Passive House – the next decade | Methodology

This article is a chapter of the paper “Passive House - the next decade” by Wolfgang Feist. Click here to the beginning of the article on Passipedia.

This study is based on three simulation models:

1. A building simulation for energy, which determines the final energy consumption of all household applications from hour to hour; for this, we used Dynbil, a program well founded on field data [Feist 1997] [Kaufmann/Feist 2001].

  • Heating (shortened to “heat” in formulas in this paper), generally with an electrical heat pump with outdoor air as a heat source and heat output via surface heating,
  • If necessary, cooling (cool), also with an electrical heat pump and component cooling or air conditioning,
  • Hot water supply (DHW), also using outdoor air as a heat source, and
  • Domestic electricity (DE) including auxiliary power

2. A simulation of renewable primary power production from photovoltaics (PV) and wind energy (wind). The basis here, as with the building simulation in point 1, is the climate data for each region's test reference year. We were able to use current German test reference years and IWEC data for sites around the world. We assumed base load supply from an international hydropower network, with ten percent of the power supply a reasonable figure for the German grid. Other international power network concepts (Desertec, etc.) were not included in the basic investigation for now.

3. A simplified grid model including a short-term storage structure (with, say, pumped storage plants, although there is no specification of a certain technology here) with an overall efficiency of 70 percent and a storage capacity in accordance with users' needs but at least 146 hours on average over the year. A simulation had already been used to optimize the short-term storage capacity in terms of its cost-benefit ratio. All primary power that exceeds the storage capacity undergoes H2 electrolysis and then metha­nisation for P2G storage (as described in Section Focus – basis of efficiency criteria). As it is needed, the methane stored there can be turned back into electricity or used directly in cogeneration plants for district heat or in individual heating systems (conversion expenditure factor is then 1.75 kWh/kWh for the methane).

The grid model and the utilisation model are connected in such a way that at all times:

  • A user's overall consumption is calculated (in kW of electricity; can include direct power, heat pumps, and local heat storage for domestic hot water, etc.).
  • First, consumption is directly covered by the renewable primary power available at the time.
  • Second, power is made available from short and mid-term storage to the extent possible.
  • Third, seasonal storage is mobilised (reconversion to electricity), with a potentially unlimited availability. Required storage capacity is determined as another measurement of expenditure in the supply structure (average storage time Tsai = Wa/Pav in kWh/kWav, storage capacity, that is the annual work generated by the storage Wa relative to the annual average application load Pav.
  • Adding direct power coverage to refilling mid-term storage (including conversion losses) and the average renewable production of P2G methane over the year tells us how big the primary power generators need to be. Their annual primary power production EPE in kWhPER relative to the demand in question Qel gives us the PER factor for each generator mix and each application in kWhPER/kWh.

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