Optimizing Micro Renewable Generation for Smart Cities by

Combining Solar and Geothermal Energy Potentials

A Case Study of the Hannover Region

Claudia Palmas

, Holger Jensen

, Christina von Haaren

and Robert Schöner

Department of Environmental Planning, Leibniz University of Hannover, Herrenhäuserstr. 2, Hannover, Germany

State Authority for Mining, Energy and Geology, Stilleweg 2, Hannover, Germany

Keywords: Micro Solar Energy Potential, Micro Geothermal Energy Potential, Smart Cities, Renewable Energies.

Abstract: In recent years there has been an increasing interest on small renewable energy production systems to

supply energy consumption of buildings. In Europe, cities face the challenge of combining energy

efficiency and sustainable urban development. This challenge is likely to have an impact on grid

infrastructures by implementing intelligent networks and storage facilities in order to secure energy supply.

This paper presents an approach for integrating solar and geothermal energy generation on the basis of a

spatially explicit assessment of potentials for both energy sources. The results should be applicable for

spatial planning. The case study area is the Hannover region. The results demonstrate that with data

available in blanked coverage in Lower Saxony the assessment of both renewables energy potentials could

be performed. The generated place based information meets the specific demands of regional as well as

municipal land use planning. It can be used for allocation and prioritisation of housing development with

micro-renewables and for proposing areas with the combination of both.

1 INTRODUCTION

Europe is facing the challenge to reach the so called

20/20/20 objective. This objective includes reducing

greenhouse gas emissions by at least 20% compared

to 1990, increasing the share of renewable energy

sources in final energy consumption to 20%; and

improving 20% energy efficiency (European

Commission, 2010). To this end a redefinition of

strategies may be necessary as several factors like

increasing of energy demand, fossil fuel energy

scarcity and high environmental impacts are

hampering target compliance. An important part of

such strategies could be to more efficiently activate

the potential of existing and new buildings for

producing their own energy. To that end we need

innovative strategies and approaches for integrating

energy concepts in regional and municipal land use

planning. In this context smart cities play a crucial

role. Countries in Europe are at different stages of

technological, political and administrative

development. However, in all cases the development

of smart cities depends significantly on smart grids,

intelligent grids to leverage energy consumption

between the different producers and consumers. The

successful combination of smart technologies can

help by improving energy efficiency and savings in

planning residential development and by adopting

measures for existing buildings. Smart technologies

need infrastructural changes of energy distribution

grids in an optimized way and are seen as a major

opportunity to merge energy and ICT industries and

technologies (Net!Works European Technology

Platform, 2011). Because of the intermittency

associated with the most renewable energy

production, it is necessary to combine renewable

energy technologies and to add some storage

mechanism in order to ensure the energy supply.

However, energy-saving measures in buildings are

either conventional (thermal insulation, energy-

efficient air conditioners and appliances) or based on

automatic intelligent systems (Wicaksono et al.,

2012). The deficits in practice correspond with

knowledge deficits about appropriate methods of

calculating energy potentials for supporting spatial

planning. In this context the micro renewable heat

potential, is especially important because it covers

the major part in urban energy consumption. The

common sources of micro renewable heat energy

production are solar thermal geothermal energy.

283

Palmas C., Jensen H., von Haaren C. and Schöner R..

Optimizing Micro Renewable Generation for Smart Cities by Combining Solar and Geothermal Energy Potentials - A Case Study of the Hannover

Region.

DOI: 10.5220/0004860602830288

In Proceedings of the 3rd International Conference on Smart Grids and Green IT Systems (SMARTGREENS-2014), pages 283-288

ISBN: 978-989-758-025-3

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

Against this background, the objective of this

paper is to present an innovative planning approach

which according to energy potentials identifies the

best locations for combining solar and geothermal

energy. The approach is based on the research

conducted in the context of the Project Smart Nord

of Lower Saxony, where all renewable energy

sources (solar, wind, biomass, hydro and geothermal

energy) are taken into account. Here we focus on

solar and geothermal energy in order to lead the way

for activating the synergies of combining both

technologies. In this case, synergies may occur for

the following reasons (Tepe, 2011):

- Reduction of borehole depth or number of

boreholes in new systems

- Improvement of deficits existing systems to

achieve better performance.

The main research questions are:

 How to estimate micro renewable energy

potentials? Which methods are needed?

 How to combine solar and geothermal energy

systems?

For answering these questions we present in section

2 methods for estimating the geographical

distribution of the solar energy potential. In section 3

an application on geothermal energy developed by

the LBEG about is presented and integrated with

solar energy combinations. Finally we discuss data

availability and transferability to other regions as

well as possible planning application (section 4) and

conclude with recommendations for regional and

municipal planning (section 5).

2 METHODS

2.1 General Methodological Approach

To calculate the solar energy potential we have

estimated the global irradiation annual average for a

horizontal surface, which can be converted

according optimized angle for solar panels and solar

thermal collectors.

To calculate the geothermal energy potential we

have focused on typical shallow geothermal systems

for northern Europe. The energy abstraction is

achieved by vertical closed loop heat exchangers

with a vertical depth of around 100 m. The

subsurface model is a three layer model covering the

depth of ground surface to 100 m below surface. The

horizontal resolution is given by a 50 m by 50 m cell

size raster grid.

2.2 Data

In Table 1 datasets used for the calculation of solar

and geothermal energy potential maps for the

Hannover region, Lower Saxony, northern Germany

are shown:

Table 1.

Layer name Scale/unit Source

DEM (Digital

Elevation Model)

DGM50,

50 m raster

grid

Landesamt Bergbau

Energie und Geologie

Niedersachsen (LBEG)

http://nibis.lbeg.de/cardo

map3/

Water level in

unconsolidated rocks

in Lower Saxony

1:200000

only

applicable

for

unconsidated

rocks

LBEG (HUEK 200

“Grundwasser-

oberfläche”)

http://nibis.lbeg.de/cardo

map3/

Basal plane of

quaternary

unconsolidated rocks

in Hannover, Lower

Saxony

1:500000

edited by

detailed

point and

vector line

data

LBEG (GSKH 1:25000)

Rohde, P. & Becker-

Platen, J. D.

Geologische Stadtkarte

Hannover 1:25000

NLFB 1998

Geological map

1:500000 Lower

Saxony

1:200000

LBEG (GUEK 500)

http://nibis.lbeg.de/cardo

map3/

Geo-tectonic

Atlas 3D

Only

uppermost

layer from

the 3D model

was used

Bombien et al. (2012),

based on Baldschuhn et

al. (2001)

PK OG 2008

“Geothermal Data

Catalogue”

Thermal

conductivity

table of

typical rock

types in

Germany

http://www.infogeo.de/d

okumente/download_po

ol/PKOG_Abschlussberi

cht_1.3_08-04-25.pdf

2.3 Methodology for the Estimation of

the Micro Solar Energy Potential

The solar energy potential is calculated using the

r.sun solar radiation model implemented in GRASS

GIS (6.4.2) and the PVGIS CM-SAF estimation

utility, derived from the Photovoltaic Geographical

Information System Interactive Maps (Joint

Research Center of the European Commission,

2010). The r.sun model calculates the global solar

radiation (beam, diffuse and reflected), for both clear

sky and overcast atmospheric conditions from the

digital elevation model (DEM) (Šuri et al., 2007).

An important factor in producing reliable maps of

solar irradiation was the estimation of sky cloud

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coverage, as the total amount of cloud cover

significantly affects ground irradiation. For this

reason, the data was validated using PVGIS. The

output of this model is a raster map of the global

irradiation annual average for a horizontal surface.

The PVGIS calculation of PV potential for a

specific site is based on spatial data automatically

taken from the PVGIS database. Generally, the

overall error for the whole year is quite small

(approximately 5%) (ibid.). The database is based on

climatic data from 566 meteorological stations

covering the 1981–1990 periods and includes

monthly averages of daily sums of global and

diffuse irradiation and Linke atmospheric turbidity.

Elevations and terrain features are represented by a

1-km digital elevation model. More details about the

European solar database implemented in the PVGIS

estimation utility can be found on its website (ibid.).

2.4 Methodology for the Estimation of

the Micro Geothermal Energy

Potential

All calculations were done in ArcGIS (ESRI)

version 10.0 and Microsoft Access 2007. Input data

as described in 3.2 are vector data (polygons) or

raster data (DEM). The raster layer was converted to

a point vector dataset. The data belonging to each

point consist of x,y-coordinates and the elevation.

Additional data from the polygon layers were

attached to the point layer. For the calculation of the

geothermal energy potential a three layer model was

used. The first layer consists of the distance from the

ground surface to the water table in the quaternary

porous rocks (dry unconsolidated rock). The second

layer consists of the thickness of the water saturated

porous quaternary rocks (saturated unconsolidated

rock). The third layer consists of the thickness and

type of the “hard rock” up to 100 m below ground

which were defined as the pre-quaternary rocks

(hard rock base).

Using the thickness and the thermal conductivity

for unsaturated and saturated unconsolidated rocks

as well as for each hard rock type an average

thermal conductivity up to 100 m could be computed

for each 50 m raster point. For the estimation of the

specific heat extraction values the transformation

from thermal conductivity to specific heat extraction

was performed following Pannike et al. (2006).

Here, the simplified geological stratification from

surface to 100 m depth is derived from the data

described above, and the specific heat extraction is

obtained from the following equation:

EWS

= -0,85 λ

+ 13,62 λ + 18,8

where P

EWS

= specific heat extraction capacity, and

λ = average heat conductivity of the rock.

The raster points were converted to a raster layer

with a cell size of 50 m. A continuous raster layer

set is the result, expressing the specific heat

extraction in each cell with 100 m heat exchangers.

For the solid rocks, there were some data

limitations due to the decreasing geological

information with the increasing depth. Therefore, the

rock type sometimes could only be estimated. The

data for unconsolidated rocks were taken from

geological maps on a scale of 1:25:000. The

information regarding the groundwater flow

component was not considered according to the VDI

4640 German directive.

2.5 Integration of the Energy Potentials

A first integration can be performed by an overlay of

the two energy potentials, because we assumed that

all the micro-energy potential maps are of the same

weight. The maps obtained show the best locations

for the integration of solar and geothermal energy

with vertical loops (40 m and 100 m).

3 RESULTS

3.1 Micro Solar Energy Potential Map

The latitude was computed directly from the DEM

raster, while the albedo and the Linke turbidity were

believed constant over the entire region, as a first

approximation. The clear sky indexes were not

available. After validation of the date, the output

raster map representing the annual average of global

irradiation daily sums estimated on optimally

inclined plane (Figure 1).

Figure 1: Annual average of daily sums of global

irradiation on optimally inclined plane [Wh/m

/d].

OptimizingMicroRenewableGenerationforSmartCitiesbyCombiningSolarandGeothermalEnergyPotentials-ACase

StudyoftheHannoverRegion

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The output units are [Wh/m

/day].

3.2 Micro Geothermal Energy

Potential Maps

As an example, we present here the geothermal

energy potential for vertical loops (100 m) (see

Figure 2). We calculated for further residential

appliance the energy potential for vertical loops (40

m).

3.2.1 Geothermal Vertical Loops (100 M)

The evaluated specific heat extraction capacities,

which were calculated from thickness and thermal

conductivity of geological strata, has been used to

evaluate the geothermal energy potential for the

Hannover region. The resulting map was classified

into three categories. Class 1 represents very high

geothermal energy potential with average specific

heat abstraction values of > 45 W/mK, class 2

represents high geothermal energy potential with

average specific heat abstraction values of 40-

45 W/mK, and class 3 represents standard

geothermal energy potential with average specific

heat abstraction values of <40 W/mK. Areas not

suitable for geothermal energy use because of

drilling restriction reasons, e.g. drinking water

protection zones, lakes etc., were classified

separately as prohibited areas.

Figure 2: Specific heat abstractios for geothermal vertical

loops (100 m) [W/mK]

The GIS overlay results x categories of areas are

shown in Figure 3.

The map of the geo-solar combinations

demonstrate that the Hannover region is

characterized almost by good-high potential for the

whole case study area. Nevertheless, areas where the

potential is relatively low (areas in green), because

of the terrain aspect and slope and rocks

characteristics should be integrated with others

renewables.

Figure 3: Energy potentials by combining solar and

geothermal energy (vertical loops 100 m).

4 APPLICATIONS

The specific heat extraction/geothermal energy

potential maps are used for online applications

(“Geothermie geht das bei mir?”, LBEG 2012)

which allow to calculate the required dimension of

the closed loop system as subsurface part of a

geothermal space heating. With limited input data of

a conventional home (area to be heated, energy

consumption per area and location of the house) the

dimension and costs of the subsurface part can be

estimated. This is a powerful tool for architects,

planning engineers, and house owners to estimate

costs of different heating supply systems.

Furthermore the maps can be used in local and

regional planning in various ways: In combination

with other spatial information in particular about

environmental vulnerability the maps can be used

for the allocation of urban development into areas

with high potential for a combined micro renewable

used. On the regional level this can be prepared by

rating and prioritizing areas with reference to the

regional or state wide average and by pointing out

their potential contribution to regional energy

targets. Regional energy targets as to the share of

different energy sources will rely on such

information. The implementation of such regional

planning information may be realized by

designations in the mandatory regional plan. On

local level, the information can be used in order to

allocate housing development as well as to include

regulations about adding respective RE facilities in

every legally binding development plan. For the

technical upgrading of exiting housing areas

incentive programs can be set up, which differentiate

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payments according to the expected results.

5 DISCUSSION

Both methods produce results that are differentiated

enough to serve as information basis for regional

and local planning as well as for individual house

owners. In our estimation the solar energy potential

estimation depends on the application of the r.sun

model and on the pvgis data, therefore it can be

applied in every region. However, the accuracy

depends on input data (DEM) and on pvgis data

availability.

For the geothermal energy potential maps we can

consider the typical amount of vertical heat

exchanger per area, which depends on the urban

settlement structure. The necessary input data for

this advanced model are land use maps and average

density of heat exchangers per land use type. With

this approach a comparison based on raster layers

with an energy value per cell would be possible. For

the geothermal energy potential the output energy

for space heating is higher than the energy

abstracted from the ground due to the input of a heat

pump. The seasonal performance factor (spf) of the

heat pump is the dimension of surplus from output

energy dependent of the input energy. The energy

which is available for space heating should be based

on a typical spf factor.

Research projects like Geo-Solar (Pärisch et al.,

2012) and first pilot products from the geothermal

market are focusing of the combination of

solarthermal and geothermal systems. The advantage

of solarthermal systems is the high effectiveness of

collecting energy, the advantage of the geothermal

system is the independent availability of energy 24

hours 365 days a year. Combining both systems

provides a constantly available effective heating

system driven by renewable energy. However, the

potentials of combining both energy sources need

further research. In the future, for a better integration

of both energy sources and the comparison to other

energy forms, all potential maps should be all

transformed to the same ordinal scaling and best

presented on cardinal scales which quantify

kilowatt-hour.

6 CONCLUSION

In many regions geodata already allows the spatially

concrete estimation of solar and geothermal energies

potentials. Our methodologies allow not only for

representing the separate potentials but also give a

first insight into the added value of combining both

sources. The results should be used in regional and

local land use planning as a contribution for

allocating housing development specifically

designed for micro generation of RES. It also can be

used for a targeted and results oriented approach to

allocating incentives to house owners for upgrading

existing houses by RE installation. Last not least the

maps could be made accessible to the public and

used by architects and house owners for calculating

the efficiency of planned solar or geothermal

installations.

ACKNOWLEDGEMENTS

The Lower Saxony research network "Smart Nord"

acknowledges the support of the Lower Saxony

Ministry of Science and Culture through the

"Niedersächsisches Vorab" grant program (grant ZN

2764).

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