certification:passive_house_categories:per
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certification:passive_house_categories:per [2015/03/11 17:45] – bwuensch | certification:passive_house_categories:per [2015/09/12 18:25] (current) – [Site-specific PER factors] wfeist | ||
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====== The PER sustainability assessment ====== | ====== The PER sustainability assessment ====== | ||
- | Which parameter can be used as a suitable indicator for the sustainability of buildings from an energy standpoint? The so-called PER factors (Primary Energy Renewable) were first introduced in the final presentation at last year’s International Passive House Conference, as future-oriented sustainability assessment criteria [Feist 2014]. With the new release of the Passive House Planning Package (PHPP version 9), | + | Which parameter can be used as a suitable indicator for the sustainability of buildings from an energy standpoint? The so-called PER factors (Primary Energy Renewable) were first introduced in the final presentation at last year’s International Passive House Conference, as future-oriented sustainability assessment criteria [Feist 2014]. With the new release of the Passive House Planning Package (PHPP version 9), |
==== PER factors: The methodology ==== | ==== PER factors: The methodology ==== | ||
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The modelled future energy supply network is based purely on electricity from renewable sources. Three different sources are taken into account: Photovoltaics, | The modelled future energy supply network is based purely on electricity from renewable sources. Three different sources are taken into account: Photovoltaics, | ||
- | The hourly electricity production through solar power is calculated based on a photovoltaic system oriented toward the equator. The power output is calculated based on the solar radiation information from the respective climate data set, taking into account a tempe-rature-sensitive efficiency of the photovoltaic module. The model’s inclination is determined such that the highest possible annual energy yield is reached at the considered location. | + | The hourly electricity production through solar power is calculated based on a photovoltaic system oriented toward the equator. The power output is calculated based on the solar radiation information from the respective climate data set, taking into account a temperature-sensitive efficiency of the photovoltaic module. The model’s inclination is determined such that the highest possible annual energy yield is reached at the considered location. |
The hourly electricity produced through wind energy is calculated based on a smoothed profile of hourly wind velocities. The same climate data set is used, in order to take account of local climatic correlations between wind and radiation or temperature. However, such localised wind data is rarely representative of the potential of wind energy in the surrounding region. The original wind velocity data is therefore calibrated based on long-term measured averages of the region [SSE] and extrapolated to a hub height of 150 m. The actual power output then depends on the turbine’s power curve, which is modelled with a specific power output of 380 W/m² and 200 W/m² for regions with strong and weak wind, respectively (based on [Mono et.al. 2014]). If the average wind speed at hub height is lower than 4 m/s, a significant development of wind energy in the area is unlikely for economic reasons. The contribution of wind energy to the total mix in the calculations is therefore limited to 0.5 % of the annual yield. Offshore wind energy is not considered at this stage – the calculations are slightly on the safe side in this regard. | The hourly electricity produced through wind energy is calculated based on a smoothed profile of hourly wind velocities. The same climate data set is used, in order to take account of local climatic correlations between wind and radiation or temperature. However, such localised wind data is rarely representative of the potential of wind energy in the surrounding region. The original wind velocity data is therefore calibrated based on long-term measured averages of the region [SSE] and extrapolated to a hub height of 150 m. The actual power output then depends on the turbine’s power curve, which is modelled with a specific power output of 380 W/m² and 200 W/m² for regions with strong and weak wind, respectively (based on [Mono et.al. 2014]). If the average wind speed at hub height is lower than 4 m/s, a significant development of wind energy in the area is unlikely for economic reasons. The contribution of wind energy to the total mix in the calculations is therefore limited to 0.5 % of the annual yield. Offshore wind energy is not considered at this stage – the calculations are slightly on the safe side in this regard. | ||
- | Last but not least, the electricity produced from hydropower is taken into account based on the predicted contribution of this energy source to each country’s future total energy demand. The prediction for future hydropower generation | + | Last but not least, the electricity produced from hydropower is taken into account based on the predicted contribution of this energy source to each country’s future total energy demand. The prediction for future hydropower generation |
==== Electricity demand at the building ==== | ==== Electricity demand at the building ==== | ||
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It is further assumed that the seasonal storage has the required capacity to store exactly the amount of energy storage required over the course of the year (supply = demand + losses). One possibility of a working seasonal storage system is the conversion of RE electricity into methane, for which a conversion efficiency of 57 % is assumed. The re-conversion from gas into electricity in a CCTG plant is modelled with an efficiency of 50 %. Electricity consumed via the seasonal storage, therefore has an overall efficiency of only approx. 30 %. Finally, 5 % distribution losses are added for all electricity transmission via the electrical grid. | It is further assumed that the seasonal storage has the required capacity to store exactly the amount of energy storage required over the course of the year (supply = demand + losses). One possibility of a working seasonal storage system is the conversion of RE electricity into methane, for which a conversion efficiency of 57 % is assumed. The re-conversion from gas into electricity in a CCTG plant is modelled with an efficiency of 50 %. Electricity consumed via the seasonal storage, therefore has an overall efficiency of only approx. 30 %. Finally, 5 % distribution losses are added for all electricity transmission via the electrical grid. | ||
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certification/passive_house_categories/per.1426092337.txt.gz · Last modified: 2015/03/11 17:45 by bwuensch