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How SketchUp plugin DesignPH can facilitate effective retrofit

Ricardo Moreira

As energy costs rise, DesignPH is a useful early-stage design tool to help predict and reduce heating demand

Moreira models his own home in SketchUp.
Moreira models his own home in SketchUp.

I recently moved into a typical Victorian terrace: uninsulated solid walls, floors and roofs, and poor levels of air tightness. In other words, typical UK housing stock. As the house is in urgent need of energy efficient improvements, I decided to put it to test on a retrofit scenario. But complex modelling is usually not justified for a single-dwelling or small project, and common tools like SAP are notoriously inadequate for energy predictions.

An interesting tool, still relatively little-known to architects, is DesignPH, a plug-in for SketchUp that was developed to facilitate entering data into PHPP, the modelling tool for Passivhaus. For a steady-state energy modelling tool, PHPP is surprisingly accurate due to its level of detail but that makes it time-consuming to use. DesignPH not only speeds it up, but allows users to compare changes to fabric specification and systems in terms of the energy savings at an early stage.

The DesignPH process for PHPP input consists of modelling a simplified geometry of the building in SketchUp, adding information to that model by tagging surface types and thermal properties, running an analysis and importing the model into PHPP for final data entry. However, for option appraisal purposes, I’m only interested in the initial analysis step using SketchUp.

Inputting current build-ups to create a baseline, the space heating demand sits at 249 kWh/m²/yr, which is 20% better-performing than a typical pre-1920 mid-terrace, probably due to its decent quality double-glazing. From there, multiple iterations were run, including insulating walls, roofs and floors, reducing thermal bridging, improving air tightness, using triple glazed windows and installing mechanical ventilation with heat recovery (MVHR), a pillar of Passivhaus. Iterations were analysed individually – so the impact of each measure could be understood – but also collectively, to see how the building might be able to perform. Results can be obtained in real time or recorded in an iteration list.

He then tagged its surfaces and thermal properties before importing it into the DesignPH to interrogate it.
He then tagged its surfaces and thermal properties before importing it into the DesignPH to interrogate it.

Of the measures tested, wall insulation showed most potential. Roof and floor insulation also performed well, while more intrusive interventions such as air tightness and thermal bridging improvements yielded lower savings. 

It’s important to recognise the limitations of a steady-state tool. For instance, savings from better air tightness and MVHR combined and individually are the same, and do not account for the measures’ interaction. 

Naturally, an ability to prioritise measures doesn’t negate the need to take a whole-building approach, in which all retrofit interventions and interactions are considered in conjunction. However, when financial limitations prevent a deep retrofit in one go, phasing can be used within a long-term, whole-building strategy. Pinpointing ‘low-hanging fruit’ will help generate immediate savings.

Users can consider not only fabric specification, but physical design aspects like massing, orientation, window sizing and configuration, with a real-time display of resulting form factor and heat demand. This demonstrates the opportunity to use DesignPH as a decision-making tool for both energy efficient retrofits and new build schemes.

In all, it is very helpful to be able to easily comprehend energy performance and the impact of interventions using a modelling tool that is widely familiar to designers. It offers much needed performance feedback and helps educate architects on the impact of their designs.

Ricardo Moreira is managing director of building performance consultancy XCO2. With contributions by Tom Willis, XCO2



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