Scholarly article on topic 'Impact of Battery Cost on the Economics of Hybrid Photovoltaic Power Plants'

Impact of Battery Cost on the Economics of Hybrid Photovoltaic Power Plants Academic research paper on "Electrical engineering, electronic engineering, information engineering"

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Abstract of research paper on Electrical engineering, electronic engineering, information engineering, author of scientific article — Svetlana Afanasyeva, Christian Breyer, Manfred Engelhard

Abstract In recent years, photovoltaic (PV) technology has experienced a rapid cost reduction. This trend is expected to continue, which in many countries drives interest in utility-scale PV power plants. The main disadvantage of such plants is that they operate only when the sun is shining. The installation of PV modules together with energy storage and/or fossil fuel backup is a way to solve that issue, but consequently increases the costs. In the last few years, however, lithium-ion batteries as well have shown a promising price reduction. This paper studies the competitiveness of a hybrid power plant that combines a PV system, lithium-ion battery and gas turbine (GT) compared to conventional fossil-fuel power plants (coal and natural gas-fired) with focus on the battery cost. To fulfil the demand an auxiliary GT is used in the hybrid PV plant, but its annual generation is limited to 20% of the total output. The metric for the comparison of the different technologies is the levelized cost of energy (LCOE). The installation of the plants is showcased in Morocco, a country with excellent solar resources. Future market scenarios for 2020 and 2030 are considered. A sensitivity analysis is performed to identify the key parameters that influence LCOE.

Academic research paper on topic "Impact of Battery Cost on the Economics of Hybrid Photovoltaic Power Plants"

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Energy Procedía 99 (2016) 157 - 173

10th International Renewable Energy Storage Conference, IRES 2016, 15-17 March 2016,

Düsseldorf, Germany

Impact of battery cost on the economics of hybrid photovoltaic

power plants

Svetlana Afanasyeva^*, Christian Breyera, Manfred Engelhardb

aLUT School of Energy Systems, Lappeenranta University of Technology, Skinnarilankatu 34, Lappeenranta 53850, Finland bM+W Group GmbH, Lotterbergstraße 30, Stuttgart 70499, Germany

Abstract

In recent years, photovoltaic (PV) technology has experienced a rapid cost reduction. This trend is expected to continue, which in many countries drives interest in utility-scale PV power plants. The main disadvantage of such plants is that they operate only when the sun is shining. The installation of PV modules together with energy storage and/or fossil fuel backup is a way to solve that issue, but consequently increases the costs. In the last few years, however, lithium-ion batteries as well have shown a promising price reduction. This paper studies the competitiveness of a hybrid power plant that combines a PV system, lithiumion battery and gas turbine (GT) compared to conventional fossil-fuel power plants (coal and natural gas-fired) with focus on the battery cost. To fulfil the demand an auxiliary GT is used in the hybrid PV plant, but its annual generation is limited to 20% of the total output. The metric for the comparison of the different technologies is the levelized cost of energy (LCOE). The installation of the plants is showcased in Morocco, a country with excellent solar resources. Future market scenarios for 2020 and 2030 are considered. A sensitivity analysis is performed to identify the key parameters that influence LCOE. © 2016 The Authors. Published by ElsevierLtd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of EUROSOLAR - The European Association for Renewable Energy

Keywords: photovoltaic; hybrid PV plant; lithium-ion battery; coal power plant; gas power plant; power supply security; dispatchable generation

1. Introduction

Solar energy is one of the primary sources of energy among renewable energy (RE) options. To convert sunlight into electricity one of the most popular utility-scale options is the photovoltaic (PV) power plant [1]. Prices of PV

* Corresponding author. Fax: +358-5-621-2350. E-mail address: svetlana.afanasyeva@lut.fi

1876-6102 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of EUROSOLAR - The European Association for Renewable Energy doi:10.1016/j.egypro.2016.10.107

systems have been dropping dramatically with an average learning rate of 20.9% [2], [3]. In the last 5 years the global annual installation rate of PV systems averaged around 40 GW, resulting in more than 234 GW being in operation by the end of 2015 [3], [4]. Among newly installed PV capacities about 50% are utility-scale projects. And in many countries the interest continues to grow [3]. With higher penetration of RE, dispatchability and flexible power generation is becoming increasingly important. The main disadvantage of PV plants is the intermittency of power production. This can be solved by installing PV in tandem with batteries, which is more costly but better fulfils the load requirements. Lithium-ion (Li-ion) batteries showed a great reduction in costs in recent years and further experience curve driven cost reductions are expected [5]-[8], which makes hybrid PV-Battery plants more competitive for utility-scale applications.

In this paper a feasibility analysis and a benchmarking based on future market scenarios are presented to identify whether PV is economically feasible for a utility-scale application. A hybrid PV-Battery-Gas Turbine (GT) plant is benchmarked with several utility-scale fossil-fuel power plants: (1) coal-fired, (2) open cycle gas turbine (OCGT) and (3) combined cycle gas turbine (CCGT) plants. Wet and dry cooling systems are considered for coal-fired and CCGT power plants.

For a comprehensive and objective comparison, the functionality of the hybrid PV plant has to match the functionality of fossil-fuel power plants, i.e. the production profiles have to follow a given demand. For the hybrid PV plant, a PV single-axis tracking system, Li-ion batteries and gas turbines for balancing are chosen.

Power plants connected to the grid must operate under varying environmental conditions and under changing load, start-ups and shut-downs, etc. The efficiency of the power plants is strongly affected by the actual operation conditions. Many studies use a single "design point" efficiency value when comparing different technologies [9], which can easily cause misleading conclusions. In this paper the operation of the plants is modeled on an hourly resolution taking into account variations in component performance.

The resource and demand profile are considered as fixed scenarios for the site of Ouarzazate in Morocco (30.9167° N, 6.9167° W) and are related to the load profile of Morocco, respectively. The components of the hybrid PV plant are dimensioned to limit the electricity generation by the natural gas-fired GT to 20%. Ultimately, the LCOE of each plant is compared.

2. Methodology

This section focuses on the power plants' design and discusses the aspects affecting the production efficiency. The method for the economic analysis of the technologies is described.

2.1. Power plant components

Fig. 1-4 show the schematic of the considered power plants' layouts, connected to the grid. The main components are listed below.

Hybrid Photovoltaic (PV) power plant:

• PV modules

• Single-axis tracking system

• Lithium-ion batteries

• OCGT

Fig. 1. Schematic view of hybrid PV power plant.

Coal-fired power plant:

• boiler

• steam turbine

Fig. 2. Schematic view of coal-fired power plant.

Open cycle gas turbine power plant: • gas turbine

Fig. 3. Schematic view of OCGT power plant.

Combined cycle gas turbine power plant:

• gas turbine

• steam turbine

Fig. 4. Schematic view of CCGT power plant.

2.2. Modeling of hybrid PV-Battery-GT plant

The nominal capacity of the considered power plant is 100 MW AC. A standard PV system layout is assumed as shown in Fig. 5. A modular design approach is considered. It has shown to be a successful industrial solution, since it gives greater flexibility in designing the power plant. The plant is divided into ten independent medium voltage sectors. Each sector has five 2000 kVA low voltage to medium voltage (LV/MV) transformers. To every transformer two 1000 kW inverters with a corresponding array of PV modules are connected. To decrease the LCOE of the plant, a DC overdimensioning factor of around 140% is chosen. This means a PV unit of 1408 kWp is installed for every 1000 kW inverter unit, or 2816 kWp for every standard block. PV modules and batteries are coupled on the AC side. It is assumed that two battery blocks of 3000 kWh with a C-rate (which is the rate at which the battery is discharged with a specified continuous current) of 0.33 are installed to each inverter, resulting in a discharge time of six hours. Additionally, two 50 MW GT are chosen for backup.

Fig. 5. Hybrid PV-Battery-GT power plant schematic layout.

A substation is installed for the connection to the grid. It includes a transformer to change the voltage level from medium to high (MV/HV transformer), switchgear, protection, measuring and control equipment.

2.2.1. PVsystem modeling

A single axis tracking system is considered, which can typically increase annual energy yield up to 25-35% [3], [10]. PV modules are installed in a single-row with portrait orientation and row spacing of 2.5 m for easy access. Backtracking is assumed for single-axis tracking, to reduce shading losses.

The production of the PV single axis tracking system is calculated using the software PVsyst [11], which is widely used in the industry. The components considered for simulation are PV modules JAP6-72/300-320/3BB [12], with a rated efficiency of 16.51%, and inverters Sunny Central 1000CP XT by SMA [13]. Overall 44,000 modules are installed with a combined area of 85,289 m2, resulting in 2122 full load hours (FLh) for the considered PV system.

2.2.2. Battery storage system modeling

In this paper a simple battery model is used. It accounts for self-discharge, degradation and charge/discharge losses. Temperature effects are not considered and it is assumed that the batteries are installed in an environment with recommended operating temperature. Cooling demand is taken into account as additional 1% power loss. The maximum capacity fade is parameterized as guaranteed by some producers by the end of the operational lifetime of the battery. The degradation per full cycle is modelled as a ratio of the maximum capacity fade to the total number of cycles.

2.2.3. OCGT modeling

The net efficiency ^net and power output Pnet are calculated as

7net = Egress ISO ' ./load ' fl^ ' JPamb (1)

where "qgross ISO is the efficiency of the gas turbine at the standard ISO conditions, /oad, /-„i, and /P^t are the correction factors due to variation in the load, ambient temperature and pressure, respectively.

Pnet ~ ^grossISO ' ^net ' I1 _ r (/parasitic)) (2)

where Pgross ISO is the GT power output at ISO conditions, r/net is the efficiency for changed operation conditions, r(Pparasitic ) is the ratio of parasitic consumption because of the losses, e.g. due to bearing friction, which is assumed 0.1% of the nominal capacity.

In this paper, approximate equations are used for correction factors that were obtained from analysis of data from different measurement campaigns. Variations in efficiency due to load and temperature are shown in Fig. 6. A change of the ambient pressure affects power output of the GT proportionally.

0.6 0.7 0.8 0.9 1

load [-]

Fig. 6. Efficiency of the OCGT with varying ambient temperature and load.

2.2.4. Operation rules for hybrid PV plant

Operation rules for the hybrid PV power plant are set to yield the annual energy. To simulate the propagation of the state of charge (SoC) of the battery, the Euler method with an integration step size of one hour is used.

ESoC i +1= ESoC , • f fc, ESoC i ) (3)

where ESoC i and ESoC i +1 is the SoC at time ti and ti+1, respectively, At is the time step from time tt to ti+1, and f(ti,ESoC i) is the ordinary differential equation, which is integrated numerically

f if i, ESoC i ) _ (Pcharge! '^charge _ -^discharge! /^discharge)^^ (4)

where Pcharge i and 7chalge are the power and efficiency when the battery is charged, Pdischarge i and 7discharge are the power and efficiency when the battery is discharged.

For every hour the power plant production must follow the demand. An example of a typical operation day is shown in Fig. 7.

Fig. 7. Example of a daily operation cycle: Eload is the demand energy, EPV is the energy supplied to the net from PV modules directly, EGT is the production from auxiliary GT, Ebattery discharge is the energy supplied from batteries, Ebattery cfarge is the energy during charging mode of the battery, Eproduced by Pv is the overall available energy and Edumped PV is the dumped energy that is produced by solar panels, Efrom grid is the energy required by

the plant from the grid during shut-downs.

• t1-t2: standby operation, energy is consumed by the grid due to parasitic electrical consumption of inverter, isolation transformer, control, protection systems, etc.

Eload = 0, EPV = 0 ^ Efromgnd > 0

t2-t3: load covered partly by battery and partly by GT

Eload > 0, EPV _ 0, SoC > 0 ^ Eload _ Ebattery discharge + EGT

t3-t4: load covered by GT

Eload > 0 EPV = 0, SoC = 0 ^ Eload = EGT

t4-t5: load covered partly by PV and partly by GT

Eload > 0, EPV > 0, SoC = 0 ^ Eload = EPV + EGT

t5-te: battery is in charge mode, as battery charge is limited, a part of the energy is dumped

Eload > 0, EPV> Eload ^ Eload _ Eproduced by PV Ebattery charge Edumped PV

t6-t7: battery is in discharge mode, part of load covered by PV, part by battery and rest by GT

Eload > 0, Eload > EPV, SoC > 0 ^ Eload _ EPV + Ebattery discharge + EGT

• t7-t8: equivalent to t2-t3

• tg-tj: equivalent to trt2

2.3. Modeling of fossil- fired power plant

Three types of conventional fossil-fired power plants are studied: coal-fired, OCGT and CCGT. Additionally, wet and dry-cooling systems are considered for coal-fired and CCGT plants.

The same conditions as for the hybrid PV plant are set: the fossil-fired power plant's output must follow the load. At part-load operation, the power plant output efficiency decreases. For OCGT the efficiency curve shown in Fig. 6 is used. For coal-fired and CCGT plant efficiency, the curve is based on [14] and is shown in Fig. 8 and Fig. 9, respectively. Power output and efficiency are calculated with Eq. (1) and Eq. (2).

Fig. 8. Efficiency of the CCGT plant with varying ambient temperature and load.

Fig. 9. Efficiency of the coal-fired power plant with varying ambient temperature and load.

The start-up energy required for the OCGT is negligible. For the CCGT it is assumed that start-up takes 40 min and it requires half of the thermal energy needed for a full load hour. Parasitic losses for the steam turbine are 2.5% of maximum power. For coal-fired and CCGT power plants with dry cooling systems the efficiency drops 3% absolutely [15] and investments are 10% higher [16], [17].

2.4. Economic analysis method

Levelized cost of electricity (LCOE) is one of the most popular metrics to compare power plants with a different type of energy resource, operating lifetime or/and cost structure [18]. Fundamentally LCOE is the ratio of the accumulated costs, discounted to the present, and the electricity produced over the project lifetime, i.e. it is a cost of generating electricity. In this work the capital investment (Capex), operation and maintenance (Opex), fuel and CO2 greenhouse gas (GHG) emission costs are considered. The general formula for LCOE calculation is

Capex ■ crf + Opex+fuel cost + emission costCO

LCOE=-L (11)

AEPl ( )

where AEPel is the power plant annual electrical energy production

AEPel — FLh PR-installed capacity (12)

The degradation of power plant components is included in the so-called performance ratio (PR). For the PV system the PR assumed for the FLh includes an annual degradation of 0.3% [19]-[21] for crystalline silicon PV modules over the entire lifetime averaged for the lifetime. Degradation of the batteries is considered as a function of NFC and degradation rate per cycle. For turbines to quantify performance loss is challenging, as it is a result of wear of different turbine components. This depends on climate, type of fuel, operation mode, number of start-ups and shutdowns, etc. Typically, during the first 24,000 hours of operation degradation is 2-6% [22]. When degraded parts are replaced it decreases to 1-1.5% [22]. Thus, an optimally developed maintenance strategy is essential to keep degradation to a minimum. It is assumed that at the end of the project lifetime expected performance degradation is approximately 5% [23].

crf is a uniform capital recovery factor, which is equal to

. WACC -(1 + waccy

crf =----rrr-— (13)

J (1 + WACCJ -1

Weighted Average Cost of Capital (WACC) is the rate at which the company is expected to earn in order to return to different investors and is commonly used as the discount rate. Usually a company is financed using equity and debt, therefore, in this paper the basic formula for WACC calculation is used:

WACC =--kE +--kD (14)

E + D E E + D D

where E is equity and D is debt, kE and kD are rates of return on equity and interest, respectively, N is the project lifetime.

Fuel cost is found from:

fuel cost = AEP ■ hfue! • cfUel (15)

where hfcel is the heat value and cfuel is the price of fuel.

Eventually, the annual emission cost is the product of the specific emission cost cCO2 (€ per ton of CO2) and the specific mass qCO and thermal annual production AEPth from burning fuel.

emission costCO2 = AEPth, fuel • ^CO2 • cCO2 (16)

CO2 emission calculation

To calculate the CO2 emission costs, firstly, the resulting mass of CO2 after burning the fuel is calculated. The combustion of natural gas (CH4) is an exothermic reaction, as shown in the chemical equation:

CH4 + 2-O2 ^CO2 + 2• H2O+heat (17)

The lower heating value (LHV) of natural gas is 47.1 MJ/kg [24], i.e. burning one kilogram of fuel gives 47.1 MJ or 0.0131 MWh of heat energy. Thus, to produce 1 MWh of heat 76.43 kg of methane is used and 210 kg of CO2 are emitted:

qC02 = qCH4 ■ MC0JMCh4 = 76.43 kg/MWhth ■ 44/16 = 210 kg/MWhth (18)

where qCOi and qCH4 are specific masses, MCO and MCH^ are molar masses in g/mol, of CO2 and CH4, respectively.

MCH = MC + 4 • MH =[12 + 4-i\g/mol = 16 g/mol (19)

MCO = MC + 2 • MO =[12 + 2-16]g/mol = 44 g/mol (20)

Steam (thermal) coal is often used for power generation. Its grade is between bituminous coal and anthracite. Coal varies widely in chemical composition and energy content. In this paper, coal LHV is assumed with 25.83 MJ/kg [25]. Using information about the main components proportions, the specific CO2 emissions can be determined:

CpH,Ok +{p +1/4 - k/2) • O2 ^ p ■ CO2 + (//2) • H2O + heat (21)

Mcoal=p ■ MC +1 ■ MH + k ■ MO = p-12+1-1+k-16 (22)

Mco2 = p ■ [Mc + 2 • Mo ] = p • 44 g/mol (23)

p • 44

qC02 = qcoal •MC02/Mcoal = mcoal--10 , , , ^ (24)

2 21 p-12 +1-1 + k-16

where p, l and k are the proportions of carbon, hydrogen and oxygen, respectively.

In this paper, it is assumed that combustion of 1 ton of coal results in 2.36 tons of C02 emissions [25], i.e. nearly 340 kg of C02 are emitted to produce 1 MWhth.

3. Studied case

The installation of the plant is considered in Ouarzazate, Morocco (30.9167° N, 6.9167° W), with an annual global horizontal irradiation of 2117 kWh/(m2-a) equal to 2703 kWh/(m2-a) incident on module pane for a single-axis tracking PV system, based on PVsyst results. A map of the solar resource in Morocco [26] is shown in Fig. 10.

titfrn*

Kfnfrl I - .Tut ' iinca- ■

Uuarziizme

Average annual sumh period 1994-2010

i » 2« Un

<1600 1700 I SCO 1900 2000 2100 2200 2300kWli m-

Fig. 10. Map of global horizontal irradiation (GHI) in Morocco.

The nominal capacity of the plant is 100 MW AC. The total energy of an isolated system is constant. The derivative of energy inside the system equals the sum of powers passing the system bounds, where power going into the system is positive and out of the system is negative. Therefore, the conservation of energy is expressed in powers for the plants. The annual full load hours are more than 5000, according to the assumed load profile (Fig. ii).

Fig. 11. Daily load profile.

Economic assumptions for the years 2020 and 2030 for the hybrid PV plant and the fossil-fuel plants are given in Table 1 and Table 2, respectively. Assumptions for the PV system are derived from [27], [28], taking into account a tracking system cost. For OCGT and CCGT plants values for Capex, Opex, lifetime and efficiency are based on [29]. Coal-fired power plant parameters are based on [30]. For power plants with dry-cooling systems Capex is 10% higher [16], [17]. Based on current cost numbers and cost development estimates according to [5]-[8] the numbers for batteries are derived. The weighted average cost of capital (WACC) is 7%. Prices of gas and coal are given in Table 2 and the price per ton of C02 emissions is 27.4/59.8 €/tC02 for the cost years 2020 and 2030, respectively. The C02 emission and fuel prices are based on [31] assumptions. Cost for the heavy metal emissions of coal-fired power plants [32]-[35] are not taken into account and remain as further risk and cost factors for coal plants.

Table 1. Economic parameters for the hybrid PV-Battery-GT plant.

System component Dimension Capex 2020/2030 Opex fix 2020/2030 Lifetime 2020/2030

PV single-axis tracking 282 MWel 900/650 €/kWp 13.5/9.75 €/(kWp-a) 30/35

Battery Power price per MW (power 448 MWhel, 150/100 €/kWei 8.1/4.2 €/(kWei-a) 15/20

electronics, transformer, 6.2 hr,

switchgear, control) 6000/10,000

Energy price per MWh (BMS, max cycles 300/150 €/kWhei

Battery, Control)

Open cycle gas turbine 2x50 MWel 475 €/kWei 14.25 €/(kWefa) 30

Table 2: Economic parameters for coal and natural gas-fired power plants.

Power plant Capex Opex fix Fuel cost 2020/2030 Lifetime Efficiency

Coal-fired steam turbine 1500 €/kWel 20 €/(kWefa) 52.5/64.5 €/ton 40 43%

Gas-fired OCGT 475 €/kWel 14.25 €/(kWel*a) 30 43%

21.8/32.1 €/MWhth

Gas-fired CCGT 775 €/kWel 19.4 €/(kWel*a) 30 58%

4. Results and discussion

Dimensions of the hybrid PV power plant components are chosen for a minimum LCOE with a constraint of gas share of up to 20% in the annual production. As a result the total energy produced by the hybrid PV plant to cover the load is 562.8 GWh, from which 61% is delivered by PV modules directly, 21% from batteries and the rest by auxiliary GT. The annual number of full cycles (NFC) of the battery is 275. An example of the power plant operation cycle and summary on monthly and annual energy production are presented in Fig. 12.

The power plant's AEP, consumption of fossil-fuel, C02 emissions and LCOE values are summarized in Table 3.

Table 3: Overview of the key power plants' operational parameters.

Power plant AEP, [GWh] Annual fossil-fuel consumption *103, [ton/a] Annual CO2 emissions •103, [ton/a] LCOE 2020/2030, [€/MWh]

Hybrid PV-Battery-GT 562.8 19.6 53.9 97.7/74.3

Coal-fired steam turbine, wet cooling 518.4 201.0 474.2 72.8/108.0

Coal-fired steam turbine, dry cooling 518.4 207.2 488.9 76.4/112.8

Gas-fired OCGT 523.7 96.6 265.8 78.5/120.9

Gas-fired CCGT, wet cooling 518.4 71.6 197.0 67.3/99.0

Gas-fired CCGT, dry-cooling 518.4 73.9 203.1 70.1/102.8

Fig. 12. Monthly and annual production values of the hybrid PV plant. Example of operational cycle for the days 90-92 of the sample year is

given.

In Fig. 13 power plants' LCOE for given market scenarios are shown, where each influencing component is defined. Capex for PV system drops by almost 30% and battery cost is reduced by 50% in the assumed scenarios. Prices of fuel and C02 emissions are increased for 2030 (Table 2). Results indicate an advantage for the hybrid PV-Battery-GT plant in Morocco in 2030. The OCGT plant is the least favorable compared to the other options. 140

120 ^,100 S SO W 60

|-J 40

i C02 LtueL

I Power block

25,7 20.9 26.2

2020 2030 Coal-fired ST wet caolín"

26.5 21.5 28,4

57.9 i

2020 2030 Coal-fired ST dry cooling

C02 Lgas_

2020 2030

Gas-fired OCGT

2020 2030 G as-fired CCGT wet cooling

i GT i Battery

¡"FV"—

2020 2030 Gas-fired CCGT dry cooling

2.Ü 10.7

9.2 34.4

15.7 9.2 15.6

2020 2030

Hybrid

PV-Battery-GT

Fig. 13. Power plants' LCOE for 2020 and 2030 market scenarios.

The future battery cost development is the major unknown factor. Sensitivity analyses are performed for the hybrid PV plant, coal fired power plant and CCGT plant for 2020, shown in Fig. 14, and for 2030, shown in Fig. 15. It identifies the relative importance of the parameters. The parameters are changed by +50% (orange color) and -50% (blue color) and the impact is referenced to the LCOE of the plants in Table 3.

Key parameters for the hybrid PV plant in 2020 are WACC and Capex in PV modules and batteries. These results show that improving bankability of PV projects and reducing the overall risk for respective investments are key priorities, which was also emphasized in [27]. The effect of the CO2 emission prices on the LCOE plays only a minor role. However, LCOE of the coal-fired plant is most sensitive to CO2 emission price in 2030. It clearly shows the effect that governmental policies on mitigation of GHG emissions have on the competitiveness of the two technologies.

There seems to be a very recent trend in accordance to the COP21 agreement [36] that countries decide by regulation that newly built coal-fired power plants are not allowed anymore at all, as recently announced by Vietnam [37] and the UK [38]. An alternative may be carbon capture and storage (CCS) technology, however, the costs are estimated to result in about 110 - 130 €/MWh [39] for coal-based electricity and the technology may be not available before the year 2030 [40]. Therefore, the uncertainty is not only about the appropriate CO2 price, but also whether coal-fired power is allowed anymore at all, and whether there may be a coal-based technology available to the market for a reasonable price.

For the CCGT power plant the greatest risk lies with the price of natural gas. CO2 emission costs have less impact compared to coal-fired plants, as CCGTs emit less CO2. For a coal-fired plant the fuel price contributes to a lesser part of the total LCOE, as coal is a comparably cheap resource.

Fig. 14. Tornado diagrams for sensitivity analysis of LCOE to + and - 50 % economic parameters for hybrid PV-Battery-GT plant and fossil-fuel

power plants in 2020.

Hybrid PV-Battery-GT plant

Capex PV Capex Battery Capex GT WACC gasfi/MWhth €/ton C02

-15.0% 15.0%

-8.8% 8.8%

-4.8% | 4.8%

-18.2% 20.7%

-10.3%

-4.0% ■ 4.0%

Coal-fired power plant wet cooling

Capex PB WACC €/ton coal e/ton C02

-10.3% -7.7% -11.9% 5 10.3% 8.8% 11.9%

-26.0% 2fi.0%

Capex PB WACC gas €/MWhth €/ton C02

CCGT plant

-40% -20% 0% 20% 40%

-6.2% J -4.1%| 6.2% 4.6%

-30.0% 30.0%

-11.8%| 11.8%

-30% -20% -10% 0% 10% 20% 30%

-40% -20% 0% 20% 40%

Fig. 15. Tornado diagrams for sensitivity analysis of LCOE to + and - 50 % economic parameters for hybrid PV-Battery-GT plant and fossil-fuel

power plants in 2030.

5. Conclusion

PV technology is one of the solutions for reducing GHG emissions. The aim of this paper is to check if it is economically viable for a utility-scale application. A comparison of utility-scale power production technologies between the hybrid PV-Battery-GT and conventional fossil-fired power plants is presented based on the LCOE. Market scenarios for 2020 and 2030 are considered.

The results clearly indicate that coal and natural gas fired power plants are not competitive anymore to hybrid PV-Battery-GT plants in very sunny regions such as Morocco from 2030 onwards for the assumed scenarios when CO2 costs are considered.

Sensitivity analysis shows the importance of WACC to the competitiveness of the hybrid PV project. The top priority for industry is to increase confidence of the investors in the PV projects as a promising investment, but also for governments to reduce respective investment risks. The progress in cost and performance for big stationary battery installations are also key enablers for such hybrid power plants, as well as CO2 emission cost. The responsibility for this incentive lies on the policy-makers of the countries.

Acknowledgments

The authors gratefully acknowledge the public financing of Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit, Berlin, for the 'THERMVOLT' project under the number 41V6706. The authors would like to thank Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Institut für Solarforschung and Institut für Technische Thermodynamik, Stuttgart, for solar resource data, Fichtner GmbH for providing efficiency curves of gas turbines and combined cycles, M+W Central Europe GmbH for description of standard PV system configuration including battery integration. The authors would like to thank Michael Child for proofreading.

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