treatment of uncertainties through a monte carlo approach for...

Treatment of uncertainties through a Monte Carlo approach for offshore wind farms in Greece

George Caralis NTUA / NUIST

“Best practice policies to finance renewable energy”, DIA-CORE Regional Workshop in Athens, Friday 6th of November 2015

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G.Caralis, “Treatment of uncertainties through a Monte Carlo approach for offshore wind farms in Greece” , in DIA-

CORE Regional Workshop in Athens, 6th of November 2015

Objectives

- Evaluation of the feed-in tariff scheme for offshore

- Analysis of the attractiveness of offshore wind farms investments

- Relevant risks (wind potential, cost and macroeconomic parameters).

- Monte Carlo simulation approach integrated into a typical financial model,

- A probability distribution is used for the description of the examined uncertain parameters (not a single value)

- Implemented in each of the 12 projects, performing many hundreds of iterations, each characterized by a randomly selected set of the examined uncertain parameters.

-Resulting a probability distribution of the IRR

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Wind capacity in EU and world

Source: EWEA,GWEC

Growth rate 2014 : World 16.2%, Europe 9.7%

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Annual wind investments in EU and world

Source: EWEA, GWEC

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Net Capacity Installed by Fuel in EU (2000-2014)

Source: Platts, EWEA

Wind energy development in EU

Wind GAS PV Biomass&WasteHydro CSP Nuclear Coal Fuel Oil

net capacity 116.8 101.3 87.9 9.9 6.9 2.3 -13.2 -24.6 -25.3

-40

-20

0

20

40

60

80

100

120

140

GW

2000-2014: Net capacity installed 262.3GW

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Offshore wind capacity (2000 – 2014)

Source: EWEA

Source: Platts, EWEA

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Offshore statistics (end of 2014)

Source: EWEA Source: www.ewea.org/stats/eu-offshore-2014

http://www.ewea.org/stats/eu-offshore-2014





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Current offshore foundation technology

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Offshore wind applications

- several offshore wind application (~4GW, since 2006)

- preliminary study (CRES, 2010)

- low prospects for realization

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Twelve candidate offshore wind energy projects in Greece (CRES)

Source: T.Chaviaropoulos, M.Papadopoulos, Seanergy (2011)

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Uncertainties - Parameters

Internal parameters (site-specific factors, affecting the cost and

efficiency of wind farms)

- Water depth and seabed conditions

- Wind potential evaluation

- Seismicity

- Complex orography

- Project approval (Delays, unclear licensing procedure, environmental

issues and conflicts over alternative uses of marine and coastal

areas)

External parameters (economic and social environment)

- Feed-in tariff (basic value of 129.96€/MWh with an optional surplus up

to 30% ->162.45€/MWh )

- Financing issues

- Social acceptance

- Limited offshore Grid in Mediterranean

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12 projects / data / cost estimation

No Offshore Wind

Farm

Proposed

Polygon

Area

(km2)

Qualitative evaluation criteria

Source: CRES

Capacity-

Size (MW)

Cost estimation

(€/kW) - function of

grid distance, depth

and size Wind Grid Depth Size Total

1 Agios Efstratios 5 +1 -1 0 -1 -1 20-30 3550-4050

2 Alexandroupoli 55 -1 +1 +1 +1 +2 200-300 2500-3000

3 Thassos 35 -1 +1 0 +1 +1 130-200 2600-3100

4 Karpathos 6 +1 -1 0 -1 -1 22-33 3500-4000

5 Corfu 8 0 +1 0 0 +1 32-48 2800-3300

6 Krioneri 6 -1 +1 0 -1 -1 22-33 2900-3400

7 Kymi 9 +1 +1 0 -1 +1 35-55 2900-3400

8 Leukada 8 -1 +1 +1 -1 0 32-48 2550-3050

9 Lemnos 49 +1 -1 0 +1 +1 180-270 3100-3600

10 Petalioi 25 0 +1 0 0 +1 70-110 2650-3150

11 Samothraki 33 +1 0 -1 +1 +1 120-190 2700-3200

12 Fanari 41 -1 +1 +1 +1 +2 150-240 2450-2950

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Aeolian maps of Greece

Source: CRES

Source: CRES (2001)

Source: National Observatory of Athens (2014)

Source: K.Rados (based on mesoscale modelling)

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12 projects / data / cost estimation

No Offshore Wind

Farm

Qualitative

evaluation

criteria

[CRES]

High resolution wind atlas of

Greece based on typical wind

year (www.meteo.gr)

Mesoscale

map

based on

year 2011

[K.Rados]

European

Wind atlas

[RISO]

Capacity

factor

estimation

(%)

Wind W/m2 C (m/s) k m/s m/s

1 Agios Efstratios +1 344-368 7.2-7.4 1.8 7.5-8 7.5-8.5 36-41%

2 Alexandroupoli -1 179-289 5.5-6.5 1.6 5.5-6.25 6-7 28-33%

3 Thassos -1 95-130 4.4-4.9 1.5 5.5-6.25 6-7 27.7-32.7%

4 Karpathos +1 446-558 7.9-8.7 1.8 8-8.5 8-9 35-40%

5 Corfu 0 221-228 5.9-6.3 1.6 6.25-7 6.5-7.5 30-36%

6 Krioneri -1 230-264 5.2-5.7 1.2 5.5-6.25 6-7 27-32%

7 Kymi +1 272-282 6.7-7 1.7 7-7.5 7-8 34.5-40%

8 Leukada -1 104-131 4.8-5.1 1.7 5.5-6.25 6-7 27.5-32.5%

9 Lemnos +1 406-427 7.4-7.6 1.7 7.5-8 8-8.5 36.5-41.5%

10 Petalioi 0 300-372 6.8-7.5 1.8 6.25-7 6.5-7.5 29-35%

11 Samothraki +1 182-257 5.2-6 1.5 7-7.5 7.5-8.5 35.5-40.5%

12 Fanari -1 85-172 4.3-5.3 1.6 5.5-6.25 6-7 28.5-33.5%

http://www.meteo.gr/

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Overview of the “12” projects cost and capacity factor modelling

26%

28%

30%

32%

34%

36%

38%

40%

42%

2400 2600 2800 3000 3200 3400 3600 3800 4000 4200

Ca

pa

city

Fa

cto

r (%

)

Project Cost (€/kW)

1 - AgiosEfstratios

2 - Alexandroupoli

3 - Thassos

4 - Karpathos

5 - Corfu

6 - Krioneri

7 - Kymi

8 - Leukada

9 - Lemnos

10 - Petalioi

11 - Samothraki

12 - Fanari

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Values of the “certain” parameters

Parameter All types of projects

Own capital 30%

Loan 70%

Subsidy 0%

Loan’s payback period 10year

Lifetime (years) 20

Depreciation rate (%) 5%

Tax (%) 25%

Annual Operational & Maintenance Cost 2% of investment cost

Absorption rate 100%

Rate to local authorities (% Income) 0%

Salvage value (%) 15% of investment cost

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Assessing the attractiveness of the established Feed-in Tariff

Average IRR and range with confidence interval 90%

• Scenario “a”: The lower limit (129.96€/MWh) = basic FIT value (108.34€/MWh + 20%

foreseen in the absence of subsidy)

• Scenario “b”: The upper limit (162.45€/MWh) = 129.96 €/MWh + 30% (optional)

• Scenario “c”: A uniform distribution of the above limits (129.96-162.45€/MWh)

representing the uncertainty when the exact level of surplus is not yet clarified.

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Identifying the optimal site-specific feed-in tariff

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Classification of offshore wind projects in Greece

No Offshore Wind

Farm

Capacity-

Size

(MW)

Cumulative

capacity

(MW)

IRR >12% IRR>16% Priority

groups

Capacity

of each

group

(MW)

FIT

(€/MWh)

Surplu

s (%)

FIT

(€/MWh)

Surplus

(%)

11 Samothraki 120-190 120-190 134,17 3% 155,21 19%

1 335-515 7 Kymi 35-55 155-245 146,43 13% 169,15 30%

9 Lemnos 180-270 335-515 149,27 15% 172,43 33%

10 Petalioi 70-110 405-625 153,31 18% 176,51 36%

2 452-698 12 Fanari 150-240 555-865 154,11 19% 178,26 37%

2 Alexandroupoli 200-300 755-1165 156,14 20% 181,07 39%

5 Corfu 32-48 787-1213 159,15 22% 184,27 42%

8 Leukada 32-48 819-1261 162,54 25% 188,83 45%

3 204-311 3 Thassos 130-200 949-1461 163,28 26% 188,99 45%

4 Karpathos 22-33 971-1494 169,55 30% 196,57 51%

1 AgiosEfstratios 20-30 991-1524 172,43 33% 198,57 53%

6 Krioneri 22-33 182,98 41% 212,01 63%

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Discussion

• A common Feed-In-Tariff scheme is ineffective, even if an optional

case-specific surplus is set.

• The current perplexity on the final value of FIT introduces further

uncertainty on the feasibility of the projects.

• Large deviations on the wind potential and investment cost

• A higher surplus is necessary

• Need to establish different feed-in tariff options for different sub-

regions or evolve the current FIT in the near future following the

offshore technology evolution.

• Useful tool and valuable results for private investors and policy

makers

Thank you for your attention!

e-mail: [email protected]

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