HIGH RESOLUTION MODELLING FOR PERFORMANCE ASSESSMENT OF FUTURE DWELLINGS Nick Kelly, Jon Hand, Aizaz Samuel ESRU, University of Strathclyde, Glasgow

Overview temporal resolution in building simulation (BS) previous work with high temporal resolution simulations improving resolution in building simulation electrical power hot water solar radiation what difference does it make? conclusions and further work

Temporal Resolution in Building Simulation BS grounded in modelling of building thermal performance some physical processes with longer time constants e.g. heat conduction in constructions many tools (by default) run at hourly resolution however, scope of building simulation increasing HVAC systems renewables control lighting electrical are longer time-step simulations sufficient?

Some Previous Work – Lighting Simulation simulation of lighting controller at 60-min and 5-min resolution using real hourly and stochastic 5-min solar data (Clarke & Janak 1998) as BS evolves to model more processes in buildings can modelling at higher resolution bring benefits? … also what are the constraints?

Temporal Resolution in Building Energy Modelling in a temperate climate like the UK solar radiation can change rapidly with time due to cloud transit across the sun BS typically uses hourly averaged solar data

Temporal Resolution in Building Energy Modelling resulting PV output

Temporal Resolution in Building Energy Modelling electrical demand characterised by rapid fluctuation

Temporal Resolution in Building Energy Modelling hot water draws also typically short duration and highly variable

Improving Temporal Resolution many BS tools can already operate at sub-hourly resolution achieving higher temporal resolution in BS often question of data and models here we look at how ESP-r has been adapted to accommodate high resolution data and possible impact higher resolution has on predictions

Solar Data ESP-r’s default climate database holds hourly data sub-hourly time steps interpolation is used temporal definition database (TDF) can hold sub-hourly data (either real or generated) tool developed to generate sub hourly data from hourly datasets (1st order Markov model) [1] transition probabilities need to be calibrated using measured high resolution data [1] McCracken D 2011. Synthetic High Resolution Solar Data, MSc Thesis, University of Strathclyde, Glasgow.

Solar Data

Electrical Demand tool developed by Richardson [2] adapted to pre-simulate annual domestic electrical demand at 1-min resolution … and corresponding thermal gains pre-simulated data held in TDF used as a boundary condition by ESP-r’s electrical systems solver [2] Richardson I, Thompson M, Infield D, Clifford C 2010. Domestic electricity use: A high-resolution energy demand model. Eng. and Build. 4210) pp 1878-1887.

Hot Water Draws work of Jordan and Vagen [3] (IEA SHC Annex 26) used to generate new stochastic hot water draw component in ESP-r determines if hot water draw takes place ,draw flow rate and duration at each simulation time step (at up to 1-min resolution) model also used as basis of draw profiles generated in IEA ECBCS Annex 42 [3] Jordan U and Vajen K, 2005. DHWCALC: Program to Generate Domestic Hot Water Draws with Statistical Means for User Defined Conditions, Proc. ISES Solar World Congress, Orlando, US.

What Difference Does it Make? comparison of results from ‘Zero Energy’ building simulated at 1-min and 60-min resolution

What Difference Does it Make? ‘Zero Energy’ building simulated at 1-min and 60-min resolution

What Difference Does it Make? Power import/export

What Difference Does it Make? DHW & heating

What Difference Does it Make?

Conclusions many processes occurring in buildings occurring at high resolution hourly averaged boundary data fails to capture characteristics e.g. variability of solar radiation, electrical demand and import/export of electricity ESP-r adapted to utilise higher resolution boundary data tools developed/adapted to generate high resolution solar data, appliance demand/thermal gains and hot water draws [3] Jordan U and Vajen K, 2005. DHWCALC: Program to Generate Domestic Hot Water Draws with Statistical Means for User Defined Conditions, Proc. ISES Solar World Congress, Orlando, US.

Conclusions simulation of hypothetical zero energy building – passive house insulation, PV array, heat pump, MVHR. little difference in energy performance of heat pump and hot water systems (thermal buffering) unbuffered simulations show short duration cycling differences in PV output (thermal/electrical dependencies) significant difference in electrical import export and self consumption suggests higher resolution preferable for modelling of microgeneration and involving interaction with electrical network

Further Work this presentation has focused on solar and HVAC processes however high resolution modelling perhaps also appropriate for modelling of wind driven infiltration (e.g. typical gust duration 10s) … also air movement in buildings, modelling of control action, air conditioning.

Further Work and calculating maximum electrical demand

Acknowledgements this work was undertaken as part of the UKRC Energy Programme - Grand Challenge in Energy Systems: Top and Tail Transformation

Thank you!