Heat sources / Local Resources

4.2.1 Resource typologies

The HP resources analysed in this study are:

 Air

 Geothermal (geothermal boreholes)

 Lake (lake of Geneva, deep layer at 35 m depth)

 River (Rhône river, corresponding to the top layer of the lake))

 Groundwater (main groundwater areas)

 Solar (solar thermal collectors as HP heat absorbers)

Of these resources, air, geothermal, groundwater and solar are locally available (Table 4:1). The others (deep lake, river, and to some extent groundwater, see Figure 4:2-left) are regional resources, which may not be available at local building scale. The spatial constraints of the deep lake and river resources in relation to the territorial distribution of the heating demand are illustrated in Figure 4:2-right. Their use is therefore subject to a specific distribution infra-structure. As an alternative to local valorisation by way of decentralized HPs, these resources can be valorised by way of a centralised HP connected to a district heating system (not treated in this study). However, in latter case the direct cooling feature (without use of cooling machines) is not possible.

Air Geo. Lake River Gr. water Solar

Locally

available x x (x) x

Space

extensive x x

Table 4:1 Availability (local or regional) and resource type (extensive or intensive).

From these resources, geothermal and solar are space extensive, i.e. subject to available roof or ground area in the premises of the building. At local building scale, the other ones can be considered as unlimited heat sources. Their sole limitations would be their local availability (existing distribution infrastructure), legislative/normative constraints (e.g noise levels for air HP systems, environmental protection issues for groundwater) or integration constraints in the building (e.g. integration of air HPs on roof tops).

Finally, this study doesn’t consider the use of HPs with local or regional waste heat.

Note that, from here forward, whenever the term hydrothermal is referred, it concerns lake, river and groundwater heat sources. Moreover, the term lake concerns deep lake.

Potential and constraints of available heat sources in relation to various building demands.

Figure 4:2 Left - Main groundwater⁶ areas in the Canton of Geneva (source: PGG, 2011) Right - Heating demand density of the Canton of Geneva (source: Quiquerez et al., 2016)

4.2.2 Reference year

While standard weather hourly data is readily available for air temperature, wind, and solar irradiation (SIA2028, 2010), such is not the case for the hydrothermal resources, in particular concerning the temperatures of deep layers of the lake of Geneva and of the Rhône river. For the sake of our study, we hence start by defining a common refer-ence meteorological year, on the hand of following existing data sets, covering the 2006 – 2015 decade:

 Concerning the common meteorological variables (air temperature, solar irradiation, wind velocity), archives of continuous acquisition on urban and peri-urban sites is being provisioned on the web by the University of Geneva, since several decades (Ineichen, 2013). The data used in this study concerns the peri-urban site

“Batelle”.

 For the lake of Geneva, hourly temperature data of the “Prieuré” fresh water pumping station (pumped wa-ter form a depth of 35 m) was handed over by SIG. A previous comparison with the nearby situated GLN dis-trict cooling station (for which data is only available since April 2010) shows a very good correspondence be-tween the two data sets (Viquerat, 2012).

 For the Rhône river, hourly temperature and flow rate data is available from the Swiss Federal Office for the Environment (FOEN, 2015).

So as to define the most representative year of the decade, following procedure was adopted, for each of the 3 sets of temperatures (air, lake, river):

 The sorted hourly temperatures profiles were averaged on an hourly basis, yielding an average sorted hourly temperature profile (see Annex H).

 For each year of the decade, the actual sorted hourly temperatures profile was compared to the averaged sorted hourly temperatures profile, in terms of the mean square hourly difference ΔTms.

Out of the 10 years, 2010 turns out to be the one with the smallest ΔT , as averaged over the 3 resources (air, lake,

Potential and constraints of available heat sources in relation to various building demands.

Comparison of the reference year (2010) with the decade average (2006 – 2015) is given in Table 4:2. For all three resources, the mean square hourly difference is small (0.45 K for air, 0.30 K for the lake, 0.65 K for the Rhône river).

The difference between 2010 and the decade average remains also small in terms of the temperature extremes (for all three resources, less than 1 K difference between the minimum values, as well as between the maximum values).

Reference (2010) Decade average Reference - Decade

Tavg Tmin Tmax Tavg Tmin Tmax ΔTavg ΔTmin ΔTmax ΔTms

°C °C °C °C °C °C K K K K

Air 12.6 -5.3 35.4 12.5 -5.5 34.7 +0.09 +0.21 +0.75 ±0.45

River 12.2 4.0 25.5 12.7 4.3 25.3 -0.51 -0.37 +0.27 ±0.65

Lake (deep) 7.7 4.6 17.5 7.8 5.1 18.0 -0.14 -0.53 -0.51 ±0.30

Reference (2010) SIA 2028 Reference – SIA

T_avg T_min T_max T_avg T_min T_max ΔT_avg ΔT_min ΔT_max ΔT_ms

°C °C °C °C °C °C K K K K

Air 12.6 -5.3 35.4 10.9 -9.7 34.7 +1.62 +4.40 +0.70 ±1.65

Table 4:2 Benchmarking of air and hydrothermal temperatures. Top - comparison of the reference year (2010) with the decade average (2006 – 2015); Bottom - comparison of the reference year (2010) with standard weather data (SIA 2028).

Tavg , Tmin , Tmax average, minimum and maximum hourly temperature

ΔTavg , ΔTmin , ΔTmax difference between average, minimum and maximum hourly temperature ΔTms mean square difference between hourly sorted temperatures

As far as air is concerned, comparison of the reference year (2010) with standard weather data (SIA2028, 2010) is also given in Table 4:2 (as well as in Annex H, in terms of sorted temperature profiles). As can be seen, 2010 is 1.7 K warm-er than the standard meteorological year, and has a less pronounced minimum (-5.3°C instead of -9.7°C). As a result, the heating degree days of 2010 (2048 K.day over the Oct-Apr period, on an 18/12 °C basis) are 14% lower than for the standard weather (2385 K).

Regarding global solar irradiance, in the horizontal plane, the comparison of the reference year (2010) with the dec-ade average (2006 – 2015) is given in Table 4:3 and it shows that the mean square hourly difference is a consequent value (9.5 W/m²). The difference between 2010 and the decade average is -6 W/m² (difference between sums: -51 kWh/m²). Comparison of the reference year (2010) with standard weather data (SIA2028, 2010) show slightly smaller differences (mean square hourly difference of 7.5 W/m², average difference of -5 W/m² and sum difference of -41 kWh/m²).

Reference (2010) Decade average Reference - Decade SIA 2028 Reference - SIA

G_h.avg G_h.sum G_h.avg G_h.sum ΔG_h.avg ΔG_h.sum ΔG_h.ms G_h.avg G_h.sum ΔG_h.avg ΔG_h.sum ΔG_h.ms

W/m² kWh/m² W/m² kWh/m² W/m² kWh/m² W/m² W/m² kWh/m² W/m² kWh/m² W/m²

Solar 141 1236 147 1288 -5.9 -51.3 9.5 146 1277 -4.7 -40.8 7.5

Table 4:3 Benchmarking of global solar irradiance, in horizontal plane. Left - comparison of the reference year (2010) with the decade average (2006 – 2015); Right - comparison of the reference year (2010) with standard weather data (SIA 2028).

Gh.avg , Gh.sum hourly average and annual sum of global solar irradiance

ΔG_h.avg , ΔG_h.sum difference between hourly average and annual sum of global solar irradiance

ΔGh.ms mean square difference between hourly sorted global solar irradiance

Potential and constraints of available heat sources in relation to various building demands.

Concerning groundwater, a study with punctual data (PGG, 2011) shows that the main groundwater areas in Geneva have a temperature between 10 and 15°C, with variations according to depth and season. Do to the lack of hourly data and for simplification purposes, a constant temperature of 13°C was considered in this study.

Finally, the hourly dynamic of the 2010 resources is presented in Figure 4:3, for the air, lake, river (Rhône) and groundwater temperatures as well as for the global horizontal solar irradiation. Note that the geothermal borehole temperature, as well as the solar collector temperature fed to the HP, are not presented here, as they result from forthcoming numerical simulation.

Figure 4:3 Dynamic profile of air and hydrothermal temperatures (top) and global horizontal solar irradiation (bottom), hourly values (2010).

Figure 4:3 shows that air is the resource with higher seasonal and daily variability, with a minimum temperature in winter of -5°C and a maximum temperature in summer of 35°C (in 2010). Next is the river (which is equivalent to the superficial layer of the lake), with smaller seasonal and low daily variability. Its minimum and maximum temperatures, in 2010, are 4°C and 26°C. The lake (35m depth) follows with a minor seasonal variability but some peak temperatures between May and November due to lake currents effects (Viquerat, 2012). Its minimum and maximum temperatures are 5°C and 18°C. Finally, by hypothesis, groundwater has a constant temperature of 13°C. Solar irradiance follows the

-10 -5 0 5 10 15 20 25 30 35

0 720 1440 2160 2880 3600 4320 5040 5760 6480 7200 7920 8640

Temperature [°C]

h Air

Rhone Lake Groundwater

0 100 200 300 400 500 600 700 800 900 1000 1100

0 720 1440 2160 2880 3600 4320 5040 5760 6480 7200 7920 8640 Solar irradiation [W/m2]

h Global horizontal

Potential and constraints of available heat sources in relation to various building demands.