DSM? Understanding the determinants of the shape of electricity load curves and demand shifting: Socio-demographic characteristics, appliance use and attitudes," Energy Policy, Elsevier, vol. 133(C).
    11. Shiljkut, Vladimir M. & Rajakovic, Nikola Lj., 2015. "Demand response capacity estimation in various supply areas," Energy, Elsevier, vol. 92(P3), pages 476-486.
    12. O'Doherty, Joe & Lyons, Sean & Tol, Richard S.J., 2008. "Energy-using appliances and energy-saving features: Determinants of ownership in Ireland," Applied Energy, Elsevier, vol. 85(7), pages 650-662, July.
    13. Félix Iglesias & Wolfgang Kastner, 2013. "Analysis of Similarity Measures in Times Series Clustering for the Discovery of Building Energy Patterns," Energies, MDPI, vol. 6(2), pages 1-19, January.
    14. Paulus, Moritz & Borggrefe, Frieder, 2011. "The potential of demand-side management in energy-intensive industries for electricity markets in Germany," Applied Energy, Elsevier, vol. 88(2), pages 432-441, February.
    15. Fleiter, Tobias & Fehrenbach, Daniel & Worrell, Ernst & Eichhammer, Wolfgang, 2012. "Energy efficiency in the German pulp and paper industry – A model-based assessment of saving potentials," Energy, Elsevier, vol. 40(1), pages 84-99.
    16. Rogers, John Geoffrey & Cooper, Samuel J. & Norman, Jon B., 2018. "Uses of industrial energy benchmarking with reference to the pulp and paper industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 23-37.
    17. Chicco, Gianfranco, 2012. "Overview and performance assessment of the clustering methods for electrical load pattern grouping," Energy, Elsevier, vol. 42(1), pages 68-80.
    18. Motlagh, Omid & Berry, Adam & O'Neil, Lachlan, 2019. "Clustering of residential electricity customers using load time series," Applied Energy, Elsevier, vol. 237(C), pages 11-24.
    19. Wang, Shaobin & Liu, Haimeng & Pu, Haixia & Yang, Hao, 2020. "Spatial disparity and hierarchical cluster analysis of final energy consumption in China," Energy, Elsevier, vol. 197(C).
    20. Hong, Gui-Bing & Ma, Chih-Ming & Chen, Hua-Wei & Chuang, Kai-Jen & Chang, Chang-Tang & Su, Te-Li, 2011. "Energy flow analysis in pulp and paper industry," Energy, Elsevier, vol. 36(5), pages 3063-3068.
    21. Alasseri, Rajeev & Tripathi, Ashish & Joji Rao, T. & Sreekanth, K.J., 2017. "A review on implementation strategies for demand side management (DSM) in Kuwait through incentive-based demand response programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 617-635.
    22. Grünewald, Philipp & Torriti, Jacopo, 2013. "Demand response from the non-domestic sector: Early UK experiences and future opportunities," Energy Policy, Elsevier, vol. 61(C), pages 423-429.
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    5. Golmohamadi, Hessam, 2022. "Demand-side management in industrial sector: A review of heavy industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).

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