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Mapping demand flexibility: A spatio-temporal assessment of flexibility needs, opportunities and response potential

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  • Agbonaye, Osaru
  • Keatley, Patrick
  • Huang, Ye
  • Ademulegun, Oluwasola O.
  • Hewitt, Neil

Abstract

Demand flexibility is needed to manage the challenges of decarbonising the heating and transport sectors and integrating large shares of intermittent renewable generation. While existing literature has provided models for estimating the response potential of some flexible devices, they have not been applied to assess if the response in a location is sufficient to solve the grid issue. Grid issues such as constraint and congestions are geographical issues and hence can be studied through GIS analysis. This paper presents a methodology for the spatio-temporal assessment of demand flexibility opportunities, response potential and adequacy in solving various grid issues of a country. We provide a method that may be used to link the electrical network with socio-demographic spatial data when the low voltage network data is not available using the k-nearest neighbour classification algorithm. The proposed method was able to match neighbourhoods with their primary substation with an accuracy of 60–94%. By segmenting neighbourhoods based on various metrics, we perform a left-behind analysis to identify vulnerable consumer groups at risk of being left behind in the energy transition and propose a flexibility prioritisation model that ensures a fair distribution of flexibility opportunities across all locations. Finally, we present the Northern Ireland demand flexibility map, an interactive tool for use by system planners to help in developing an effective flexibility strategy as well as a flexibility implementation pathway for Northern Ireland.

Suggested Citation

  • Agbonaye, Osaru & Keatley, Patrick & Huang, Ye & Ademulegun, Oluwasola O. & Hewitt, Neil, 2021. "Mapping demand flexibility: A spatio-temporal assessment of flexibility needs, opportunities and response potential," Applied Energy, Elsevier, vol. 295(C).
    • Handle: RePEc:eee:appene:v:295:y:2021:i:c:s0306261921004815
    DOI: 10.1016/j.apenergy.2021.117015
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    Cited by:

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    2. Neil J. Hewitt, 2024. "Decarbonizing Energy of a City: Identifying Barriers and Pathways," Energies, MDPI, vol. 17(1), pages 1-13, January.
    3. Leila Luttenberger Marić & Hrvoje Keko & Marko Delimar, 2022. "The Role of Local Aggregator in Delivering Energy Savings to Household Consumers," Energies, MDPI, vol. 15(8), pages 1-27, April.
    4. Pablo Carnero & Pilar Calatayud, 2021. "A Parametric Analysis for Short-Term Residential Electrification with Electric Water Tanks. The Case of Spain," Sustainability, MDPI, vol. 13(21), pages 1-26, November.
    5. Agbonaye, Osaru & Keatley, Patrick & Huang, Ye & Odiase, Friday O. & Hewitt, Neil, 2022. "Value of demand flexibility for managing wind energy constraint and curtailment," Renewable Energy, Elsevier, vol. 190(C), pages 487-500.
    6. Li, Han & Johra, Hicham & de Andrade Pereira, Flavia & Hong, Tianzhen & Le Dréau, Jérôme & Maturo, Anthony & Wei, Mingjun & Liu, Yapan & Saberi-Derakhtenjani, Ali & Nagy, Zoltan & Marszal-Pomianowska,, 2023. "Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives," Applied Energy, Elsevier, vol. 343(C).

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