IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i24p8070-d1300467.html

Cluster-Based Approach to Estimate Demand in the Polish Power System Using Commercial Customers’ Data

Author

Listed:
  • Tomasz Ząbkowski

    (Institute of Information Technology, Warsaw University of Life Sciences-SGGW, Nowoursynowska 159, 02-787 Warsaw, Poland)

  • Krzysztof Gajowniczek

    (Institute of Information Technology, Warsaw University of Life Sciences-SGGW, Nowoursynowska 159, 02-787 Warsaw, Poland)

  • Grzegorz Matejko

    (Polskie Towarzystwo Cyfrowe, Krakowskie Przedmieście 57/4, 20-076 Lublin, Poland)

  • Jacek Brożyna

    (Department of Quantitative Methods, The Faculty of Management, Rzeszow University of Technology, Aleja Powstańców Warszawy 10/S, 35-959 Rzeszow, Poland)

  • Grzegorz Mentel

    (Department of Quantitative Methods, The Faculty of Management, Rzeszow University of Technology, Aleja Powstańców Warszawy 10/S, 35-959 Rzeszow, Poland
    INTI International University, Persiaran Perdana BBN, Putra Nilai, Nilai 71800, Malaysia)

  • Małgorzata Charytanowicz

    (Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland)

  • Jolanta Jarnicka

    (Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland)

  • Anna Olwert

    (Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland)

  • Weronika Radziszewska

    (Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland)

  • Jörg Verstraete

    (Institute of Fluid-Flow Machinery, Polish Academy of Sciences, Fiszera 14, 80-231 Gdańsk, Poland)

Abstract

This paper presents an approach to estimate demand in the Polish Power System (PPS) using the historical electricity usage of 27 thousand commercial customers, observed between 2016 and 2020. The customer data were clustered and samples as well as features were created to build neural network models. The goal of this research is to analyze if the clustering of customers can help to explain demand in the PPS. Additionally, considering that the datasets available for commercial customers are typically much smaller, it was analyzed what a minimal sample size drawn from the clusters would have to be in order to accurately estimate demand in the PPS. The evaluation and experiments were conducted for each year separately; the results proved that, considering adjusted R 2 and mean absolute percentage error, our clustering-based method can deliver a high accuracy in the load estimation.

Suggested Citation

  • Tomasz Ząbkowski & Krzysztof Gajowniczek & Grzegorz Matejko & Jacek Brożyna & Grzegorz Mentel & Małgorzata Charytanowicz & Jolanta Jarnicka & Anna Olwert & Weronika Radziszewska & Jörg Verstraete, 2023. "Cluster-Based Approach to Estimate Demand in the Polish Power System Using Commercial Customers’ Data," Energies, MDPI, vol. 16(24), pages 1-21, December.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:8070-:d:1300467
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/24/8070/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/24/8070/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hanna, Richard & Gross, Robert, 2021. "How do energy systems model and scenario studies explicitly represent socio-economic, political and technological disruption and discontinuity? Implications for policy and practitioners," Energy Policy, Elsevier, vol. 149(C).
    2. Ouedraogo, Nadia S., 2017. "Modeling sustainable long-term electricity supply-demand in Africa," Applied Energy, Elsevier, vol. 190(C), pages 1047-1067.
    3. Chaudry, Modassar & Jayasuriya, Lahiru & Jenkins, Nick, 2021. "Modelling of integrated local energy systems: Low-carbon energy supply strategies for the Oxford-Cambridge arc region," Energy Policy, Elsevier, vol. 157(C).
    4. Pfenninger, Stefan & Hirth, Lion & Schlecht, Ingmar & Schmid, Eva & Wiese, Frauke & Brown, Tom & Davis, Chris & Gidden, Matthew & Heinrichs, Heidi & Heuberger, Clara & Hilpert, Simon & Krien, Uwe & Ma, 2018. "Opening the black box of energy modelling: Strategies and lessons learned," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 19, pages 63-71.
    5. Tomasz Ząbkowski & Krzysztof Gajowniczek & Grzegorz Matejko & Jacek Brożyna & Grzegorz Mentel & Małgorzata Charytanowicz & Jolanta Jarnicka & Anna Olwert & Weronika Radziszewska, 2023. "Changing Electricity Tariff—An Empirical Analysis Based on Commercial Customers’ Data from Poland," Energies, MDPI, vol. 16(19), pages 1-17, September.
    6. Sahoo, Somadutta & van Stralen, Joost N.P. & Zuidema, Christian & Sijm, Jos & Yamu, Claudia & Faaij, André, 2022. "Regionalization of a national integrated energy system model: A case study of the northern Netherlands," Applied Energy, Elsevier, vol. 306(PB).
    7. Wen, Xin & Jaxa-Rozen, Marc & Trutnevyte, Evelina, 2022. "Accuracy indicators for evaluating retrospective performance of energy system models," Applied Energy, Elsevier, vol. 325(C).
    8. Kwon, Pil Seok & Østergaard, Poul, 2014. "Assessment and evaluation of flexible demand in a Danish future energy scenario," Applied Energy, Elsevier, vol. 134(C), pages 309-320.
    9. Trotter, Philipp A. & Cooper, Nathanial J. & Wilson, Peter R., 2019. "A multi-criteria, long-term energy planning optimisation model with integrated on-grid and off-grid electrification – The case of Uganda," Applied Energy, Elsevier, vol. 243(C), pages 288-312.
    10. Andrea Herbst & Felipe Andrés Toro & Felix Reitze & Eberhard Jochem, 2012. "Introduction to Energy Systems Modelling," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 148(2), pages 111-135, June.
    11. Mirakyan, Atom & De Guio, Roland, 2015. "Modelling and uncertainties in integrated energy planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 46(C), pages 62-69.
    12. Daniel C. Steinberg & Bryan K. Mignone & Jordan Macknick & Yinong Sun & Kelly Eurek & Andrew Badger & Ben Livneh & Kristen Averyt, 2020. "Decomposing supply-side and demand-side impacts of climate change on the US electricity system through 2050," Climatic Change, Springer, vol. 158(2), pages 125-139, January.
    13. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    14. Nadia S. Ouedraogo, 2017. "Modeling sustainable long-term electricity supply-demand in Africa," WIDER Working Paper Series wp-2017-23, World Institute for Development Economic Research (UNU-WIDER).
    15. Kaixin Huang & Matthew J. Eckelman, 2022. "Appending material flows to the National Energy Modeling System (NEMS) for projecting the physical economy of the United States," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 294-308, February.
    16. DeCarolis, Joseph & Daly, Hannah & Dodds, Paul & Keppo, Ilkka & Li, Francis & McDowall, Will & Pye, Steve & Strachan, Neil & Trutnevyte, Evelina & Usher, Will & Winning, Matthew & Yeh, Sonia & Zeyring, 2017. "Formalizing best practice for energy system optimization modelling," Applied Energy, Elsevier, vol. 194(C), pages 184-198.
    17. Heilmann, Erik & Klempp, Nikolai & Wetzel, Heike, 2020. "Design of regional flexibility markets for electricity: A product classification framework for and application to German pilot projects," Utilities Policy, Elsevier, vol. 67(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tomasz Zabkowski & Krzysztof Gajowniczek & Jacek Brożyna & Grzegorz Matejko, 2024. "Matching Electricity Footprint of Commercial Customers to Industry-Specific Profiles for Enhanced Power Management," Energies, MDPI, vol. 17(23), pages 1-14, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    2. Riasad Amin & Deepika Mathur & David Ompong & Kerstin K. Zander, 2024. "Integrating Social Aspects into Energy System Modelling Through the Lens of Public Perspectives: A Review," Energies, MDPI, vol. 17(23), pages 1-33, November.
    3. Silinto, Berino Francisco & van der Laag Yamu, Claudia & Zuidema, Christian & Faaij, André P.C., 2025. "Hybrid renewable energy systems for rural electrification in developing countries: A review on energy system models and spatial explicit modelling tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 207(C).
    4. Dioha, Michael O. & Kumar, Atul, 2020. "Exploring the energy system impacts of Nigeria's Nationally Determined Contributions and low-carbon transition to mid-century," Energy Policy, Elsevier, vol. 144(C).
    5. Larisa Vazhenina & Elena Magaril & Igor Mayburov, 2022. "Resource Conservation as the Main Factor in Increasing the Resource Efficiency of Russian Gas Companies," Resources, MDPI, vol. 11(12), pages 1-14, December.
    6. Bissiri, M. & Moura, P. & Figueiredo, N.C. & Silva, P.P., 2020. "Towards a renewables-based future for West African States: A review of power systems planning approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    7. Lopion, Peter & Markewitz, Peter & Robinius, Martin & Stolten, Detlef, 2018. "A review of current challenges and trends in energy systems modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 156-166.
    8. Thimet, P.J. & Mavromatidis, G., 2022. "Review of model-based electricity system transition scenarios: An analysis for Switzerland, Germany, France, and Italy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    9. Meysam Pourarshad & Younes Noorollahi & Farideh Atabi & Mostafa Panahi, 2024. "Reducing energy and environmental challenges by modeling clean electricity generation in oil-rich regions," Energy & Environment, , vol. 35(3), pages 1185-1215, May.
    10. Fabian Scheller & Frauke Wiese & Jann Michael Weinand & Dominik Franjo Dominkovi'c & Russell McKenna, 2021. "An expert survey to assess the current status and future challenges of energy system analysis," Papers 2106.15518, arXiv.org.
    11. Felder, F.A. & Kumar, P., 2021. "A review of existing deep decarbonization models and their potential in policymaking," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    12. Després, Jacques & Hadjsaid, Nouredine & Criqui, Patrick & Noirot, Isabelle, 2015. "Modelling the impacts of variable renewable sources on the power sector: Reconsidering the typology of energy modelling tools," Energy, Elsevier, vol. 80(C), pages 486-495.
    13. Yuo-Hsien Shiau & Su-Fen Yang & Rishan Adha & Syamsiyatul Muzayyanah, 2022. "Modeling Industrial Energy Demand in Relation to Subsector Manufacturing Output and Climate Change: Artificial Neural Network Insights," Sustainability, MDPI, vol. 14(5), pages 1-18, March.
    14. Terfa, H. & Baghli, L. & Bhandari, R., 2022. "Impact of renewable energy micro-power plants on power grids over Africa," Energy, Elsevier, vol. 238(PA).
    15. Wabukala, Benard M. & Bergland, Olvar & Otim, Jacob & Elasu, Joseph & Muwanga, Robert & Adaramola, Muyiwa S., 2025. "Keeping the lights on: Assessing energy dynamics and electricity security in Uganda," Energy, Elsevier, vol. 330(C).
    16. Blanco, Herib & Gómez Vilchez, Jonatan J. & Nijs, Wouter & Thiel, Christian & Faaij, André, 2019. "Soft-linking of a behavioral model for transport with energy system cost optimization applied to hydrogen in EU," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    17. Nieves, J.A. & Aristizábal, A.J. & Dyner, I. & Báez, O. & Ospina, D.H., 2019. "Energy demand and greenhouse gas emissions analysis in Colombia: A LEAP model application," Energy, Elsevier, vol. 169(C), pages 380-397.
    18. Santika, Wayan G. & Anisuzzaman, M. & Simsek, Yeliz & Bahri, Parisa A. & Shafiullah, G.M. & Urmee, Tania, 2020. "Implications of the Sustainable Development Goals on national energy demand: The case of Indonesia," Energy, Elsevier, vol. 196(C).
    19. Müller, Jonas & Trutnevyte, Evelina, 2020. "Spatial projections of solar PV installations at subnational level: Accuracy testing of regression models," Applied Energy, Elsevier, vol. 265(C).
    20. Jacques Després & Patrick Criqui & Silvana Mima & Nouredine Hadjsaid & Isabelle Noirot, 2014. "Variable renewable energies and storage development in long term energy modelling tools," Post-Print hal-01279467, HAL.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:8070-:d:1300467. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.