Mapping demand flexibility: A spatio-temporal assessment of flexibility needs, opportunities and response potential. (1st August 2021)

• Record Type: Journal Article
• Authors: Agbonaye, Osaru; Keatley, Patrick; Huang, Ye; Ademulegun, Oluwasola O.; Hewitt, Neil
• Is Part Of: Applied energy. Volume 295(2021)
• Publication Date: 2021-08-01
• Subjects: Flexibility response potential -- Flexibility adequacy assessment -- Left-behind analysis -- Flexibility prioritisation -- Whole energy system -- Geographic Information System (GIS); Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2021.117015
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Flexibility opportunities and response potential is assessed across space and time. A demand flexibility adequacy assessment framework is proposed for various services. A method for coupling an electrical network with socio-demographic data is proposed. A framework to identify and prioritise potentially left-behind groups is proposed. Northern Ireland Demand Flexibility Map: A tool for energy system planning. 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.