# Economic Feasibility of Semi-Underground Pumped Storage Hydropower Plants in Open-Pit Mines

^{1}

^{2}

^{3}

^{4}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Pumped Hydro Storage

#### 2.1. Principles of PHS and Situation in Germany

#### 2.2. Markets for Large-Scale Storage Operation

#### 2.3. Concept for an Open-Pit Mine Semi-Underground Pumped Hydro Storage Power Plant

#### 2.4. Energy Storage and Conversion

^{3}/s), $g$ the gravitational constant (9.81 m/s

^{2}), ${\mathsf{\eta}}_{l}$ the efficiency of the loading process (%), h the head (m), and ρ the density of water (~1000 kg/m

^{3}). The conversion of the potential energy into kinetic and electric energy is calculated as:

^{3}/s), and ${\eta}_{d}$ the efficiency of the discharging process (%). The correlated capacity is also dependent on the storage volume and the flow rate and is the product of the maximum power and the duration of a complete discharge of the storage volume:

^{3}). The overall efficiency $\eta $ of PHS power plants is calculated by the product of the loading efficiency in the pumping mode (${\eta}_{l})$ and the discharging efficiency (${\eta}_{d})$ in the turbine mode.

#### 2.5. Technical Concept

^{6}m

^{3}. The possibility of storage on a mine dump would require geotechnical studies that are beyond the scope of this study. Maximum achievable heights are estimated to be about a 200 m (height difference between mine dump and pit lake). Ranges for the dimension of the pit lake are volumes of 25 × 10

^{6}m

^{3}to 5.8 × 10

^{9}m

^{3}and lake surface areas between 1 × 10

^{6}m

^{2}to 40 × 10

^{6}m

^{2}. These values are derived from German lignite pit mines in operation. The maximum values for volume and surface area are provided by the pit lake in Hambach [27].

#### 2.6. Cost Analysis

#### 2.6.1. Capital Expenditures (Capex)

^{3}for the upper reservoir, depending on the diameter at a constant height (=height of embankment, with freeboard of 2 m, resulting in 8 m water depth) of 10 m with varying embankment construction costs between 5 €/m

^{3}, 10 €/m

^{3}, and 20 €/m³. At a diameter of 1500 m, the costs per m³ of storage volume of the reservoir converge asymptotically to approx. 2.50 €/m

^{3}, 3 €/m

^{3}, and 4 €/m

^{3}, respectively, comprising owner’s costs of 5 €/m

^{2}, embankment construction and material costs of 5 €/m

^{3}, and sealing costs or 10 €/m

^{2}, according to [25].

^{3}(see Figure 4). The costs per installed power rise slightly with the storage volume, whereas the costs per unit of installed capacity fall rapidly. Compared to the Capex of other PHS projects reported in Table 2, the costs of an open-pit mine PHS are in the lower range.

#### 2.6.2. Operational Expenditures (Opex)

#### 2.7. Flooding of Pit Lake

^{6}m

^{3}/a is assessed for the pit lake in Inden (Scen. 2) by water extraction from the Rur river [22]; 270 × 10

^{6}m

^{3}/a from the Rhine is assessed for the flooding in Hambach (Scen. 1) [27,32]. Given these filling rates, more than 20 years will elapse until a pumped-storage hydropower plant eventually goes into full operation after an investment of several hundred million Euros. During these years, obviously, such a power plant will not generate any revenues. The maintenance costs for this time are assumed to be 10% of the maintenance and operation costs during operation.

#### 2.8. Fees and Regulations

#### 2.8.1. Grid-Use Fees

#### 2.8.2. EEG Levy

#### 2.8.3. Water Extraction Fees

## 3. Methodology

#### 3.1. Economic Model and Input Description

#### 3.2. Economic Evaluation

#### 3.3. Integration of Cash Flow

#### 3.4. Monte Carlo Simulation

#### 3.4.1. Statistical Testing

#### 3.4.2. Empirical Analysis of Historical Spot Prices

#### 3.4.3. Simulation of Spot Prices

#### 3.4.4. Retrieval of Secondary Reserve Capacity

#### 3.5. Sensitivity Analysis

## 4. Results

#### 4.1. Economic Evaluation

#### 4.1.1. Excluding Flooding Time

#### 4.1.2. Including Flooding Time

#### 4.2. Sensitivity Analysis

#### 4.3. Value-at-Risk

_{t}

_{+T}– NPV

_{t}|, if NPV

_{t}

_{+t}< NPV

_{t}, with probability (1-α). For the VaR computation, the probability distributions of the economic outcomes, considering price uncertainties on the spot and balancing markets, need to be calculated. The data from the spot and balancing markets are reported in Section 3.4. The Monte Carlo simulation is conducted with 5000 runs. The resulting histograms are reported in Appendix C (Figure A3, Figure A4, Figure A5 and Figure A6). The fitted distributions with mean, standard deviation, and confidence interval, e.g., for an NPV > 0, are listed in Table 13 (excl. flooding time) and Table 14 (inc. flooding time). The VaR is applied to NPV, NCR, PIR, and SPC—before and after tax—and for both scenarios, excluding and including flooding time.

#### 4.3.1. Excluding Flooding Time

#### 4.3.2. Including Flooding Time

## 5. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## Abbreviations

AC | Accruals | LLV | Lake level variation |

A_{LR} | Area lower reservoir | NC | Network charges |

AMD | Acid mine drainage | NCR | Net cash recovery |

AN | Annuity | NPV | Net present value |

AT | After tax | η | Efficiency |

AC_{UR} | Area costs upper reservoir | η_{d} | Efficiency deload |

A_{UR} | Area upper reservoir | η_{l} | Efficiency load |

α | Inclination | om | Operation & maintenance costs |

BT | Before tax | Opex | Operational expenditures |

Capex | Capital expenditures | PHS | Pumped hydro storage |

c_{d} | Capacity deload | PIR | Profit to investment ratio |

c_{fix} | Opex, fixed | P_{l} | Power load |

c_{l} | Capacity load | P_{d} | Power deload |

c_{power} | Spot price per MW bought electricity | p_{power} | Spot price per MW sold electricity |

PT | (Dynamic) Payback time | ||

c_{var} | Opex, variable | P_{SR} | Electric load for second. reserve market |

δ | Depreciation rate | ρ | Density of water |

DR_{neg} | Demand rate secondary reserve, negative base | q | Discounting factor |

DR_{pos} | Demand rate secondary reserve, positive peak | Q_{d} | Flow rate per turbine deload |

D_{UR} | Diameter upper reservoir | Q_{l} | Flow rate per turbine load |

EEG | German Renewable Energy Sources Act (Erneuerbare Energien Gesetz) | r | Inflation |

EEX | European Energy Exchange | R | Revenues |

Emb_{UR} | Embankment costs | S | Number of full cycles per year |

EnWG | German Energy Industry Act (Energiewirtschaftsgesetz) | Seal_{UR} | Sealing costs, upper reservoir |

ER_{neg} | Energy rate secondary reserve, negative base | SPC | Specific production costs |

ER_{pos} | Energy rate secondary reserve, positive peak | T | Lifetime |

g | Gravitational constant | T_{#} | Number of machine units |

h | Height difference | t_{d} | Discharge time |

h_{d} | Full load hours deload per day | tax | Tax rate |

h_{l} | Full load hours load per day | TSO | Transmission system operator |

HPFC | Hourly price forward curve | TWh | Terawatt hour |

H_{UR} | Height upper reservoir | V | Utilizable volume |

i | Interest rate | var_{d} | Var. costs of deloading per start of unit |

I_{PHS} | Total Capex | var_{l} | Var. costs of loading per start of unit |

I_{PHSp} | Capex power-related | var_{o} | Other variable costs |

I_{UR} | Capex upper reservoir | V_{LR} | Volume lower reservoir |

## Appendix A. Spot Market Contracts and Price Data, Water Extraction Fees in Germany

Contract ^{1)} | Volume of Contract |
---|---|

Baseload contract,Block contract for every day, Mon–Sun | 1 MW × 24 h = 24 MWh |

Peakload contract,Block contract for Mon–Fri, 08:00–20:00 h | 1 MW × 12 h = 12 MWh |

Weekend baseload contractBlock contract Sat 00:00–Sun 24:00 h | 1 MW × 48 h = 48 MWh |

Hourly contract for every hour of a day | 0.1 MW × 1 h = 0.1 MWh |

Combination of hourly contracts to hourly blocks | 0.1 MW × number of h |

EEX – night, 00:00–06:00 h | 0.1 MW × 6 h = 0.6 MWh |

EEX – morning, 06:00–10:00 h | 0.1 MW × 4 h = 0.4 MWh |

EEX – business, 08:00–16:00 h | 0.1 MW × 8 h = 0.8 MWh |

7 other combinations ^{2)} |

^{1)}Special contracts are traded for transition between winter- and summertime;

^{2)}EEX—high-noon, EEX—afternoon, EEX—rush-hour, EEX—evening, base load, peak load, off-peak load. Source: [39].

**Table A2.**Water extraction fees in Germany for ground- and surface waters and hydropower applications, by federal state (incl. North-Rhine Westphalia) (€/1000 m

^{3}).

Federal State | Groundwater | Surface Water | Hydropower |
---|---|---|---|

Baden–Wuerttemberg | 5.1 | 1 | 1 |

Berlin | 31 | - | - |

Brandenburg | 10 | 2 | 2 |

Bremen | 2.5 | 0.3 | - |

Hamburg | 13 | - | - |

Mecklenburg–Western Pomerania | 5 | 2 | - |

Lower Saxony | 2.556 | 2.045 | 2.045 |

North Rhine–Westphalia | 5 | 5 | - |

Rhineland–Palatinate | 6 | 2.4 | - |

Saarland | 8 | - | - |

Saxony | 1.5 | 2 | 0.01 |

Saxony–Anhalt | 7 | 4 | 4 |

Schleswig–Holstein | 7 | 0.77 | 0.077 |

Bavaria | - | - | - |

Hesse | - | - | - |

Thuringia | - | - | - |

**Figure A1.**(

**a**–

**c**) EEX spot market prices, base-load and peak-load, 2012–2014. Source: own illustration, based on weekly EEX data (1 January 2012–31 December 2014).

## Appendix B. Statistical Testing

_{1}). The lower the measured distance, the better the goodness of fit. The greatest vertical distance is calculated by using the following equation [47]:

## Appendix C. Additional Results

**Figure A2.**Capex and net present value and net cash recovery before and after tax; excluding (plots (

**a**–

**d**)) and including (plots (

**e**–

**h**)) flooding time, Scen. 1 and 2.

**Figure A3.**Value at risk for Scen. 1, excl. flooding time, based on a Monte Carlo simulation with 5000 runs. Plots (

**a**) and (

**b**) show the net present value (NPV) before and after tax, plots (

**c**) and (

**d**) the NCR before and after tax, plots (

**e**) and (

**f**) the profit-to-investment ratio (PIR) before and after tax, and plots (

**g**) and (

**h**) the per unit (specific) production costs (SPC) before and after tax. The solid lines denote the fitted probability distribution, the red areas the confidence interval of not encountering a neg. NPV, neg. NCR, or PIR < 1 (i.e., depending on the performance indicator concerned; as the costs considered are all positive, there is only a blue histogram in those two plots).

**Figure A4.**Value at risk for Scen. 2, excl. flooding time, based on a Monte Carlo simulation with 5000 runs. Plots (

**a**) and (

**b**) show the net present value (NPV) before and after tax, plots (

**c**) and (

**d**) the NCR before and after tax, plots (

**e**) and (

**f**) the profit-to-investment ratio (PIR) before and after tax, and plots (

**g**) and (

**h**) the per unit (specific) production costs (SPC) before and after tax. The solid lines denote the fitted probability distribution, the red areas the confidence interval of not encountering a neg. NPV, neg. NCR, or PIR < 1 (i.e., depending on the performance indicator concerned; as the costs considered are all positive, there is only a blue histogram in those two plots).

**Figure A5.**Value at risk for Scen. 1, incl. flooding time, based on a Monte Carlo simulation with 5000 runs. Plots (

**a**) and (

**b**) show the net present value (NPV) before and after tax, plots (

**c**) and (

**d**) the NCR before and after tax, plots (

**e**) and (

**f**) the profit-to-investment ratio (PIR) before and after tax, and plots (

**g**) and (

**h**) the per unit (specific) production costs (SPC) before and after tax. The solid lines denote the fitted probability distribution, the red areas the confidence interval of not encountering a neg. NPV, neg. NCR, or PIR < 1 (i.e., depending on the performance indicator concerned; as the costs considered are all positive, there is only a blue histogram in those two plots).

**Figure A6.**Value at risk for Scen. 2, incl. flooding time, based on a Monte Carlo simulation with 5000 runs. Plots (

**a**) and (

**b**) show the net present value (NPV) before and after tax, plots (

**c**) and (

**d**) the NCR before and after tax, plots (

**e**) and (

**f**) the profit-to-investment ratio (PIR) before and after tax, and plots (

**g**) and (

**h**) the per unit (specific) production costs (SPC) before and after tax. The solid lines denote the fitted probability distribution, the red areas the confidence interval of not encountering a neg. NPV, neg. NCR, or PIR < 1 (i.e., depending on the performance indicator concerned; as the costs considered are all positive, there is only a blue histogram in those two plots).

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**Figure 1.**Efficiency and energy losses of PHS. Source: own illustration, based on [24].

**Figure 3.**Specific capital costs of PHS projects in Germany. Source: own illustration after [31].

**Figure 5.**Specific investment costs as a function of storage volume, both in terms of installed power (€/kW) and installed capacity (€/kWh).

**Figure 7.**Hourly price forward curve, Phelix Base, and Phelix Peak. Source: own illustration, based on EEX data for 2014 (obtained from www.eex.com).

**Figure 8.**Operation strategy of a PHS power plant for given spot prices on a daily basis. Notes: white bars denote inactivity (neither discharging nor charging the upper reservoir); price variation derived (downscaled) from the Phelix future prices shown in Figure 7.

**Figure 9.**Energy rate (left plot) and demand rate (right plot) for secondary reserve capacity (base/peak; pos./neg.) in Germany, 2014. Source: own illustration, based on regelleistung.net [44].

**Figure 10.**Net present value before tax as a function of the interest rate, Scen. 1 and 2, excl. flooding time.

**Figure 11.**Net present value before tax as a function of the price spread, Scenarios 1 and 2, excl. flooding time.

**Figure 12.**Net present value before tax as a function of the interest rate, Scen. 1 and 2, incl. flooding time.

**Figure 13.**Net present value before tax as a function of price spread, Scen. 1 and 2, incl. flooding time.

**Figure 14.**Sensitivity analysis of Scen. 2 on the net present value before tax, with a variation of ± 50% of key parameter values.

Area (km^{2}) | Volume (mill. m^{3}) | Max. Depth (m) | End of Operation | |
---|---|---|---|---|

Scen. 1: Hambach | 38 | 5800 | 450 | 2040 |

Scen. 2: Inden | 11.2 | 800 | 180 | 2030 |

Country/German Fed. State | Head (m) | Power (MW) | Costs (mill. €) | Planned Completion (a) | Specific Costs (€/kW) | |
---|---|---|---|---|---|---|

Vianden M11 | Lux | 280 | 200 | 155 | 2013 | 775 |

Waldeck 2plus | HE | 360 | 300 | 250 | 2017 | 833.33 |

Blautal (Ulm) | BW | 170 | 60 | 60 | 2016 | 1000 |

Schweich (Trier) | RP | 200 | 300 | 400 | 2018 | 1333.33 |

Forbach | BW | 320-360 | 200 | 250 | 2018 | 1250 |

Riedl | BY | 350 | 300 | 350 | 2019 | 1166.67 |

Atdorf | BW | 600 | 1400 | 1200 | 2019 | 857.14 |

Heimbach | RP | 500 | 600 | 700 | 2019 | 1166.67 |

Nethe (Höxter) | NW | 220 | 390 | 500 | 2019 | 1282.05 |

Schmalwasser | TH | 200-300 | 400 | 500 | 2019 | 1250 |

Simmerath (cancelled) | NW | 240 | 640 | 700 | 2019 | 1093.75 |

System | Parameter | Symbol | Value | Unit |
---|---|---|---|---|

PHS system | Gravity | g | 9.81 | (m/s^{2}) |

Utilizable volume | V | 10,000,000 | (m^{3}) | |

Height difference | h | 200 | (m) | |

Number of turbines | T_{#} | 4 | (-) | |

Flow rate/Turbine load | Q_{l} | 80 | (m^{3}/s) | |

Flow rate/Turbine deload | Q_{d} | 100 | (m^{3}/s) | |

Efficiency load | η_{l} | 86 | (%) | |

Efficiency deload | η_{d} | 88 | (%) | |

Power load | P_{l} | 540 | (MW) | |

Power deload | P_{d} | 630 | (MW) | |

Capacity deload | c_{d} | 4360 | (MWh) | |

Density of water | ρ | 1000 | (kg/m^{3}) | |

Upper reservoir | Diameter | D_{UR} | 1300 | (m) |

Height | H_{UR} | 10 | (m) | |

Freeboard | - | 2 | (m) | |

Inclination | α | 32 | (°) | |

Volume | V_{UR} | 10,000,000 | (m^{3}) | |

Area | A_{UR} | 1.4 × 10^{6} | (m^{2}) | |

Lower reservoir | Volume | V_{LR} | 5.8 × 10^{9} | (m^{3}) |

Area | A_{LR} | 40 × 10^{6} | (m^{2}) | |

Lake level variation | LLV | 0.25 | (m) |

Parameter | Symbol | Value | Unit |
---|---|---|---|

Capex, power-related | I_{PHSp} | 704 | (€/MW) |

Capex, upper reservoir | I_{UR} | 16 × 10^{6} | (€) |

Area costs | AC_{UR} | 5 | (€/m^{2}) |

Embankment costs | Emb_{UR} | 5 | (€/m^{3}) |

Sealing costs | Seal_{UR} | 10 | (€/m^{2}) |

Opex, fixed | c_{fix} | - | (€/a) |

Operation and maintenance | Om | 10,000 | (€/Mwa) |

Opex, variable | c_{var} | - | (€/a) |

Start loading | var_{l} | 2 | (€/MW/start) |

Start deloading | var_{d} | 2 | (€/MW/start) |

Other | var_{o} | 1 | (€/MWh) |

Parameter | Symbol | Value | Unit |
---|---|---|---|

Power market | - | - | (-) |

Full cycles per year | S | 350 | (-) |

Spot price per MW sold electricity | p_{power} | 43 | (€/MWh) |

Spot price per MW bought electricity | c_{power} | 24 | (€/MWh) |

Full-load hours load | h_{l} | 9 | (h) |

Full-load hours deload | h_{d} | 7 | (h) |

Demand rate sec. res. market pos. peak | ER_{pos} | 517 | (€/MWh/w) |

Energy rate sec. res. market pos. peak | DR_{pos} | 456 | (€/MW/w) |

Demand rate sec. res. market neg. base | ER_{neg} | 1227 | (€/MWh/w) |

Energy rate sec. res. market neg. base | DR_{neg} | 491 | (€/MW/w) |

Electricity load for sec. res. market | P_{SR} | 20 | (MW) |

Parameter | Symbol | Value | Unit |
---|---|---|---|

Depreciation rate | δ | 10 | (%) |

Accruals | AC | 10 | (%) |

Interest rate | i | 6 | (%) |

Inflation rate | r | 2 | (%) |

Tax rate | tax | 29 | (%) |

Discounting factor (nominal) | q | 1.06 | (-) |

Lifetime | T | 70 | (a) |

Variable | Symbol | Unit |
---|---|---|

Revenues | R | (€) |

Capex | I_{PHS} | (€) |

Opex, fixed | c_{fix} | (€) |

Opex, variable | c_{var} | (€/MWh) |

Specific production costs | SPC | (€/MW) |

Annuity | AN | (€/MW) |

Net cash recovery | NCR | (€) |

Net present value | NPV | (€) |

Profit to investment ratio | PIR | (-) |

Payback time | PT | (a) |

Distribution | Anderson–Darling | Kolmogorov–Smirnov | Chi-Square |
---|---|---|---|

Logistical | 7.0802 | 0.0340 | 392.2842 |

Student t | 7.6012 | 0.0372 | 422.8631 |

Normal | 19.7925 | 0.0594 | 427.6037 |

Beta | 20.3815 | 0.0601 | 445.2282 |

Gamma | 21.7549 | 0.0635 | 470.0104 |

Lognormal | 25.0144 | 0.0689 | 463.6037 |

Weibull | 105.8409 | 0.0971 | 1210.7093 |

Min. extreme value | 106.4567 | 0.0974 | 1218.9935 |

Max. extreme value | 348.3581 | 0.1848 | 2505.8175 |

Beta PERT | 586.6824 | 0.2649 | 4767.9974 |

Triangular | 945.5238 | 0.3793 | 5482.0130 |

Uniform | 1545.4198 | 0.4844 | 13,001.1786 |

Year | Base (9 p.m.–8 a.m.) | Peak (8 a.m.–9 p.m.) | Price Spread | ||
---|---|---|---|---|---|

Mean (€/MWh) | Std. Dev. (€/MWh) | Mean (€/MWh) | Std. Dev. (€/MWh) | Mean (€/MWh) | |

2009 | 29.60 | 12.00 | 46.68 | 13.66 | 17.08 |

2010 | 36.98 | 7.59 | 50.83 | 10.52 | 13.85 |

2011 | 43.88 | 8.29 | 57.26 | 9.34 | 13.38 |

2012 | 35.38 | 14.98 | 48.70 | 13.83 | 13.32 |

2013 | 31.12 | 9.16 | 43.38 | 14.48 | 12.26 |

2014 | 27.89 | 10.45 | 37.41 | 12.90 | 9.52 |

Pos. SBC | Offered Capacity (MW) | Demand Rate (€/MWh) | Energy Rate (€/MW) | |||
---|---|---|---|---|---|---|

Peak | Base | Peak | Base | Peak | Base | |

Mean | 32.88 | 24.27 | 516.99 | 485.61 | 456.15 | 781.71 |

Std. Dev. | 16.48 | 16.81 | 961.79 | 902.27 | 52.67 | 84.36 |

Max. | 67.71 | 75.48 | 5160.12 | 4864.63 | 589.35 | 988.36 |

Min. | 5.00 | 5.00 | 57.72 | 56.48 | 352.63 | 608.78 |

Neg. SBC | Offered Capacity (MW) | Demand Rate (€/MWh) | Energy Rate (€/MW) | |||

Peak | Base | Peak | Base | Peak | Base | |

Mean | 19.73 | 21.46 | 1087.73 | 1226.67 | 293.24 | 491.29 |

Std. Dev. | 15.47 | 16.12 | 1882.51 | 1972.79 | 73.10 | 80.94 |

Max. | 75.75 | 67.48 | 6006.76 | 5982.51 | 538.33 | 659.44 |

Min. | 5.00 | 5.00 | 0.31 | 0.89 | 163.64 | 316.51 |

Scenario Parameter | Unit | Scen. 1 (Inden) | Scen. 2 (Hambach) |
---|---|---|---|

Head | (m) | 100 | 200 |

Storage volume | (m^{3}) | 6,000,000 | 10,000,000 |

Pit lake volume | (m^{3}) | 800,000,000 | 5,800,000,000 |

Lake level variation | (m/d) | 0.54 | 0.25 |

Duration of flooding ^{*} | (a) | 20 | 22 |

Power | (MW) | 314 | 628 |

Capacity | (MWh) | 1308 | 4360 |

Yearly production | (MWh) | 457,800 | 1,526,000 |

Cash Flow Items: | |||

Investment | |||

PHS system | (1000 €) | 221,000 | 442,000 |

Storage | (1000 €) | 15,000 | 25,000 |

Annual Revenues | |||

Peak shaving | (1000 €) | 21,517 | 66,264 |

Pos SBC | (1000 €) | 1750 | 1750 |

Neg SBC | (1000 €) | 1787 | 1787 |

Annual Operating Costs | |||

Fixed | (1000 €) | 3139 | 6278 |

Variable | (1000 €) | 13,940 | 43,198 |

Annual accruals | (1000 €) | 425 | 833 |

NCR BT | (1000 €) | 296,949 | 955,664 |

NPV BT | (1000 €) | −54,998 | 16,170 |

PIR BT | (-) | 1.26 | 2.05 |

SPC BT | (€/kWh) | 0.08 | 0.07 |

PT BT | (a) | n.a. | n.a. |

Annual depreciation | (1000 €) | 3371 | 6671 |

Annual tax | (1000 €) | 2208 | 5894 |

NCR AT | (1000 €) | 142,394 | 543,091 |

NPV AT | (1000 €) | −107,489 | −123,950 |

PIR AT | (-) | 0.60 | 1.16 |

SPC AT | (€/kWh) | 0.09 | 0.07 |

PT AT | (a) | n.a. | n.a. |

Cash Flow Item | Unit | Scen. 1 (Inden) | Scen. 2 (Hambach) |
---|---|---|---|

NCR BT | (1000 €) | 290,670 | 943,106 |

NPV BT | (1000 €) | −156,433 | −251,727 |

PIR BT | (-) | 1.23 | 2.02 |

PT BT | (a) | n.a. | n.a. |

NCR AT | (1000 €) | 136,115 | 530,534 |

NPV AT | (1000 €) | −180,753 | −316,648 |

PIR AT | (-) | 0.6 | 1.14 |

PT AT | (a) | n.a. | n.a. |

Distribution | Mean | Std. Dev. | Conf. Level (%) | ||
---|---|---|---|---|---|

(a) Scen. 1 | |||||

NPV (mill. €) | BT | normal | −55.59 | 165.55 | >0; 37.26 |

AT | normal | −107.91 | 117.54 | >0; 18.8 | |

NCR (mill. €) | BT | normal | 295.22 | 165.55 | >0; 73.07 |

AT | normal | 141.16 | 346.01 | >0; 66.07 | |

PIR (-) | BT | normal | 1.25 | 2.07 | >1; 54.69 |

AT | normal | 0.6 | 1.47 | >1; 39.53 | |

SPC (€/kWh) | BT | gamma | 0.08 | 0.01 | <0.1; 91.51 |

AT | normal | 0.09 | 0.01 | <0.1; 39.53 | |

(b) Scen. 2 | |||||

NPV (mill. €) | BT | gamma | 14.04 | 461.37 | >0; 50.46 |

AT | gamma | −125.46 | 327.58 | >0; 34.88 | |

NCR (mill. €) | BT | gamma | 949.4 | 1358.48 | >0; 75.6 |

AT | gamma | 538.64 | 964.53 | >0; 71.24 | |

PIR (-) | BT | lognormal | 2.03 | 2.91 | >1; 63.45 |

AT | lognormal | 1.15 | 2.07 | >1; 52.24 | |

SPC (€/kWh) | BT | lognormal | 0.07 | 0.01 | <0.1; 99.74 |

AT | gamma | 0.07 | 0.01 | <0.1; 99.76 |

Variable (unit) | Distribution | Mean | Std. Dev. | Conf. Level (%) | |
---|---|---|---|---|---|

Scen. 1 | |||||

NPV (mill. €) | BT | Beta | −263.57 | 53.66 | >0; 0.0 |

AT | Beta | −256.82 | 38.10 | >0; 0.0 | |

NCR (mill. €) | BT | Beta | −390.18 | 341.03 | >0; 12.75 |

AT | Beta | −347.23 | 242.13 | >0; 7.38 | |

PIR (-) | BT | Beta | −1.65 | 1.45 | >1; 3.13 |

AT | Beta | −1.47 | 1.03 | >1; 0.69 | |

SPC (€/kWh) | BT | Beta | 0.06 | 0.01 | <0.1; 100 |

AT | Beta | 0.06 | 0.0 | <0.1; 100 | |

Scen. 2 | |||||

NPV (mill. €) | BT | Normal | −254.77 | 212.54 | >0; 11.51 |

AT | Normal | −318.81 | 150.91 | >0; 1.68 | |

NCR (mill. €) | BT | Beta | 930.15 | 1380.99 | >0; 74.64 |

AT | Beta | 521.33 | 980.50 | >0; 69.98 | |

PIR (-) | BT | Beta | 1.99 | 2.96 | >1; 52.19 |

AT | Beta | 1.14 | 2.1 | >1; 63.24 | |

SPC (€/kWh) | BT | Beta | 0.04 | 0.01 | <0.1; 100 |

AT | Normal | 0.04 | 0.00 | <0.1; 100 |

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Wessel, M.; Madlener, R.; Hilgers, C.
Economic Feasibility of Semi-Underground Pumped Storage Hydropower Plants in Open-Pit Mines. *Energies* **2020**, *13*, 4178.
https://doi.org/10.3390/en13164178

**AMA Style**

Wessel M, Madlener R, Hilgers C.
Economic Feasibility of Semi-Underground Pumped Storage Hydropower Plants in Open-Pit Mines. *Energies*. 2020; 13(16):4178.
https://doi.org/10.3390/en13164178

**Chicago/Turabian Style**

Wessel, Michael, Reinhard Madlener, and Christoph Hilgers.
2020. "Economic Feasibility of Semi-Underground Pumped Storage Hydropower Plants in Open-Pit Mines" *Energies* 13, no. 16: 4178.
https://doi.org/10.3390/en13164178