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APPLICATION OF MULTI-CRITERIA DECISION ANALYSIS FOR
THE OFFSHORE WIND FARMS
M. Antonopoulou and V.K. Tsoukala
School of Civil Engineering, National Technical University of Athens,
National Technical University of Athens
Iroon Polytechniou 5, Zografou, 15 780 Athens, Greece
E-mail: mirtoant@hotmail.com, tsoukala@mail.ntua.gr
ABSTRACT
Offshore wind farms make use of wind energy in sea areas and therefore are considered to be a
Renewable Energy Sources application. In recent years, not only internationally but particularly in
Europe, the installation of wind turbines at sea has gained ground, thus offering a solution to the
problem of the lack of available sites on land to install wind farms, mainly due to the existence of
natural barriers, and to exploit the richest wind resources found in the sea areas. Public acceptance
is a key factor for successfully selecting an installation location for an offshore wind farm. This is
an extremely complex issue as the local residents are unsurprisingly opposed to the development of
offshore wind farms due to their lack of knowledge as far as the environmental benefits and the
actual repercussions caused by the installation of an offshore wind farm in their region are
concerned. Although offshore wind power is generally environmentally friendly, there are some
slight influences on marine ecosystems and birdlife, the morphology of the seabed, water quality
and human activities in the region.
In the present paper the offshore areas which were deemed viable by the Ministry of Environment
Energy and Climate Change as candidates for the location of the first offshore wind farms in
Greece, are evaluated using the DPSIR (Driving Force - Pressure – State – Impact – Response)
model. The multi-criteria decision analysis for the evaluation of the proposed sites is applied by
using the software “MindDecider”. The aforementioned software uses the grading performance of
the proposed sites in the examined criteria and weighs the criteria according to their importance.
The resulting ranking of the positions is different for the four different scenarios that are being
examined. The proposed scenario is the one which maximizes the importance of cost and minimizes
the significance of potential environmental impact.
Keywords
Offshore wind farm, multi-criteria analysis, DPSIR, Renewable Energy Sources
Renewable energy sources
Protection and restoration of the environment XI
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1. INTRODUCTION
Nowadays, harsh climate change has lead to the “hierarchy” of new priorities in energy planning.
The solution to the energy problem is to promote “green”, environmentally friendly technologies,
which can reduce the dependence on increasingly expensive oil and concurrently tackle climate
change. Thus, the promotion of Renewable Energy Resources, and specifically wind energy,
contributes to reducing Europe's dependence on imported energy and reduces climate change
significantly.
Wind energy is a relatively inexhaustible source of energy. Greece, due to its geomorphology and
climate conditions, has a vast amount of potential concerning wind power. Wind farms are the only
realistic renewable alternative to fossil fuels and nuclear energy because of both their technological
maturity and environmental safety. Particularly, in comparison to:
x the production of energy through fossil fuels, wind energy does not require any fossil fuel
and produces no pollutants to the atmosphere.
x the production of nuclear energy, wind energy does not impose a danger in the event of an
accident.
x solar energy, wind energy can obviously be produced even when there is no sunlight.
In recent years, the installation of wind farms in offshore areas has gained popularity. Offshore
wind farms are the most technologically advanced form of wind energy exploitation. The force of
the wind in sea areas is stable, lasting, permanent and faster than on land. The sea areas are
characterized by an absence of occlusions and high obstacles. Moreover, the absence of wind
turbulence has resulted in less stress on wind turbines and thus the efficiency and longevity of the
turbines increase. Finally, offshore wind turbines are efficient machines, quiet and environmentally
friendly (www.aegean-energy.gr, 2012). The main disadvantage of offshore wind farms is the
higher construction, operation and maintenance cost because of the seabed foundation, installation
of turbines and connection to the mainland electrical system through an underground cable. TABLE
1 illustrates the comparison between the costs of offshore wind farms and the costs of developed
wind farms on land.
TABLE 1: Wind energy cost on land and at sea (IEA, 2009)
Onshore Offshore
Investment costs 0.98 – 1.9 M€/MW 2.1 – 3.2 M€/MW
Operation & Maintenance costs 12 – 32 €/MWh 14 – 48 €/MWh
Lifecycle cost of energy 50 – 90 €/MWh 75 – 90 €/MWh
2. OFFSHORE WIND ENERGY IN EUROPE
The European Union is the world leader in offshore projects (Hadjibiros et al., 2011). In the North –
East Atlantic there are 35 generating power wind farms; 14 of them are in the UK with 1931.6 MW
total power, 11 are in Denmark with 500.18 MW, 3 in Germany with 69.5 MW, 4 in the
Netherlands with 246.8 MW, 2 in Belgium with 195 MW and 1 in Ireland with 25.2 MW
(Hadjibiros et al, 2011). In the Mediterranean Sea there are not any fully commissioned offshore
wind farms. However some offshore wind farms are already authorized and others are in the stage
of early planning or application submitting. The offshore wind energy sector has experienced strong
growth over recent years. In the last decade the trend has been visible in all Baltic Sea countries,
with a somewhat higher frequency in Denmark and Germany, and a lower frequency in Latvia,
Lithuania and Russia. Sweden has 4 offshore wind farms with a total capacity of a 134 MW,
Renewable energy sources
Protection and restoration of the environment XI
1440
Finland has 3, with a total capac
i
51 MW and Denmark has 2 win
d
all wind farms in the Baltic Sea
i
farm. In Romania, only the Bla
c
2011). It is expected that offshor
e
wind power by 2020 similar t
o
offshore wind capacity in the
E
installations - from 366 MW i
n
EWEA’s prediction for the offsh
o
Figure 1: Predic
t
i
3. OFFSHORE WIND ENER
G
3.1 The Greek plan for offshor
e
In Greece, there are no offshore
w
meet a total percent of 10
%
(bioenergynews.capitalblogs.gr,
appropriate offshore sites with
e
wind farms in Greece. In 2005, t
h
locations according to their suit
a
2005-2009, efforts for licensing
and one at Limnos. In 2010, the
the plans for the development
installation of the first offshore
2012-2017. Subsequently, envir
o
sites (MEECC, 2010).
In the first phase of developm
e
turbines on the seabed, in depth
s
effectiveness of the facilities as
depths of less than 30 m. In Gree
depth in most offshore areas. T
h
farms are very few. In respect to
smaller wind farms closer to t
h
promoted as this is more econo
m
phase of the program which will
i
ty of 32 MW, Germany has 2 wind farms,
w
d
farms, with a total capacity of 373 MW.
T
i
s 590 MW. In the Black Sea there is no ful
l
c
kstone project (500 MW) has been author
i
e
wind capacity will increase up to 40 GW
o
o
3.6Ǧ4.3% of EU electricity consumption.
E
U by 2020 would require an average gro
w
n
2008 to 6.9 MW in 2020 (EWEA, 20
0
o
re wind capacity installed within the next y
e
t
ion for the development of offshore wind ca
p
i
nstalled in Europe (EWEA, 2009)
G
Y IN GREECE
e
wind energy
w
ind farms installed as yet. However, it is as
s
%
of its energy consumption with 500
2011). As a result, research was conducte
d
e
xploitable wind potential, for the installati
o
h
e Public Electricity Corporation evaluated t
h
a
bility for installation of offshore wind far
m
two farms were made; one at the region of
Ministry of Environment Energy and Clim
a
of offshore wind energy in Greece. This
wind farms at twelve proposed offshore s
i
o
nmental impact assessments must be con
d
e
nt, MEECC is planning to construct the f
o
s
of less than 50 m in order to ensure not o
n
well, although the existing European experi
e
ce, due to the morphology of the seabed,
the
r
h
erefore, the appropriate areas for develop
m
the dilemma posed by the criteria for visual
i
h
e coast or greater at a larger distance, t
h
m
ic and efficient. Floating solutions will be c
o
be held between 2017-2025 (MEECC, 2010)
w
ith a total capacity of
T
he total capacity from
l
y commissioned wind
i
zed (Hadjibiros et al,
o
r 25% of all European
Reaching 40 GW of
w
th of 28% in annual
0
9). Figure 1 presents
e
ars in Europe.
p
acity
s
umed that Greece can
large wind turbines
d
in order to find the
o
n of the first offshore
h
e 24 most appropriate
m
s. During the period
Schoinias (Marathon)
a
te Change announced
plan is aimed at the
i
tes during the period
d
ucted at the proposed
o
undation of the wind
n
ly reliability but cost
e
nce is found at water
r
e is a rapid increase in
m
ent of offshore wind
i
mpact, allowing either
h
e second scenario is
o
nsidered in the second
.
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Protection and restoration of the environment XI
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3.2 Technical features of an offshore wind farm
Wind turbines should not be placed too close to each other to ensure proper operation. For example,
a wind turbine should not be affected by air turbulence caused by the operation of another turbine,
as this would reduce the exploitable wind potential. The original placement of wind turbines will be
a grid of 8Dכ8D (where D is the diameter of the rotor). The turbines’ capacity is 5 MW and rotor’s
diameter is 125 m long (MEECC, 2010). The distance between the turbines will be:
ૡ כ ࡰ ൌ ૡ כ ൌ
In TABLE 2 the areas of polygons that will be occupied by the wind farms are given. Since the
distance between turbines is 1000 m and each turbine has a nominal capacity of 5 MW, the number
of turbines in each farm and the nominal capacity are also calculated.
TABLE 2: Proposed areas of polygons of offshore wind farms, number of wind turbines and their
nominal capacity (MEECC, 2010)
No Proposed site Proposed area
(km
2
)
Number of wind
turbines
Capacity
(MW)
1 Kymi 9 16
80
2 Petalioi 25 36 180
3 Alexandroupolis 55 71 355
4 Samothraki 6 14 70
5 Fanari 41 56 280
6 Thassos 35 48 240
7 Limnos 49 64 320
8 Ai-Stratis 5 12 60
9 Karpathos 6 14 70
10 Lefkada 8 18 90
11 Corfu 8 18 75
12 Kryoneri 5 12 60
TOTAL 252 379 1880
3.3 Exclusion criteria for locating offshore wind farms
During the preliminary process of determining a location for offshore wind farms in Greece, the
Ministry of Environment Energy and Climate Change set four basic exclusion criteria for locating
an offshore wind farm. These criteria were defined and analyzed by the Ministry as follows
(MEECC, 2010):
Criterion 1: Development of offshore wind farms within 6 nautical miles from shore.
Criterion 2: Ensure the technical possibility of installing wind turbines at specific sites. That
means that the maximum installation depth will be 50 m.
Criterion 3: Avoid areas with any significant impact on the environment (based on the initially
available data). This approach excluded all areas included in the network NATURA
2000 from the areas concerned.
Criterion 4: Minimize the visual impact of the facilities. This criterion applies only for
observation points where there is or it is expected to be significant anthropogenic
activity. The criteria used were maximum visible height and maximum visible
surface of wind turbines (MEECC, 2010).
The degree of satisfaction of the above criteria for the proposed sites is given in TABLE 3.
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TABLE 3: Degree of satisfaction of exclusion criteria for the proposed sites
No Proposed site CRITERIA
Criterion 1 Criterion 2 Criterion 3 Criterion 4
1 K
y
mi 9
9 9
2 Petalioi 99 9
3Alexandrou
p
olis
9
9 9 ×
4 Samothraki 99 9
5Fanari
9
9 9 ×
6Thassos 99 9
7Limnos
9
9 9 ×
8 Ai-Stratis 99 9 9
9Kar
p
athos 9
9 9
10 Lefkada 99 9
11 Corfu
9
9 9
12 Kr
y
oneri 99 9
Note:
9
: The criterion is satisfied
: Only the criterion of maximum visible height of turbines is satisfied (MEECC, 2010)
: ȃeither of the criteria for visual impact is satisfied
The criteria for visual impact are based on an international practice, where technical experience
allows the construction of offshore wind farms at long distances from shore and not within 6
nautical miles. This limitation leads to the location of farms at a closer proximity from shore than
the distances that farms are located abroad. It is therefore expected that in Greece, almost none of
the sites meets this criteria. Thus, the criterion 4, for visual impact is not considered to be an
exclusion criterion for the proposed sites which are evaluated in the next paragraphs using multi–
criteria decision analysis.
3.4 Evaluation criteria for locating offshore wind farms
In order to evaluate the suitability of the proposed sites for the installation of an offshore wind farm,
characteristic indicators are introduced concerning economic, environmental and energy efficiency
criteria. These criteria were selected based on previous international experience concerning cost and
environmental impact of offshore wind farms, the operational characteristics of wind turbines and
the available data in the first phase (Antonopoulou, 2011). The application of DPSIR framework
was used for the classification of each indicator. DPSIR is a general framework based on
distinguished driving forces (D), pressures (P), states (S), impacts (I) and responses (R) which helps
to obtain an approach for the development of an integrated environmental assessment strategy
(EEA, 1998). The application of this framework allows the chosen indicators to enable feedback to
decision makers (Kristensen, 2004).
The proposed indicators and each value for every set of criteria are presented in TABLE 4. In the
same TABLE the DPSIR classification of each indicator is also given. To quantify the performance
of each site according to the evaluation criteria, a scale of natural numbers for each criterion was
established and then the proposed sites were rated based on these scales. The criteria may be
positive or negative and each criterion has its own scale. For example, the “Available wind
potential” is a positive criterion and its scale ranges between 1 and 4 depending on the level of
average annual wind speed. On the other hand, the “Total routing of cables” is a negative criterion
and its scale ranges between 1 and 6 (Antonopoulou, 2011). The results of the rating are shown in
the following summary TABLE 5.
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TABLE 4: Evaluation criteria for proposed sites
Criteria Description of
indicators
Impact
classification
according to
(DPSIR)
Comments
Type Code Data sources
ENERGY EFFICIENCY
Meteorological
criteria
A1 Available wind
potential (S)
Average annual wind speed (m/sec) The available wind data are derived from statistical analysis of wind
measurements at the nearest meteorological stations. These data come
from the base of climatic data of the Statistical Climatology
Department of National Meteorological Agency.
A2 Duration of blow of
exploitable wind (S)
Number of days during the year that exploitable wind blows
A3 High levels of
rainfall (S)
Average annual level of precipitation (mm) The available data come from the data base of the Statistical
Climatology Department of National Meteorological Agency.
Total capacity
A4 Degree of total
capacity (D)
Total capacity (MW) Total capacity of the proposed wind farm by MEECC
COST
Oceanographic
criteria
B1 Water depth (P)
Calculation of the maximum depth of installation of wind
turbines in each wind farm (m) According to the Google Earth map
B2 Wave climate / Wave
Energy (P)
Calculation of the maximum wave height, Hmax (m) Application of the SMB model
Required
infrastructure-
Associated
works
B3 Total routing of
cables (P)
Measurement of the route of cables from the installation
area to the nearest high voltage station (km)
The measurement was made on the geophysical map of the
Administration of Greek electricity transmission system
B4
Available capacity of
the existing network
of Public Electricity
Corporation
(S)
Check if the network at the region is congested and it cannot
raise additional power from wind farms
According to the available data from the Administration of Greek
electricity transmission system
B5
Distance from the
installation area to
the major
commercial port
(S)
Measurement of the distance (km) The measurement was made on the Google Earth map
ENVIRONMENT
Environmental
criteria
C1 Risk for earthquakes (S)
Assessment of seismic hazard According to the New Seismic Hazard Map of Greece
C2 Visual impact (I)
Check if the criteria for maximum visible height and
maximum visible surface of turbines are being satisfied These criteria have been set by MEECC
C3 Impacts on birds (I)
Presence of sensitive species
According to FILOTIS base
C4 Impacts on marine
mammals (I)
C5 Impacts on fish (I)
C6 Impacts due to the
routing of cables (I)
Check if the cables of the wind farm are cross areas inclu ded
in the network NATURA 2000 According to FILOTIS base
Anthropogenic
activities
C7 Crossing lines of
ships (D)
Check if a line crosses the offshore polygon which is
occupied by the wind farm According to the Google Earth map
C8
Fishing as an
economic activity in
the region
(D)
Involvement of local residents with fishing According to FILOTIS base
C9 Air traffic (D)
Measurement of the distance from the installation area to the
nearest airport (km) The measurement was made on the Google Earth map
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TABLE 5: Summary of indicators evaluation for all the proposed wind farms
ENERGY EFFICIENCY
COST ENVIRONMENT
Meteorological
criteria
Total
capacity
Oceanographic
criteria
Required
infrastructure-
Associated works
Environmental criteria Anthropogenic
activities
ǹ1 ǹ2 ǹ3 ǹ4 Ǻ1 Ǻ2 Ǻ3
Ǻ4 Ǻ5 C1 C2 C3 C4 C5 C6 C7 C8 C9
Kymi 1 3 3 1 1 2 2 2 3 1 2 2 1 1 1 1 1 1
Petalioi 4 1 1 2 3 1 1 2 3 1 2 4 1 2 1 1 1 3
Alexandroupolis 4 1 2 3 1 1 1 1 1 1 3 4 1 1 1 1 1 2
Samothraki 4 1 2 1 2 1 3 1 1 2 2 3 2 1 1 1 2 1
Fanari 3 1 2 3 1 2 2 1 2 1 3 3 1 1 1 1 2 1
Thassos 2 1 2 3 3 1 1 2 2 1 2 3 1 1 2 2 2 2
Limnos 4 2 2 3 3 2 6 2 2 2 3 4 2 1 1 1 2 1
Ai-Stratis 4 2 2 1 3 2 6 2 3 2 1 3 2 1 1 2 1 1
Karpathos 2 3 1 1 2 2 6 2 3 2 2 4 2 1 1 2 1 3
Lefkada 4 2 3 1 2 2 1 2 2 3 2 4 1 2 1 1 2 3
Corfu 3 1 3 1 3 2 2 2 3 2 2 3 2 1 1 2 1 1
Kryoneri 2 1 2 1 2 1 1 2 1 2 2 4 1 1 1 1 2 2
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4. MULTI-CRITERIA DECISION ANALYSIS
Using the data from the grading of the proposed sites and the multi-criteria analysis software
“MindDecider” (Roodchenko, 2008), the ranking of proposed sites from the best to the worst for
installing an offshore wind farm was conducted (Antonopoulou, 2011). The criteria are categorized
in three main sectors; Energy Efficiency, Cost, Environment. The significance of the criteria was
chosen through personal assessments and reasonable assumptions and it is presented at TABLE 6.
For example, the parameter which mainly affects the energy efficiency of an offshore wind farm is
the total capacity of its wind turbines. Therefore, the criterion “Degree of total capacity” is the most
important in this sector and takes the weight factor “+3”. The use of wind energy demands durable,
strong but not destructive winds. Therefore, the criteria “Available wind potential” and “Duration of
blow of exploitable wind” take the weight factor “+2” equally. The criterion “High levels of
rainfall” is of secondary importance as modern wind turbines are designed properly to withstand
fatigue and loss of blades support. Thus, this criterion takes the weight factor “-1”.
TABLE 6: Significance of the criteria
ENERGY
EFFICIENCY COST
ENVIRONMENT
Criteria
ǹ1 ǹ2 ǹ3 ǹ4 Ǻ1 Ǻ2 Ǻ3 Ǻ4 Ǻ5 C1 C2 C3 C4 C5 C6 C7 C8 C9
Weights -1 +2 +2 +3 -3 -2 -3 +1 -2 -6 -4 -5 -3 -2 -1 -6 -5 -4
Four different scenarios are being examined depending on the relative weight given to the three
previously mentioned sectors of the analysis. Scenario 0 gives the three main sectors the same
importance for the selection of the optimal site. In Scenario 1 the most important criteria for the
selection are those for Energy Efficiency. The aim is to maximize the power output from the
facility. Secondly, those parameters related to Cost are taken into account, while the environmental
criteria and anthropogenic activities are the least important. In Scenario 2, Cost is the most
important sector, Environment is of less importance and Energy Efficiency comes last. In Scenario
3, Cost is the most important sector for the decision, while Environment is the least. Scenario 3 is
chosen as the most reliable. This scenario maximizes the importance of economic criteria while
minimizes the importance of environmental criteria in the overall scoring. This approach is logical
considering that the main disadvantage of offshore wind energy is its cost. At the same time,
environmental criteria are the least important since offshore wind farms are environmentally
friendly and offshore polygons have also been located outside nature protection areas, NATURA
2000. Finally, human activities were also evaluated at the minimum rate in this scenario, as wind
turbines will be marked with light signals to avoid collisions with ships or airplanes and the
possible decline of the fishing industry as an economic activity may be offset by the creation of new
jobs for the local community as a result of the maintenance needs of the offshore wind farm.
TABLE 7 shows the alternative scenarios and the weight factors given to the three main sectors in
each scenario.
TABLE 7: Weight factors given to the three main sectors in each scenario
Scenario Energy
Efficienc
y
Cost Environment
0
+1
+1
+1
1+3+2+1
2+1 +3 +2
3+2+3+1
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In Figure 2 the ranking of the proposed sites for the four scenarios is given. The proposed sites are
ranked according to their rate (degree of preference) (Antonopoulou, 2011). According to Scenarios
0 and 1 Alexandroupolis is the optimal site while Corfu is the worst. Corfu comes in last due to its
poor performance at criteria related to Cost. In particular, this area is characterized by deep waters
and its long
distance from the major commercial port. The fact that Energy Efficiency gains relative
importance in Scenario 1 compared to Scenario 0 affects the ranking of the proposed sites. For
example, Kymi ranks as the fourth, while Thassos ranks as the fifth optimal site in Scenario 0.
However, in Scenario 1, Thassos ranks as the fourth while Kymi as the sixth optimal site. This is
logical as Thassos presents a better general performance than Kymi concerning criteria related to
Energy Efficiency (mainly because of higher total capacity).
Figure 2: Ranking of the proposed sites for the four scenarios
In Scenario 2 Ai-Stratis comes in last while in Scenario 1, Corfu is the worst choice. This is a
logical conclusion considering that Cost gains while Energy Efficiency loses importance in
Scenario 2 relatively to Scenario 1 and Ai-Stratis performs worse than Corfu in the criterion “Total
routing of cables” which is related to Cost although better in the meteorological criteria which are
related to Energy Efficiency.
5. CONCLUSIONS
In the present paper 12 offshore areas are evaluated using the DPSIR model and multi-criteria
decision analysis. The optimal site according to the most reliable scenario which is Scenario 3 is
Alexandroupolis while the worst is Ai-Stratis. Alexandroupolis presents this high performance as
this is a highly environmentally friendly area amongst the other proposed sites but mainly because
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Renewable energy sources
Protection and restoration of the environment XI
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the proposed wind farm has high total capacity. On the other hand, Ai-Stratis will provide low total
capacity while deep waters and poor performance at criteria related to the required infrastructure
and associated works increase the overall cost.
In order to evaluate the proposed sites more accurately, it is necessary to conduct studies and
surveys based on on-site measurements at the sea areas of development, so as to collect data which
was unavailable during this study, including:
• More data on the stability of the seabed and thus the type of the appropriate foundation
(e.g., geomorphological and geological characteristics and the specific type of sediment
in each area - sand, gravel or mud). Elements such as grain size (coarse or fine) are
critical to the assessment of the environmental impacts of an offshore wind farm.
• Data on the composition and geochemical properties of sediments, such as organic matter
concentration as well as potential pollutants that can emerge when scraping.
• The speed and direction of sea currents in the areas of installation.
• The various types, populations and importance of phytobenthos and zoobenthos
• The existence of archaeological remains on the seabed.
The methodology developed and applied in this paper leads to the first ranking of proposed sites by
MEECC for the first offshore wind farms in Greece. Further research and improvements could
include a more objective assessment of weighting and grading the criteria based on experience.
REFERENCES
1. Antonopoulou, M. (2011) “Application of multi-criteria decision analysis for siting an
offshore wind farm (in Greek)”.
2. ǼǼǹ (1998) “Guidelines for data collection and processing”, EU State of the Environment
Report, Annex 3.
3. EWEA (2009) “Oceans of Opportunity, Harnessing Europe’s largest domestic energy
resource”, report, pp. 67.
4. Google Earth (2010).
5. Hadjibiros K., C. Lioumi and M. Aravantinou (2011) “Support for EEA Coastal Assessment
2012 and Climate Change Impacts Assessment 2012”, Sub-assessment Energy and Resource
Extraction, pp. 36.
6. IEA (2009) “Key world energy statistics”, Report, pp. 78.
7. “Investments in offshore wind farms in Greece (in Greek)”, http://bioenergynews.capital
blogs.gr/showArticle.asp?id=10470&blid=210, (accessed November 14, 2011).
8. Kristensen, P. (2004) “The DPSIR Framework”, Proceeding of workshop on A
comprehensive/detailed assessment of the vulnerability of water resources to
environmental resources in Africa using river basin approach, UNEP Headquarters, Kenya,
2004.
9. Ministry of Environment Energy and Climate Change [MEECC] (2010) “Preliminary siting of
offshore wind farms: Responding of MEECC to the proposals for informal consultation
(in Greek)”, Press Release 23/07/2010.
10. Ministry of Environment Energy and Climate Change [MEECC] (2010) “Process of
preliminary siting of offshore wind farms (in Greek)”, Press Release 06/07/2010.
11. “Offshore wind farms in Aegean (in Greek)”, http://www.aegean-energy.gr/pdf/newsletter/dt-
march2010.pdf, (accessed January 8, 2012).
12. Roodchenko, S.V. (2008) Mind Decider Software Program
,
http://www.minddecider.com
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