An urban-scale residential stock model for grid-constrained regions

Peter McCallum, David P. Jenkins, Paraskevi Vatougiou

Research output: Contribution to conferencePaperpeer-review

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This work was conducted to enhance residential demand modelling for energy system integration in grid-constrained regions. The Orkney Islands are used in this study to contextualise new methods for physics-integrated thermal stock models, using data from the UK’s Energy Performance Certificate (EPC) register, the Home Analytics database, and an open GIS database.

A localised urban district is studied in detail (population ~500) in which an automated archetyping process captures key geometry features of the constituent buildings through a parametric dwelling model, whilst integrating the various underlying datasets. To derive thermal demands, the model com piles and runs large numbers of EnergyPlus simulations, to give transient demands for a full year. Preliminary model outputs are discussed; however, the focus of this work is the encompassing framework and novel parametric dwelling model, which is central to the archetyping scheme. Discussions are provided on obstacles to scaling the model to much larger regions; concerns over manual interventions during input verification exercises are considerably more likely to limit scale, than computational concerns. This newly developed package – ‘ParaDwell.jl’ – was written in Julia, and is publicly available on GitHub.
Original languageEnglish
Publication statusPublished - 21 Sept 2020
Event5th IBPSA-England Conference on Building Simulation and Optimization 2020 - online
Duration: 21 Sept 202022 Sept 2020


Conference5th IBPSA-England Conference on Building Simulation and Optimization 2020
Abbreviated titleBSO 2020


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