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

Cowie, Andrew and Kelly, Nick and McGhee, Raheal and Samuel, Aizaz and Higgins, Ciaran Andrew and Peat, Watson; (2017) Predicting the effect of changes to the urban environment on future electrical demand using building simulation and archetype models. In: Proceedings of Building Simulation 2017. International Building Performance Simulation Association, USA, pp. 455-464. (https://doi.org/10.26868/25222708.2017.120)

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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.

ORCID iDs

Cowie, Andrew ORCID logoORCID: https://orcid.org/0000-0002-1852-7113, Kelly, Nick ORCID logoORCID: https://orcid.org/0000-0001-6517-5942, McGhee, Raheal ORCID logoORCID: https://orcid.org/0000-0001-6481-4159, Samuel, Aizaz ORCID logoORCID: https://orcid.org/0000-0002-7107-3130, Higgins, Ciaran Andrew and Peat, Watson;
CORE (COnnecting REpositories)