Inkling at Building Simulation and Optimisation 2018 Conference

I represented Inkling at the Building Simulation and Optimisation 2018 Conference at Emmanuel College, University of Cambridge on 11-12 September.

I was able to attend two of the three keynote sessions, the first was from Dr Penny Carey of Portakabin on “Meeting the challenges of improving building standards within the construction industry”. This engaging presentation was based on Penny’s many years in the construction industry and highlighted the many environmental challenges that good design has to address such as snow, flooding, heatwaves and fire; as well as current themes, issues and changes in the built environment such as increasingly high density building, urban heat islands, decentralised renewables and the regulatory landscape. Although the EPBD (European Performance of Buildings Directive) commits us to reduce carbon emissions by at least 80% (compared to a 1990 baseline) by 2050, with nZEB (net Zero Energy Buildings) as the new standard for buildings in the EU,  it is not clear if/how the UK will commit to these targets post-Brexit, and there is a worrying skills gap that needs to be addressed.

The closing keynote session was from Professor Joe Clarke of the University of Strathclyde on “The future role of building performance simulation.” Joe suggested that the simulation community has become ‘thermodynamically corrupt’ using a check-list approach with simplified models and linear inputs leading to ill-informed decisions and the growth of the performance gap between design intent and actual performance. The solution presented was the use of persistent simulation with stochastic ‘gremlins’ to progressively test resilience. This involves running models for extended periods of time with events, such as extreme heatwaves or equipment failure popping up probabilistically. The longer the model was run, the greater variety of conditions would be tested. This would give us a much richer understanding of the building performance than a single model run.

The conference was split into 3 simultaneous sessions, I attended the following sessions:

• Optimal Controls
• Building Stock Modelling
• Data-centric Models
• Overheating Risk
• Simulation Approaches
• Occupant Behaviour

There was a wealth of information presented, so I will just summarise some of the points which I personally found particularly interesting or insightful. The full programme can be found on the website and it is expected that the conference papers will available on the website soon.

In the session on Optimal Controls, a paper on the energy saving potential of different setpoint control algorithms in mixed-mode buildings was presented by Charalampos Angelopoulos of Loughborough University. This research investigated the control of mixed mode buildings in Mumbai, India. My take-home from this was that energy savings are possible from mixed-mode operation, even in a hot climate.

Mehdi Taebnia of Aalto University, Finland presented on qualitative control of a hybrid energy system in a residential building. Whereas in conventional control strategies each system is controlled independently with basic thermostat control and fixed temperature set points, qualitative control strategies include intelligence to estimate future energy requirements based on weather and temperature set points, to check available stored energy and to prioritise energy systems based on renewable availability, system COPs and electricity prices.

Gilles Baudoin of Université Catholique de Louvain-la-neuve, Belgium presented on the combined optimisation of melting-peak temperature and melting temperature range of phase change materials in buildings. The melting-peak temperature and melting temperature range of phase change materials can be used to tune the PCM solution to provide the required thermal storage effect. Gilles emphasised that the melting temperature range of PCMs, although not generally assigned as much importance as the melting peak temperature, affects the performance of the product and is therefore a key parameter in the performance of PCMs when used in buildings to buffer the room temperature.

In the session covering Building Stock Modelling a lot of interesting research was presented based on publically available datasets, using the available information in new and interesting ways. Rajat Gupta of Oxford Brookes University presented a new GIS based decision support tool for enabling local energy retrofits. As funding for domestic retrofits has been reduced in recent years it becomes more important that those retrofits carried out are targeted to those most in need. In order to identify these households, publically available datasets were used to identify focal areas based on ECO requirements, EPC ratings, fuel poverty and physical and social vulnerability of occupants.

Stephen Evans of UCL presented on the relationship between building density and energy use using publically available data by postcode including EPCs and energy data. The research is intended to determine the energy-intensitivity of different building types. The interesting metric of ‘UPRNs per hectare’ (Unique Property Reference Number per hectare) was used to represent density and to identify the building type (detached, semi-detached, terraces or flats) characteristic of that area. This data was then used to produce a relation between CO2 emissions per unit area and density and then finally between density and energy use.

The session on Overheating Risk kicked off with an interesting paper on the implications of algorithm choice on the TM59 domestic overheating risk assessment, presented by Giorgos Petrou of the UCL Energy Institute. Many simulation tools allow the user a choice of algorithms, for example for exterior and interior convection and/or solar radiation distribution. The choice of these algorithms is likely to affect the results produced by the tool and in some cases these differences may be the difference between passing and failing the TM59 assessment. However there is no specific guidance in TM59 on which algorithms should be used in the software, there also appears to be a lack of guidance from the software vendors or in published industry guidance on appropriate algorithm choice. Some commercial dynamic simulation packages do not allow the user to change the algorithms used, is this a better approach? What is the value in allowing the user to adjust the algorithms used? The paper concluded that, as most users do not change the algorithms in the software, the choice of default algorithm is most important. In some cases this choice may lead to more pessimistic results and in others it may lead to more optimistic results and may be the difference between a pass and a fail of the relevant criteria. More work comparing modelling results to empirical measured data will hopefully indicate which algorithms are most suitable for different types of analyses.

Ronita Bardhan of the Indian Institute of Technology Bombay, India presented a paper on evaluating the impact of interior layout on indoor air quality in a low income tenement unit in Mumbai. This paper looked at how the addition of a partition and the positioning of the bed could improve air quality in the sleeping area of a tiny dwelling in which the window was kept closed whilst cooking for privacy. This paper had a powerful impact as it demonstrated that we must consider all the human factors whilst carrying out modelling and design including cultural considerations such as the requirement for modesty and it also illustrated that seemingly simple and low- or cost-free changes to a room layout can make a big difference to people’s lives.

There were many other interesting papers and enthusiastic speakers, with many papers somewhat outside my areas of expertise. It was great to be exposed to lots of different modelling approaches from data modelling and mathematical modelling to controls and scripting and programing methods. There was also an award for best student paper awarded to second-year LoLo PhD student Matej Gustin for “Prediction of internal temperatures during hot summer conditions with time series forecasting models”. Congratulations to Matej. Finally, thank you to Cambridge University and the whole organising team for putting on this great conference.