Siting enhanced geothermal systems (EGS): Heat ...

Accepted Manuscript Siting enhanced geothermal systems (EGS): Heat benefits versus induced seismicity risks from an investor and societal perspective Theresa A.K. Knoblauch, Evelina Trutnevyte PII:

S0360-5442(18)30746-1

DOI:

10.1016/j.energy.2018.04.129

Reference:

EGY 12768

To appear in:

Energy

Received Date: 14 November 2017 Revised Date:

9 March 2018

Accepted Date: 22 April 2018

Please cite this article as: Knoblauch TAK, Trutnevyte E, Siting enhanced geothermal systems (EGS): Heat benefits versus induced seismicity risks from an investor and societal perspective, Energy (2018), doi: 10.1016/j.energy.2018.04.129. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT 1

Siting enhanced geothermal systems (EGS): Heat benefits versus induced

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seismicity risks from an investor and societal perspective

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Theresa A. K. Knoblauch1) *, Evelina Trutnevyte1) 2)

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1)

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SoE) and D-USYS Transdisciplinarity Lab, Department of Environmental Systems

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Science (D-USYS), ETH Zurich, Switzerland

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Renewable Energy Systems, Institute of Environmental Sciences (ISE), Section of Earth and Environmental Sciences, Faculty of Science, University of Geneva, Switzerland

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*corresponding author

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Energy

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Swiss Competence Center for Energy Research-Supply of Electricity (SCCER-

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Abstract Enhanced geothermal systems (EGS) harness thermal energy from the deep

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underground to produce renewable and low-carbon electricity and heat. Siting EGS

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in rural versus urban areas involves trading off benefits of sold heat and avoided

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CO2 emissions and induced seismicity (IS) risk. In remote areas, IS risk is minimal,

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but EGS heat cannot be purposefully used for residential district heating. In urban

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areas, the heat can be sold, but EGS poses higher IS risk. We quantify this trade-off

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using cost-benefit analysis (CBA) from both private and social perspectives. We

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model 12 hypothetical EGS scenarios, with EGS of differing size (water circulation

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rate of 50 to 150 l/s) and siting (0 to 100’000 residents nearby). We bound

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uncertainties using Monte Carlo and sensitivity analyses. According to CBA, from the

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private perspective, large EGS (150 l/s) near a large population (10’000 or 100’000

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residents), enabling high heat sales, are most profitable. The CBA from the social

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perspective shows that medium- or large-sized EGS (100 or 150 l/s) near some

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residents (1’000 or 10’000) are most beneficial, based on reasonable heat sales

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while limiting potential IS damage. Siting EGS in remote areas is less favorable,

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even if expected IS damage is zero.

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1 Introduction Enhanced geothermal systems (EGS) harness thermal energy from the deep

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underground to produce electricity and heat. Electricity production requires

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subsurface temperatures above 100 °C, which are com monly found at depth of at

43

least 3 km [1]. At this depth, an artificial reservoir is created by enhancing the

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permeability of the subsurface. Fluid is then circulated through the reservoir,

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absorbing heat from deep underground and transporting it to the surface. As the

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reservoirs can be artificially created, in contrast to other types of geothermal

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systems, EGS (also known as petro-thermal or hot-dry-rock systems) can be

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deployed nearly anywhere [2]. Other benefits of EGS are its negligible direct

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greenhouse gas emissions [3,4], its renewable resource abundance, and its reliable

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base-load availability. EGS is already contributing to electricity and heat production

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in Australia, France, Germany, and elsewhere [5], while energy strategies in

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countries like Switzerland [6] and the United States [7] include planned

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implementation of EGS in the near future which requires strategic siting of EGS. If

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sited successfully, EGS can technically meet 3% of global electricity and 5% of

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global heat demand by 2050 [4].

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However, creating EGS reservoirs by injecting highly pressurized fluid into the deep

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underground and later, circulating water for energy production, carries the risk of

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induced seismicity (IS) [1]. Although unavoidable and even helpful for reservoir

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creation [8], IS can lead to public nuisance and damage to buildings and

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infrastructure and interrupt or even delay projects [9,10]. Induced earthquakes

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associated to EGS projects have been observed around the globe [11–15]. For

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instance an EGS project in Basel, Switzerland, caused an induced event of ML 3.4,

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resulting in damage claims of 9 million USD [9]. A deep geothermal project in St.

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Gallen, Switzerland, an induced earthquake of ML 3.5 occurred. However, damage

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claims were negligible [16]. Within the EGS project in the Geysers, United States, an

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induced earthquake of ML 4.6 was recorded [17]. Likewise, in Berlin, El Salvador, an

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induced earthquake of ML 4.4 was observed [18] and one of ML 3.7 in the Cooper

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Basin, Australia [12]. After a M 5.4 event in November 2017 near the deep

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geothermal site in Pohang, South Korea, investigation is ongoing with respect to

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potential links between this earthquake and the injections activities, although it is too

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ACCEPTED MANUSCRIPT early for any conclusions [19].

Current risk assessment from industry anticipate

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possible IS events equal or larger than ML 4.5 for Switzerland [20,21]; whereas

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detailed forecasting models from seismologists anticipate potentially maximum IS

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events that can be coextensive with the largest naturally possible earthquakes

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[22,23]. This range of potential IS events is confirmed by a recent EGS expert

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elicitation which also revealed disagreement between the various seismological

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schools of thoughts [24].

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The literature has repeatedly drawn attention to the dilemma of siting EGS projects,

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as siting influences both IS risk and EGS profitability (see, for instance, [1,25]). IS

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risk is a composite of the IS hazard, local soil amplification, exposure of buildings,

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and vulnerability of those buildings, whereat IS hazard specifies the energy released

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during an earthquake in magnitude and probability of occurrence and exposure

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specifies how many buildings, and thus how much value may be damaged by the

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seismic hazard [26]. On the one hand, siting EGS projects in remote areas away

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from populated spaces and buildings can reduce exposure and thus IS risk

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[17,27,28]. Recent EGS guidelines accordingly allocate urban EGS projects to a

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higher risk class than remote projects in terms of both physical risk and public

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concern and recommend more extensive risk governance as compared to projects in

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less populated areas [29,30]. On the other hand, heat sales, especially to a dense

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district heating network (DHN), make EGS projects more economically viable and

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the price of electricity more competitive and reduce CO2 emissions as compared to

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conventional heat systems [25,31–33]. Proximity to infrastructure and buildings is

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necessary to efficiently use heat. Thus, there is a trade-off between IS risks and heat

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benefits when siting EGS projects.

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Motivated by ambitious EGS targets and hence complex siting decisions, we use

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cost-benefit analysis (CBA) to quantify the trade-off of siting EGS of different

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capacities in remote or in densely populated areas. Among all parameters that could

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be varied for CBA, we put primary emphasis on the trade-off between benefits of

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supplying geothermal heat to residential buildings and avoiding CO2 emissions from

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fossil fuel heating versus IS risk to the same residential buildings. As both the

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benefits of selling heat and IS damage to residential buildings can be monetized,

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CBA is an adequate tool for quantifying the siting trade-off. We analyze 12 4

ACCEPTED MANUSCRIPT hypothetical scenarios combining different EGS size (water circulation rates of 50,

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100, or 150 l/s) and siting (0, 1’000, 10’000, or 100’000 residents nearby). We model

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the EGS plant and its heat and electricity production in detail and couple it to a

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purposely developed model of IS hazard and risk that is adequate for first order-of-

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magnitude estimates, given the high uncertainties and lack of data for IS [24]. We

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distinguish between CBA from the perspectives of both private investors: hereafter

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CBA (private) and society (CBA (social)) [34]. CBA (private) reflects the viewpoint of

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the EGS operator and thus includes net present value (NPV (private)), internal rate

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of return (IRR), and levelized cost of electricity (LCOE) for every scenario. CBA

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(social) reflects costs and benefits, to society as a whole, including damage due to

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IS, CO2 savings, and revenues, in order to quantify NPV (social) and benefit-to-cost

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ratio (B/C ratio). We complement both private and social CBA with an uncertainty

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assessment by using Monte Carlo and sensitivity analyses.

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2 Past studies on EGS cost and benefits and IS Table 1 summarizes the literature on EGS profitability for both current and

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prospective projects. According to this literature, EGS has the potential to become

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an economically viable supplier of electricity and heat in the future. Efficiency of

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converting thermal energy to electricity is crucial for profitability of EGS and has

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been investigated in [35,36]. The conversion system has further been considered

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with regard to optimally exploiting EGS reservoirs [37–39]. Although IS is typically

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covered within environmental impact assessment of EGS [29] and carries a

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monetary risk to EGS projects, few scientific studies that modelled EGS from techno-

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economic perspective have explicitly addressed IS. In addition, other studies have

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discussed EGS lifecycle assessment of environmental impacts [40–42] and

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sustainability performance as compared to other renewable energy sources [43].

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Further, techno-economic assessments have investigated the profitability for heat

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from deep geothermal energy [44], as well as from shallow heat pumps [45,46].

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Table 1 Past studies on EGS and other deep geothermal systems profitability assessment

International Energy Agency (IEA) Intergovernmental Panel on Climate Change (IPCC) German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety

OM/ yr [USD/kWhe] 87.3–134.3

LCOE [USD/kWhe] 0.3

2008

2000–5900

0.09–0.25

0.1–0.3

[32]

1800– 5200

83–187

0.03–0.17

[4]

2005 2011

JRC Geothermal energy status report Association of Swiss Electricity Companies Financial valuation of EGS (Euronaut) Assessment of reservoir management scenarios (3D thermo-hydraulic geologic model) Economic optimization of CO2 based EGS (Thermodynamic model [54])

2675–5350

Electric efficiency 40%

8–12%

2020 / 2030 2018

746

2020

11021

2010/ 2050

7315/ 12428

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3.5% of CAPEX

Ref. [47]

[48]

0.2 / 0.16

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UK Department of Energy & Climate Change

[49]

0.09–0.33

10–13%

[31]

0.06–0.18

11.2%

[50]

0.28/0.1

10–15%

[51]

@ 180°C 14%

[52]

10.5%

[53]

0.24–0.5

[55]

Combined heat and power (CHP), USA

0.11–0.57

34%

[56]

Economic evaluation of EGS plants (GETEM [57])

Combined heat and power (CHP), Switzerland Electricity only, USA Combined heat and power (CHP), Germany Electricity only, Europe

0.06–0.31

16%

[14]

0.035– 0.085 0.31–0.38

10%

[3]

10–12%

[58]

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Technical and financial performance of EGS systems (Geophires)

Economic feasibility of EGS (MIT EGS)

Economic and environmental assessment of EGS (Generic model) Comparison of electricity from EGS to other renewables (LCOE)

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Electricity only, EU Combined heat and power (CHP), UK Combined heat and power (CHP), EU Electricity only, Switzerland Electricity only, Soultz-sous-Forets, France Electricity only, Soultz-sous-Forets France

2000-2030

CAPEX [USD/kWe] 6663–13853

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Swiss electricity model (TIMES)

Case study, Country Electricity only, Switzerland Combined heat and power (CHP), Worldwide Electricity only, Worldwide Electricity only, Germany

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Study (model)

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2020

8326

0.18–0.24

[59]

.

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ACCEPTED MANUSCRIPT Literature touching topically on siting trade-offs that take into account IS has not

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addressed EGS costs and benefits. More specifically, IS caused by EGS projects

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has been the focus of multiple seismic hazard and risk assessments, among them

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[10,12,13]. In addition to geophysical considerations, Hosgör et al. have also looked

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at social concern initiated by IS and spatial siting of EGS [60]. Another study

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contrasted IS in Swiss projects in Basel and St. Gallen and the resulting damage

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claims, which were considerably apart partially due to differing perception of IS [16].

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One lifecycle assessment incorporates IS in a qualitative way; however, it does not

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consider siting or heat production [41]. Thus, a more holistic model of benefits and

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costs, including IS, is needed to quantitatively assess EGS siting trade-offs.

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3 Method

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3.1 EGS scenarios and case study To quantify the trade-offs described above, we generate 12 EGS scenarios with

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different siting and water circulation rates (Table 2). Siting ranges from remote areas

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(no residents or residential buildings within a radius of 5 km [29]) to urban areas (in

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the middle of a larger city). Based on siting and thus number of surrounding

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residents, we estimate the amount of heat that can be sold to a local DHN and how

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many residential buildings are exposed to potential IS. Circulation rate determines

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the rate at which heated water is withdrawn from the reservoir by two production

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wells and thus how much electricity and heat can be produced. The smallest

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considered circulation rate of 50 l/s corresponds to the operating range of current

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EGS plants (e.g. [15]). The largest considered circulation rate of 150 l/s is limited by

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the range of current pump capacity and their maximum flow rates [61,62]. We take

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Switzerland as a case study because the ambitious goals of the Swiss Energy

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Strategy to produce up to 4.4 GWhe/year of electricity by 2050 [6] require

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coordinated planning for multiple EGS plants.

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Table 2 Characteristics of 12 EGS scenarios

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Total circulation rate

during operation (triplet well configuration) Number of residents 0

Village

1’000

Town Urban

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100 l/s

150 l/s

S1

S2

S3

S4

S5

S6

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Remote

50 l/s

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Siting

10’000

S7

S8

S9

100’000

S 10

S 11

S 12

3.2 Cost-benefit analysis framework

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The quantification of the EGS siting trade-off needs to compare the benefits of sold

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heat with the costs of IS damage to buildings. As both these costs and benefits

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involve direct and indirect costs to society, we choose the cost-benefit analysis

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(CBA) as a method. While we acknowledge the limitations of CBA [63,64], CBA is

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common in policy assessment as well as energy research [65], including renewable

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ACCEPTED MANUSCRIPT energy specifically [66,67]. We conduct private and social CBA for the scenarios

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presented in Table 2. Figure 1 depicts the system boundaries for the respective

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analysis. CBA (private) takes the viewpoint of a project investor. Thus, for CBA

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(private), we quantify direct costs and revenues, such as investment, operation and

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maintenance cost, and revenues from electricity and heat. For estimating the

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project’s value over the EGS lifetime of 30 years, we use net present value from the

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private perspective (NPV (private)), for which cash flows are discounted [53]. To

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further compare EGS scenarios, we calculate internal rate of return (IRR), which is

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less influenced by initial investment than NPV. For both, NPV (private) and IRR,

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prices of electricity are exogenously assumed. To calculate the cost of producing

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one unit of electricity in each EGS scenario, we use levelized cost of electricity

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(LCOE). These three parameters are commonly used for appraising investments in

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energy technology [28], [54].

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Figure 1 EGS framework for CBA from private and social perspectives. Respective EGS scenarios are determined by water circulation rate and residents near the EGS.

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CBA (social) includes external costs and benefits that are borne by other actors in

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addition to the investor [68]. The boundaries of CBA (social) thus include damage

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due to IS and reduction in CO2 emissions. To compare the various EGS scenarios

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from a social perspective, we use NPV (social) and cost-benefit ratio (C/B ratio)

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[63,69,70].

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3.3 Model of EGS plant and its operation According to Figure 1, we will now discuss major technical aspects of the EGS under

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consideration. Among all possible configurations, the assumed EGS always

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produces electricity that is entirely supplied to a transmission grid. Residual heat

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from the EGS is supplied to a local DHN according to the scenario’s heat demand.

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We do not further differentiate seasonal EGS configurations or seasonal heat

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demand but base our calculations on annual heat demand for residential buildings.

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The respective equations are given in Supplement A. The EGS is based on a triplet

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well configuration (one injection and two production wells), which has been

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suggested for efficient extract of heat from deep underground [71]. Well depth,

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production temperature, temperature drawdown, reservoir impedance, circulation

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fluid loss, and thermal drawdown are kept constant across all scenarios (Table 3).

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With carbon dioxide plume technology being still in research stage [72], it is

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assumed that water is circulated through the deep-underground reservoir as a heat

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carrier. The water’s circulation rate determines at what rate thermal energy is

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extracted from the subsurface and thus the conversion rate to electricity and heat for

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DHN.

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Heated water is circulated from the reservoir to the EGS conversion system by

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downhole pumps. The EGS converts the extracted heat to electricity through a

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binary conversion cycle, known as the organic rankine cycle (ORC). Binary ORC is

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an established technology which reaches relatively high efficiencies [35,73]. We

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calculate the EGS plant’s capacity based on the scenario’s circulation rate. One

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downhole pump per well maintains this circulation rate by overcoming the reservoir

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pressure drop. The downhole pump power that is necessary to maintain the

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circulation rate quadruples with increasing circulation rate [52] and increases linearly

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with reservoir impedance [74] and can be modelled accordingly (Supplement A,

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Equation (3)) [39]. Table S1 in Supplement B summarizes technical details for

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downhole pumps. Further, we do not consider wellbore pressures losses, buoyancy

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effects, hydraulic drawdown, or thermosiphon effect. Thermal drawdown is kept

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constant across scenarios in Table 3. In scenarios where the necessary pump power

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exceeds the electricity produced by EGS, downhole pumps are powered with

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electricity bought from the grid.

230 Depending on the siting scenario, the EGS either produces electricity only or

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operates as a combined heat and electricity plant (CHP). We do not consider

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exclusive heat production by EGS. In the electricity-only case, the circulated water

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must be cooled down after using it for electricity production. To protect local water

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sources, this can be done by dry cooling, which means additional parasitic power

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consumption of approximately 10–12% of gross power [75]. In the CHP case, we

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assume a topping or serial cycle [39,56]. In a serial cycle, residual heat is fed into a

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local DHN after heat withdrawal for electricity production. The amount of residual

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heat supplied to the DHN corresponds to the respective scenario’s heat demand,

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which is specified by number of residents multiplied by living space per resident [76],

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times heat demand per living space in Switzerland [77] (Table S3 in Supplement D).

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Table 3 EGS assumptions that are kept constant across analyzed scenarios

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Symbol ηele ℎ,

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Unit

km % h/ yr MPa*s / l %/ yr °C °C °C

Value 0.13 0.95 5 8 8’760 0.2 3 1 55 170 90

Ref. [14,31,35,48,51,78] [50,52] [79] [14,52] [56] [57] [3] [26] [80]

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Definition Thermal efficiency Availability factor Reservoir depth Circulation fluid loss Full electricity load hours / year Reservoir impedance Number of wells Thermal drawdown of reservoir Reinjection temperature Production temperature Temperature to feed to DHN

3.4 Induced seismicity risk and hazard of EGS scenarios

246 247

For estimating IS risk, we use the composite definition of IS hazard, local soil

248

amplification, exposure of buildings and infrastructure, and vulnerability of those

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buildings [28]. IS hazard describes how much energy is released during an

250

earthquake and is specified by magnitude and probability of occurrence [29]. Local

251

soil amplification characterizes how the hazard propagates through geology,

252

resulting in ground shaking. Exposure defines how many buildings, and thus how

253

much value, may be damaged by the seismic hazard [28]. Vulnerability defines the

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ACCEPTED MANUSCRIPT extent of damage and depends on the fragility or resilience of the exposed buildings

255

[30].

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We couple each EGS scenario with a stylized IS model to estimate hazard during

258

creation of the EGS reservoir and later operation of the EGS. Addressing EGS IS

259

hazard entails lack of data, deep uncertainty, and disagreement among experts

260

[9,22,24,29]. Evidence suggests that injection volume during hydraulic stimulation is

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a major determinant of IS activity during reservoir creation [17,23,81]. The

262

seismogenic index offers one generic way to estimate IS hazard related to injection

263

volume. It describes the injection site’s seismotectonic features and, together with

264

the Gutenberg-Richter distribution, can be used to calculate occurrence probability

265

for IS earthquake magnitudes [82,83]. This approach has been validated for

266

reservoir creation but not operation [22,84]. To couple our EGS scenarios to IS

267

hazard model, we assume that higher EGS circulation rate (capacity), requires

268

increased reservoir size [85] and hence increased injection volume for stimulation.

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We therefore linearly relate EGS circulation rate to injection volume around data

270

points from past EGS projects [24,86].

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Only a few studies describe EGS IS hazard after reservoir stimulation during long-

273

term operation, for instance [87,88]. It is typically argued that a felt and damaging

274

earthquake would anyway lead to a project’s termination and hence long-term EGS

275

operation with IS is unrealistic. We, however, assume a hypothetical case, where

276

EGS would still continue operating, for example, similarly to geoenergy projects

277

continue operating in Oklahoma despite periodic IS [89]. Owing to the lack of data on

278

IS during long-term EGS operation, we illustrate two different IS hazard cases during

279

the 30-year operation phase. These two cases are derived from the IS hazard during

280

creation (Figure 2) and bound our analysis [90]: (i) no IS during operation (lower

281

bound); and (ii) low IS during operation (base case). Further results are conditional

282

to those two IS cases.

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Figure 2 Assumed EGS IS hazard during reservoir creation and operation.

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3.5 Direct costs and revenues for CBA (private)

Direct EGS costs include investments and operation and maintenance; revenues are

289

generated from selling electricity and heat. Investments must be made for both the

290

subsurface and the surface portions of the EGS. Subsurface investments include

291

well drilling and reservoir creation. Cost for well drilling increases with well depth, but

292

there is no generalizable pattern (Figure S1 in Supplement E). Hence, we assume a

293

fixed cost of 10 million USD for each well drilling plus a fixed cost of 1 million USD

294

for reservoir creation (Table 4). Reservoirs and consequently their costs are kept

295

constant across scenarios.

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Table 4 Cost assumptions for CBA (private and social) Definition Scaling factor for EGS plant cost Cost of cooling unit (electricity only case) Cost of heat unit (CHP case) Cost of operation and maintenance Cost of reference EGS plant Cost of water Private discount rate Social discount rate Number of downhole pump Power capacity reference EGS plant Cost of downhole pump Lifetime of EGS Lifetime of pumps Average value of a building Building class ratio B to C Cost of creation reservoir Cost of electricity Cost of heat Cost of well drilling

EP

Symbol ∝ ! "# " $ % $ &'! &$

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Unit USD USD/ kW th million USD/ yr USD 3 USD/m

kW e USD Year years million USD million USD USD/kWhe USD/kWhth million USD/

Value 0.5 0.3 of plant 150 1 8'560'000 1.8 10 % 3% 2 4000 100’000 30 5 1.95 0.5 1 0.043 0.07 10

Ref. [56,73] [75] [56] Table S2 [91] [85] [68] Table S2 Table S1 Table S1 [10] [92] [93] [25] Figure S1

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ACCEPTED MANUSCRIPT Emission allowance price of CO2 for electricity production Emission allowance price of CO2 for heat production Greenhouse emissions electricity mix Greenhouse emissions heating oil

well USD/tCO2

4.53

USD/tCO2

88.03

g CO2-eq/ kWhe g CO2-eq/ kWhth

181.5 313

[94]

[95] [96]

298 Surface investments include an EGS plant to convert thermal energy to electricity

300

and either a unit to cool residual heat or a unit to supply residual heat to the DHN.

301

The EGS plant’s cost is scaled from previous projects on the basis of the scaling

302

factor ∝ (Table 4 and Supplement A, equation (3)) [56,73]. Table S2 in Supplement

303

C shows the range of EGS plant costs from previous projects and literature. To

304

process residual heat, the electricity-only EGS is assumed to have a dry cooling unit,

305

which comes at relatively high investment cost [75]. For the CHP EGS plant, we

306

consider an additional investment cost for the heat unit proportional to its heat output

307

[56].

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For operation and maintenance costs, we account for the currently limited lifetime of

310

downhole pumps and recurring additional costs by assuming replacement of both

311

downhole pumps every 5th year (Table S1 in Supplement B). An additional operation

312

and maintenance cost of 1 million USD is assumed to compensate for salaries, small

313

repairs, and the like. Also, 8% of the circulating water is assumed to diffuse through

314

the reservoir, which must be replaced [79].

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Direct revenue calculation assumes that all produced electricity is sold at average

317

market price (mean of Swissix Day Base and Swissix Day Peak 2016: 43.04

318

USD/MWh) [93]. Produced heat is sold to the local DHN up to its maximum heat

319

demand [25] (Table 4). We assume a discount rate (private) of 10% [85], which is

320

relatively high [25] but justifiable regarding the risks of EGS projects. All cost and

321

revenues estimates are converted to USD2017. In general, we do not consider

322

inflation because it is relatively low in Switzerland [97].

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323 324

3.6 Indirect and external costs and benefits for CBA (social)

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To calculate indirect costs and benefits of EGS projects, we also consider damage to

326

residential buildings caused by IS as well as CO2 savings. We monetize damage to

327

buildings caused by IS by linking the respective IS hazard described in Section 3.4 to 15

ACCEPTED MANUSCRIPT the scenario’s exposure and vulnerability of buildings. More specifically, we translate

329

hazard magnitudes into intensities by using the Earthquake Catalogue of Switzerland

330

(ECOS) [98], assuming no spatial variation of earthquake intensity. We then

331

calculate the scenario’s building exposure in two steps: first, we calculate the

332

number of exposed buildings by multiplying the number of residents in scenarios by

333

the average number of residents per household and average number of households

334

per building in Switzerland [99,100]. Second, to obtain a monetary value for buildings

335

exposed, we multiply the number of exposed buildings by the average value of

336

buildings for the city of Basel (Swiss part) (Table 4) [10]. For building vulnerability,

337

that is, the extent to which buildings will be damaged by various IS intensities, we

338

use a simplified approach developed by Fäh et al. [92]. This approach quantifies

339

vulnerabilities for different building types and for earthquake intensities leading to an

340

overall expected damage ratio, which indicates what share of total exposed building

341

value will become damaged on an aggregated level, so a village, town, or urban area

342

(Table 2). Within this study, we assume equally spatially distributed residential

343

buildings of building classes B and C, as suggested for the city of Basel [92].

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344

In terms of benefits, we calculate CO2 savings from electricity and heat production by

346

EGS with respect to current electricity and heat production in Switzerland. As EGS

347

issue no direct greenhouse gases during operation [3,4], CO2 savings are calculated

348

by comparison to the Swiss electricity mix [95] or heating with heating oil [96], which

349

is commonly used in Switzerland [101]. CO2 savings from electricity production are

350

then monetized using the current price of European Emission Allowances [94] as

351

suggested by the European Commission [68] (Table 4). CO2 savings from heat

352

production are monetized using an emission tax according to Swiss Federal

353

regulations [102]. We further assume a social discount rate of 3% [68].

355

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345

3.7 Monte Carlo analysis and sensitivity analysis

356

We proceed in four steps to obtain and interpret results from both private and social

357

CBA. First, we conduct deterministic CBA based on data presented in Table 3 and

358

Table 4. Second, due to the limited empirical evidence, we use Monte Carlo analysis

359

for pivotal parameters where data is ambiguous or uncertain [103], allowing us to

360

simultaneously capture the uncertainty of various parameters. Those parameters

16

ACCEPTED MANUSCRIPT (Table 5) concern more specifically technical and cost aspects of the EGS

362

conversion system as well as input parameters for the seismogenic index applied for

363

estimating IS hazards. Third, we illustrate sensitivity cases for different discount

364

rates. For CBA (private), we bound our analysis with discount rates of 7% and 12%;

365

for CBA (social), we bound our analysis with discount rates of 1% and 5%. Fourth,

366

as discussed in Section 3.4, we consider two sensitivity cases for IS hazard during

367

the 30-year operation phase of the EGS: no or low IS hazard (Figure 2), where the

368

low IS case is our base case while the no IS case are the bounds of our analysis.

Table 5 Parameters varied in Monte Carlo Analysis Symbol α

Definition Scaling factor for EGS plant cost

ηele Σ

Thermal efficiency of EGS plant Seismogenic Index

b

b-value

Thermal drawdown

Ref. [56,73]

Normal Normal

[14,31,35,48,51,78] [82]

Normal

[10]

Normal

[56] [57] [3]

Uniform

[24], [73]

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Distribution Uniform

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Coefficient to linearly model water volume for reservoir creation

Value M = 0.33, σ = 0.19 13%, σ = 2% M = 0.25, σ = 0.05 M = 1.50, σ = 0.05 M = 1% σ = 0.5% M = 20.000 3 m ,σ= 3 5’773m

M AN U

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17


4 Results

373

4.1 Results of CBA from the private perspective In this section, we present characteristics of the 12 EGS scenarios and then present

375

CBA (private) results, including NPV (private), IRR, and LCOE. Table 6 shows

376

technical details and intermediate results for these 12 EGS scenarios, such as gross

377

electricity output in year 1 of operation, which ranges from 2.2 MW for the lowest

378

circulation rate (50 l/s) to 6.53 MW for the highest circulation rate (150 l/s). Electricity

379

output decreases considerably over the lifetime of EGS due to thermal drawdown of

380

the reservoir. These technical details translate into discounted direct costs and

381

revenues, as depicted for EGS scenario 9 (150 l/s circulation rate, 10’000 residents)

382

in Figure 3a. EGS entails high upfront investment costs, in this case 42.7 million

383

USD, followed by decreasing revenues from electricity during lifetime (Figure 3a) due

384

to thermal drawdown (Section 3.3).

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18

ACCEPTED MANUSCRIPT

- Base case: low IS during OP

387

2 100 4.35

3 150 6.53

4 1'000 50 2.18

5 1'000 100 4.35

6 1'000 150 6.53

7 10'000 50 2.18

8 10'000 100 4.35

9 10'000 150 6.53

10 100'000 50 2.18

11 100'000 100 4.35

12 100'000 150 6.53

MW

1.01

2.01

3.02

1.01

2.01

3.02

1.01

2.01

3.02

1.01

2.01

3.02

MW

0.33

1.33

3.00

0.33

1.33

3.00

0.33

1.33

3.00

0.33

1.33

3.00

MW

1.63

2.58

2.88

1.84

3.02

3.53

1.84

3.02

3.53

1.84

3.02

3.53

MW

0.57

0.48

-0.28

0.67

0.68

0.02

0.67

0.68

0.02

0.67

0.68

0.02

12.82 4.52 0.00 0.00 0.00 5.42 2.32

20.37 3.78 0.00 0.00 0.00 7.67 3.29

22.68 -2.21 0.00 0.00 0.00 9.39 4.02

1’000 USD 1’000 USD 1’000 USD

11 4 0

18 3 0

1'000 USD/ year 1'000 USD/ year

0 0

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GWh GWh GWh GWh GWh million USD million USD

RI PT

l/s MW

1 50 2.18

14.53 5.31 11.54 6.71 6.71 5.42 0.77

23.81 5.37 23.07 6.71 6.71 7.67 1.54

27.83 0.17 34.61 6.71 6.71 9.39 2.31

14.53 5.31 11.54 67.14 11.54 5.42 0.77

23.81 5.37 23.07 67.14 23.07 7.67 1.54

27.83 0.17 34.61 67.14 34.61 9.39 2.31

14.53 5.31 11.54 671.38 11.54 5.42 0.77

23.81 5.37 23.07 671.38 23.07 7.67 1.54

27.83 0.17 34.61 671.38 34.61 9.39 2.31

20 0 0

188 180 387

196 180 701

200 175 964

314 306 3'872

623 607 7'009

927 903 9'638

314 306 38'716

623 607 70'093

927 903 96'379

0

0

0

0

0

0

0

0

0

0

0

0

0

27

54

80

272

539

803

2'716

5'391

8'027

TE D

Unit

EP

Scenario Number of residents Water circulation rate Gross electricity output (year 1) Gross electricity output (year 30) Electricity for downhole pump Net electricity output Pnet (year 1) Net electricity output Pnet (year 30) Net electricity (year 1) Net electricity (year 30) Heat output Heat demand Heat sold Cost of EGS plant Cost of heat exchanger / cooling unit CO2 savings (year 1) CO2 savings (year 30) IS damage during reservoir creation Annual IS damage sensitivity cases - Case no IS during OP

SC

Table 6 Technical details and intermediate results of 12 EGS scenarios (yr: year; OP: operation)

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Figure 3 EGS scenario 9: (a) Discounted costs and revenues from private perspective using private discount rate; (b) discounted costs and benefits from social perspective using social discount rate.

Error! Reference source not found.a shows the resulting NPV from the private

389

perspective. In general, NPV (private) ranges from -17 to 30 million USD and

390

increases for both EGS siting in an area surrounded by a growing number of

391

residents and increasing circulation rate. NPV remains constant from EGS siting

392

surrounded by approximately 10’000 residents and upwards because in these

393

scenarios, heat demand from residents exceeds heat produced by EGS. Thus, all

394

heat produced by EGS can be supplied to the local DHN. Thus, NPV is the highest

395

for scenarios 9 and 12. Thus, locating an EGS near many residents (10’000 and

396

100’000) combined with relatively high circulation rate (150 l/s) makes investing in

397

EGS most profitable from the private perspective. In contrast, NPV (private) is

398

negative for EGS scenarios in remote areas or with few residents as well as for EGS

399

scenarios with the lowest circulation rate. In these scenarios EGS is unprofitable

400

from the private perspective. This investment appraisal is confirmed by IRR, the

401

results of which correspond to those of NPV (private) and show a similar pattern:

402

IRR below an assumed discount rate, in this case 10%, would not be considered an

403

attractive investment.

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20

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Figure 4 (a) NPV (private) and IRR for EGS scenarios where bold typeface represents profitable scenarios; (b) LCOE for EGS scenarios. Green corresponds to less favorable and yellow to more favorable scenarios from the private perspective. 405

LCOE, which represents the cost of producing one unit of electricity, shows a similar

407

but inverted pattern compared to NPV (private) and IRR. According to Error!

408

Reference source not found.b, LCOE ranges from 0.16 to 0.50 USD/kWhe across

409

EGS scenarios. Generally, LCOE decreases with both EGS siting near a growing

410

number of residents and increasing circulation rate. LCOE remains constant when

411

EGS is located near 10’000 residents and upwards because all heat can be sold to

412

the DHN. LCOE is lowest for EGS scenarios 9 and 12 thus highest circulation rate

413

(150 l/s) and many surrounding residents (10’000 or 100’000 residents). In contrast,

414

LCOE is highest for EGS scenarios without any surrounding residents in remote

415

areas as well as EGS scenarios with low circulation rate.

417

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4.2 Results of the CBA from the social perspective

418

CBA (social) includes indirect and external costs and benefits, such as damage to

419

buildings due to IS or benefits of CO2 savings. Table 6 lists the intermediate results

420

such as damage due to IS during operation (base case), which ranges from no

421

damage for EGS located in remote areas to 8 million USD for EGS surrounded by a

422

large number of residents (100’000) and operating at the highest circulation rate.

423

Monetized CO2 savings (year 1 of operation) range from 11,000 USD to 927,000

424

USD, respectively. Figure 3b displays costs and benefits from the social perspective

425

during EGS lifetime for scenario 9 (150 l/s circulation rate, 10’000 residents).

21


Damage due to IS amounts to significant costs when creating the reservoir (9.6

427

million USD), whereas during operation, the cost of IS (800’000 USD) roughly

428

balances against benefits of CO2 savings (927’000 USD for year one of operation

429

and 903’000 USD for year 30 of operation).

430 Error! Reference source not found.a displays NPV from the social perspective

432

which spans from -154 to 74 million USD. Essentially, the most profitable EGS

433

scenarios for society according to the NPV (social) are located centrally right in

434

Error! Reference source not found.a: these are the scenarios with mid- or large-

435

size circulation rate (100 or 150 l/s) combined with siting near some but not too many

436

residents (10’000 or 100’000 residents). Among eight EGS scenarios with positive

437

NPV (social), the most profitable is EGS scenario 9, wherein EGS is located near a

438

considerable number of residents (10’000) combined with highest circulation rate

439

(150 l/s). Mid-range profitability can be expected from EGS scenarios near some

440

residents (1’000 or 10’000 residents) in combination with the small circulation rate

441

(50 l/s) and EGS scenarios located near no residents combined with medium

442

circulation rate (100 l/s). Regarding negative NPV (social), EGS scenarios located

443

near an especially large number of residents are clearly unattractive investments

444

from the social perspective. This can be attributed to extensive damage due to IS.

445

Also, EGS scenarios surrounded by no residents show negative NPV for the

446

smallest circulation rate (50 l/s). In this scenario, EGS produces too little electricity to

447

compensate for high upfront investment (50 l/s).

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22

ACCEPTED MANUSCRIPT Figure 5 (a) NPV (social) for EGS scenarios (base case); (b) B/C ratio for EGS scenarios (base case). Blue corresponds to less favorable and green to more favorable scenarios from the social perspective; bold typeface represents profitable scenarios. 449 Error! Reference source not found.b presents the B/C ratio, which divides benefits

451

by costs (social). Preferably, benefits outweigh risks, resulting in a B/C ratio

452

exceeding 1, as is the case for most scenarios. The B/C ratios of these scenarios

453

show a similar pattern to NPV (social); the most attractive scenarios are located

454

centrally right and are a combination of EGS near medium density (1’000 and

455

10’000) and medium or large circulation rate (100 l/s or 150 l/s). According to the B/C

456

ratio, scenario 9 (150 l/s circulation rate, 10’000 residents) is the most preferable for

457

investment from the social perspective. Other scenarios with mid-range B/C ratios

458

include EGS located near a medium number of residents (1’000 or 10’000) and small

459

circulation rate (50 l/s) or scenarios with location near no residents combined with

460

medium circulation rate (100 l/s or 150 l/s). In contrast, costs (social) outweigh

461

benefits when EGS is sited near a large number of residents (100’000). These

462

scenarios do not generate enough benefits from electricity and heat sales and CO2

463

savings to compensate IS damage. Likewise, costs (social) outweigh benefits for the

464

EGS scenario near no residents with the smallest circulation rate (50 l/s). Again,

465

revenues from electricity do not compensate high upfront investments.

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450

IS becomes increasingly substantial when siting EGS in areas with a growing

468

number of residents. Figure 6 displays the development of costs (social) and benefits

469

across the 12 EGS scenarios. Two factors contribute to damage due to IS other than

470

siting EGS in remote areas: increasing circulation rate and the number of

471

surrounding residents, which is illustrated by vertical comparison of the EGS

472 473 474

scenarios, shown in Figure 6.

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23

481

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Figure 6 Discounted costs and benefits, summed, and NPV [millions USD] for 12 EGS scenarios from the social perspective. Benefits are displayed counterclockwise from top, and costs are displayed clockwise from top. Benefits and cost are separated by black lines.

4.3 Monte Carlo and sensitivity analyses

EP

475 476 477 478 479 480

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ACCEPTED MANUSCRIPT

We now assess the uncertainty of the CBA results via Monte Carlo analysis. Figure 7

483

shows the distribution of intermediate technical results, specifically, the produced

484

electricity in year 1 versus year 30 of operation and heat supplied to the DHN. For

485

both electricity and heat production, results become more uncertain with increasing

486

circulation rate. This is because, according to our model, electricity and heat

487

production are proportional to circulation rate and thermal efficiency. Further, results

488

for electricity production in year 30 of operation are more dispersed than in year 1 of

489

operation. This can be attributed to potentiation of uncertainty over EGS lifetime with

490

regard to thermal efficiency and reservoir drawdown temperature. Electricity

491

production decreases to thermal drawdown of the reservoir over lifetime. In contrast,

492

pump power remains constant, which can lead to pump power exceeding net

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24

ACCEPTED MANUSCRIPT electricity output and the consequent additional expense of buying electricity from

494

the grid, which is presented as negative electricity production in Figure 7. For the first

495

two EGS siting scenarios (0 and 1’000 residents), heat supply is limited by residents’

496

heat demand and is thus constant, while for the remaining siting scenarios, all

497

produced heat can presumably be sold to the DHN, which is linked to some

498

uncertainty.

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25

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Figure 7 Monte Carlo sensitivity analysis for electricity in year 1 and year 30 of EGS operation and heat. Thermal drawdown can lead to insufficient net electricity production, leading to purchase of additional electricity from the grid, presented as negative electricity output.

506

Error! Reference source not found. presents the uncertainty of monetized results

507

from both the private and social perspectives (NPV (private), NPV (social), LOCE,

508

and B/C ratio). Four major findings can be derived from Error! Reference source

509

not found. and the corresponding analysis. First, in general, uncertainty becomes

510

larger with increasing circulation rate, which can be attributed to uncertainty in

511

electricity production as discussed above plus uncertainty within cost assumptions

512

that depend on EGS size and therefore also on circulation rate (Section 3.5).

513

Second, mid-range NPV (private) and NPV (social) amounting to approximately

514

9 million USD in absolute value can easily flip between positive and negative if input

515

values are slightly varied, as demonstrated by EGS scenarios 3 (150 l/s circulation

516

rate and no residents). Consequently, for EGS projects of comparable NPV, there is

517

no clear evidence whether the project will eventually be profitable according to our

AC C

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500 501 502 503 504 505

26


analysis. For remaining NPV (private) and (social), outliers indicate that only

519

substantial changes in parameters lead to flipping NPV (private) or NPV (social).

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520

Figure 8 Monte Carlo analysis for NPV (private), NPV (social), LCOE, and B/C ratio (base case). 521

Third, results are more dispersed for NPV (social) than for NPV (private). This is

523

because of uncertainties within CO2 savings for scenarios in remote areas and

524

additional uncertainty from IS estimates for all other scenarios, which are only

525

considered for the social perspective. CO2 savings uncertainty can be attributed to

526

uncertainty within electricity and heat production, and estimated IS uncertainty

527

reflects the current state of knowledge [24], which, in our analysis, is represented by

528

the input values from the seismogenic index (Table 5). For NPV (social), these

529

uncertainties are amplified with increasing number of residents, most prominently for

530

urban scenarios (100’000 residents). Fourth, in contrast to NPV (social), uncertainty

531

of B/C ratio is relatively stable across increasing numbers of residents, indicating that

532

uncertainty of cost (social) and of benefits develop more or less the same. Yet,

533

uncertainty in the B/C ratio declines for EGS scenarios with the largest number of

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27

ACCEPTED MANUSCRIPT residents. The reason is the growing uncertainty in cost (social), which is reflected in

535

the denominator of the B/C ratio.

536 537

Error! Reference source not found. and Error! Reference source not found.

538

present sensitivity cases for LCOE and the B/C ratio for a range of private and social

539

discount rates. In general, lower discount rates lead to higher profitability from both

540

private and social perspectives and consequently to lower LCOE and higher B/C

541

ratio. LCOE shows substantial sensitivity to private discount rates while the pattern

542

of LCOE over EGS scenarios holds across sensitivity cases. Similarly, B/C ratio is

543

highly sensitive to social discount rates but its pattern remains stable across

544

sensitivity cases.

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546

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Figure 9 Sensitivity of LCOE for EGS scenarios for private discount rates: (a) 7%; (b) 12%. Green corresponds to less favorable and yellow to more favorable scenarios from the private perspective

28

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ACCEPTED MANUSCRIPT

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Figure 10 Sensitivity of B/C ratio for EGS scenarios for social discount rates. (a) 1%; (b) 5%. Blue corresponds to less favorable and green to more favorable scenarios from the social perspective; bold typeface represents profitable scenarios. 547 Error! Reference source not found. contrasts the sensitivity of the B/C ratios for no

549

IS during operation to potentially low IS during operation (base case) as discussed

550

above. As described in Section 3.7, the no IS case anticipates no damage during

551

operation past the IS hazards during reservoir creation. The respective B/C ratios for

552

the 12 EGS scenarios show patterns similar to the base case but reach higher

553

values. For the top and central EGS scenarios, benefits outweigh risks (Error!

554

Reference source not found.a). In contrast to the base case (Error! Reference

555

source not found.b) B/C ratios are around one for EGS in a city near large

556

population (100’000 residents) when no IS during operation is to be expected. Thus,

557

when no IS is to be expected, siting EGS in a city could be an option although not

558

the most attractive one.

EP

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29

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Figure 11 Sensitivity of B/C ratio for EGS scenarios for IS cases. Left: no IS during 30-year operation; right: base case of IS during 30-year operation as in Error! Reference source not found.a. Blue corresponds to less favorable and green to more favorable scenarios from the social perspective ; bold typeface represents profitable scenarios. 560 561

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30


5 Discussion

564

5.1 Discussion of the results and practical implications Siting EGS of different capacities in remote or densely populated areas involves

566

trading off IS damage with the benefits of supplying heat to surrounding residents

567

and avoiding CO2 [1,25]: in remote areas the IS risk is minimal, but EGS heat cannot

568

be fully used for district heating, whereas in densely populated areas, the residual

569

heat can be supplied into the DHN, but IS risk is higher. This study quantifies for the

570

first time this trade-off using CBA from both the private and social perspectives. We

571

modeled 12 EGS scenarios differing by siting and circulation rate with their heat and

572

electricity production and coupled it to a simplified IS model. Our underlying

573

assumptions seem to be reasonable as we obtain LCOE estimates (Error!

574

Reference source not found.b) that are exactly in the same range as LCOE

575

estimates from previous literature (Table 1). Our IS damage values during operation

576

are similar to damage observed in the past and in detailed risk assessments [10,20].

577

Also, our finding that EGS are less profitable in remote areas with no revenues from

578

residual heat is in line with previous research [25]. This suggests quantitative

579

validation of our results.

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580

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565

The results of CBA (private) suggest that EGS should be located in areas where all

582

residual heat can be sold to a DHN, thus, towns or cities with 10’000 or more

583

residents. In contrast, the results of CBA (social) suggest locating EGS where a fair

584

amount of residual heat can be sold but potential damage due to IS is limited, thus

585

areas with 1’000 to 10’000 residents. Sensitivity analysis to IS cases showed that

586

EGS are significantly more profitable in areas where no potential IS hazards are to

587

be expected during operation. There, benefits outweigh costs for society as a whole

588

for most cases, even when siting EGS in large cities.

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589

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581

590

Concerning circulation rate and hence EGS capacity, CBA from both the private and

591

social perspectives suggest implementing EGS of a certain circulation rate with

592

respect to two technical constraints: on the lower end, circulation rate must ensure

593

that the EGS produces sufficient electricity and heat to compensate and ideally

594

exceed the high upfront investment costs. On the higher end, the circulation rate

595

should ensure that pump power does not exceed net electricity output, thus avoiding

31


additional purchase of electricity from the grid, which would considerably decrease

597

profitability. This could be bypassed by increasing wellbore diameter with installation

598

of additional wells; however, this in turn significantly increases the cost of EGS.

599

Additionally, according to our model, IS damage increases with circulation rate which

600

could be an additional constraint.

RI PT

601 Close attention should be paid to uncertainties regarding electricity and heat

603

production and costs, which themselves present a risk to investors and society.

604

Within this study, uncertainties in cost, efficiency, thermal drawdown, and IS input

605

parameters have been analyzed. These uncertainties amplify with increasing

606

circulation rate, which seems plausible as only EGS with relatively small circulation

607

rates have been realized so far. Uncertainties also affect indirect costs and

608

externalities, such as benefits of CO2 savings and, in particular, estimated damage

609

due to IS [9,22,24,29]. Furthermore, EGS scenarios with positive but rather low

610

expected NPV (both private and social) can easily flip to unprofitability if EGS

611

parameters change slightly. Consequently, when designing and siting EGS, thorough

612

analysis of parameters as well as sufficient swing of investment is vital.

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The results have implications for practical and scientific discussions of siting and

615

designing EGS. Our results do not necessarily sustain the arguments for siting EGS

616

in remote areas [17,27,28] because of the lack of revenues from heat sales. Poor

617

profitability from private perspective can, however, be enhanced with incentives for

618

investors, such as feed-in tariffs [104], for EGS scenarios that are profitable for

619

society. In our case, this would apply to EGS scenarios with circulation rates of 100 l/

620

and 150 l/s and no surrounding residents, which are beneficial for society but would

621

not be considered profitable from the private perspective unless incentivized. When

622

IS risk is not considered, EGS are most attractive in areas where all residual heat

623

can be sold. When IS risk is considered, EGS should be sited where a considerable

624

amount of heat can be supplied to a DHN while IS damage is limited, not

625

automatically zero. When designing EGS, water circulation rate and thus capacity

626

must be optimized with respect to revenues to compensate large upfront investments

627

and with respect to the auxiliary power demands of downhole pumps.

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614

628

32


5.2 Limitations and future research Quantifying the trade-off when siting EGS with different circulation rates is not

631

without limitations. We omitted variation of technical and economic parameters

632

where plausible and included relevant parameters in uncertainty analysis in order to

633

make the trade-off clearly visible. More specifically: first, regarding EGS and its

634

integration into DHN, we have merely considered a simplified thermodynamic EGS

635

model without varying reservoir configuration, such as thermal drawdown across

636

different circulation rates and thus different EGS capacities [3]. We also neglected

637

the uncertainty of the thermal gradient and thus adequate reservoir temperature. For

638

integrating EGS into DHN, we limited our analysis to constant heat patterns of

639

residents

640

surroundings. We also limited our analysis to constant future heat demand despite a

641

potential future decline due to better insulation. Further, we have not considered the

642

cost of connecting EGS to the transmission grid or DHN or the cost of the DHN itself.

643

We also excluded long-distance transmission of EGS residual heat from our

644

analysis, focusing instead on residential heat customers nearby, and did not include

645

industrial heat users or alternative heat applications.

of

potential

differences

between

remote

and

urban

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regardless

SC

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630

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646

Second, our IS model relied on very little empirical data. Creating and operating EGS

648

does not necessarily induce seismicity. However, regarding the large uncertainties

649

characteristic to EGS and other subsurface projects [9,22,24,29], our approach might

650

be justifiable. Also, we have simplified the IS hazard model by not spatially varying

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earthquake intensity and not considering differences in regional seismic and

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geological conditions, for instance, faults. We captured some of these differences

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through uncertainty analysis of the seismogenic index parameters and further

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acknowledge that in-depth modeling of IS is much more complex. Regarding

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damage due to IS, we used an overall expected damage ratio [92] that only

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considered earthquakes equal to or greater than intensity 5. Thus cosmetic, non-

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structural, and other minor damage is neglected in our analysis. We further limited

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our study to residential buildings and have not considered differences in housing

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structure or spatial arrangement of houses across siting scenarios, such as less

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dense housing in remote areas. Scenarios of siting EGS close to sensitive or critical

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infrastructure such as archaeological sites, research laboratories, or nuclear power

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ACCEPTED MANUSCRIPT plants are also outside the scope of our analysis; the consequences due to IS in

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such locations would be dire and realization of such EGS projects is problematic

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[29]. We have also not incorporated potential differences in building value across

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EGS sites (villages, towns, or urban areas). Further, damage due to IS could have

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been accounted for through insurance costs for CBA (private) instead of only

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including it in CBA (social) as a cost to society. Third, limitations concerning CBA in

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general [63,64] include monetizing certain aspects of EGS, which might not

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necessarily reflect the actual price society would be willing to pay to avoid damage

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due to IS or CO2.

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Forth, for our specific study, we restricted our analysis to 12 discrete, very specific

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EGS scenarios within the boundaries presented in Figure 1. This led to reasonable

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complexity of our CBA from both the private and social perspectives while

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representing reality only to a certain degree. Also, we primarily derived costs from a

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few pilot EGS. This again implies large uncertainties [32], which we tried to account

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for via Monte Carlo analysis. Thus, results might only be applicable to real EGS

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projects under consideration of the limitations described.

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In reality, however, investor’s or society’s profitability are not the only elements that

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will influence decisions about the future deployment of EGS; public reaction towards

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EGS and its IS risks [105] and whether society is willing to trade off these risks [9]

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will also be considered. This has not been quantified within our study, as CBA

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glosses over such trade-offs by simply summing costs (social) and benefits, limiting

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the analysis to set parameters. We therefore suggest four specific questions for

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future research: First, what costs and benefits matter to society and to society’s

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acceptance of EGS when siting and designing projects? Second, how does society

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trade off these costs and benefits of EGS projects beyond simply summing? Third,

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how can science provide the best available information about risks and uncertainties

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inherent to EGS projects and how can this be communicated to facilitate wiser

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decisions [106]? Fourth, how can society, which eventually bears the IS risk of such

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EGS projects, contribute to IS risk appraisal and IS risk management, for instance,

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by participation [107]? This study as well as future research can contribute to more

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robust decision-making when siting EGS in conjunction with efforts to reduce

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greenhouse gas emissions from electricity and heat production while continuously

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providing both.

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6 Conclusion In this study, we quantified the trade-off between heat benefits and IS risks when

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siting EGS projects of different sizes using CBA from both the private and social

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perspectives. Despite uncertainties inherent to EGS and model limitations, our study

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provides relevant implications for practitioners, policy makers and further research.

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Accordingly, our study does not necessarily support the claim to site EGS in remote

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areas to avoid IS risks due to lacking benefits from remaining heat. Considering CBA

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from the private and social perspectives jointly, EGS should be sited where

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considerable heat can be sold but damage due to IS remains limited not necessarily

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zero. In addition, EGS need to be carefully designed in order to generate sufficient

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revenues from electricity and heat sales in order to pay-off high upfront investment

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costs.

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With only few realized projects worldwide, EGS is a rather emerging, yet promising

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low-carbon renewable energy resource. In order for EGS to contribute to energy

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strategies realization, EGS projects need to be sited within boundaries that are

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attractive for both, private investors and the society. Ultimately, however, not only the

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EGS project’s viability will decide whether or not a project is being realized but also

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the outcome of societal and political discourse around EGS and its uncertainties

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which should be informed by scientific evidence.

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7 Acknowledgements This work has been completed within the Swiss Competence Center for Energy

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Research-Supply of Electricity (SCCER-SoE) Task 4.1 “Risk, safety, and social

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acceptance”. This is one of only a few teams worldwide in which seismologists,

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earthquake engineers, energy analysts, and social scientists collaborate closely to

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tackle the challenge of induced seismicity while fostering exchange with

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practitioners. The support of the Energy Turnaround National Research Program

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(NRP70) of the Swiss National Science Foundation (T.K.) and of the Swiss National

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Science Foundation Ambizione Energy grant No.160563 is also acknowledged

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(E.T.). The authors thank Koenraad Beckers, Falko Bethmann, Dimitrios Karvounis

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and Michael Stauffacher, as well as two anonymous reviewers for their constructive

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feedback.

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Supplemental material

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This supplemental material provides additional information regarding literature on

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downhole pumps, EGS surface cost, living and heating in Switzerland, well-drilling

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cost, and equations underlying the cost-benefit analysis from both private and social

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perspectives.

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Supplement A. Underlying equations for CBA

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This section presents equations underlying the CBA that are explained and

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referenced in the main manuscript of this study.

%,( = * ∗ ,- ∗ .,/ ∗ ( (&) − ) %$

%$4 = 9

1

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%,! = %( − %$3 %$4 ,- / = 6 8 *$ 7

|;% 0.1 ∗ %( |>?>.&@"."&A B?A

(1) (2) (3)

(4)

%!C = *!C ∗ ,- ∗ .,/ ∗ ( − )

(5)

D,! = %! ∗ >? ∗ ℎ, D!C,! = %!C ∗ &ℎ ∗ ℎ!C,

(7)

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(&) = (0) ∗ (1 − )!

D!C,

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D!C, = ! ∗

@> D!C ∗ @>E">& @>

0; >?>.&@"."&A B?A = F D!C, | D!C, < D!C,! D!C,! | D!C, > D!C,!

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∗

JKD =

∑!

%∗ ∝ = 6 8 %

.BE&(&) − @>MC! (&) (1 + ")! D (&) ∑! ! (1 + ")

(6)

(8) (9)

(10)

(11)

(12)

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@>M(&) + K/ EM(&) (1 + ")! O = .BE&E(&) + ,P>QR (&) ∑! (1 + ")! ∑!

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Supplement B. Literature on EGS downhole pumps

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Table S1 summarizes values, specifically price, lifetime, maximum flow rates, and

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pump efficiency from literature concerning downhole pumps.

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Table S1 Literature values for downhole pumps Lifetime 12 month 10 years

Value 125 160 0.5-0.75 0.5-0.65 0.5-0.85

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Maximum flow rate Maximum flow rate Downhole pump efficiency Downhole pump efficiency Downhole pump efficiency

Price [USD] 1’180’965 94’477 118’097 2’361- 8’857/m3/h Unit l/s l/s

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Ref. [108] [52] [52] [58] Ref [62] [61] [39] [52] [109]

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Description Electro submersile pump Line-shaft/ submersible pump Reinjection pump Downhole pump

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Supplement C. Literature on EGS surface cost

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Table S2 presents cost estimates from both past projects and literature for EGS

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surface plants.

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[USD/kWe] 2’361

Neustadt-Glewe, Germany Bruchsal, Germany St. Gallen, Switzerland Holzkirchen, Germany Literature estimates

4’499

1’181-4’724 4’200 1’771 2’361

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Ref. [110] [111] [110] [112] [51] [113]

[114] [14] [52] [110] Part I/14

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Plant [USD] 9’447’720 18’895’440 944’773 20’076’405 (heat only) 25’925’543 (heat only) 34’247’985

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Project Unterhachingen, Germany

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Table S2 Surface EGS surface plant cost Cpp

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Supplement D. Literature on externalities for CBA from social perspective

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Table S3 shows average values concerning heat consumption and living conditions

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of residents in Switzerland.

1121 Table S3 Input values heat demand Definition Heat consumption per living area Residents per household Households per building Living area per capita

Unit 2 kWhth/ m / yr cap/ househ. househ./ house 2 m

Ref. [77] [99] [100] [76]

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Supplement E. Well-drilling cost estimates from the literature Figure S1 displays cost estimates by reservoir depth for EGS wells from the

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Figure S1 Cost for well drilling from literature

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Highlights •

First analysis of EGS siting trade-off of induced seismicity (IS) and heat benefits

•

Cost-benefit analysis from private and social perspective of EGS size and siting Large EGS sited in urban areas are most profitable from investor’s

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perspective •

Medium EGS sited in smaller towns are most profitable from societal perspective

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Siting EGS in remote areas is unfavorable despite lack of expected IS

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damage

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•