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In order to be able to calculate the life cycle module B6, the operational energy demand of the building must be known. The use phase of buildings can range from 30, to 50, to over 100 years, making the operational energy demand calculation an important parameter for the LCA of buildings.

In general, energy demand in buildings can refer to three types of definitions (cf. DIN V 18599-1:2011, p.11):

- Primary energy: energy as it is available in the natural environment, i.e. the primary source of energy.

- Final energy: energy which the consumer receives at the boundary of the building envelope.

- Useful energy: energy which is an input to an end-use application, i.e. the energy provided in a room in the form of heat.

To calculate the final energy demand, the useful energy demand can be multiplied by a factor for losses within the building. The primary energy demand can be calculated by multiplying the final energy demand with a primary energy factor dependent on the energy carrier, such as gas or electricity.

Different types of energy demand occur during the use phase. Lützkendorf et al. (2015, p.65) distinguish between two types: building-related operations and user-related operations (see Table 6). While the architect has no influence on user-related operations, energy demands for building-related operations, such as space heating and cooling, are directly influenced by the architect’s design. The thermal quality of the building envelope and the choice of heating system, but also geometric parameters, such as the window layout, amongst others,

determine this kind of energy demand. However, it should be noted that the user’s behaviour also influences energy consumption to a certain degree, e.g. through the temperature that tenants set in their rooms (Hegger et al. 2007, p.189).

Table 6: Examples for building- and user-related operations based on Lützkendorf et al. (2015, p.67)

Building-related operations User-related operations

Space heating Plug-in supplementary lighting

Space cooling Household / Office appliances

Air movement Refrigerator

Fixed lighting Hot water

Auxiliary energy (e.g. for heat pumps) Devices in data centre

Indoor transportation Other specific functional devices

In general, there are two possibilities for determining the building’s operational energy demand: dynamic building performance simulation (DBPS), such as EnergyPlus15 _or

15 _{EnergyPlus is an open source whole-building simulation software. The development is funded by the U.S.}

Department of Energy’s (DOE) Building Technologies Office (BTO), and managed by the National Renewable Energy Laboratory (NREL). The software is available at https://energyplus.net/downloads (accessed February, 9th 2016)

TRNSYS16_{, and quasi-steady state methods (QSSM), such as ISO 13790:2008, DIN V 18599-}

2:2011, or DIN V 4108-6:2003.

For both methods it is necessary to define a boundary for the energy balance, which

corresponds to the thermal envelope of the building. To calculate the heating demand, heat sinks and useable heat sources are balanced within this defined boundary and a defined time step. To calculate the cooling demand, excess heat sources are balanced. The resulting heating or cooling demand has to be provided through building services.

The main difference is the time steps in which the energy balance is established. Time steps for DBPS usually range between 1 minute and 1 hour. DBPS considers the thermal heat storage capacity in every time step. Thus, the heating and cooling behaviour can be

simulated in detail. Furthermore, DBPS allows for detailed simulation of dynamic regulation, such as dynamic shading elements that track the sun's movement. As such, DBPS is advisable for complex situations, because it allows for detailed modelling of complex systems and their interrelation. However, DBPS requires a great number of boundary conditions, and input of these boundary conditions requires extensive knowledge on the part of the user. In

EnergyPlus, for example, the user can choose between different heat balance and surface convection algorithms, which have a significant impact on the results. This makes it difficult to apply for architects without a profound education in building physics. Furthermore, the simulation takes a lot of computational time. Depending on the size of the building, the simulation can take between 20 seconds and 5 minutes on a standard PC17_.

QSSM usually balance energy sources and sinks on a monthly basis, and consider the heat stored in the building material only via a global factor. Due to the simplification, some aspects are not considered, and complex interactions cannot be represented. The simplified approach allows for quick feedback of results, with computation times ranging from 0.1 to 5 seconds, making QSSM much more time-efficient for the optimization of simple systems, such as residential buildings. According to van Dijk et al. (2006, p.262), the accuracy of the results from QSSM are acceptable for residential buildings in warm, moderate, and cold climates. QSSM is also used for national energy saving regulations, such as EnEV 2014

16 _{TRNSYS is a graphically based software environment used to simulate the behaviour of transient systems. It}

includes TRNSYS3D - a plugin for SketchUp that allows the user to draw multi-zone buildings and import the geometry. The software is available at http://www.trnsys.com/ (accessed March 2nd 2016)

(Bundesregierung 2013), and European energy performance certificates (Economidou et al. 2011, p.64).

An overview of the main characteristics of both methods is provided in Table 7. Table 7: Characteristics of quasi-steady state methods and dynamic building performance simulation

QSSM DBPS

Time step 1 month 1 minute to 1 hour

Calculation method for heat conduction

Analytical function for steady-state heat conduction

Analytical functions or differential equations for dynamic heat conduction

Relation between building surfaces No interaction between surfaces Interaction between surfaces is

considered

Consideration of solar radiation Dependent on cardinal direction

(azimuth)

Dependent on cardinal direction (azimuth) and altitude

Consideration of heat storage

capacity Global factor

Direct consideration in every time step

Consideration of building services Global factor for efficiency Detailed simulation of heating and

cooling phases

Consideration of moisture No Optionally

Computation time Low (0.1 to 5 seconds) High (20 seconds to 5 minutes)

Accuracy Low to moderate High

The building-related operations defined by Lützkendorf et al. (2015, p.65) are further divided into energy demand affected by the design and energy demand not affected by the design. Energy demand significantly affected by the building design, such as heating demand, is most important for architects, because they have a great influence on this kind of energy demand. The thermal quality of the building envelope, the window layout, and the choice of heating system, among other variables, directly influence this kind of energy demand. Therefore, it is calculated using QSSM or DBPS. It should be mentioned that the user’s behaviour also influences energy consumption to a certain degree, e.g. through the temperature that tenants set in their rooms (Hegger et al. 2007, p.189).

The architects’ influence on other kinds of energy demand, such as electricity for lighting or escalators, is limited. Nevertheless, it can be useful to assess this design-independent energy demand to provide a relation for the optimization potential of the design-affected kind in the context of the whole building. Therefore, this kind of energy demand is integrated optionally using statistical values.

The first German heat insulation ordinance (Wärmeschutzverordnung) was published in 1977. Since then, further regulations have been passed and are continuously refined and updated in all European countries. Most European countries now have implemented

national regulations for building energy performance which comply with the demands of the European Directive on the Energy Performance of Buildings (EU 2010). In Germany, the current energy saving ordinance, EnEV 2014 (Bundesregierung 2013), stipulates a monthly energy balance using QSSM. The algorithms for calculating the energy demand are defined in DIN V 18599-2:2011. At present, the older DIN V 4108-6:2003 can still be used for residential buildings.

As noted in the introduction, since the 1980s much attention has been paid to the opera- tional energy demand and - compared to LCA - the field is well known. For the objective of this thesis, there is no need for further research, and existing approaches are integrated into the new LCA method developed for this thesis.