4.8 Article

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

Journal

APPLIED ENERGY
Volume 295, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2021.117015

Keywords

Flexibility response potential; Flexibility adequacy assessment; Left-behind analysis; Flexibility prioritisation; Whole energy system; Geographic Information System (GIS)

Funding

  1. European Union's INTERREG VA Programme [IVA5038]

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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. The proposed method links the electrical network with socio-demographic spatial data using the k-nearest neighbour classification algorithm to ensure fair distribution of flexibility opportunities. Additionally, an interactive Northern Ireland demand flexibility map is provided for system planners to develop an effective flexibility strategy and implementation pathway.
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.

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