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This platform integrates the virtues of existing housing stock energy models, in particular their representation of the composition and attribution of the stock—albeit in reduced form—with mechanisms to quantify uncertainties and to explore the potential impacts of policies and strategies to decarbonise the UK housing stock.

• Development of an open-access modular platform

• Generation of explicit volumetric archetypes

• Evaluation using dynamic simulation based on data survey

  (i.e. of envelope properties and household variables)

• Standardisation of data and modelling algorithms

• Analysis of drivers of decision-making regarding energy use intensity

  ♦

• R is used to manage the processing of data characterising the housing stock and the corresponding constructing of typological models.

• EnergyPlus is used to perform the dynamic simulation

• The processes are decoupled from the platform, so they can be executed using a High Performance Computing facility

In brief, the homogeneity of the UK housing stock is represented by adaptable cuboids. In this way, we can represent the key residential types of the stock such as detached houses, semi-detached, end of terrace, mid terraced, apartments and bungalows. These forms, complemented with their semantic attributes that extend to describe occupancy and systems characteristics (e.g. heating, lighting and appliance) comprehensively and robustly describe our stock typologies, but now based on an explicit volumetric representation.

The process described in the Figure is applied to study 3 main areas:

We have a platform that enables the interplay between energy, comfort and fuel poverty to be systematically explored as well as the effectiveness of strategies to bring about changes in investment and day-to-day operational behaviours and the technologies destined to support these changes. This is essential in the formulation of robust decarbonisation policies and strategies.

The housing stock decarbonisation in the UK is a process that requires constant update and validation. EnHub provides the ability to support such a long-term strategy for its successful accomplishment.

The software has been developed and tested on

• Ubuntu 14.04 or later
• Mac OS X 10.9.0 or later
• Scientific Linux SL7
• Windows 10 ⁺

⁺ The support for parallelisation has not been tested in Windows. Hence, it is possible that some of the functions will not work on this OS. ↩

▪️ G. Sousa, B.M. Jones, P.A. Mirzaei, D. Robinson, A review and critique of UK housing stock energy models, modelling approaches and data sources, Energy and Buildings (2017) 66–80. doi:http://dx.doi.org/10.1016/j.enbuild.2017.06.043.

▪️ G. Sousa, B.M. Jones, P.A. Mirzaei, D. Robinson, An open-source simulation platform to support the formulation of housing stock decarbonisation strategies, Energy and Buildings (2018). doi:http://doi.org/10.1016/j.enbuild.2018.05.015

📧 Get in touch by email at University of Sheffield
📓 Follow the project in ResearchGate
🔧 Follow the wiki

EnHub-UK is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. You can also read the full terms in LICENSE.md