Predicting the effect of changes to the urban environment on future electrical demand using building simulation and archetype models

Andrew Cowie, Nick Kelly, Raheal McGhee, Aizaz Samuel, Ciaran Andrew Higgins, Watson Peat

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Abstract

Future urban electrical loads are of interest to a range of stakeholders from utilities to network planners. In this paper, a pragmatic approach to the modelling of urban electrical demands using archetype models and simulated building demand profiles is described. The profiles can be scaled, transformed and combined to produce time-series electrical loads for multiple buildings connected to a substation in a distribution network. The modelling approach has been verified against measured demand data. Possible changes in future peak urban electrical demand were quantified for a sample of substations in Glasgow, UK, using four future demand scenarios. The picture emerging was complex, with peak demand increasing in some cases where electric vehicles and electrified heating combine. However, there were many situations where a combination of improved energy efficiency and microgeneration lead to reduced peak demand.
Original languageEnglish
Title of host publicationBuilding Simulation 2017
Subtitle of host publicationThe 15th Biennial Conference of the International Building Performance Simulation Association (IBPSA)
Place of Publication[Vancouver, B.C.]
Number of pages10
Publication statusAccepted/In press - 3 Mar 2017
EventBuilding Simulation 2017: The 15th Biennial Conference of the International Building Performance Simulation Association (IBPSA) - Hyatt Regency Embarcadero, San Fransisco, United States
Duration: 7 Aug 20179 Aug 2017
Conference number: 15
http://www.buildingsimulation2017.org/

Conference

ConferenceBuilding Simulation 2017
Abbreviated titleBS17
CountryUnited States
CitySan Fransisco
Period7/08/179/08/17
Internet address

Keywords

  • building simulation
  • urban electrical demand
  • electrification of heat
  • electric vehicle (EV)
  • archetype building models
  • demand profiles
  • time-series electrical loads

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