Autor: Fabian Ochs, Georgios Dermentzis, Berthold Kaufmann, Jan Steiger

The implementation of renewable energy sources plays a crucial role in increasing the energy efficiency of buildings. However the evaluation of the possibility to directly use or store the gains within the building or sell the gains to a public grid is tricky, as these concepts depend on the energy demand of the building and the climate of the location considerably. Besides mere financial considerations, the ability to use or store PV energy within the building is also relevant for the future energy supply, when the energy storage within buildings will and the prices and funding for selling PV electricity or own use vary greatly from country to country. This tool to assess PV self-consumption potential of a building, the possibility to improve the self-consumption ratio by temporary storing PV electricity within a building, and supports to evaluate the economic potential of selling PV to the grid. It allows the user to receive information to which extend RES implementation makes sense to supply the building with energy, and) if the revenues of the PV electricity either saved or sold to the grid can compensate or exceed the investment costs.

For the assessment how much PV energy can be used within a building, a simple energy balance of annual energy demand and annual energy production will not lead to reasonable results regarding the potential to cover the buildings energy demand with renewables generated by the building nor inform how much energy can still be sold to the grid. This is due to the winter gap that is created by the high heating demand and low PV production in the winter. During the heating season, even very efficient buildings / renovations may have to use energy from the grid to cover the demand, especially of the heating, even if, on an annual balance, the buildings may be able to compensate the electricity demand with the energy generated by the implemented PV system:

Figure 1: Winter Gap demonstrated by monthly electricity demand and PV production for an EnerPHit building (Heating demand of 25 kWh/(m²a)) with 40 PV panels on the roof and 14 panels in the south facade.

The Passive House Planning Package (PHPP) allows to very reliably calculate the energy demand of building projects, especially very efficient projects like Passive Houses, EnerPHit renovations or NZEBs. In the Passive House Planning Package, both, PV electricity generation and the energy demand for heating, domestic hot water (DHW), auxiliary electricity and household electricity, can be very reliably calculated, as could be demonstrated in various new-built Passive Houses or deep renovation projects, described for example on Passipedia: PHPP – Passive House Planning Package .

In the latest version of PHPP (version 10), up to 5 different PV systems can be entered and the monthly PV electricity yield is calculated based on the climate data, PV system orientation and PV module specifications. The result is the total monthly and annual PV electricity yield for of the PV systems installed in a building.

Figure 2: PV electricity generation diagram in PHPP 9 (2015).

The final energy demand for household appliances, auxiliary electricity, domestic hot water and heating, however, is determined on annual basis only. The calculation of the heating demand is based on ISO 13790 standard, which was slightly adapted for the calculation of highly efficient building projects: In these buildings with extremely long time constant, the calculation according to ISO 13790 appears to be too positive, overestimating the utilisation factor of solar and internal heat gains.

With the monthly method, the space heating demand is determined on a monthly basis, but, due to the calculation of the annual performance factor of the heat pumps, the final energy demand is only presented on an annual basis. The user profiles for household electricity or domestic hot water also only allow an annual estimation of the energy demand, thereby the final energy demand within PHPP is presented on an annual basis only.

Figure 3: Space heating energy demand diagram in PHPP 9 (2015).

To allow a more detailed evaluation of the monthly energy demand of all building applications and the potential to cover this demand with PV energy generated by the building, and without further enlarging the PHPP calculation with such specific calulations, PVecon has been developed as an external add-on tool to PHPP.

By connecting PVecon to a PHPP calculation, all relevant data on energy demand and PV yield is transferred. PVecon thereby allows to split the annual final energy demand for heating, domestic hot water, auxiliary electricity and household appliances from PHPP into monthly demand. Especially in case of a heat pump, PVecon calculates the monthly electricity consumption of the heat pump system including (direct electricity and ground source pump)

In PVecon, a diagram visualizes the monthly energy demand of all building appliances and PV electricity generation, thereby also demonstrates the winter gap:

Figure 4: Building Energy demands and PV Yield on monthly basis in PVecon

Figure 5: Energy demands on monthly basis in PVecon

In order to receive monthly electricity consumption for the heat pumps, the annual electricity consumption calculated within PHPP has to be split into monthly demands. From PHPP, the total annual electricity demand for the heat pump is known:

annual 𝑊_{𝐻𝑃_𝐸𝐿_𝑡𝑜𝑡c} and monthly 𝑄 _{𝐻𝑃,𝑚𝑜𝑛} , T _source and T_sink

Then monthly 𝐶𝑂𝑃_{𝐶𝑎𝑟𝑛𝑜𝑡} = 𝑇_{𝑠𝑖𝑛𝑘} / (𝑇 _{𝑠𝑖𝑛𝑘} – 𝑇_𝑠 )

Within PVecon, the Carnot performance factor is “recalculated” based on monthly temperatures:

𝑊_{𝐻𝑃_𝐸𝐿_𝑡𝑜𝑡} =

𝑊_{𝐻𝑃_𝐸𝐿_𝑡𝑜𝑡} =

𝑊_{𝐻𝑃_𝐸𝐿_𝑡𝑜𝑡} =

The monthly electricity consumption then is:

PVecon then is able to provide monthly electricity demand for heating and DHW:

Figure 6: Monthly Electricity Demand of the Heat Pump for Heating and DHW in PVecon

Based on PHPP inputs and splitting up the annual demand for the heating and DHW, PVecon calculates the monthly energy demand of the building. The monthly PV yield is also known from PHPP. The question, however is, how much of the energy generated by the PV system can be used within the building and how much must be provided / sold to the grid.

PVecon calculates the part of PV electricity that is directly consumed by the building (“PVown”) in each month. This depends on the choice of storage options and in the ratio of annual electricity load of the building over the annual PV produced electricity, (so called inverse load factor LF -1).

The monthly WPV own is: WPV own = min (WPV ftuning ··W el_tot_mon)

Figure 7: Inverse Load Factor LF -1 based on various storage options in PVecon

Electricity generated by the PV system, that cannot be used directly within the building for household appliances, auxiliary, DHW or heating, usually must be fed and sold into the electricity grid. Storing the PV energy, that is produced during the daytime, and consume this energy overnight, can increase the amount of energy. By using this energy storage, less energy has to be sold back to the grid and the PV-self-consumption is improved. In order to store the energy produced by the PV systems for the buildings own consumption, batteries are assumed. The size of the battery can be entered into PVecon individually.

The reasonable size of the battery depends on the annual electricity demand of the building and the installed kW peak of the PV system. It is usually recommended to foresee a battery size of around:

• 5 - 7 kWh per residential unit
• 1 – 1,5 kWh per installed kWp of installed PV
• 1 – 1,5 kWh per 1000 kWh/a energy consumption of the building

By estimating the impact of the battery storage capacity on the PVown consumption of the building, PVecon supports the user to decide for a reasonable battery size. Other storage options, for example electric cars, that would further reduce the amount of electricity that must be sold to the public grid, are currently not included.

Based on the potential to consume PV electricity within the building, PVecon calculates the monthly and annual Load and Supply Cover Factors (LCF and SCF)

Load Cover Factor The Load Cover Factor (LCF) informs, how much of the monthly electricity demand of the building can be covered by the PV energy that is generated by the PV system.

Supply Cover Factor The Supply Cover Factor (LCF) informs, how much of the monthly PV yield can be consumed within the building. The fraction of PV energy that cannot be consumed is sold to the grid.

Figure 8: Load Cover Factor and Supply Cover Factor in PVecon

With the information how much of the PV electricity is consumed by the building, a more detailed assessment of monthly or annual remaining Primary Energy Demand (PE) or CO2-Emissions can be carried out. The final energy demand of other heat generation systems, other than electric, that have been calculated in PHPP, will then also be taken into account, and added to the left-over electricity demand:

Figure 9: Monthly remaining CO2 Emissions in PVecon

Thereby, the following heat generation system options can be considered by PVecon:

• Heat pumps (HP) including Compact units (for heating, DHW and ventilation)
• Direct electric systems (e.g. infrared heaters, electric boilers)
• District heating,
• Boiler systems for oil or gas, biomass etc.
• Solar thermal can also be included

PVecon offers even the opportunity to use monthly conversion factors (to convert final energy to non-renewable primary energy or to CO2 emissions) for Electricity or Distric Heating for the monthly calculation of the non-renewable primary energy or the CO2 emissions.

Figure 10: Monthly conversion factors (for PE) in PVecon

With this detailed assessment of the potential how much of the PV electricity can be used within the building, it is possible to determine:

• The amount of electricity that can be used within the building
• the amount of electricity that can, or better, must be sold to the public grid:
• The amount of electricity that must be bought from the public grid

As can be seen in the diagram below, PV energy can be sold to the grid mainly in summer:

Figure 11: Energy demand, energy generation, self-consumption and need to sell or buy electricity in PVecon

With this information, further economic assessment about the PV systems can be undertaken in order to evaluate the economic viability of the PV system defined in PHPP. In order to do so, the economic data for the PV system must be entered as well as the energy prices that can be achieved when either buying or selling PV. PVecon offers to enter this data in up to 10 different variants to allow a better assessment to find the best economic option.

PVecon first of all offers to enter a total of 10 different variants for the following economic data for the PV system as it has been defined within PHPP:

• Costs PV Panels [€]
• Costs for Support Structure [€]
• Costs for Cables [€]
• Costs for Inverters [€]
• Costs for smart meters [€]
• Funding or financial support for the PV system (enter negative amounts) [€]

Furthermore, the costs for the energy storage system can be entered:

• Costs for batteries [€]

Until now, the functionality of PVecon focuses on buildings only works with some limitations:

PVecon works for residential buildings only, for example for single family homes (SFH), detached or semi-detached houses, and multi-family homes (MFH) like apartment buildings.

Energy used for mechanical cooling of the building through inverse heat pumps or split units is not yet included.

The energy storage in electric cars has been simulated but is currently not included in the calculation models.

[PHPP 9] Wolfgang Feist, Witta Ebel, Rainer Pfluger, Zeno Bastian, Esther Gollwitzer, Jessica Grove-Smith, Oliver Kah, Berthold Kaufmann, Benjamin Krick, Jürgen Schnieders, Jan Steiger, Passivhaus Projektierungspaket 9: Das Energiebilanzierungs- und Planungstool für effiziente Gebäude und Modernisierungen , Darmstadt 2015

[PHPP 10] Wolfgang Feist, Witta Ebel, Zeno Bastian, Corinna Geiger, Esther Gollwitzer, Jessica Grove-Smith, Wolfgang Hasper, Roberto Iannetti, Oliver Kah, Berthold Kaufmann, Benjamin Krick, Laszlo Lepp, Aurelia Lippolis, Tomas Mikeska, Rainer Pfluger, Elena Reyes Bernal, Jürgen Schnieders, Jan Steiger, Passivhaus Projektierungspaket 10: Das Energiebilanzierungs- und Planungstool für effiziente Gebäude und Modernisierungen, Darmstadt 2021

[PHPP] PHPP – Passive House Planning Package

[PHPP accuracy] PHPP - validated and proven in practice