Combined heat and power from hydrothermal geothermal resources in Germany: An assessment of the potential

Renewable and Sustainable Energy Reviews 120 (2020) 109661

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Combined heat and power from hydrothermal geothermal resources in Germany: An assessment of the potential S. Eyerer a ,∗, C. Schifflechner a , S. Hofbauer a,b , W. Bauer c , C. Wieland a , H. Spliethoff a,d a

Institute for Energy Systems, Faculty of Mechanical Engineering, Technical University of Munich (TUM), Boltzmannstraße 15, 85748 Garching, Germany United Nations Institute for Training and Research (UNITAR), Geneva Area, Switzerland GeoZentrum Nordbayern, Chair of Geology, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, Schlossgarten 5, 91054 Erlangen, Germany d The Bavarian Center for Applied Energy Research (ZAE Bayern), Division 1, Technology for Energy Systems and Renewable Energy, Walter-Meissner-Straße, 85748 Garching, Germany b c

ARTICLE

INFO

Keywords: Geothermal energy Combined heat and power generation Binary power plants Technical potential Economic potential Levelized costs of electricity

ABSTRACT This study investigates the potential of hydrothermal geothermal energy for combined heat and power (CHP) generation in Germany. Based on the theoretical potential of hydrothermal heat in place, the technical and economic potential is determined with a review and an analysis of existing geothermal plants. To this end, the thermodynamic and economic performance of operating power plants is analyzed and models for the efficiency and the production costs are developed. Based on this analysis, a technical potential of 12.2 PWh el and 16.7 PWh th as well as an economic potential of 9.1 PWhel and 12.5 PWhth is determined. In order to derive an annual contribution from the economic potential, the regeneration of the resource is taken into account. Considering a sustainable exploitation rate, an annual economic potential of 9.1 TWhel /a and 12.5 TWhth /a is derived. This corresponds to a share of 1.51% of the gross electricity demand and a share of 1.48% of the demand for space heating and domestic hot water. This analysis provides a profound review about the existing geothermal power plants and their thermodynamic and economic performance. Furthermore, the assessment of the geothermal potential in Germany is necessary for political decision making, particular with a view towards future adjustments of the feed-in tariffs defined by the Renewable Energy Act.

1. Introduction The initial operation of the first German geothermal power plant in Neustadt-Glewe, with an installed power of 0.23 MWel , in the year 2003, moved power generation via the exploitation of hot water aquifers from an hypothetical idea to reality. It took four more years before the next power plant, with a capacity of 3 MWel , was installed in Landau in 2007. In the following years further plants were commissioned proving the fact that power generation from low-enthalpy reservoirs via binary power plant concepts, such as the Organic Rankine Cycle [1] or Kalina Cycle [2,3], is feasible in Germany [4]. However, the question still remains whether geothermal energy will develop into a significant factor on the German energy market. This question is particularly relevant due to the enormous technical potential as estimated by several studies. Kayser and Kaltschmitt [5] evaluate the technical potential of hydrothermal resources in Germany for heat production. Paschen et al. [6] investigate the technical potential of geothermal energy in Germany for power production. Their work concludes the technical potential of geothermal power production in Germany to be around 321 PWhel . This

would correspond to an amount 600 times higher than the current annual German electricity demand. 95% of this potential is provided by petrothermal resources, 4% by fault zones and only 1% by hydrothermal resources. While Paschen et al. [6] remains unclear about the attribution of the fault zones, Agemar et al. [7] declare that fault zones are allocable to hydrothermal resources. Thus, the potential of the hydrothermal resources would amount to 14.2 PWh, which is 50 times greater than the current annual German electricity demand. Agemar et al. [7] provide an updated estimate of the potential of fault zones. By using a new fault map and a new 3D temperature model, they obtain a 31% greater amount of heat in place in comparison to the original work of Paschen et al. [6]. The publications of Chamorro et al. [8] and Jain et al. [9] provide an updated analysis of the potential of enhanced geothermal systems (EGS) in Germany. Chamorro et al. [8] estimates a total electrical energy potential of 179 PWhel , whereas the study of Jain et al. [9] obtains a 38% lower number (129 PWhel ). Both results are significantly lower than the total EGS potential of 305 PWhel as estimated by Paschen et al. [6]. The

∗ Corresponding author. E-mail address: [email protected] (S. Eyerer).

https://doi.org/10.1016/j.rser.2019.109661 Received 23 April 2019; Received in revised form 6 December 2019; Accepted 9 December 2019 Available online 16 December 2019 1364-0321/© 2019 Elsevier Ltd. All rights reserved.

Renewable and Sustainable Energy Reviews 120 (2020) 109661

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Nomenclature

𝑜𝑝𝑟 𝑜𝑡 𝑃𝑃 𝑝𝑟𝑜𝑐𝑒𝑠𝑠 𝑟𝑒𝑓 𝑟𝑒𝑔 𝑠𝑢𝑚 𝑠𝑢𝑠𝑡 𝑠𝑦𝑠 𝑡𝑒𝑐ℎ 𝑡ℎ 𝑡ℎ𝑒𝑜 𝑡ℎ𝑖𝑐𝑘 𝑇𝑊 𝑢𝑡𝑖 𝑉 𝐷𝐷 𝑊𝐻

Latin symbols 𝐴 𝐴𝐹 𝐶 𝐷 𝐸 ℎ 𝑖 𝑄 𝑄̇ 𝑅 𝑅2 𝑡 𝑇 𝑧

annuity [e] annuity factor[-] cost [e] distance [m] potential [TWh] enthalpy [J/kg] interest rate [%] amount of heat [TWh] heat transfer rate [kW] extraction factor [-] coefficient of determination [-] time [a] temperature [ ◦ C ] drilling length [m]

operational related other power plant process reference regeneration sum sustainable system technical thermal theoretical thickness thermal water utilization vertical drilling depth wellhead

Greek symbols 𝜂

efficiency [-]

potential in Germany shows that only a small number of new reports was published to update the results. In addition, none of the existing studies considers the operational experience gathered from the first geothermal power plants in Germany. In addition to its tremendously high technical potential, geothermal power generation provides several additional technological advantages due to its base load capacity as well as also innovative operation strategies for an increased flexibility are developed [11–13]. Furthermore, geothermal plants are beneficial for the combined production of heat and power [14–16]. Moreover, Frick et al. [17] and Heberle et al. [18] determined an environmental impact over the entire system lifetime between 45 - 50 gCO2-equ /kWhel and 15 - 130 gCO2-equ /kWhel , respectively. The lower values in these ranges are reachable if fluids with a low global warming potential (GWP) are used as working fluids for the power plant, such as for example R1233zd-E or R1224yd-Z instead of the common R245fa [19,20]. For those working fluids, the geothermal power production is competitive with the CO2 equivalents of other renewable energy sources such as wind (3 - 41 gCO2-equ /kWhel ) and solar (13 - 190 gCO2-equ /kWhel ) energy [21]. A multitude of further relevant parameters with regard to the assessment of the social and environmental impact of geothermal energy are discussed in detail by Shortall et al. [22]. The geothermal power production was and still is strongly supported by the government through the Renewable Energy Sources Act (EEG), which currently guarantees a fixed feed-in tariff of 25.2 ct/kWh for 20 years for new geothermal plants [23,24]. However, the increase in plant capacity was only 20 MWel between 2010 and 2015 [25]. As a result, in 2017 only ten geothermal power plants are operating and two plants are currently under construction [26]. The plants have an installed gross capacity of 41.2 MWel (cf. Table 1) and produced 0.16 TWh of electricity in 2017 [27], which corresponds to 0.03% of the German gross electricity demand for the same year. These numbers show the low relevance of geothermal power production for the German renewable energy sector, considering that in 2017 36.2% of the gross electricity demand was produced by renewable sources [27]. However, the advantages of a local resource as well as weather-independent and decentralized generation makes geothermal energy promising especially for combined heat and power (CHP) production. The important role of CHP can also be seen by the fact that currently seven geothermal plants are designed for CHP operation. The installed thermal capacity of these seven projects is 142.5 MWth (cf. Table 1). This fact reveals that current geothermal power generation in Germany is strongly connected with simultaneous heat supply. Therefore, the geothermal potential for power generation, evaluated in this study, will be accompanied by an additional result for heat supply.

Acronyms CHP DHS EGS ESP ICE LCOE NGB PV SMB UNFC URG

combined heat and power district heating system enhanced geothermal system electrical submersible pump Internal combustion engine levelized costs of electricity North German Basin Photovoltaic South German Molasse Basin United Nations Framework Classification Upper Rhine Graben

Subscripts 𝐴𝐷𝐿 𝑎𝑟𝑒𝑎 𝑎𝑢𝑥 𝑐𝑎𝑟 𝑐𝑜𝑟 𝑑𝑟𝑖𝑙𝑙𝑖𝑛𝑔 𝑒𝑐 𝑒𝑙 𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑒 𝑒𝑞𝑢 𝑒𝑥𝑝 𝑔𝑒𝑜 𝑔𝑟𝑜𝑠𝑠 𝑖𝑛𝑗 𝑙𝑓 𝑚𝑎𝑥 𝑛𝑒𝑡

actual drilling length area auxiliary demand capital related consumption related drilling economical electrical employee equivalent exploitation geological gross injection project lifetime maximal net

difference can mainly be explained by the updated geological data and the assumptions regarding power plant efficiencies, as well as the taking into consideration of areas such as nature reserves. Although EGS would be possible in these areas, it is not likely due to the legal situation. The summary of the existing literature about the geothermal 2

Renewable and Sustainable Energy Reviews 120 (2020) 109661

S. Eyerer et al. Table 1 Plant characteristic of geothermal projects with power generation in Germany [10]. Plantd Initial 𝑃𝑒𝑙,𝑔𝑟𝑜𝑠𝑠 𝑄̇ 𝑡ℎ Type Region Depth Depth operation [MWel ] [MWth ] Well 1 [m] Well 2 [m] LD BS UH IH DH KS SL LZ TR TK Ø 𝛴

2007 2009 2009 2012 2012 2013 2013 2014 2016 2017

3.0 0.6 3.4a 4.8 5.5 5.5 5.0 4.3 4.1 4.3

5 1.2 38 – – – 4 40 12 40

4.1 40.5

20.0c 140.2

ORC ORC KC ORC ORC ORC ORC ORC ORC KC

URG URG SMB URG SMB SMB SMB SMB SMB SMB

3300 1877 3350 3800 3926 3882 4757 4083 5067 3763

3170 2542 3590 3700 4114 3794 5060b 4453 5412 4258

3910

𝑇𝑊 𝐻 [◦ C]

𝑇𝑖𝑛𝑗 [◦ C]

𝛥𝑇 [◦ C]

Gradient [K/km]

Flow rate [l/s]

160 124 122 165 138 135 140 128 118 136

50 60 60 70 45 45 45 50 55 70

110 64 62 95 93 90 95 78 63 66

44 63 32 39 32 32 26 29 20 32

70 23 150 80 130 135 110 140 165 120

136.6

55.0

81.6

34.9

112.3

LD: Landau, BS: Bruchsal, UH: Unterhaching, IH: Insheim, DH: Dürrnhaar, KS: Kirchstockach, SL: Sauerlach, LZ: Laufzorn, TR: Traunreut, TK: Taufkirchen a The Kalina Cycle was shutdown in 2018 due to major technicals problems. b The depth of the third well is 5567 m. c Average value of the seven plants with heat generation. d

The power plant in Neustadt-Glewe is not listed, since the power plant was shut down in 2010 due to major technical problems.

2. Methodology

This discrepancy between high technical potential as well as high feed-in tariffs on the one hand and the low number of existing projects on the other hand creates a strong interest in an updated technical and especially economic potential of geothermal energy for combined heat and power production in Germany. While the exploitation of petrothermal reservoirs by enhanced geothermal systems is still under a research state [28], the experience with hydrothermal plants allows a re-evaluation of the technical potential of the hydrothermal reservoirs by considering for the first time thermodynamic performance data of existing plants in Germany. Furthermore, the commissioning of the first plants also allow for an overall economic evaluation based on real experience. Thus, a realistic evaluation of the current economic potential of the hydrothermal resources can be made. In short, the aim of this study is to review the thermodynamic and economic performance of the existing plants and thus, to re-evaluate the technical and economic potential of combined heat and power generated from hydrothermal geothermal energy. This study therefore intends to deliver a scientific and independent view of the potential and thus contribute to the opinion-forming on the electricity and heat generation from hydrothermal geothermal energy.

In this section, the methodology of the analysis is presented. First, the applied terms are defined. Then the calculation procedure for the technical and economic potential is introduced. The economic potential of hydrothermal geothermal heat and power generation in Germany is determined in three steps: 1. Evaluation of the theoretical potential 2. Evaluation of the technical potential 3. Evaluation of the economic potential First, the theoretical potential of the hydrothermal amount of heat is determined based on the available amount of heat per temperature class in the hydrothermal resources and a geological utilization factor. Second, this study analyzes the technical potential by considering the results of the analysis of the existing power plants’ thermodynamic performance. Finally, these results are combined with the findings obtained after conducting an economic evaluation of the operating plants in order to determine the current economic potential. The steps are summarized in Fig. 1. 2.1. Definition of the potential terms

In order to meet the above purpose, the methodology of this potential analysis is presented in Section 2. Based on this methodology, the input data used for the evaluation are introduced in the third section. The results are then presented and discussed in Section 4. Finally, conclusions are drawn and the policy implications of the results are discussed in Section 5.

There is a wide range of possible classification categories for the potential evaluation of geothermal resources [29,30]. The classic approach is to classify geothermal potential into resources and reserves [31]. This approach is quite common for evaluating energy sources such as oil or gas. However, the classification into the terms resource and reserve is only partly applicable to geothermal energy [32]. The 2009

Fig. 1. Graphical description of the single steps for the potential evaluation. 3

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For the evaluation of the technical potential of the technology, it is relevant to analyze the amount of electricity can be produced from a given production well. Therefore, the electric net system efficiency 𝜂𝑒𝑙,𝑠𝑦𝑠,𝑛𝑒𝑡 is defined as the ratio of the electrical net power to the maximal available enthalpy flow rate between the wellhead and the reference temperature of 10 ◦ C:

United Nations Framework Classification (UNFC) on fossil energy and mineral reserves and resources is an universally accepted evaluation scheme for categorizing fossil energies and minerals, which is currently also adapted for the classification of geothermal resources [33]. However, the framework is currently mainly applied to single geothermal projects or smaller regions, and some enhanced guidelines for precisely executing the various steps need to be developed [30]. Another approach is the classification of geothermal resources by enthalpy and exergy. However, this approach is neglecting the technical and economical perspectives and provides therefore only limited insights [34]. Rybach [35] describes five potential definitions for classifying geothermal resources. The theoretical potential describes the heat in place within the geothermal resources and is only defined by physical limits of use. The technical potential summarizes the amount of the theoretical potential, which is exploitable under the consideration of the currently available technology. The economic potential is the fraction of the technical potential that is economically exploitable under current market conditions. Furthermore, the sustainable potential considers that only a certain amount of the available potential can be utilized at once if the geothermal technology should still be sustainable. Finally, the so-called developed potential evaluates the fraction of the economic potential that can be developed when considering legal, environmental and social restrictions. This work mainly focuses on the classifications analogous to Rybach [35]. The study will calculate the technical, economic and sustainable potential for hydrothermal resources in Germany. To analyze the technical potential, a distinction is made between the technical potential of the hydrothermal amount of heat and the technical potential of the electricity generation. This means that the technical potential of the hydrothermal amount of heat is the share of the theoretical potential, which is utilizable with the current state of the art. Based on this, the technical potential of the electricity generation is the amount of electricity that can be generated by this amount of heat. The economic potential in this study refers to the current market situation by including the current subsidies provided by the guaranteed feed-in tariff.

𝜂𝑒𝑙,𝑠𝑦𝑠,𝑛𝑒𝑡 =

𝜂𝑒𝑙,𝑠𝑦𝑠,𝑔𝑟𝑜𝑠𝑠 =

𝑃𝑒𝑙,𝑔𝑟𝑜𝑠𝑠 𝑃𝑒𝑙,𝑔𝑟𝑜𝑠𝑠 = . 𝑚̇ 𝑇 𝑊 ⋅ (ℎ𝑊 𝐻 − ℎ𝑟𝑒𝑓 ) 𝑄̇ 𝑚𝑎𝑥

(4)

This definition of the system efficiency should not be confused with the process efficiency, defined as ratio of the power output and the thermal input to the power plant. The net and gross process efficiency is calculated for providing an additional insight about the performance characteristic of the power plants. These efficiencies only consider the actual heat flow, which is transferred towards the working fluid of the power plant, computed with the enthalpy difference between the state at the well head ℎ𝑊 𝐻 and after the power plant ℎ𝑃 𝑃 ,𝑜𝑢𝑡 . The respective brine temperatures after the power plant are summarized in Appendix.

𝜂𝑒𝑙,𝑝𝑟𝑜𝑐𝑒𝑠𝑠,𝑛𝑒𝑡 = 𝜂𝑒𝑙,𝑝𝑟𝑜𝑐𝑒𝑠𝑠,𝑔𝑟𝑜𝑠𝑠

𝑃𝑒𝑙,𝑔𝑟𝑜𝑠𝑠 − 𝑃𝑎𝑢𝑥,𝑃 𝑃 𝑃𝑒𝑙,𝑛𝑒𝑡 = ̇ 𝑚 ̇ 𝑄𝑃 𝑃 𝑃 𝑃 ⋅ (ℎ𝑊 𝐻 − ℎ𝑃 𝑃 ,𝑜𝑢𝑡 ) 𝑃𝑒𝑙,𝑔𝑟𝑜𝑠𝑠 𝑃𝑒𝑙,𝑔𝑟𝑜𝑠𝑠 = = ̇ 𝑚 ̇ ⋅ (ℎ 𝑄𝑃 𝑃 𝑃𝑃 𝑊 𝐻 − ℎ𝑃 𝑃 ,𝑜𝑢𝑡 )

(5) (6)

Due to the definition from Eq. (3), both the net system efficiency 𝜂𝑒𝑙,𝑠𝑦𝑠,𝑛𝑒𝑡 and the theoretical potential 𝑄𝑡ℎ𝑒𝑜 are referred to the same reference temperature of 10 ◦ C. Thus, no further temperature correction are necessary in Eq. (2) to derive the technical potential for power generation. The relevance of the net and gross efficiencies depends mainly on the point of view. For estimating the potential of a technology within a country, the achievable net amount is relevant, since from an overall energy system perspective it is only interesting how much additional power can be provided by the geothermal plants. In contrast, the plant operators in Germany are currently focusing on a maximal gross power, since the guaranteed feed-in tariff of 25.2 ct/kWh is higher than the costs for either buying the necessary electricity for the auxiliary power on the market for industrial enterprises or producing it by an additional small fossil-fired engine. Due to this, they provide the complete gross power towards the public grid for improving the economic performance of the project. As stated above, the net efficiencies are used for the technical potential, because this study wants to estimate the national economic impact of geothermal CHP. All results in this study are therefore net potentials, which will no longer be highlighted in the following.

The theoretical potential 𝑄𝑡ℎ𝑒𝑜 is defined as the heat which could theoretically be released if the geothermal resource were cooled down to the reference temperature of 15 ◦ C. Based on this theoretical potential, the technical potential of the hydrothermal amount of heat 𝑄𝑡𝑒𝑐ℎ is calculated by considering the maximum possible geological extraction factor 𝑅𝑔𝑒𝑜 [6]: (1)

𝑄𝑡𝑒𝑐ℎ describes the amount of heat that can be extracted from the reservoir by means of today’s available technology. The extraction factor 𝑅𝑔𝑒𝑜 represents the ratio between the utilizable amount of heat and the heat in place. In accordance with Paschen et al. [6], this value is 0.33 for the hot water aquifers and 0.072 for the fault zones. The technical potential for power generation 𝐸𝑒𝑙,𝑡𝑒𝑐ℎ is then derived by the determined technical potential of utilizable amount of heat 𝑄𝑡𝑒𝑐ℎ for each temperature step and a function of the electric net system efficiency 𝜂𝑒𝑙,𝑠𝑦𝑠,𝑛𝑒𝑡 , which is a function depending on the wellhead temperature 𝑇𝑊 𝐻 and is modeled based on the power plant’s performance (cf. Section 3.3). While the study of Paschen et al. [6] divided the geothermal reservoirs based on their temperature in three categories and assumed a constant efficiency of each of the three classes, this work uses a model function for the net system efficiency, which allows a determination of the technical potential for power generation in a continuous function. 𝐸𝑒𝑙,𝑡𝑒𝑐ℎ = 𝑄𝑡𝑒𝑐ℎ (𝑇𝑊 𝐻 ) ⋅ 𝜂𝑒𝑙,𝑠𝑦𝑠,𝑛𝑒𝑡 (𝑇𝑊 𝐻 )

(3)

The respective electric gross system efficiency 𝜂𝑒𝑙,𝑠𝑦𝑠,𝑔𝑟𝑜𝑠𝑠 is defined analogously using the gross power output:

2.2. Calculation method for the technical potential

𝑄𝑡𝑒𝑐ℎ = 𝑄𝑡ℎ𝑒𝑜 ⋅ 𝑅𝑔𝑒𝑜 .

𝑃𝑒𝑙,𝑔𝑟𝑜𝑠𝑠 − 𝑃𝑇 𝑊 ,𝑝𝑢𝑚𝑝 − 𝑃𝑎𝑢𝑥 𝑃𝑒𝑙,𝑛𝑒𝑡 = . 𝑚̇ 𝑇 𝑊 ⋅ (ℎ𝑊 𝐻 − ℎ𝑟𝑒𝑓 ) 𝑄̇ 𝑚𝑎𝑥

2.3. Calculation method for the economic potential The economic evaluations of the existing power plants are carried out by a model that is based on the VDI Guideline 2067/1 [36], as well as the methodology described in the work of Schlagermann [37]. The main parameter for evaluating the economic performance are the Levelized Costs of Electricity (LCOE). The LCOE are the ratio between the overall annuity 𝐴𝑠𝑢𝑚,𝑡 of the project and the produced amount of electricity 𝑃𝑒𝑙,𝑡 over the project lifetime 𝑡𝑙𝑓 . The LCOEs represent the required electricity revenue price during the lifetime of the power plant to reach break even over the lifetime [38]: ∑𝑡𝑙𝑓 𝐴 𝑡=1 𝑠𝑢𝑚,𝑡 𝐿𝐶𝑂𝐸 = ∑ . (7) ∑𝑡𝑙𝑓 𝑡=20 𝑃 𝑡=1 𝑃𝑒𝑙,𝑔𝑟𝑜𝑠𝑠,𝑡 + 𝑡=21 𝑒𝑙,𝑛𝑒𝑡,𝑡

(2) 4

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20 years of guaranteed feed-in tariff, it is expected that the auxiliary demand of the power plant will be provided by the geothermal power plant, since the expected revenues for the electricity are lower than the costs for the generated electricity by the ICE. Thus, after the first 20 years of operation, the annual annuity of the consumption-related costs (cf. Eq. (8)) will decrease significantly. Further costs, such as the refilling of the working fluid or inhibitors, are assumed as 0.5% of the capital-related costs 𝐶𝑐𝑟 [37]. The operation-related costs describe the expenses for the employees and the maintenance service. The costs for the manpower are calculated by an equation by Schlagermann [37]:

The overall annuity consists of four single annuity components, representing the capital-related (car), consumption-related (cor), operation-related (opr) and other (ot) costs [36]: 𝐴𝑠𝑢𝑚 = 𝐴𝑐𝑎𝑟 + 𝐴𝑐𝑜𝑟 + 𝐴𝑜𝑝𝑟 + 𝐴𝑜𝑡 .

(8)

The annuity for the capital related costs 𝐴𝑐𝑎𝑟 is determined based on the capital related costs 𝐶𝑐𝑎𝑟 , which mainly represent the investment costs, and the annuity factor 𝐴𝐹 : 𝐴𝑐𝑎𝑟 = 𝐶𝑐𝑎𝑟 ⋅ 𝐴𝐹 .

(9)

𝑡𝑙𝑓

𝐴𝐹 =

(1 + 𝑖) ⋅ 𝑖 . (1 + 𝑖)𝑡𝑙𝑓 − 1

(10)

𝐶𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑒 = 220000 ⋅ 𝑒(5⋅10

Very little literature on the interest rate 𝑖 of German geothermal projects is available. However, due to the fact, that geothermal projects are often considered as high-risk investments, interest rates are typically in the range of 6 − 10% [39]. The report by Weimann [40] investigated the costs for the first geothermal projects in Germany and reports an average interest rate of 9.3%. For comparison, Zhang et al. [41] used an interest rate of 8% for hydrothermal geothermal projects in China. Knoblauch and Trutnevyte [42] assume a discount rate of 10% for EGS projects. They comment, that this discount rate is quite high, but appropriate due to the high risk of EGS projects. Clauser and Ewert [43] use a discount rate of 13% for estimating the LCOEs of geothermal power generation. The authors apply this discount rate for different types of geothermal technologies (steam reservoirs, hot water reservoirs and EGS) without further justification of the value’s origin. Generally, the interest rate, especially for capital-intensive geothermal projects, is understood as the weighted average interest rate, which combines the cost of debt and the cost of equity. Typically, the cost of equity is significantly higher than the cost of debt [39]. Thus, the actual interest rate of a specific project depends on the actual capital structure. Based on a discussion with several experts from industry and from the German geothermal sector, an interest rate of 8.25% is chosen in this study. In comparison to Weimann [40], this takes the increasing number of completed projects in Germany during the last years as well as the trend of decreasing cost for debt [39] into account. However, this value for the interest rate is still associated with some uncertainty. Therefore, the influence of the interest rate is investigated in the sensitivity analysis (cf. Section 4.3). Furthermore, the selection of the project lifetime cannot be based on real experiences because of the young age of the plants in Germany. The entitlement for exploiting a geothermal claim in Germany is given for 50 years by authorities [30]. In addition, it is realistic to assume that the wells have a lifetime of at least 50 years. However, since the normal lifetime of a power plant is mostly between 20 and 30 years, and assumptions about the performance and investment costs of a potential re-investment after the lifetime of the first power plant are associated with high uncertainty, the economic performance of the projects is evaluated for the lifetime of the originally installed plant, which is assumed to be 25 years. However, due to the described uncertainty, the influence of both parameter is discussed in detail during the sensitivity analysis (cf. Section 4.3). The consumption-related costs consist mainly of the costs for the provision of the required auxiliary power. It is assumed that the auxiliary power is provided by an additional small gas-fired internal combustion engine (ICE), which is operated in CHP. This is, for example, the case at the projects in Unterhaching or Traunreut. The costs for the provided electricity by a small gas-fired ICE are calculated based on the information for the current installation costs as well as gas price [44]. As a result, an electrical price of 8.5 ct/kWhel is obtained. The revenue of the heat produced by this small ICE has not been considered in this calculation. Thus, the obtained electricity price serves as a conservative result. The production of the auxiliary power by an ICE is a specific cause due to the legal configuration of the guaranteed feed-in tariff, which is paid for the gross electricity. Thus, after the

−6 ⋅𝑄̇ 𝑇𝑊

[𝑘𝑊 ])

(11)

.

For remote monitoring of the plant as well as the necessary on-call service, additional costs of 25% of the 𝐶𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑒 are considered [37]. In addition, costs of 60,000 e/a are incurred for the seismic monitoring of a plant [45]. For the maintenance of the well, as well as the aboveground facility, annual costs of 0.46% of the capital-related costs 𝐶𝑐𝑟 are assumed [37]. The other costs and revenues contain the expenses for further costs such as insurances and the obtained revenues for CHP projects by selling the heat. The expenses for the electricity and machinery breakdown insurance is assumed with 0.26% of the capital-related costs 𝐶𝑐𝑟 [37]. Furthermore, the costs for the liability insurance are considered with 90,000 e/a [37]. Analogous to the studies of Hirschberg et al. [46] and Weimann [40], it is assumed that the revenues from the sale of heat will be used to repay the annual payments. They are thus ‘‘negative costs’’. In order to adapt the drilling costs of a project to other regions with a different geothermal gradient, the hypothetical drilling costs 𝐶𝑑𝑟𝑖𝑙𝑙𝑖𝑛𝑔 are estimated by the drilling cost model presented in Schlagermann [37], which describes an exponential correlation between 𝐶𝑑𝑟𝑖𝑙𝑙𝑖𝑛𝑔 and the vertical drilling depth 𝑧𝑉 𝐷𝐷 : 𝐶𝑑𝑟𝑖𝑙𝑙𝑖𝑛𝑔 = 1.190 ⋅ 𝑒(0.0004354⋅𝑧𝑉 𝐷𝐷 ) ⋅ 106 .

(12)

However, since the geothermal boreholes are deflected, the following equation is applied to describe the relation between the actual drilling length 𝑧𝐴𝐷𝐿 and vertical drilling depth 𝑧𝑉 𝐷𝐷 , based on the distance between the end of the boreholes 𝐷 [37]: √ (13) 𝑧𝐴𝐷𝐿 = 1.1 ⋅ 𝑧2𝑉 𝐷𝐷 + 𝐷. The cost model in Eq. (12) refers to the year 2011. To estimate the drilling costs in the actual year of drilling, the ‘‘Geothermal drilling index’’ by the European Geothermal Energy Council (EGEC) is applied [47]. Furthermore, a revenue of 7.1 ct/kWhel is expected for the time after the guaranteed feed-in tariff ends (after 20 years). This value was obtained as a mean result of a metastudy, which investigated multiple prediction for the electricity revenues after 2030 [48]. For calculating the annual power and heat production of the projects, the full load hours which are expected by the plant operators are assumed. On average this results in 7474 h/a electrical and 2049 h/a thermal full load hours for the seven CHP projects. In summary, all main parameters for the economic model are summarized in Table 2.

Table 2 Model parameter for the economic evaluation.

5

Parameter

Value

Interest rate Project lifetime Electrical full load hours Thermal full load hours Revenue for electricity for the first 20 years Revenue for electricity after the first 20 years Heat selling price Costs for providing the electricity for the auxiliary power

8.25% 25 a 7474 h/a 2049 h/a 25.2 ct/kWhel 7.1 ct/kWhel 3 ct/kWhth 8.5 ct/kWhel

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high salinity (200 - 300 g/kg) of geothermal fluids. Reservoir quality changes laterally due to facies changes and halotectonics [51,52]. Geothermal gradients were found between 33 - 37 K/km. The URG is a graben structure with Cenozoic sediments of up to 3,5 km [53]. Main geothermal reservoirs are fractured sandstones of Mesozoic and Paleozoic age below the graben fill and granites in the Variscan basement. Geothermal fluids have a high salinity (80 - 130 g/kg). The Tertiary graben fill consists predominantly of clayey sediments which have a blanketing effect. Their low heat conductivity causes local geothermal anomalies with gradients of up to 100 K/km. Within the geothermal reservoirs, the gradients are much lower; between 10 - 30 K/km. The SMB is the foreland basin of the Alpine orogeny. The main geothermal reservoir is the 400 - 600 m thick Upper Jurassic carbonate sequence that crops out North of the Danube river and dips to the South below the Alpine front to depth of more than 5000 m. Permeability of the carbonates is mainly controlled by carstification and fractures while dolomitic rocks show some matrix porosity. Geothermal gradients reach 30 - 35 K/km. Geothermal fluids show very low salinities, between 1 2 g/kg [52]. The data on the available ‘‘amount of heat’’ stored in the hydrothermal reservoirs in the URG and the NGB is taken from Paschen et al. [6]. For the fault zones, the results from Agemar et al. [7] are considered, as this work provides updated numbers based on the methodology provided by Paschen et al. [6]. For the SMB, most recent data provided by the Bavarian Environment Agency [54] are applied. These data were obtained from the GeoMol project [55]. The thermal gradients of the four classes are taken from Bauer et al. [49] and Agemar et al. [50]. In summary, the amount of heat in place (corresponding to the theoretical potential) for each region and temperature class are listed in Table 3. Fig. 2. Geothermal attractive provinces in Germany.

3.2. Data of the existing power plants 3. Data To have a profound basis for the work, a detailed review on all available data of the existing geothermal power plants was carried out. As far as possible, scientific literature or direct publications by the operator were considered, however for crucial information, e.g. the exact investment costs, non-scientific sources such as newspaper articles were used, since the operators keep this information unpublished due to economic reasons. For mitigating this issue, the results of the literature review were sent to all plant operators to verify the information collected. Feedback has been received from eight of the ten operators. Thus, it was either confirmed that the collected data is within a realistic range or corrected information were provided. Landau and Insheim are the only plants for which no operator feedback was received. Table 1 presents the main information of the geothermal power plants in Germany. The broad amount of additional information is summarized in Appendix.

In this section, the input data for the potential study are presented. At first, the geological data for the heat in place are analyzed. Then, the technical and economic data of the operating geothermal plants are discussed. Based on this, models for the thermodynamic and economic performance of the plants are derived. 3.1. Geological data There are three areas with hydrothermal resources for geothermal power generation in Germany, which are depicted in Fig. 2: The Upper Rhine Graben (URG), the North German Basin (NGB) and the South German Molasse Basin (SMB). The NGB is a sub-basin of the Southern Permian Basin. It contains Permian to Cenozoic sediments, with a thickness of up to 12 km. Geothermal reservoirs have been identified in sandstones of Paleozoic and mainly Mesozoic age and in Permian volcanites. The Mesozoic sandstone reservoirs are porous reservoirs with porosities of 20 - 30% and permeabilities of 500 mD and more [51]. Thick Permian salt deposits cause halotectonics and are the cause for

Table 4 Thermal efficiencies of the existing geothermal power plants in Germany.

Table 3 Theoretical potential and geothermal gradient of the hydrothermal resources in Germany [6,7,49,50]. Temperature classes

Theoretical potential [PWhth ] SMB

100–130 ◦ C 130–160 ◦ C 160–190 ◦ C

NGB

URG

117.70 25.56 7.53 555.56 71.60 65.56 13.25 722.22 – 4.72 6.72 861.11

Geothermal gradient [K/km] 32

35

43

Sum per class

Fault zones

32

706.34 872.63 872.56 -

6

Plant

Gross process efficiency

Net process efficiency

Gross system efficiency

Net system efficiency

LD BS UH IH DH KS SL OH TK TR

12.4% 7.5% 13.9% 16.5% 11.6% 11.6% 13.8% 10.7% 16.6% 15.3%

11.4% 6.0% 10.8% 15.1% 9.9% 10.5% 11.9% 8.9% 13.9% 13.1%

7.5% 4.2% 5.0% 10.2% 8.5% 8.3% 9.0% 6.6% 7.3% 5.8%

5.2% 2.4% 1.9% 7.6% 4.8% 5.8% 5.2% 3.6% 4.2% 3.0%

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Fig. 3. Net system efficiency of the existing plants and the model function.

Fig. 4. Levelized cost of electricity of the existing plants and the model function.

3.3. Thermodynamic performance of the reference plants

capacity (cf. Table 1) and the respective full load hours of Table 2. With this, the power-to-heat ratio of the investigated CHP projects is 1.37. This means that for each produced kWhel within a year, on average 1.37 kWhth are provided for district heating, based on the assumption that the future plants will exhibit the same average characteristic as the current CHP projects.

The derived efficiencies of the existing power plants are listed in Table 4. Experience shows that the plant efficiency is significantly influenced by the actual ambient temperature, due to its high impact on the condensation conditions within the plant. Therefore, the efficiency of a geothermal power plant varies widely over a year [56]. However, for the consideration of longer periods, the average plant power is sufficient. As the design points of the plants were calculated for ambient conditions, which are close to the average annual temperatures, the application of the design plant power is reasonable, as it represents the approximated annual mean plant power. In Table 4, it can be seen, that the process and system efficiency is quite low compared to conventional fossil fuel fired power plants. This is due to the low heat source temperature of geothermal plants and thus a significantly lower carnot efficiency and exergy content of the heat source. As a consequence, a high proportion of the heat transferred to the power plant as cooled against the environment. This heat however, is at temperatures only sightly above the ambient temperature and thus contains almost only anergy. When looking at and exergetic analysis, Kanoglu [57] concluded that only 23% of the brine exergy is lost in the condensers, although 60% if the brine energy is released to the environment in the condenser. This relationship is characteristic for low temperature heat utilization in general. Fig. 3 presents the results for the net system efficiency of the reference plants and the obtained model function. The basic form of the model function is chosen following the work of Zarrouk and Moon [58], which is based on the thermodynamic characteristics of the triangular process. As expected, the efficiency increases for higher wellhead temperatures. The coefficient of determination 𝑅2 of the model function is 0.76, which is slightly better than that for the overall model function for binary plants by Zarrouk and Moon [58] (0.67). 𝜂𝑒𝑙,𝑠𝑦𝑠,𝑛𝑒𝑡 (𝑇𝑊 𝐻 )[%] = 13.59 ⋅ 𝑙𝑛(𝑇𝑊 𝐻 [◦ C]) − 62.38

3.4. Economic performance of the reference plants Fig. 4 shows the derived LCOE as well as the model function for the reference plants. While for the calculation of the efficiency model all ten power plants were taken into account, the Bruchsal site was not considered for the LCOE model (gray data-point in Fig. 4). This plant is characterized as a ‘‘research plant’’ and thus the economic operation of the plant is not the main focus. The basic model reveals that the LCOE decrease with increasing thermal water temperature. The average LCOE of the nine considered projects are 23.5 ct/kWhel , which is slightly below the guaranteed feed-in tariff. Some of the LCOE show a large variance. For instance, based on the developed economic model, for the project in Sauerlach (𝑇𝑊 𝐻 of 140 ◦ C) LCOE of 30.3 ct/kWhel are derived, which are significantly higher than for the projects with slightly lower wellhead temperatures. This can be explained by major unexpected problems during drilling. For two of the

(14)

The equation of the net system efficiency takes the whole required auxiliary power of the geothermal plants into account. Therefore, the complete on-site power of the plant is considered in the calculation of the net efficiency. Thus, the model function already considers the additional effort for pumping the thermal water to supply the district heating network. This means that the technical potential for the electrical power generation based on Eq. (2) also contains a certain amount of heat for district heating supply as an additional product. The amount of heat for the district heating supply can be derived from the average power-to-heat ratio of the existing CHP plants This power-to-heat ratio can be computed by the ratio of the installed electrical and thermal

Fig. 5. Levelized cost of electricity as a function of wellhead temperature and the respective region. 7

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for wellhead temperatures above 165 ◦ C, the exponential increase of the drilling costs is implemented within the model. The resulting four different model functions are presented in Fig. 5. The LCOE basic model (cf. Eq. (15)) is included as a dashed line. The different model functions reveal that for low temperatures (and therefore low required drilling depths) there is no significant difference among the regions. However, the differences increase significantly for higher wellhead temperatures. 4. Results and discussion The results are presented in this section. Based on the derived technical and economic potential, the sensitivity of the input parameters will be analyzed. In a last step, the limitations of the developed models and results will be critically discussed. 4.1. Total technical and economic potential Based on the technical potential of the hydrothermal heat in place 𝑄𝑡𝑒𝑐ℎ and the model of the system efficiency, the technical potential for power generation in Germany can be calculated according to Eq. (2). The potential per 1 K temperature interval (dashed line), as well as the cumulated technical potential (solid line), are shown in Fig. 6. These first results show that the cumulated technical potential is 12,201 TWhel . Most of the technical potential lies between 130 ◦ C and 190 ◦ C, while reservoirs with a wellhead temperature between 100 ◦ C and 130 ◦ C contain only 16.5% of the whole technical potential. Based on the above described methodology, it should be noted, that the CHP operation of the current plants leads to additionally 16,715 TWhth as a technical potential for heat production. The above model for the LCOE is now combined with the technical potential per temperature step. Therefore, the best sites are assumed to be developed first, while more expensive sites will be developed subsequently. The best sites are those with the lowest LCOE, which result from a high wellhead temperature at a low drilling depth. With this, the geothermal gradient and the wellhead temperature are considered for the economic potential. With this approach, a supply-cost curve can be derived, showing the possible electricity generation for the corresponding LCOE (cf. Fig. 7). This type of curve can be read as follows: Starting with the best sites on the left side of the 𝑥-axis, only a small potential with low production costs can be accessed. Moving

Fig. 6. The technical potential for power generation as a function of the wellhead temperature.

three boreholes, additional sidetracks were necessary because parts of the initial borehole were unstable. This led to an increase of the planned drilling time and especially to a significant increase of 66 million Euros in project costs [59]. Thus, the presented LCOE contain already the risk of potential cost increases during the project realization and do not present only ideal cost assumptions. In summary, a base model function is derived for the LCOE as a function of the wellhead temperature. The model function was chosen from several investigated function types based on the highest coefficient of determination 𝑅2 = 0.49. 𝐿𝐶𝑂𝐸(𝑇𝑊 𝐻 )[𝑐𝑡∕𝑘𝑊 ℎ] = 334.6 ⋅ 𝑒𝑥𝑝(−0.01995 ⋅ 𝑇𝑊 𝐻 [◦ C])

(15)

In the next step, the basic model is applied to the geothermal gradients of each region and the exponential increase of the drilling cost. For this, all existing plants are analyzed for the hypothetical situation that they would be installed in a region with a different geothermal gradient. Furthermore, since there are no existing projects

Fig. 7. Supply-cost curve for the geothermal power generation in Germany. 8

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Table 5 The annual economic and sustainable potential.

on this curve to the right means that further, more expensive sites, are exploited. Thus, a higher potential can be reached, but at higher production costs. The highest value of the curve corresponds to the technical potential of 12,201 TWhel (cf. Fig. 6). Therefore, if the total technical potential should be exploited, the maximum LCOE will reach up to 45 ct/kWh. The economic potential strongly depends on the electricity price which will be paied for the geothermal electricity. In this study, a project lifetime of 25 years is considered (cf. Table 2). The feed-in tariff in Germany guarantees a revenue of 25.2 ct/kWh for the first 20 years. During the last 5 years of the project lifetime, it is assumed that the net electricity is sold at the stock market, with a mean price of 7.1 ct/kWh (cf. Table 2). This leads to a mean revenue of 22.7 ct/kWh over the entire lifetime of the project. With this, an economic potential 𝐸𝑒𝑐 of 9133 TWhel electricity and 12,512 TWhth heat production is derived. This means that, according to the model, 75% of the technical potential would be economical extractable based on the current guaranteed feedin tariff. The total potential (shown in Fig. 7) is the sum of the potential for the different provinces (cf. Table 3). Depending on the data quality for each province, the uncertainty range of the supply-cost curve might differ. While there are several existing geothermal power plants in the South German Basin and the Upper Rhine Graben, currently no power plants are in operation in the North German Basin. Therefore, the NGB might be seen as a region with a higher uncertainty concerning the actual costs for geothermal projects within this region. The region’s suitability for geothermal utilization can however be verified by several existing heating projects. One of this heating projects is also the former first geothermal power plant in Neustadt-Glewe, which produced initially also electricity. Due to technical problems, however, it has been operated as a pure heat project since 2010. The expected costs for power generation within this region are still based on adaptations from the models for the provinces with existing power plants. Thus, in reality the supply-cost curve for the NGB, with a current economic potential of 1110 TWhel and a maximal technical potential of 1420 TWhel , may be shifted a little further to the right due to the possible higher LCOEs. This might lead to a lower overall economic potential of the hydrothermal resources in Germany. A critical discussion about the model accuracy for the NDB is presented in Section 4.4.

Annual economic and sustainable potential for power production Share of the gross electricity demand Installed gross capacity Number of plants (with an average size of 4.1 MWel,gross ) Annual economic and sustainable potential for heat production Share of the heating demand for space heating and hot water

9.1 TWhel ∕𝑎 1.51% 1,878 MWel,gross 458 12.5 TWhth ∕𝑎 1.48%

regeneration is highest at the beginning and decreases over time. The initial temperature is only reached after 8000 years. In this study, a regeneration period of 𝑡𝑟𝑒𝑔 = 1000 years is assumed in accordance with Paschen et al. [6]. According to Wenderoth et al. [61], this results in a cooling of the reservoir of 8%. Under these conditions, the plant operation cannot be endless, but this period is long enough to consider geothermal as a regenerative resource. In order to ensure the utilization of the geothermal resources as a renewable energy source, the exploitation period 𝑡𝑒𝑥𝑝 must be higher than, or at least equal to, the regeneration period of the geothermal heat: 𝑡𝑒𝑥𝑝 ≤ 𝑡𝑟𝑒𝑔 . Nevertheless, a faster exploitation of the potential is possible. But then geothermal energy would become a finite, non-renewable resource. Assuming a regeneration period of 1000 years, the annual economic and sustainable potential 𝐸𝑒𝑐,𝑠𝑢𝑠𝑡 can be calculated: 𝐸𝑒𝑐,𝑠𝑢𝑠𝑡 =

𝐸𝑒𝑐 . 𝑡𝑢𝑡𝑖

(16)

With the total economic potential of 9133 TWhel , an annual economic and sustainable potential of 𝐸𝑒𝑐,𝑠𝑢𝑠𝑡 = 9.1 TWhel ∕𝑎 can be derived. This corresponds to an annual potential of 12.5 TWhth ∕𝑎 for heat production. In order to further detail this potential, factors such as the share of gross electricity demand or the number of installed plants are summarized in Table 5. The average German gross electricity demand in the years between 2011 and 2016 was 603 TWhel /a [62]. Therefore, the hydrothermal economic and sustainable potential could provide 1.51% of the current German gross electricity demand. An installed net capacity of 1221 MWel,net can be achieved, assuming the average full-load hours of 7474 h/a. Based on the average auxiliary share of 35%, an installed gross capacity of 1878 MWel,gross is necessary to achieve this net power. This installed capacity corresponds to 458 plants assuming an average gross capacity per plant of 4.1 MWel . The potential for heat production of 12.5 TWhth ∕𝑎 corresponds to 1.48% of the heating demand for space heating and domestic hot water, which was 843 TWhth /a in the year 2012 [63]. The assumption of a regeneration period of 1000 years can be verified by estimating the sustainable potential using a different approach. As stated above, the mean geothermal heat flux in Germany is 65 mW/m2 . Multiplying this value with the area of Germany, which is 357.600 km2 [64] and the mean net system efficiency of 4.4% (cf. Fig. 3), a net technical and sustainable potential for power production of 1023 MWel can be derived. The corresponding gross potential would be 1573 MWel . Comparing these values with the potential described above (cf. Table 5), it can be seen, that both approaches lead to the same order of magnitude in the respective potentials. Hence, the assumption of 1000 years regeneration period is valid for sustainable exploitation of the geothermal resource.

4.2. Annual technical and economic potential The above derived potential is the entire amount of electricity or heat which can be produced based on the stored heat within the geothermal resources. In order to derive the annual possible production with a sustainable utilization, the regeneration of the geothermal resource needs to be considered. The utilization of the geothermal heat incorporates a cooling down of the reservoir. If all of the heat is removed at once, the reservoir will cool down to such an extent that power production is no longer possible. In reality, the heat is used over a longer exploitation period 𝑡𝑒𝑥𝑝 . The length of this time period depends on the installed capacity and thus on the cost-effectiveness of the technology. The extraction of heat is counteracted by a certain regeneration due to the geothermal heat flux. The German average value is 65 mW/m2 [6,60]. If the heat is extracted with the same flux as it is regenerated, the operation of the plant can theoretically be endless. Due to the very low regenerative heat flux, however, this is not feasible. Wenderoth et al. [61] investigate the time needed to regenerate a reservoir that was cooled down to the injection temperature of 55 ◦ C , which is also the average reinjection temperature of the existing plants (cf. Table 1). These investigations consider a geothermal doublet with a depth of 2746 m or 3020 m in the South German Molasse Basin. The results show, that after 1000 years, 92% of the original temperature of the reservoir (here 97 ◦ C ) is reached and after 2000 years the reservoir temperature is 98% of the initial temperature. The rate of temperature

4.3. Sensitivity analysis In order to identify the most dominant impact factors on the economic potential (cf. Table 2), a detailed sensitivity analysis is carried out. For this purpose, each of the influencing factors is varied in steps of ±20%, while all other parameters remain constant. For the electrical full load hours and the net system efficiency, there is some deviation from this procedure. An increase of the electrical full load hours by more than 20% would lead to a higher number of hours than one year has. In the case of the net system efficiency, only an efficiency enhancement up to 30% has been considered with 5% increments. 9

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Fig. 8. Results of the sensitivity analysis for the economic potential.

The results for the whole economic potential are presented in Fig. 8. Here, the base case can be found for a sensitivity factor of 1. A very dominant influencing factor is the system efficiency. An increase in plant efficiency by 10% would lead to an increase in economic potential by 21%. Since the model function is based on existing plants from more than one decade, it can be expected that the achievable efficiency of currently planned projects might be higher due to technical improvements of the plant. Looking at the plants which are commissioned more recently (cf. Tables 1 and 4 as well as Fig. 3) an efficiency enhancement of 10% in comparison to the model function has already been proven. Concerning the other influencing factors, the electrical full load hours have a strong impact on the economic potential. A reduction of 20% in full load hours leads to a reduction of 21% in economic potential. This can especially be explained by the high feed-in tariff for the geothermal power and thus the significantly reduces revenue in case of lower full load hours. From a technical perspective it can therefore be concluded that the availability of power production needs to be as high as possible. However, this behavior should also be discussed against the background of an increasing share of volatile renewable power production from photovoltaic (PV) and wind. With this, the controllable and predictable production such as from conventional plants but also from biomass and geothermal, needs to provide the residual load with much higher fluctuations and lower capacity utilization. In the case of geothermal energy, however, the potential for power production is quite low at 1.51% of the gross electricity demand (cf. Table 5). Particularly due to the decentralized character of geothermal power generation, the plants can also be used very well for local grid stabilization due to their rotating mass. Furthermore, the most attractive and active regions in Germany are located in the south, where geothermal base load could even help to reduce the demand of grid extensions slightly. From this consideration, it can be concluded that the comparable small electrical capacity of 1922 MWel,gross (cf. Table 5) can always be operated with high full load hours. Another dominant impact factor is the project lifetime. It can be seen in Fig. 8 that a maximum can be found at a sensitivity factor of 0.8. This corresponds to a project lifetime of 20 years. The maximum can again be explained with the high feed-in tariff, which is guaranteed over the first 20 years of the project. Since the stock price is far lower than the feed-in tariff, the economic potential drops with higher lifetime. Another interesting finding is the comparably low influence of a reduction in specific investment cost. If the investment cost can be reduced by 20%, the economic potential will only increase by 16% and,

with further cost reduction, the potential increase gets smaller. This behavior can be explained with the already high economic potential in comparison to the technical potential (cf. Fig. 7). A similar trend can also be observed for the interest rate. A reduction of the interest rate by 20% only leads to an increase in economic potential of 11.3%. On this basis, it can be seen that the impact of the interest rate on economic potential is limited. Although this statement is true for this general view on the economic potential, the profitability of a certain project is of course significantly affected by the interest rate. Another prominent impact factor is the exploitation period, which is depicted in Fig. 9. Again, a variation of ±60% around the base case value of 1000 years has been made. If the requirement of the source being renewable is dropped, the exploitation period of the geothermal heat may also be shorter than the regeneration period. Considering for instance an exploitation period of 400 years, the annual economic potential will rise to 22.8 TWhel /a, which corresponds to 3.78% of the gross electricity consumption in Germany. In this case, the heat generated by CHP operation could cover 3.7% of the heat demand for space heating and hot water. With a 10% increased system efficiency (dashed line in Fig. 9), even a 4.58% share of the gross electricity consumption can be reached.

Fig. 9. Results of the sensitivity analysis for the annual economic potential. 10

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the plants are in the South German Molasse Basin, and few or no plants are operated in the Upper Rhine Graben and the North German Basin, this unified modeling approach is used. However, the transfer of the standard LCOE model to the different regions assumes that all parameters, except for the geological gradient, are identical. In reality, not only the gradient but also other parameters, such as the achievable flow rate or the required pump power, might differ. This applies mainly for the North German Basin. For greater reservoir depths the porosity decreases while at the same time the salt content increases [68]. Both effects can worsen the economic performance significantly. The unfavorable brine conditions can cause corrosion and scaling and thus effect the technical equipment of the geothermal plants [69]. To tackle these problems, either more expensive high-alloyed materials such as super austenitic stainless steels and nickel-based alloys can be used [69] or further measures such as the addition of inhibitors can be applied [70]. All these measures can lead to significantly higher costs for utilizing the geothermal resources within this region. However, since there are currently no operating plants within this region and no scientific or technical reports about the expected additional expenses are available, the potential higher LCOEs for the North German Basin are not included within the methodology of this study. Therefore, it must be considered that the economic potential of the North German Basin (which corresponds to 13% of the overall economic potential) might be estimated too optimistic and could be significantly lower in reality. The present potential analysis aims to give a number for the total geothermal potential for combined heat and power production. Thus, legal issues and the impact of the local circumstances on the utilization possibilities are not considered. In reality, certain hydrothermal resources might not be utilized due to legal restrictions such as nature or water conservation areas. Referring back to the definition of the potential terms (cf. Section 2.1), legal restrictions would be considered within the developed potential [35], which has not been analyzed in this study. A further limiting factor might be the social acceptance of the technology. For example, the recent study by Schumacher et al. [71] on the public opinion on different renewable energy technologies in the Upper Rhine Graben reveals that the public acceptance of geothermal energy is lower than for other different types of renewable sources. This issue is especially linked to the potential risk of induced seismic events by geothermal projects as it occurred for example for the project in Landau or Unterhaching [72]. Even if these events caused no significant damage, the flow rate of the plant in Landau was reduced afterwards [72]. The impact of potential seismic events on the economic performance is investigated by several studies [42,73], however the major focus lies on EGS, since the risks for major seismic events is expected to be significantly higher for EGS systems than for hydrothermal projects [74,75]. The recent study by Mignan et al. [76] presents a detailed model for including seismic risk mitigation measures into the LCOE of EGS. To incorporate the impact of potential seismic events on the LCOE requires complex models for the seismic risk (what again needs an empirical magnitude-intensity relationships for seismic hazard assessment for the analyzed regions), the expected damage and the behavioral decision-making of the public after an occurring seismic event. Due to missing geological models for the hydrothermal regions in Germany and the high complexity of the model presented in [76], the risk of seismic events is not considered within the financial model of this work. Thus, when interpreting the results it must be considered that the negative effect of consequences by potential seismic events is not incorporated within the presented LCOE model. In addition, as shown by Eq. (7) the derived LCOE model as well as economic potential is based on the current political framework conditions in Germany, which consists of a guaranteed feed-in tariff paid for the generated gross power. Thus, the presented model is not representing the achievable LCOE of the technology in a market without political support, but is only valid for the current political framework conditions. Calculating the LCOE for a scenario without any

4.4. Critical discussion of the limitations of the model and the results The present potential analysis is based on real operating data and a comprehensive methodology. However, the approach has certain limitations, which need to be considered when interpreting the results. These limitations will be critically discussed in the following. First of all, it should be noted that the identified technical potential is determined on the basis of operating plants. These real projects need to fulfill economic boundaries, which can lead to the fact that technically possible measures to increase efficiency are not implemented due to a lack of economic profitability. Furthermore, the plants in operation focus on the gross power output, due to the framework of the feedin tariff. Thus, the plants are optimized for the highest possible gross power output. The model function of this study, however, is based on the net efficiency, as discussed above. The pure technical potential could therefore be higher than the one derived in this study. In addition, plants, which have recently been commissioned, such as those in Traunreut and Taufkirchen, show higher efficiencies compared to the model function, so that a higher technical potential is conceivable with the state of the art. Concerning the economic potential, it should be noted that the LCOE of the investigated power plants are calculated using the unified methodology and assumptions (e.g., project life of 25 years, interest rate of 8.25% or uniform heat remuneration price) presented in Section 2.3. Thus, the real production costs of the individual plants may deviate from that model, especially when the operator expects different project durations or different heat remuneration prices. The estimation of the project lifetime is particularly difficult, since the age of the current plants in Germany is still quite young. Furthermore, the individual interest rate of each project depends mainly on the individual financial situation of the investor. Nevertheless, this unified model delivers a comparable basis for the potential evaluation. However, it has to be clearly stated that it does not serve to evaluate the economic efficiency of an individual plant, since further internal data would be necessary. Furthermore, the cost model only considers plants in operation, which thus have proven a benefit for the operator or the investor. But there are also some projects, such as Geretsried, Weilheim or Icking, where no or too little groundwater was found. These projects are not considered in the present model. However, the high interest rate of 8.25%, which is assumed for the economic model, indicates the high risk of investment. For comparison, the interest rates for lower-risk investments, such as the installation of a utility-scale PV plant, are below 6% [65]. For example, Egli et al. [39] investigated the development of the capital costs for large scale PV fields in Germany and reported a range between 1.6 and 4% weighted average interest rate in 2017. For geothermal projects a report [66], which serves for the preparation of the EEG experience report according to §97 Renewable Energy Sources Act, comes to the conclusion that for geothermal projects an interest rate of at least 7% is necessary to convince outside creditors to invest in geothermal energy. From this comparison, it can be concluded that the assumed interest rate in this study can be considered for high risk investments and already includes the risk of not finding the geothermal resource. Looking at the small number of plants currently operating in Germany and the derived high economic potential of 454 plants, a huge discrepancy is apparent. The above-mentioned risk of discovery might be one explanation for this discrepancy. It is not clearly stated how this risk is considered within the geological data of the reservoirs [6]. Flechtner and Aubele [67] investigated the success rate of geothermal wells within the SMB. Their results conclude that for drilling depths above 3000 m𝑉 𝐷𝐷 , 3% of the boreholes show too low flow rates, while for drilling depths below 3000 m𝑉 𝐷𝐷 , this is the case in 31% of the projects. The above described approach to transfer the cost model to the different provinces is necessary to quantify the economic potential in each of the three geothermal provinces in Germany. Since most of 11

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political support (and therefore using the generated net electricity for the whole project lifetime in Eq. (7)) would for example increase the derived LCOE for the three pure power projects in Landau, Dürnhaar and Kirchstockach by 13, 38 and 22% respectively. It might appear obvious to present the economic potential also for the case of net LCOE. However, the existing plants are optimized for a high gross power output due to the current support scheme. Thus, for a scenario with sole focus on the net power output over the whole project lifetime, the installed plant components as well as the operational strategy might differ significantly from the current plants. Therefore, to ensure a fair evaluation of the net LCOE, a detailed adjustment of the existing plants would be required to estimate their plant layout in case of a sole focus on net power output. However, the advantage of the methodology in this study is that the operational experience of current plants is used. Therefore, the methodology is oriented to the current political situation. Finally, the economic potential depends strongly on the political support for the technology. Without the currently guaranteed feed-in tariff, the economic potential would decrease nearly to zero. While the derived technical potential can be evaluated quite reliably for the next years (and will only increase due to efficiency increases of the power plants), the determined economic potential can change significantly during the next years, depending on the further political support. Schifflechner et al. [77] conclude that the economic potential might vanish if the political support is stopped during the 2020s, since the predicted cost reductions of the technology might not be enough for a successful geothermal project for power generation within the German electricity market.

Besides the above drawn conclusions, the results of this study have several implications for policy makers within the geothermal sector in Germany, which will be presented in the following. The characteristic of the supply-cost curve (cf. Fig. 7) highlights, that a too strong decrease (or complete abolition) of the guaranteed feed-in tariff in the near future could dissolve the complete economic potential. The current legal situation, which implies an annual reduction of the guaranteed feed-in tariff for new projects by 5%/a from 2021, seems reasonable based on the obtained results. However, a potential further reduction should not be carried out in the future without analyzing the economic situation of the plants in detail at that time in order to avoid a complete throttling of the technology. The sensitivity analysis reveals the over-proportional impact of the plant efficiency on the economic potential. Due to the stronger focus on a sustainable transition of the heating sector, geothermal projects for district heating might increase significantly within the future. Therefore, it can be concluded that there should be a strong focus on increasing the efficiency of geothermal power plants, which are operated within a CHP project. Since the available geothermal heat flow will vary strongly over the year at projects with a strong focus on heat decoupling, the future power plants must be optimized mainly with respect to their part load behavior, as they will only operate during the summer months at full load conditions due to the lower heat demand in this period. Based on this consideration, research concerning the efficient and flexible geothermal CHP production should be supported. Furthermore, it should be considered that the presented sustainable and economic potential with a 1.5% share of the gross electricity demand in Germany is only derived for the hydrothermal resources. Since these resources correspond only to 5% of the overall geothermal resources in Germany [6], increased research and financial incentives for supporting the utilization of petrothermal resources by Enhanced Geothermal Systems (EGS), might lead to a significant increase of the potential role of geothermal energy within the ongoing energy transition.

5. Conclusions and implications In this paper, the potential of combined heat and power production from hydrothermal geothermal resources in Germany is analyzed. Therefore, this study is based on a comprehensive methodology considering the experience gathered with the construction and operation of the first plants. With this approach, the theoretical, the technical and the economic potential has been derived and the major influencing factors have been identified. Based on this analysis the following conclusions can be drawn:

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

• The total technical potential is 12.2 PWhel and 16.7 TWhth ∕𝑎, where most of the technical potential lies between 130 ◦ C and 190 ◦ C wellhead temperature. • The total economic potential is 9.1 PWhel and 12.5 TWhth , considering the current feed-in tariff of 25.2 ct/kWhel . This potential strongly depends on the price which will be remunerated for the geothermal heat and power. The share of the North German Basin on the total economic potential is 12%. While there are existing power plants within the other provinces, the economic performance of the NDB must be evaluated by adapting the LCOE models of the other regions. As the possibility of slightly higher LCOEs for this region cannot be entirely precluded, the overall total economic potential may therefore be correspondingly lower. • For a sustainable exploitation of the geothermal resource, the regeneration of the resource needs to be taken into account. With such sustainable exploitation, an annual economic potential of 9.1 TWhel /a and 12.5 TWhth ∕𝑎 can be derived. This corresponds to an installed capacity of 1.9 GWel,gross . With this, geothermal CHP can contribute to 1.51% of the gross electricity demand and 1.48% of the heating demand for space heating and domestic hot water. • The main influencing factors of the economic potential are the system availability and efficiency. With a 10% increase in system efficiency, the economic potential grows by 21%. In contrast, a 20% reduction in availability leads to a 21% lower economic potential.

CRediT authorship contribution statement S. Eyerer: Conceptualization, Methodology, Validation, Formal analysis, Resources, Writing - original draft, Writing - review & editing, Visualization. C. Schifflechner: Conceptualization, Methodology, Software, Validation, Formal analysis, Resources, Writing - original draft, Writing - review & editing. S. Hofbauer: Conceptualization, Methodology, Resources, Validation, Formal analysis, Writing - review & editing. W. Bauer: Resources, Writing - original draft, Writing - review & editing. C. Wieland: Writing - review & editing, Supervision, Project administration, Funding acquisition. H. Spliethoff: Supervision, Project administration, Funding acquisition. Acknowledgments Funding from the Bavarian State Ministry of Education, Science and the Arts in the framework of the project ‘‘Geothermal-Alliance Bavaria’’ is gratefully acknowledged. Furthermore, we are thankful to the project team of the Geothermal-Alliance Bavaria and several geothermal plant operators for many fruitful discussions and the supply of relevant data. Appendix. Data for the performance analysis of the existing geothermal plants in Germany In Tables A.6 and A.7, all relevant data used for the performacne analysis of the existing plants are summarized. 12

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Site specific data

Capacity data

Plant specific data

General data

Table A.6 Data of the existing plants for power production from hydrothermal geothermal reservoirs in Germany [10]. Plant

Landau

Bruchsal

Unterhaching

Oberhaching

Insheim

Commissioning

2007

2009

2009

2011(th)/2014(el)

2012

Operator

geox GmbH

Geothermie-Gesellschaft

Geothermie Unterhaching

Erdwärme

Pfalzwerke

Bruchsal GmbH

GmbH & Co KG

Grünwald GmbH

geofuture GmbH

electricity-driven

electricity-driven

heat-driven

heat-driven

electricity-driven

Investment costs

21 Mio. e

14.8 Mio. e

80 Mio. e

52.3 Mio. e

50 Mio. e

electricity production

25 GWh

4.1 GWh

21.5 GWh

25 GWh

38.1 GWh

Operation mode

heat production

7 GWh

2 GWh

100 GWh

78.1 GWh

None

electric full load hours

8346 h/a

7500 h/a

6399 h/a

5814 h/a

7727 h/a

thermal full load hours

1400 h/a

1700 h/a

2632 h/a

1952 h/a

None

Cycle architecture

1-stage ORC

Kalina

Kalina

1-stage ORC

1-stage ORC

Condensation concept

Air-cooled condenser

Wet cooling tower

Wet cooling tower

Air-cooled condenser

Air-cooled condenser

Working fluid

R601a

NH3 /H2 O

NH3 /H2 O (89/11)

R600a

R601a

Siemens AG

Siemens AG

Manufacturer

Ormat Technology Inc.

Brine temperature

Intec

Ormat

GMK GmbH

Technology Inc.

70 ◦ C

60 ◦ C

65 ◦ C

30 ◦ C

70 ◦ C

Injectiontemperature

50 ◦ C

60 ◦ C

60 ◦ C

50 ◦ C

70 ◦ C

Concept for heat decoupling

serial

parallel

parallel

parallel

None

DHS Supplytemperature

60 ◦ C–70 ◦ C

90 ◦ C

80 ◦ C–110 ◦ C

85 ◦ C–110 ◦ C

None

DHS Returntemperature

40 ◦ C–50 ◦ C

65 ◦ C

50 ◦ C–60 ◦ C

55 ◦ C–65 ◦ C

None

Th. capacity (to DHS)

5 MW

1.2 MW

38 MW

40 MW

None

El. gross capacity

3 MW

0.55 MW

3.36 MW

4.3 MW

4.8 MW

El. net capacity

2.1 MW

0.31 MW

1.29 MW

2.3 MW

3.6 MW

El. self-consumption (total)

0.9 MW

0.24 MW

2.07 MW

2 MW

1.2 MW

El. self-consumption (plant)

0.3 MW

0.11 MW

0.75 MW

0.7 MW

0.4 MW

El. self-consumption (ESP)

0.6 MW

0.13 MW

1.32 MW

1.3 MW

0.8 MW

Depth of production well

3300 m

2542 m

3350 m

4083 m

3800 m

Depth of injection well

3170 m

1877 m

3590 m

4453 m

3700 m

Wellhead temperature

160 ◦ C

124 ◦ C

122 ◦ C

127,5 ◦ C

165 ◦ C

Brine flow rate

70 l/s

29 l/s

150 l/s

140 l/s

80 l/s

Installation depth ESP

n.a.

480 m

860 m

730 m

n.a.

after power plant

Plant

Dürrnhaar

Kichstockach

Sauerlach

Taufkirchen

Traunreut

Commissioning

2012 SWM Service GmbH electricity-driven 60 Mio. e 40 GWh None 7727 h/a None

2013 SWM Services GmbH electricity-driven 62 Mio. e 40 GWh None 7273 h/a None

2013 Stadtwerke München GmbH electricity-driven 90 Mio. e 40 GWh 4 GWh 8000 h/a 1000 h/a

2015(th)/2017(el) geplant GeoEnergie Taufkirchen GmbH & Co. KG heat-driven 65 Mio. e 30.1 GWh 82 GWh 7000 h/a 2000 h/a

2014(th)/2016(el) Geothermische Kraftwerksgesellschaft Traunreut mbH heat-driven 80 Mio. e 34 GWh 30 GWh 8293 h/a 2500 h/a

2-stage ORC Air-cooled condenser R245fa Turboden srl

2-stage ORC Air-cooled condenser R245fa Turboden srl

2-stage ORC Air-cooled condenser R245fa Turboden srl

Kalina Hybrid cooling tower NH3 / H2 O Exorka GmbH

1-stage ORC Air-cooled condenser R134a Turboden srl

Operator

Plant specific data

Cycle architecture Condensation concept Working fluid Manufacturer Brine temperature after power plant Injectiontemperature Concept for heat decoupling DHS Supplytemperature DHS Returntemperature

45 ◦ C

45 ◦ C

45 ◦ C

65 ◦ C

55 ◦ C

45 ◦ C None None None

45 ◦ C None None None

45 ◦ C serial/parallel 90–105 ◦ C 60 ◦ C

70 ◦ C parallel ca. 115 ◦ C ca. 70 ◦ C

55 ◦ C parallel ca. 100 ◦ C ca. 65 ◦ C

Capacity data

Operation mode Investment costs Electricity production Heat production Electric full load hours Thermal full load hours

Th. capacity (to DHS) El. gross capacity El. net capacity El. self-consumption (total) El. self-consumption (plant) El. self-consumption (ESP)

None 5.5 MW 3.1 MW 2.4 MW 0.8 MW 1.6 MW

None 5.5 MW 3.8 MW 1.7 MW 0.5 MW 1.2 MW

4 MW 5 MW 2.9 MW 2.1 MW 0.7 MW 1.4 MW

39.8 MW 4.3 MW 2.5 MW 1.8 MW 0.7 MW 1.1 MW

12 MW 4.1 MW 2.1 MW 2 MW 0.6 MW 1.4 MW

Site specific data

General data

Table A.7 Data of the existing plants for power production from hydrothermal geothermal reservoirs in Germany [10].

Depth of production well Depth of 1. injection well Depth of 2. injection well Wellhead temperature Brine flow rate Installation depth ESP

3926 m 4114 m – 138 ◦ C 130 l/s 900 m

3882 m 3794 m – 135 ◦ C 135 l/s 600 m

4757 m 5060 m 5567 m 140 ◦ C 110 l/s 800 m

3763 m 4258 m – 136 ◦ C 120 l/s 550 m

5067 m 5412 m – 118 ◦ C 165 l/s 700 m

13

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