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Advancing the Industrial Sectors Participation in Demand Response within National Electricity Grids

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  • Alexander Brem

    (Department of Mechanical, Biomedical and Manufacturing Engineering, Munster Technological University, T12 P928 Cork, Ireland
    Intelligent Efficiency Research Group (IERG), Department of Civil and Environmental Engineering, University College Cork, T12 K8AF Cork, Ireland
    DePuy Ireland Unlimited Company, Loughbeg, P43 NP38 Cork, Ireland)

  • Dominic T. J. O’Sullivan

    (Intelligent Efficiency Research Group (IERG), Department of Civil and Environmental Engineering, University College Cork, T12 K8AF Cork, Ireland)

  • Ken Bruton

    (Intelligent Efficiency Research Group (IERG), Department of Civil and Environmental Engineering, University College Cork, T12 K8AF Cork, Ireland)

Abstract

Increasing the level and diversifying the sources of flexible capacity available to transmission system operators will be a pivotal factor for maintaining reliable control of national electricity grids. These response capacities are widely available; however, one area with large capacities that could benefit from advancements is the industrial sector. This sector’s highly regulated nature ensures that structured procedures and thorough investigations are required to implement significant change. This study presents a systematic methodology to effectively categorise assets and evaluate their perceived risk of participation in demand response, allowing industries to present a sustainable portfolio of flexible capacity to the grid. Following implementation on an internationally relevant industrial site, this methodology identified several assets for participation, determining that it is realistic to expect 35 to 75 kW of flexible capacity from only air handling units on a single site. A selected unit was further evaluated using an internal air-temperature modelling tool. This demonstrated its ability to respond safely to the actual 2019 and 2020 grid frequency events and even remain off, at no risk to the indoor thermal environment for at least 20 min in each case. The potential impact of advancing industrial participation is presented, with the highest scenario providing almost 15 MW of flexible capacity to the Irish national grid. The financial benefit achievable on a site from the most conservative assets was found to be between EUR 993 and EUR 2129 annually for a single response category and up to EUR 6563 based on payment multipliers. Overall, this research demonstrates the significant flexible capacities available within the industrial sector and illustrates the low-risk capabilities and considerable benefits achievable on a single site and for the wider national electricity grids with this concept.

Suggested Citation

  • Alexander Brem & Dominic T. J. O’Sullivan & Ken Bruton, 2021. "Advancing the Industrial Sectors Participation in Demand Response within National Electricity Grids," Energies, MDPI, vol. 14(24), pages 1-26, December.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8261-:d:697819
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    References listed on IDEAS

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    1. Chen, Yongbao & Chen, Zhe & Xu, Peng & Li, Weilin & Sha, Huajing & Yang, Zhiwei & Li, Guowen & Hu, Chonghe, 2019. "Quantification of electricity flexibility in demand response: Office building case study," Energy, Elsevier, vol. 188(C).
    2. Gu, Chenjia & Zhang, Yao & Wang, Jianxue & Li, Qingtao, 2021. "Joint planning of electrical storage and gas storage in power-gas distribution network considering high-penetration electric vehicle and gas vehicle," Applied Energy, Elsevier, vol. 301(C).
    3. Newbery, David, 2017. "Tales of two islands – Lessons for EU energy policy from electricity market reforms in Britain and Ireland," Energy Policy, Elsevier, vol. 105(C), pages 597-607.
    4. Chemweno, Peter & Pintelon, Liliane & Muchiri, Peter Nganga & Van Horenbeek, Adriaan, 2018. "Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 64-77.
    5. Yin, Rongxin & Kara, Emre C. & Li, Yaping & DeForest, Nicholas & Wang, Ke & Yong, Taiyou & Stadler, Michael, 2016. "Quantifying flexibility of commercial and residential loads for demand response using setpoint changes," Applied Energy, Elsevier, vol. 177(C), pages 149-164.
    6. Dababneh, Fadwa & Li, Lin & Sun, Zeyi, 2016. "Peak power demand reduction for combined manufacturing and HVAC system considering heat transfer characteristics," International Journal of Production Economics, Elsevier, vol. 177(C), pages 44-52.
    7. Leimeister, Mareike & Kolios, Athanasios, 2018. "A review of reliability-based methods for risk analysis and their application in the offshore wind industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1065-1076.
    8. Pechmann, Agnes & Shrouf, Fadi & Chonin, Max & Steenhusen, Nanke, 2017. "Load-shifting potential at SMEs manufacturing sites: A methodology and case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 431-438.
    9. Melani, Arthur Henrique Andrade & Murad, Carlos Alberto & Caminada Netto, Adherbal & Souza, Gilberto Francisco Martha de & Nabeta, Silvio Ikuyo, 2018. "Criticality-based maintenance of a coal-fired power plant," Energy, Elsevier, vol. 147(C), pages 767-781.
    10. Alexander Brem & Ken Bruton & Paul D. O’Sullivan, 2021. "Assessing the Risk to Indoor Thermal Environments on Industrial Sites Offering AHU Capacity for Demand Response," Energies, MDPI, vol. 14(19), pages 1-28, October.
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