Postertitel im Master eintragen

Research and Development

Scottish Passive Houses as wind-energy buffers

The ideaIn a future electricity grid dominated by renewableenergy, balancing supply and demand will become akey challenge. Previous research has shown thatPassivhaus standard buildings can maintaincomfortable conditions for long periods withoutsupplementary heating, and suggested thatelectrically-heated Passivhaus buildings could beused as buffers to variable renewable electricitygeneration – turning electricity into heat when it isabundant and storing that heat in order to need lessheating during periods of undersupply. This studyseeks to quantify the degree to which heating in aScottish Passivhaus could be shifted to periods ofwind-energy oversupply, and the additional energycost associated with different strategies to achievethis.

MethodA 100m2 TFA Passivhaus, located in Oban on thewest coast of Scotland, was designed using PHPP.The same building model was then built inDesignBuilder, a dynamic simulation tool.Using half-hourly synthetic weather data a scheduleof differential thermostat setpoints was created thatheated to a higher temperature when wind speedswere above 4.4 m/s and outside of peak hours(1500 – 2000). Scottish wind turbines operate closeto peak capacity for approximately 1/3 of the year,and wind speeds above 4.4 m/s represent thewindiest 1/3 of the year.Four different temperature setpoint scenarios weretested:

The larger the difference between setpointtemperatures the more heating could be shifted towindy periods, with scenario A and D shifting 97% and93% respectively, whereas scenario B shifted only 71%.However, these strategies also carry an energy cost withthem, compared to a constant 20°C setpoint strategy,since the building spends considerable amounts of timewarmer than usual. The higher the upper thermostattemperature, the higher the extra energy cost. This extraenergy cost was small for scenario A (7% extra energyrequired), since the lower setpoint was actually below20°C and for scenario B (6%) because the uppersetpoint was only 1°C higher than the lower. Scenarios Cand D required 13% and 20% extra heating energyrespectively.Scenarios A and B compare favourably, in efficiencyterms, to more conventional means of managingrenewable energy supply and demand such as batteriesand pumped hydro and to less-conventional methodssuch as smart charging of electric vehicles and power-to-gas. The total amount of energy absorbed using thesemethods is comparable to the amount of energy requiredby an electric car over the same winter period; even forhighly energy efficient buildings the size of the prize, indomestic terms, is quite big.

Future workHaving a large difference between upper and lowerthermostat setpoints presents adaptive-comfort problems(will occupants be happy at 19°C a few days after havingadapted to 22°C?) and increases total energy use.Heating to the upper setpoint is not always necessary tolast out the next calm period. Future work will model asmarter thermostat that can see a weather forecast andadjust the temperature in anticipation of coming gaps inrenewable generation.

Scenario Low temperature (undersupply) setting

High temperature (oversupply) setting

A 19 22

B 20 21

C 20 22

D 20 23

Results and discussionThe effect of these strategies on the supply ofheating to the building can be seen below forscenario A, for the month of February. Redtemperature lines indicate a period of wind over-supply, blue a period of under-supply. Implementingdifferential thermostat set-points allows most of theheating to take place during periods of over-supply.

Author: Dr Esmond TresidderDirector Lean Green Consulting and Highland Passive.Es@HighlandPassive.com