H EAT DEMAND AND HEAT DEMAND DENSITY

pattern almost equals the load pattern of the total area. While the two European countries show a clear reduction of the electric load on the weekend, the day with the lowest load in Algeria is the Friday.

3.1.3 Spatial resolution

The national load values were disaggregated spatially in order to allow for arbitrary choice of regions to be investigated. Since electricity consumption takes place mostly in urban areas, the land cover category ‘artificial surfaces and associated areas’ was chosen as the proxy parameter for the spatial disaggregation. The artificial surfaces in each raster cell of the investigation area were summed up nationally; then for each raster cell the share of artificial surfaces in the total national artificial surface was calculated. In each raster cell, this percentage was then multiplied by the national load. Figure 3.1.4 shows the distribution of the load in the year 2010 in dense urban centres (Paris, London and other English, Belgian, Dutch and German city regions), and in areas with sparse occurrence of artificial surfaces (e.g. in Northern and Eastern UK).

Figure 3.1.4:

Annual electricity demand in GWh/km²/a disaggregated with the proxy

parameter ‘artificial surfaces and associated areas’.

Extract: South-East UK, Northern France, Belgium and the

Netherlands.

3.2.1 National per-capita heat demands

Readily available statistical data on final heat consumption (EUROSTAT, IEA) only take heat sold as such into account – no fuels converted in households and in the commercial sector are regarded. However, some national studies deal with the actual heat demand, regarding all fuels used for space heating and domestic water warming.

From a German report (BDEW 2008), a value of 11.2 MWhth/(capita*a) of the annual low-temperature heat demand per capita in Germany can be derived. In Austria, 10 MWhth/(capita*a) were calculated in a bottom-up method, but according to the author of the study this value is slightly below the demand as compared with official statistics available in Austria (Schmidt 2008).

Both heat demand values were transferred to other countries by scaling them up or down according to heating degree days that were obtained from the EUROSTAT statistical database (EUROSTAT 2008). Heating degree days are a relative measure of heat demand.

In order to calculate heating degree days, the daily differences between average outside temperatures and a desired room temperature of 20 °C (if outside temperatures are lower than 15 °C) are summed up for a certain period of time. Heating degree days are frequently used as an index for heating demand changes in time.

Figure 3.2.1: Scaled low temperature heat demand in MWhth/(capita*a) compared to individual country study results.

The scaling results were compared to low temperature heat demand values from other individual country studies or appropriate statistics where available (BERR 2008), (Statistics_Finland 2008), (Statistik_Austria 2008), (Bundesamt_fuer_Energie 2008)).

Calculating the national per-capita heat demands on the basis of the German per-capita heat demand results in values closer to those values given in national studies in most cases, as can be seen in figure 3.2.1. The German value was chosen as a basis for scaling: national per-capita heat demand values for all countries considered were obtained by scaling of the German per-capita heat demand with country specific heating degree days.

For some countries, no heating degree days were available from EUROSTAT. The degree days of neighbouring countries were used as a proxy. These countries and the respective proxy countries are listed in table 3.2.1.

0 5 10 15 20 25

Austria Finland (space heating only)

Germany Sw itzerland United Kingdom

heat demand [MWh/(capita*a)]

Degree-days-approach, 10 MWh/(Austrian capita*a) Individual country statistics

Degree-days-approach, 11.2 MWh/(German capita*a)

Table 3.2.1: Proxy data sources for countries without heating degree day information.

Proxy country Bulgaria Croatia Greece Lithuania Malta Slovakia Switzerland Countries without

heating degree day information

Serbia Bosnia Albania,

Macedonia Belarus

Cyprus, Algeria, Morocco, Tunisia, Libya, Egypt

Ukraine,

Moldova Liechtenstein

3.2.2 Spatial resolution

The low temperature heat demand that is not to be exceeded by the cumulated heat delivery of all CHP technologies must fulfil the criterion that the heat demand density is high enough for economic district heating systems.

Assuming a strong correlation with the population distribution, a heat demand density map was created by multiplying the per-capita heat demand values with population numbers in each raster cell and dividing the result by the raster cell areas. Figure 3.2.2 shows the heat demand density in Europe and neighbouring countries.

For economic district heating applicability, the heat demand density must be higher than a certain threshold. Different values for this threshold can be found in literature. They are mostly given as minimum heat delivery per meter of district heating: (Reidhav and Werner 2008) indicates 556 kWh_th/(m*a), whereas in (UBA 2007), a value of 1000 kWh_th/(m*a) was assumed. The average district heat delivery in Denmark currently is 500 kWhth/(m*a); the Danish district heating system operator Dansk Fjernvarme aims at pushing the limit of economic district heating system operability down to 140 kWhth/(m*a) (Nast 2008). As a lower boundary, a value of 200 kWh_th/(m*a) was assumed here. The relation between the length of a district heating grid and the area it covers varies as well: for urban areas excluding industrial areas it ranges between 190 m/ha and 320 m/ha (UBA 2007). The

Figure 3.2.2:

Heat demand density in Europe and neighbouring countries in GWh_th/(km²*a).

resulting threshold for the heat demand density lies between 4 GWhth/(km²*a) and 32 GWh_th/(km²*a). Here, the more optimistic value of 4 GWh_th/(km²*a) was chosen as the threshold of heat demand density below which the heat demand was not considered.

3.2.3 Temporal resolution

The heat demand for heating was temporally disaggregated with normalized daily heating degree day values that were derived from 2-m-above-ground temperature data from the German Weather Service DWD (DWD 2007). Based on (BDEW 2008), the share of the heat demand for heating in the total low-temperature heat demand was calculated. In Germany, it amounted to around 85 % in 2006. This fraction of the total low-temperature heat demand was temporally disaggregated with heating degree days for all countries.

Around 15 % of the German low temperature heat demand is for hot water. This fraction of the heat demand was evenly distributed over the year.

Due to the lack of comprehensive information for the fractions of hot water and heating demand in the total low-temperature heat demand in other countries, the German shares were used for all countries in the investigation area as a best guess. The resulting temporal distribution of the total heat demand in the investigation area is shown in figure 3.2.3.

Figure 3.2.3: Mean hourly heat load in the total investigatio n area in GW_th, course over the year.

0 200 400 600 800 1000 1200 1400 1600 1800 2000

0 2000 4000 6000 8000

hour GWth