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

Author

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  • 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
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    References listed on IDEAS

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    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. 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.

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