IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i23p6355-d454781.html
   My bibliography  Save this article

Evaluation of Demand Response Potential Flexibility in the Industry Based on a Data-Driven Approach

Author

Listed:
  • Eunjung Lee

    (School of Integrated Technology, Gwangju Institute of Science and Technology, Gwangju 61005, Korea)

  • Keon Baek

    (School of Integrated Technology, Gwangju Institute of Science and Technology, Gwangju 61005, Korea)

  • Jinho Kim

    (School of Integrated Technology, Gwangju Institute of Science and Technology, Gwangju 61005, Korea)

Abstract

The rapid increase in renewable energy resources has resulted in the increasing need for a demand flexibility program (DFP) from industrial load resources as a solution to oversupply and peak load spikes. However, to reasonably estimate the DR potential flexibility, the load characteristics must be analyzed and potential assessment formulas must be validated. Thus, in this study, a novel method is proposed to evaluate the DR potential flexibility of industrial loads according to a process of related load-characteristic data analysis. The proposed potential-estimation model considers frequency, consistency, and DR event operation scores during designated ramp-up and ramp-down time intervals separately. A case study was conducted by considering typical cement industry process with actual power-consumption data analysis for demonstrating the test system. The results confirm that load reduction of more than half of the usual power consumption is possible if a potential score is about 0.27 in cement industry cases. Thus, the proposed method can be used as an indicator to determine how an industrial load is adequate for obtaining a DFP while suggesting meaningful implications through industrial load-resource data analysis.

Suggested Citation

  • Eunjung Lee & Keon Baek & Jinho Kim, 2020. "Evaluation of Demand Response Potential Flexibility in the Industry Based on a Data-Driven Approach," Energies, MDPI, vol. 13(23), pages 1-12, December.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:23:p:6355-:d:454781
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/23/6355/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/23/6355/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tanaka, Makoto, 2006. "Real-time pricing with ramping costs: A new approach to managing a steep change in electricity demand," Energy Policy, Elsevier, vol. 34(18), pages 3634-3643, December.
    2. Bradley, Peter & Leach, Matthew & Torriti, Jacopo, 2013. "A review of the costs and benefits of demand response for electricity in the UK," Energy Policy, Elsevier, vol. 52(C), pages 312-327.
    3. Afzalan, Milad & Jazizadeh, Farrokh, 2019. "Residential loads flexibility potential for demand response using energy consumption patterns and user segments," Applied Energy, Elsevier, vol. 254(C).
    4. Torriti, Jacopo, 2012. "Price-based demand side management: Assessing the impacts of time-of-use tariffs on residential electricity demand and peak shifting in Northern Italy," Energy, Elsevier, vol. 44(1), pages 576-583.
    5. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    6. Summerbell, Daniel L. & Khripko, Diana & Barlow, Claire & Hesselbach, Jens, 2017. "Cost and carbon reductions from industrial demand-side management: Study of potential savings at a cement plant," Applied Energy, Elsevier, vol. 197(C), pages 100-113.
    7. 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.
    8. Gyamfi, Samuel & Krumdieck, Susan, 2011. "Price, environment and security: Exploring multi-modal motivation in voluntary residential peak demand response," Energy Policy, Elsevier, vol. 39(5), pages 2993-3004, May.
    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. Marcin Sawczuk & Adam Stawowy & Olga Okrzesik & Damian Kurek & Mariola Sawczuk, 2024. "Managing Costs of the Capacity Charge through Real-Time Adjustment of the Demand Pattern," Energies, MDPI, vol. 17(8), pages 1-17, April.
    2. Ranaboldo, M. & Aragüés-Peñalba, M. & Arica, E. & Bade, A. & Bullich-Massagué, E. & Burgio, A. & Caccamo, C. & Caprara, A. & Cimmino, D. & Domenech, B. & Donoso, I. & Fragapane, G. & González-Font-de-, 2024. "A comprehensive overview of industrial demand response status in Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 203(C).
    3. Wu, Zhenyu & Zhao, Xia & Mao, Yang & Liu, Ruimeng, 2024. "Flexibility quantification of desalination plants for demand response: An adaptive robust optimization methodology," Applied Energy, Elsevier, vol. 373(C).
    4. Hessam Golmohamadi, 2022. "Demand-Side Flexibility in Power Systems: A Survey of Residential, Industrial, Commercial, and Agricultural Sectors," Sustainability, MDPI, vol. 14(13), pages 1-16, June.
    5. Christian Pfeiffer & Markus Puchegger & Claudia Maier & Ina V. Tomaschitz & Thomas P. Kremsner & Lukas Gnam, 2020. "A Case Study of Socially-Accepted Potentials for the Use of End User Flexibility by Home Energy Management Systems," Sustainability, MDPI, vol. 13(1), pages 1-19, December.
    6. Iurii Prokazov & Vladimir Gorbanyov & Vadim Samusenkov & Irina Razinkina & Monika Chłąd, 2021. "Assessing the Flexibility of Renewable Energy Multinational Corporations," Energies, MDPI, vol. 14(13), pages 1-19, June.
    7. Williams, B. & Bishop, D., 2024. "Flexible futures: The potential for electrical energy demand response in New Zealand," Energy Policy, Elsevier, vol. 195(C).
    8. Keon Baek & Sehyun Kim & Eunjung Lee & Yongjun Cho & Jinho Kim, 2021. "Data-Driven Evaluation for Demand Flexibility of Segmented Electric Vehicle Chargers in the Korean Residential Sector," Energies, MDPI, vol. 14(4), pages 1-10, February.

    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. Haider, Haider Tarish & See, Ong Hang & Elmenreich, Wilfried, 2016. "A review of residential demand response of smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 166-178.
    2. Haider, Haider Tarish & See, Ong Hang & Elmenreich, Wilfried, 2016. "Residential demand response scheme based on adaptive consumption level pricing," Energy, Elsevier, vol. 113(C), pages 301-308.
    3. Gils, Hans Christian, 2016. "Economic potential for future demand response in Germany – Modeling approach and case study," Applied Energy, Elsevier, vol. 162(C), pages 401-415.
    4. Martínez Ceseña, Eduardo A. & Good, Nicholas & Mancarella, Pierluigi, 2015. "Electrical network capacity support from demand side response: Techno-economic assessment of potential business cases for small commercial and residential end-users," Energy Policy, Elsevier, vol. 82(C), pages 222-232.
    5. Baxter Williams & Daniel Bishop & Patricio Gallardo & J. Geoffrey Chase, 2023. "Demand Side Management in Industrial, Commercial, and Residential Sectors: A Review of Constraints and Considerations," Energies, MDPI, vol. 16(13), pages 1-28, July.
    6. Gils, Hans Christian, 2014. "Assessment of the theoretical demand response potential in Europe," Energy, Elsevier, vol. 67(C), pages 1-18.
    7. Nolan, Sheila & Neu, Olivier & O’Malley, Mark, 2017. "Capacity value estimation of a load-shifting resource using a coupled building and power system model," Applied Energy, Elsevier, vol. 192(C), pages 71-82.
    8. Xu, Qingyang & Sun, Feihu & Cai, Qiran & Liu, Li-Jing & Zhang, Kun & Liang, Qiao-Mei, 2022. "Assessment of the influence of demand-side responses on high-proportion renewable energy system: An evidence of Qinghai, China," Renewable Energy, Elsevier, vol. 190(C), pages 945-958.
    9. Astriani, Yuli & Shafiullah, GM & Shahnia, Farhad, 2021. "Incentive determination of a demand response program for microgrids," Applied Energy, Elsevier, vol. 292(C).
    10. Cai, Qiran & Xu, Qingyang & Qing, Jing & Shi, Gang & Liang, Qiao-Mei, 2022. "Promoting wind and photovoltaics renewable energy integration through demand response: Dynamic pricing mechanism design and economic analysis for smart residential communities," Energy, Elsevier, vol. 261(PB).
    11. Paterakis, Nikolaos G. & Erdinç, Ozan & Catalão, João P.S., 2017. "An overview of Demand Response: Key-elements and international experience," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 871-891.
    12. Calver, Philippa & Simcock, Neil, 2021. "Demand response and energy justice: A critical overview of ethical risks and opportunities within digital, decentralised, and decarbonised futures," Energy Policy, Elsevier, vol. 151(C).
    13. Misconel, Steffi & Zöphel, Christoph & Möst, Dominik, 2021. "Assessing the value of demand response in a decarbonized energy system – A large-scale model application," Applied Energy, Elsevier, vol. 299(C).
    14. Ambrosius, Mirjam & Grimm, Veronika & Sölch, Christian & Zöttl, Gregor, 2018. "Investment incentives for flexible demand options under different market designs," Energy Policy, Elsevier, vol. 118(C), pages 372-389.
    15. Nilsson, Anders & Bartusch, Cajsa, 2024. "Empowered or enchained? Exploring consumer perspectives on Direct Load Control," Energy Policy, Elsevier, vol. 192(C).
    16. He, Xian & Keyaerts, Nico & Azevedo, Isabel & Meeus, Leonardo & Hancher, Leigh & Glachant, Jean-Michel, 2013. "How to engage consumers in demand response: A contract perspective," Utilities Policy, Elsevier, vol. 27(C), pages 108-122.
    17. Märkle-Huß, Joscha & Feuerriegel, Stefan & Neumann, Dirk, 2018. "Large-scale demand response and its implications for spot prices, load and policies: Insights from the German-Austrian electricity market," Applied Energy, Elsevier, vol. 210(C), pages 1290-1298.
    18. Alejandro Tristán & Flurina Heuberger & Alexander Sauer, 2020. "A Methodology to Systematically Identify and Characterize Energy Flexibility Measures in Industrial Systems," Energies, MDPI, vol. 13(22), pages 1-35, November.
    19. Cédric Clastres & Haikel Khalfallah, 2020. "Retailers' strategies facing demand response and markets interactions," Working Papers hal-03167543, HAL.
    20. Navid Rezaei & Abdollah Ahmadi & Mohammadhossein Deihimi, 2022. "A Comprehensive Review of Demand-Side Management Based on Analysis of Productivity: Techniques and Applications," Energies, MDPI, vol. 15(20), pages 1-28, October.

    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:13:y:2020:i:23:p:6355-:d:454781. 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 (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.