Simulator How-It-Works
Notices & Links
This page provides an overview of how the simulator works. For full details on the heating model read the journal article, which will be linked here shortly. The source code for the website and heating simulator, along with documentation, can be found on our GitHub
The costs of the various technologies and their fuel prices are based on data prior to Covid-19. One should therefore expect the price estimates from the simulation to underestimate the costs under current cirmcumstances.
Model Overview
The simulation model requires six inputs from the user, being the home's:
- Postcode
- Number of Occupants
- Thermostat Temperature
- Floor Area
- Yearly Space Heating Energy Consumption
- Maximum Hot Water Tank Volume
From the postcode, the longitude and latitude of the home can be determined, which are rounded to the nearest half a degree. The rounded position is used to load the hourly outside temperature and solar radiation datasets for the location. We wish to thank www.renewables.ninja who provided the weather data used by the simulator.
A home’s floor area and yearly space heating energy consumption can usually be found on your Energy Performance Certificate (EPC), a legal requirement for any building sold, let or constructed in the UK since 2007.
As the simulator only outputs the optimal hot water tank size for each heating system, an upper size limit is required as an inpute to ensure the simulator does not optimise for a tank size that could not feasibly fit into the home.
The first step of the model is to estimate the thermal transmittance (U value) of the property. This refers to how quickly heat is tranferred between the property and environment. The U value is calculated by simulating the home’s yearly space heating demand at an hourly resolution using a range of U values from 0.5 to 3.0 in 0.01 W/m2K step increments and selecting the U value which results in a yearly space heating demand closest to that specified by the user.
The hourly space heating demand is taken as the energy required to raise the inside temperature to the desired temperature. The inside temperature is a function of heat loss to the environment, and gain from body heat and solar radiation. With the U value calculated, the space heating demand is recalculated, in addition to hot water demand, using the inputted thermostat temperature.
Hot water energy consumption is a function of inlet cold water temperature and hot water consumption per occupant, accounting for daily and monthly variation. The total demand is then used to calculate the operational costs and emissions of the hydrogen, biomass and gas heating systems, by multiplying the energy demand with operating costs and emissions per unit energy respectively, whilst adjusting for system efficiencies.
As for the electrified heating technologies, the model is more complex, being simulated for a range of solar thermal and photovoltaic ancillary technology sizes and combinations, TES sizes and tariffs. The peak hourly demand is used to size the electrified heating technologies. Each solar ancillary is simulated in 2m2 area increments from 2m2 up to a quarter of the inputted floor area (assumed half the roof area). The TES size is incremented in 0.1m3 steps from 0.1 up to 3.0m3. As for tariff options, there are five, including flat-rate, night off-peak, evening-peak, EV off-peak and variable.For each hour over a year, the following steps occur.
- Calculate the change in inside temperature due to heat loss to the environment and heat gain from body heat, solar radiation and heat loss from the TES into the living space.
- Update the TES state of charge due to heat loss, solar thermal generation, space and hot water usage, and heat produced from the electrified heating technology, powered either from grid import or solar photovoltaics.
- Calculate operational costs from electricity import for the hour using the selected tariff and operational emissions associated with the solar ancillaries and grid import.
- The optimal solar ancillary size, TES size and tariff is then outputted to the user for each electrified heat technology - solar ancillary combination, where the optimal system is considered that with the lowest lifetime cost.
