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Feasibility of investment in Blue Growth multiple-use of space and multi-use platform projects; results of a novel assessment approach and case studies

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Blue Growth is the creation of economic activity and jobs at sea, while multiple use of space makes efficient use of the available sea area by combining industries. Clearly there are many combinations and many value propositions. However, most technologies to date are considered blue sky concepts, with little robust techno-economic analysis demonstrating profitability. The paper begins by providing a comprehensive review of Blue Growth and multi-use in Blue Growth; both in policy as well as the wide range of current technologies, including ocean energy, offshore wind energy, offshore aquaculture and desalination. The Maribe H2020 project provides the vehicle for the research element of the paper. The major contribution is a new methodology for selecting, filtering, developing and ranking business propositions for multiple-use of space (MUS) and multi-use platforms (MUP). Application of the method for the first time identified three case studies where Blue Growth combination projects can be economically viable, with attractive internal rate of return (IRRs). Results presented for the case studies report standard investment metrics and show the relative contribution of each product (energy, food, water) to the system profitability, as well as socioeconomic impact. Existing companies were fully engaged in the process. Co-creation between sector experts and industry led to both improved business value propositions and robust assessment of investment readiness. In contrast to the presumption that large scale platforms are commercially attractive, the highest ranking case study companies required smaller capital expenditure (CAPEX) and operated in niche subsectors. In conclusion, the positive economic performance of the case studies should provide confidence for the EC as well as investors that MUS and MUP have viable economic futures leading towards commercialisation. The
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Renewable and Sustainable Energy Reviews
journal homepage: www.elsevier.com/locate/rser
Feasibility of investment in Blue Growth multiple-use of space and multi-use
platform projects; results of a novel assessment approach and case studies
Gordon Dalton
a
, Tamás Bardócz
b
, Mike Blanch
c
, David Campbell
d
, Kate Johnson
e
,
Gareth Lawrence
b
, Theodore Lilas
f
, Erik Friis-Madsen
g
, Frank Neumann
h
, Nikitakos Nikitas
f
,
Saul Torres Ortega
i
, Dimitris Pletsas
j
, Pedro Diaz Simal
i
, Hans Christian Sørensen
g
,
Afroula Stefanakou
k
, Ian Masters
j,
a
MaREI ERI, University College Cork (UCC), Ireland, UK
b
Aquabiotech, Naggar st, Mosta, Malta
c
BVG Associates, Cricklade, Swindon SN6 6HY, UK
d
Albatern, Midlothian Innovation Centre, Roslin, Scotland, UK
e
Heriot Watt University, Orkney, Scotland, UK
f
EcoWindwater, University of the Aegean, Chios, Greece
g
Wave Dragon, Frederiksborggade 1, DK-1360 Copenhagen K, Denmark
h
Seaweed Energy Solutions, Bynesveien 48, 7018 Trondheim, Norway
i
University of Cantabria, Santander, Spain
j
Swansea University, Swansea, Wales, UK
k
University of the Aegean, Chios, Greece
ARTICLE INFO
Keywords:
Blue Growth
Multiple-use of space
Multi-use platform
Techno-economics
Ocean energy
Aquaculture
ABSTRACT
Blue Growth is the creation of economic activity and jobs at sea, while multiple use of space makes efficient use
of the available sea area by combining industries. Clearly there are many combinations and many value pro-
positions. However, most technologies to date are considered blue sky concepts, with little robust techno-eco-
nomic analysis demonstrating profitability.
The paper begins by providing a comprehensive review of Blue Growth and multi-use in Blue Growth; both in
policy as well as the wide range of current technologies, including ocean energy, offshore wind energy, offshore
aquaculture and desalination.
The Maribe H2020 project provides the vehicle for the research element of the paper. The major contribution
is a new methodology for selecting, filtering, developing and ranking business propositions for multiple-use of
space (MUS) and multi-use platforms (MUP). Application of the method for the first time identified three case
studies where Blue Growth combination projects can be economically viable, with attractive internal rate of
return (IRRs). Results presented for the case studies report standard investment metrics and show the relative
contribution of each product (energy, food, water) to the system profitability, as well as socio-economic impact.
Existing companies were fully engaged in the process. Co-creation between sector experts and industry led to
both improved business value propositions and robust assessment of investment readiness. In contrast to the
presumption that large scale platforms are commercially attractive, the highest ranking case study companies
required smaller capital expenditure (CAPEX) and operated in niche subsectors.
In conclusion, the positive economic performance of the case studies should provide confidence for the EC as
well as investors that MUS and MUP have viable economic futures leading towards commercialisation. The
https://doi.org/10.1016/j.rser.2019.01.060
Received 10 June 2018; Received in revised form 18 December 2018; Accepted 22 January 2019
Abbreviations: Maribe, Marine Investment in the Blue Economy; CAPEX, Capital expenditure prior to first operation; DECEX, Decommissioning expenditure; FID,
Final investment decision; IRR, Internal rate of return; LCOO, Levelised cost of output; LCOE, Levelised cost of energy; MUP, Multi-use platforms; MUS, Multiple-use
of space; NPV, Net present value; OPEX, Operational expenditure after first operation (includes CAPEX items); NPV/CAPEX, Profitability index; WACC, Weighted
average cost of capital or discount rate; CS, Case Study
Corresponding author.
E-mail addresses: g.dalton@ucc.ie (G. Dalton), thb@aquabt.com (T. Bardócz), MJB@bvgassociates.co.uk (M. Blanch),
david.campbell@albatern.co.uk (D. Campbell), K.R.Johnson@hw.ac.uk (K. Johnson), aquacultureprofessional@gmail.com (G. Lawrence), lilas@aegean.gr (T. Lilas),
efm@wavedragon.net (E. Friis-Madsen), neumann@seaweedenergysolutions.com (F. Neumann), nnik@aegean.gr (N. Nikitas), saul.torres@unican.es (S.T. Ortega),
D.Pletsas@swansea.ac.uk (D. Pletsas), pedro.diaz@unican.es (P.D. Simal), hcs@wavedragon.net (H.C. Sørensen), sttm10028@stt.aegean.gr (A. Stefanakou),
i.masters@swansea.ac.uk (I. Masters).
Renewable and Sustainable Energy Reviews 107 (2019) 338–359
1364-0321/ © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license
(http://creativecommons.org/licenses/BY/4.0/).
T
macro and micro assessment methods will be particularly useful in other Blue Economy contexts and in other
multiple product contexts.
1. Introduction
Over 70% of the world's surface is the ocean, with more than 40% of
the global population inhabiting the coastal areas [1]. With an ever-
growing population and uses of land areas reaching their limit, it is
timely to focus on the ocean to solve some of the world's major issues
such as security of food, water supply and energy. Significant areas of
the ocean remain unused and can potentially provide opportunity for
economic growth and resource use.
The demand for ocean resources is an important driver of economic
growth. It provides natural resources, access to trade, and opportunities
for leisure activities [2]. The ocean has the potential to become an
important source of clean energy and marine products. Blue Growth
sectors (ocean energy, aquaculture, biotechnology, deep-sea mining
and coastal tourism) present an opportunity to generate economic
growth and jobs, enhance the security of energy supply and support
local produce whilst boosting competitiveness through technological
innovation. The European Commission estimates that there will be
approximately 5.4 million jobs and almost €500 billion of Gross Value
Added (GVA) from Blue Growth in the medium term [3].
As maritime activity increases, however, so does the competition for
space as coastal areas become overcrowded. In anticipation, the EU has
driven an agenda to realise Blue Growth more efficiently through Multi-
Use of Space (MUS) and Multi-Use Platforms (MUP). However, there
has been a lack of robust techno-economic analysis examining the
economic viability of MUS/MUP combinations of Blue Growth [4–7].
This had led to a lack of confidence from investors in both the technical
and the economic viability of sharing marine space, and sharing plat-
form services [8]. A particular issue is that the additional complexity
adds to the (perceived) risk of the project. Consequently, the EC
awarded the Maribe H2020 project (https://maribe.eu) under the BG5
1
call for projects. The scope of the call was to determine if there is a
future for investment in the combining Blue Growth sectors together in
MUS and MUP. Key findings from the project are presented here.
The aim of this paper is three-fold: first to present the background
context of Blue growth and MUS/MUP (policy and business cases).
Secondly to introduce the Maribe H2020 project, objectives and
methods. Finally, the paper presents the techno-economic modelling
and results of the three most interesting case studies. The further key
findings of Maribe are reported in recently published book: Building
Industries at Sea: 'Blue Growth' and the New Maritime Economy [9].
Part 2 of the paper presents a review of Blue Growth policy, then the
state of the art of the most successful companies and enterprises in the
Blue Growth sector, as well as combinations of Blue Growth, under the
various sectors of ocean energy, offshore wind energy and offshore
aquaculture.
Part 3 presents the structure of the Maribe project, and a description
of the novel methodology for selecting and ranking the most viable
combinations of Blue Growth sectors, in a staged approach. Existing
companies and sector experts engaged with the Maribe team in co-
creation, developing business plans and financial models which led to
both improved business value propositions and robust assessment of
investment readiness for Blue Growth and MUP concepts. The approach
identified technical and non-technical barriers to the business and
calculated economic performance, using a suite of techno-economic
indicators that enabled the balanced comparison of economic perfor-
mance across vastly differing technical combination projects. The
indicators included: levelised cost of energy (LCOE), net present value
(NPV) and internal rate of return (IRR). This enabled comparative
analysis with other energy sources, gross benefits and efficiencies.
Finally, Part 4 of the paper presents the techno-economic modelling
results of three case studies examining the feasibility of the Blue Growth
sectors in MUS/MUP projects
2
:
– Albatern and Aquabiotech: Wave Energy combined with finfish
aquaculture in the Mediterranean (MUS)
– Wave Dragon and Seaweed Energy Solutions: wave energy com-
bined with seaweed farm in Welsh waters (MUS)
– Ecowindwater: Floating wind energy and desalination in Greek
waters (MUP)
Discussion and conclusions draw these findings together with socio-
economic factors and put them into a wider context.
1.1. Definitions
To understand the range of options for MUS/MUP the following
definitions are proposed (see also video discussion
3
)
1.1.1. MUS: Multiple use of space
Any combination of Blue Growth sectors, or Blue Growth and Blue
Economy sectors that share the same location but that have no common
platform. MUS can share the same infrastructure such as cabling and
substations.
1.1.2. MUP: Multi-use platform
Any two Blue Growth sectors, or any Blue Growth + Blue Economy
sector that share the same location but also share the same platform
facility. Mutual benefits (technical or economic) to both entities enable
the production and export of at least 2 products.
Further to this, Maribe split the MUP into 3 different types:
Type 1 MUP service platform (auxiliary): providing services to
the combined Blue Growth and Blue Growth and Blue Economy entities
surrounding it (e.g. processing, storage, energy, water & habitation) to
enable their operations.
Type 2 MUP multiple production platform: hosting technologies
of two or more combined Blue Growth & Blue Growth + Blue Economy
entities yielding at least two products for export (e.g. desalinated water
+ electricity both exported; exported electricity produced from wave
and wind)
Type 3 MUP combining a service platform with a multiple
production platform: yielding at least two products for export (e.g.
mixing a floating storage facility with an on-board fixed wind turbine
+ desalination).
2. Blue Growth context and state of the art
2.1. Blue Growth policy background
In 2007, The European Commission published the Integrated
Maritime Policy for the European Union [10] which reinforced the view
1
https://ec.europa.eu/research/participants/portal/desktop/en/
opportunities/h2020/topics/bg-05-2014.html.
2
The paper presents the ‘commercial business case’ results only for each
study. Maribe also conducted ‘pilot stage’ techno-economic studies which for
each case study; these are not presented in this paper, but are available in the
Maribe full reports for each case study.
3
http://maribe.eu/category/cordinator-interviews/.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
339
that growth and development of EU level maritime industries would
benefit from coordinated and streamlined sea basin level initiatives. In
2008, the European Commission (EC) stated that “Harnessing the eco-
nomic potential of our seas and oceans in a sustainable manner is a key
element in the EU's maritime policy” [11]. The EC Blue Growth Strategy
[12] in 2012 considered the potential of Blue Growth to contribute to
the objectives of the Europe 2020 Strategy [13] as well as greenhouse
gas emission reduction goals. The strategy conformed to wider reg-
ulative elements applicable for all maritime regions, thus providing a
strategic framework for development. These include the Marine
Strategy Framework Directive (MSFD) adopted in 2008 [14] and the
Maritime Spatial Planning (MSP) Strategy [15]. MSP will be particu-
larly important to establish synergies with existing maritime activities
(e.g. shipping, fishing) while MSFD is essential for maintaining good
environmental standards including biodiversity, which can impact in-
dustries such as aquaculture or tourism. The potential of offshore wind
received particular attention, with a dedicated Communication on off-
shore wind energy [16]. The strategy includes five developing areas in
the ‘Blue Economy’ that could create jobs in coastal areas:
1. Aquaculture
2. Coastal tourism
3. Marine biotechnology
4. Ocean energy
5. Seabed mining
Blue growth in Europe is divided into Seven European Sea basins, to
encourage tailor-made measures and to foster cooperation between
countries. For most of the 7 basins, there is an individual MSP as well as
an Action plan, and these are listed with references in Table 1. For
example, in 2013, the Maritime Affairs published recommendations for
the sea basins: “Blue Growth, opportunities for marine and maritime
sustainable growth” [17].
One of the most developed Action Plans is the Atlantic Action Plan
[39–41]. The Atlantic Action Plan embraces Blue Growth in its strategy
and recognises the importance of collaborative research and develop-
ment and cross-border cooperation to boost its development. The un-
derlying objective is to identify investment and research priorities in
the Atlantic sea-basin that could be considered for EU financial support
in the programming period of 2014–2020. Based on the above, the four
priorities of the Atlantic Action Plan are:
1. Promote entrepreneurship and innovation;
2. Protect, secure and enhance the marine and coastal environment;
3. Improve accessibility and connectivity; and
4. Create a socially inclusive and sustainable model of regional de-
velopment;
Ecorys [42] studied Atlantic Arc Blue Growth, and described the
maritime economy in terms of 11 economic activities, assessed from a
qualitative and quantitative perspective. The methodology and
approach was aligned with similar studies for other sea basins.
The European Commission, through its Seventh Framework
Programme for Research and Technological Development (FP7) funded
the SEAS-ERA (2010–2014) [43] project which aimed to improve co-
ordination, promote harmonisation between national and regional re-
search programmes and at the same time foster synergies at regional
and Pan-European level. The project brought together 21 partners from
18 countries with the intention of strengthening maritime research
across the European Union. The project also contributed to the Atlantic
Research Plan, publishing its own report for the Atlantic [44]. Among
the main findings were the needs for increased ocean observation in-
frastructure (e.g. vessels, observatory) and monitoring (including
seabed mapping) to gather relevant data. Such a data set provides
baseline data to establish “Good Environmental Status” under the
MSFD, a first step towards licencing of new Blue Economy projects.
The challenge for Europe is to develop a positive vision for the fu-
ture and manage this process to achieve this in a sustainable manner
while maximising benefits for maritime stakeholders and the EU
economy as a whole. Five key challenges that lie ahead for Blue Growth
in Europe are:
1) Building on the existing experience & position EU as a maritime
industries world leader, and technology exporter.
2) Making best use of EU sea space and infrastructure
3) Maintain and enhance the “good environmental status
4
” of Eur-
opean Seas under MSFD [45].
4) Achieving additionality by accelerating both the pace and scale of
investment and job creation beyond that which is possible for in-
dividual EU member states.
5) Responding to regional distinctiveness within EU seas by re-
cognising regional differences in resource distribution environ-
mental sensitivities, patterns of resource use and socio-cultural and
economic priorities.
The EU 2017 report “Report on the Blue Growth Strategy: Towards
more sustainable growth and jobs in the blue economy” [46] praised
the progress that Blue growth had made in 5 years, and was optimistic
on the potential of Blue Growth to add to EU wellbeing and sustain-
ability. The latest initiative by the EC in 2018 is the Blue Invest
5
plat-
form throughout Europe. The program promotes a series of match-
making events for blue economy entrepreneurs, innovators and
investors.
2.2. Review of EU funded FP7 “Ocean of Tomorrow”
Based on the sustainable Blue Growth policy described in Section
Table 1
The seven European basins, listing existing cross border MSP policies and basin Action Plans.
Basin Strategy Plans Ref Cross Border MSP Ref Action Plan Ref
Atlantic Ocean [18] SIMCELT, TPEA & SIMNORAT [19–21] Atlantic Action Plan [17]
Baltic Sea [22] Plan Bothnia & BaltSeaPlan [23,24] HELCOM [25]
Black Sea [26] MARSPLAN [27,28] Black Sea Action Plan [29]
Mediterranean Sea 1 [26] BlueMed [30] UNEPMAP [31]
2 SUPREME – east Med [32]
*
3 SIMWESTMED - west Med [33]
*
Adriatic and Ionian Seas [34] ADRIPLAN [35]
*
North Sea [36] MASPNOSE [37]
*
Arctic Ocean [38]
* *
* under development.
4
http://ec.europa.eu/environment/marine/good-environmental-status/
index_en.htm.
5
https://ec.europa.eu/fisheries/blueinvest-2018-ocean-opportunity-right-
backing_en.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
340
2.1, the EC designated €12M of FP7 funding to Oceans of Tomorrow
7
(OoT) projects in 2011 [47]. MUS/MUPs were considered at a ‘blue sky’
level of thinking and multiple possibilities were explored up to a
Technology Readiness Level (TRL) of 4. Díaz-Simal [48] reviewed the
projects and can be summarised as follows:
1. Tropos
6
: (completed 2014) There were 4 technology projects ex-
plored under Tropos.
1. Floating Hotel
2. Taiwan shipping terminal
3. Offshore wind service hub
4. Aquaculture and renewable energy.
All projects were at TRL 3/4. The capital expenditure for all projects
was high, and the financial analysis resulted in negative Net Present
Value (NPV). The review highlighted that there were uncertainties in
the CAPEX estimates.
2. Mermaid
8
: (completed 2014) There were 4 technology projects
explored under Mermaid.
1. Wind/wave platform in Spain
2. Aquaculture and renewables in Adriatic
3. Fixed wind and aquaculture in Baltic
4. Fixed wind and mussels in Netherlands.
The review identified one promising project: floating wind/wave
device in Spain, conditional on a sufficiently high feed-in tariff.
3. H2Ocean
9
: (completed 2012) H2OCEAN was a project aimed at
developing economically and environmentally sustainable very
large multi-use open-sea platform. Renewable energy included wind
and wave power. The MUP would convert some of the energy into
hydrogen that can be stored and shipped to shore as green energy
carrier as well as supply a multi-trophic aquaculture farm. CAPEX in
€Billions, results had very large negative NPV. Independently,
Maribe also considered large MUP and undertook two case study
developments for proposed projects:
1. Grand Port Maritime Guyana
10
TRL3 Floating shipping terminal,
aquaculture and Oil and Gas. Case study in Maribe.
2. Float Inc USA TRL 4: Very large-scale shipping terminal with wave
energy power integrated in MUP structure. Case study
11
in Maribe.
In summary, the common theme of these Ocean of Tomorrow pro-
jects is aligned to the policy driven, “top down” nature of the funding.
Many of the projects considered large scale complex MUP solutions
which can only be funded with significant subsidy. The high CAPEX and
additional costs associated with operation offshore makes many of
these systems non-competitive with land based competitors.
The Oceans of Tomorrow projects were followed up in the H2020
(FP8) programme and by two projects in particular - Maribe (Marine
Investment in the Blue Economy www.maribe.eu) completed in 2016
and MUSES (Multi-Use in European Seas https://muses-project.eu/)
completed in 2018. Maribe is described in Part 3.1 of this paper. MUSES
builds on previous projects and existing knowledge to respond
positively to the challenges of regulation and the preservation of eco-
system services. It seeks to mitigate the risks of multi-use developments.
In 2018, two new EU project in Blue growth have been awarded and
started:
1. Space@Sea
12
: to provide a workspace at sea by developing a stan-
dardised and cost efficient modular island.
2. Blue Growth Farm
13
: design multipurpose offshore floating plat-
form, hosting aquaculture, energy harvesting and test in NEOL tank
at TRL5.
2.3. Review of existing Blue Growth MUS and MUP: existing companies and
techno-economic studies
2.3.1. Offshore wind (floating or fixed) sharing with aquaculture and
shellfish farms
There are few examples for this type of MUS sharing and almost all
examples are shellfish rather than cage aquaculture. One example is a
study carried out for the Shellfish Association of Great Britain (SAGB)
by a Project Team led by Aquafish Solutions Ltd
14
who assessed co-
location with offshore wind. To date, offshore wind farms have been
extremely reluctant to share space, both due to perceived added un-
necessary risk as well as the disproportional scale of investment with
aquaculture being very small compared to that of offshore wind.
However, recent MSP and national legislation pressure is now en-
couraging offshore wind farm developers to consider other Blue Growth
in their business models. For example, a Belgian consortium,”Noordzee
Aquacultuur”,
15
of research institutions and companies has started a
project to investigate if mussels could be grown on offshore wind farms.
Wageninen University have explored the viability of aquaculture
mussels with fixed offshore wind, based on outputs of the Maribe
project.
16
Van den Burg et al. [49] assessed the techno-economic via-
bility of co-locating a mussel farm (producing both mussel seed and
consumption-sized mussels with semi-submerged longlines) amongst
the yet to be deployed Borssele fixed offshore wind farm in the Neth-
erlands. The economic results for the combination showed positive IRR
results. Jansen et al. [50], showed a positive economic outlook for
mussels with offshore wind in the North Sea. Finally, Bas et al. [51]
considered the more general socio-economic benefits of co-locating
aquaculture with offshore fixed wind. A lack of information to under-
take a thorough social cost benefit analysis made definite conclusions
difficult but the multi-use scenario is expected to be sustainable con-
sidering current policy and institutional frameworks, as well as the
environmental and socio-economic effects.
Bartelings et al. [52] in the Netherlands conducted an economic
study of combining Mussels and seaweed in the area of a fixed wind
farm. Their study concluded that mussel production was highly prof-
itable, bringing an additional profit of ca. €38 million. Seaweed culti-
vation was not profitable at the current price for seaweed. Another
study by Buck et al. [53] in German waters states that production of
consumer mussels with longline technology is sufficiently profitable
even under the assumption of substantial cost increases. If existing
vessels and equipment can be used this further reduces risk and in-
creases profits. An alternative market for the cultivation of seed mussels
depends on using existing equipment to be profitable at typical seed
mussel prices.
Finally, two papers explored the socio-economic implications of
7
http://www.gppq.fct.pt/h2020/_docs/brochuras/bioeco/ocean-of-
tomorrow-2014_en.pdf.
6
http://www.troposplatform.eu/.
8
http://cordis.europa.eu/result/rcn/183781_en.html.
9
http://www.h2ocean-project.eu/.
10
www.portdeguyane.fr/.
11
http://maribe.eu/download/2505/.
12
https://spaceatsea-project.eu/.
13
http://www.thebluegrowthfarm.eu/.
14
http://www.offshorewind.biz/2013/08/05/shellfish-aquaculture-offshore-
wind-farm-study-completed-for-sagb-uk/.
15
https://www.offshorewind.biz/2017/06/02/belgians-start-growing-
mussels-on-offshore-wind-farms/.
16
http://maribe.eu/download/2511/.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
341
combining aquaculture with fixed wind. Griffin et al. [54] also shows
that cooperation between aquaculture farms and fixed offshore wind
farms are a positive viability based on potential cost sharing whilst also
demonstrating social benefits. Krausse and Mikkelsen [55] state that the
main barriers to overcome are unresolved issues of ownership of the
process, i.e. which stakeholders are involved in the consent procedure
and their relative influence. Furthermore, socio-economic dimensions
in aquaculture operation, e.g. emotional ownership of the sea/coastal
area by the local residents/stakeholders and the social values that drive
this ownership are difficult to capture in such remote offshore settings.
2.3.2. Offshore wind sharing with wave energy
The Netherlands government has mandated that marine space for
offshore wind must also be shared with other forms of renewable en-
ergy [56]. This policy particularly favours wave energy and conse-
quently the WaveStar UPWAVE
17
project, won a H2020 project in
MUS,
18
where it received planning permission to deploy within a co-
operative offshore wind farm, ParkWind. Unfortunately, private
funding and licencing problems prevented the project proceeding, de-
spite EC funding.
Chozas et al. [57] compared the electricity network balancing costs
of a range of diversified wind/ wave power plants compared with a
system based only on wind power (Pelamis, Wave Dragon, WaveStar
and a fixed wind turbine). Results showed balancing costs of wave
converters are 35–47% smaller than those solely based on wind tur-
bines. When wave converters are combined with wind, balancing costs
keep low, 45% lower than for wind turbines alone. Perez Collazo et al.
[58] conducted a technical review of combining wave energy with
offshore wind, the scope was to consider substructures, wave energy
conversion systems and performance. The review focused on fixed wind
technologies rather than floating. Operations and maintenance was
included in the review; however, economics of the combinations was
not carried out. Astariz et al. [59,60] examined the potential cost re-
ductions in co-located offshore fixed wind and wave farms and con-
cluded that energy cost is reduced by more than 50% relative to stand-
alone wave farms.
The following reviews explore MUP of wind and wave together in a
single platform:
Floating Power Plant P80
19
: (Denmark, TRL 6), ½-scale prototype
trialled for 1.5 years up till 2015. The full scale P80 will be a single
wind turbine ranging from 5 MW to 8 MW, plus 2–3.6 MW wave power
W2Power
20
: (Norway, TRL2, 10 MW) two corners of the triangle
support one wind turbine each and the third corner houses the power
take-off for the wave energy conversion system.
O'Sullivan [61] examined a singular wind-wave energy platform
hybrid system, which included sharing space, transmission infra-
structure, O&M activities and a platform/foundation. An economic
analysis of the system was undertaken, considering a 210 MW hybrid
farm and it was found that the hybrid produced energy at a cost of
€0.22–0.31/kWh depending on the source of funding for the project.
This device and Floating Power Plant were two of the nine projects
subject to micro assessment by Maribe.
Castro-Santos [62] examined two specific hybrid systems: the
W2Power and the Poseidon. Results for two locations in Portugal (São
Pedro de Moel and Aguçadoura) indicate that the exploitation, manu-
facturing and the installation costs are the most important ones, with
the exploitation cost being the most important for the W2Power and the
manufacturing cost being the most important for the Poseidon. The
Levelised Cost Of Energy (LCOE) for both devices in both locations
ranged from €400–600/MWh, which is high compared to fixed wind.
Castro-Santos et al. [63] reviewed the economic viability of floating
wind versus wave energy and their combinations. Santos concluded
that Floating offshore wind co-located with wave systems are not as
economically viable as floating wind systems by themselves.
2.3.3. Wave energy sharing with aquaculture
Finnish wave developer Wello
21
has a diversified business model by
marketing next generation technologies to onsite generators. The
company will adopt its PowerModule power take-off unit for systems to
be installed at fish farms and other remote installations
22
.
A group of Chilean companies are analyzing the wave energy po-
tential in the Valparaiso Region, Chile. According to Revista
Electricidad,
23
a group of local and foreign companies are working
together with the Valparaiso Region's government to evaluate the po-
tential of wave energy of the region, with the specific interest in Ro-
binson Crusoe Island. The collaboration aims to install a wave energy
device capable of producing both electricity and desalinated water to
aid the aquaculture sector of the region. Zanuttigh et al. [7] explored
the technical deployment of Wave Dragon and aquaculture farm off
Sardinia Island, Italy, using 8 MUP schemes combining in different
ways a fish farm, a wind and a wave energy installation and either a
stand-alone or a connected-to-grid solution. They concluded that the
combination was technically feasible, with reasonable costs. However,
a full techno-economic evaluation was not performed. Wave Dragon are
included in one of the case studies in Part 4 below.
Zanuttigh et al. [64] also conducted a study for combined use in the
Adriatic. The project examined 12 MUP schemes combining in different
ways a fish farm, varying sizes of wind, (floating or fixed), wave energy
installation and either a stand-alone or a connected-to-grid solution.
The MUP concepts have been ranked accounting for the expected
benefits related to production and technological innovation, the im-
pacts on local and costal environment, the installation and maintenance
costs, and the risks due to structural, geotechnical, electrical failures,
and pollution. The project concluded that the best combination was the
stand-alone MUP integrating the fixed wave energy devices, the mini-
wind and the fish farm. The preference for the stand-alone solution is
mainly given by the large distance of the MUP from the shore, which
increases the costs significantly, and by the strong impact that power
cables would have on the soft bottom assemblages in this area.
Foteinis et al. [65] conducted a review of mixing wave energy with
6 combinations of Blue Growth, including tourism, and desalination.
Foteinis states that “combined offshore aquaculture facilities with
WECs would benefit for reduced installation, operation, and main-
tenance costs, as well as addressing fossil fuel dependence in aqua-
culture”.
2.3.4. Fixed and floating wind sharing with oil/gas
The ongoing recovery of offshore oil and gas was explored in the
Maribe C4 reports,
24
where renewable energy (6 MW turbines) is used
to sustainably extract oil using pressured air/water injection. Renew-
able power is not yet widely used on offshore rigs in this process or for
everyday oil recovery operations. However, the technologies behind
this process are operating and the use of renewable energy with oil rigs
to reduce emissions from gas or diesel fired generation is under active
consideration. An early example was the Beatrice platform in the Moray
Firth in Scotland where two fixed wind turbines complement the work
of the rig. These are operating at the accepted maximum depth limit for
fixed turbines of 50 m. Most North Sea rigs lie in far deeper waters. The
advent of floating wind turbines opens up new possibilities for oil/wind
17
https://upwavedoteu.wordpress.com/.
18
http://cordis.europa.eu/project/rcn/200258_en.html.
19
www.floatingpowerplant.com/company/.
20
http://www.pelagicpower.no/today.html.
21
https://wello.eu/.
22
ReNews 365, p14.
23
http://tidalenergytoday.com/2015/10/19/chilean-wave-energy-potential-
under-assessment.
24
http://maribe.eu/download/2487/.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
342
MUPs which are explored by Legorburu et al. [66]. The Norwegian state
owned oil company, Equinor (Statoil), is leading this development as a
matter of Norwegian government policy. Some Norwegian rigs in deep
water, but reasonably close to shore, have already adopted terrestrial
renewable sources of power. Floating offshore wind farms moored in
the vicinity of oil rigs can supply power both to the rig and for export in
large quantities to land, while sharing the costs of infrastructure and
operation. Legorburu et al. describe a methodology for identifying the
most suitable sites in the North Sea for such a combination.
2.3.5. Desalination combined with other Blue Growth sectors
To date, there have not been many research publications exploring
desalination in multiple use scenarios. Desalination needs an accom-
panying energy source and is energy hungry. Conventional desalination
is normally produced by fossil fuels either directly or indirectly, making
the process not environmentally friendly. Desalination can be produced
using renewables, thus becoming more sustainable. Moreover, renew-
able powered desalination will benefit from increased social accep-
tance. However, Ecowindwater
25
installed a (TRL5) 20 m x 20 m plat-
form in Greece from 2012 to 2014 comprising a 35 kW wind turbine
with a 10 kW reverse osmosis desalination unit to produce 70 m
3
per
day. Further development of this business model is given in part 4
below.
Katsaprakakis [67] examined an offshore wind ‘Pumped Storage
System’. In times of excess electricity, and where the storage capacity is
exceeded, the study modelled the production of desalinated water. The
results concluded that the process exhibited attractive financial per-
formance without needing any subsidies”. Foteinis et al. [65] conducted
a review of mixing wave energy with desalination. Foteinis concluded
that “wave energy can directly provide pressurized seawater for reverse
osmosis desalination plants, thus achieving significant energy, and re-
duction of cost and environmental footprint”.
He et al. [68], explored the use of “100% off-shore wind power,
adopting variable condition optimal control to maintain energy con-
sumption per unit due to wind power fluctuation”. A large offshore
desalination plant powered by offshore wind increases return on in-
vestment of offshore wind farms and increases utilization. Offshore
location solves the point source pollution problems caused by on-shore
seawater desalination. Tsai [69], also explored large scale desalination
powered by offshore wind, gas-turbine and hydroelectric power plants;
desalination plants and water-storage tanks and reservoirs are included
within the water- supply system. Existing hydroelectric power units
were used in combination with offshore wind to assist with peak load.
The results showed that the proposed model can fulfil the water re-
quirement of a city the size of Taichung by 2030 at a reduced carbon
footprint. The greater expense from desalination could be compensated
by the savings accrued from the power sector.
The following Table 2 is a review summary of the cost of production
of desalinated water (sometimes referred to as Levelised Cost of Water
(LCOW)) from various energy sources. The cost of production is not the
same as cost of sale. The cost of sale includes transport costs and other
energy related costs, as well as a profit margin. Therefore, cost of
production costs are consequently relatively low, and can be mis-
representative of real costs. Furthermore, in small islands, in particu-
larly Greece, the fossil fuel energy used to produce desalinated water is
heavily subsidised, thus further distorting quoted production costs of
desalinated water. It can be observed from Table 2, that there is a large
variation of production costs of desalinated water.
3. Analysis of the Blue Growth business sector and proposed
assessment methodology
3.1. Maribe project: introduction and methodology
3.1.1. Maribe project introduction
As part of the Blue Growth initiative of the EC, funding call BG-
05–2014 was awarded to Maribe (https://maribe.eu) as a Coordination
and Support Action (CSA) project to investigate the economic business
case of Blue Growth and MUS and MUP. The primary objective of
Maribe was to promote smarter and more sustainable use of the sea
through more efficient use of space and resources. It investigated the
potential of combining maritime sectors in the same location or on a
specifically built platform and paid particular attention to emerging
industries that could benefit greatly from the synergies created, in-
creasing their chances of survival and future growth [76]. The Maribe
project covered the five ‘Blue Growth (BG)’ sectors; aquaculture, energy
(wave and tide), energy (offshore wind), biotechnology and seabed
mining. Maribe also included the four ‘Blue economy’ (BE) sectors;
fisheries, offshore hydrocarbons, shipping and tourism.
3.1.2. Macro assessment methodology
The first four Maribe work packages consolidated understanding of
the Blue Growth sector and formed a macro assessment of the business
potential. The following is quoted from the Maribe website:
1) WP4
26
: A study on “Socio-economic trends and EU policy in the off-
shore economy”, reviewed each sector from a business lifecycle and
socio-economic perspective. Policy and planning frameworks were
reviewed for each of the sea basins: Baltic basin, Atlantic basin,
Mediterranean and Black Sea basin, and the Caribbean Basin.
2) WP5
27
: A study on “Technical and non-technical barriers facing Blue
Growth sectors”, looked at barriers by sector and also by combination
and to identify the barriers that exist when two sectors shared
marine space or multi-use platforms. Maribe also conducted risk
assessment and mitigation assessment for MUP [77].
3) WP6
28
: An “Investment community consultation” assesses the current
investment environment, as well as best practices and key barriers
for investment;
4) WP7
29
: A “Business model mapping and assessment” analysed and
mapped the business models that lie behind Blue Growth/Economy
industries. Fig. 1 presents the 5 BG and 4 BE sectors, and presents
examples of companies operating in the sectors. The image visua-
lises how the companies and their related supply chains can have
shared and interconnected business models. Fig. 2 presents an ex-
ample of a generic model for an Ocean energy company using the
Table 2
Cost of production of desalinated water ($/m
3
) using a variety of energy
sources. *Costs converted from to $ at €0.8 = $1.
Energy Source Reference Cost estimate
Fossil [70] 0.16*
Fossil [71] 0.30–1.18
Autonomous production (newer and larger plants) [72] 0.4–2.8*
< 0.96
Off-grid connected RO-PV [73] 0.183
Electricity and Diesel [73] 0.166–0.346
Wind [74] 3.9–6.5 BW
6.5–9.1 SW
5.2–7.8 MVC
Wave energy (WavePiston) [75] 1.30
Wave energy (Resolute marine) 1.83
SunPower's PV 0.78
Cost of transport of fresh water from land to Greek
islands by boat
8.32*
25
www.ecowindwater.gr/ViewShopStaticPage.aspx?ValueId=1995.
26
http://maribe.eu/blue-growth-deliverables/blue-growth-work-packages/.
27
http://maribe.eu/download/2581/.
28
http://maribe.eu/download/2575/.
29
http://maribe.eu/download/2569/.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
343
Business Model Canvas.
30
Adoption by BG companies of business
model methods at an early stage in development will ensure that
their project will develop more successfully to commercial stages.
3.1.3. Assessment methodology
Building on the above four workpackage deliverables, the Maribe
consortium conducted 4 stages of review and rating exercises to derive
a final list of potentially viable BG companies and projects. Therefore,
presented here is a novel multidisciplinary methodology for selecting,
filtering and ranking business propositions as outlined in Fig. 3.
3.1.3.1. Step 1. Each of the 11 sectors (5 Blue growth + 4 Blue
economy) were combined in pairs to form MUS and/or MUP,
resulting in a total 69 combinations pairs examined. The 69
combinations were then also reviewed relative to the 4 Maribe
basins: Atlantic, North Sea/Baltic, Mediterranean/ Black Sea, and the
Caribbean. The potential for each combination pair was rated from a
technical, environmental, socio-economic, financial and commercial
perspective (the evaluation template
31
rated 1–5 for each criteria, 5
being the highest).
3.1.3.2. Step 2. In preparation for the rating exercise, Blue Growth
combinations reports were written covering a wide range of sectors,
and possible combinations. Each report contained a justification why
there was potential for that combination based on evidence of existing
companies in the sector, or the potential based on the expertise of the
authors of the reports. Out of the 69 combinations, the 24 highest rated
potential Blue growth combinations were selected and published.
32
The
Maribe website presents 11 of these promising combinations,
33
which
did not make it to the case study stage, either due to lack of companies
to match the combination, or the rating wasn’t sufficiently high enough.
3.1.3.3. Step 3. The next task was match real Blue Growth company
examples with each of the shortlisted 24 Blue Growth combinations.
Businesses were contacted to establish their willingness to participate in
Maribe as a case study in developing their business models. The most
important criteria for acceptance as a case study was that the company
(or combinations of companies) would be willing to divulge economic
information on the company performance, and future estimated
commercialisation costs to the Maribe consortium (under NDA). The
requirement to share sensitive information was challenging to many
companies and restricted them from participating in the case studies.
Eventually, 9 companies were sourced to provide 9 case studies
combination concepts.
34
Each of the 9 case studies had a business
case report completed for them involving co-creation of the case study
including business plan, risk assessment and financial evaluation,
Fig. 1. Five Blue Growth and four Blue Economy sectors presented in an interlinked Business model map: Companies from each sector are presented, and interlinks
between the sectors and companies are detailed (image created by BMI Netherland (http://www.businessmodelsinc.com/) for Maribe project, for use in dis-
semination).
30
https://strategyzer.com/canvas/business-model-canvas.
31
https://www.dropbox.com/s/a5paebsom75tzmn/Atlantic%2069%
20combinations%20rating.xlsx?dl=0.
32
https://www.dropbox.com/s/qa61mqw8aqz9hrf/Final%20Combination
%20Selection.xlsx?dl=0.
33
https://maribe.eu/blue-growth-deliverables/case-studies-with-no-
company/.
34
http://maribe.eu/blue-growth-reports/case-studies-with-companies.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
344
followed by expert panel review and ranking.
3.1.3.4. Step 4. The 9 case studies were ranked on performance by
indicators. Section 4.1 of the paper describes the filtering process, and
then presents the final three case studies selected for discussion here.
3.2. Maribe assessment parameters and indicators
To model the economic performance of the combinations under as
consistent conditions as possible, standard economic metrics were used
in the techno-economic modelling (Table 3) and Table 4 presents the
tariff input rates and other revenue sources used. In addition, the fol-
lowing assumptions were adopted:
Comparable point of the product life cycle
The project cost model was assumed to occur after the second
commercial scale project has been delivered. This is the point in the
project lifecycle where costs will have stabilised somewhat, so it can
be meaningfully compared with existing commercial marine pro-
jects such as offshore wind. On the other hand, this point is not too
far in the future so that its cost can be meaningfully extrapolated
from the companies' current knowledge.
Similar time of build
The work completion date was assumed to be 2020, with final in-
vestment decision (FID) in 2016. In reality, different combinations
will have different timescales but this avoids the uncertainty in
predicting changes to underlying costs such as the price of steel and
inflation over time.
Using consistent weighted average cost of capital (WACC)
The default WACC value was assumed to be 8.9%, in line with that
used by the UK Government Department of Energy and Climate Change
in 2016 when assessing energy technologies (Table 3). As an exception,
the Greek project used a WACC of 7.9%, due to perceived lower risk due
to higher government participation in funding the project resulting in a
lower cost of capital. Some commercial offshore wind projects are
known to have achieved a lower cost of capital, but it is unlikely that
early commercial projects will secure low loan interest rates.
Maribe used 8 model parameters/ indicators to assist in the complex
assessment of multiple Blue Growth sector combinations, and their
performance relative to each other. Some of these such as LCOO and
Cost Comparator are modified indicators, and therefore could be con-
sidered novel. These indicators are described in the next sections.
3.2.1. Levelised cost of output (LCOO) for mixed Blue Growth combinations
To enable comparisons that include combinations of one Blue
Growth sector with another Blue Growth Sector that have differing
products (e.g. wind generated electricity in €/MWh and aquaculture in
€/kg), an alternative levelised cost of output (LCOO) was devised by the
Maribe project. LCOO is the annualised cost divided by annual revenue
and is used instead of levelised cost of energy (LCOE) where annualised
cost is divided by annual energy yield. LCOO is expressed as a per-
centage. As with LCOE, the lower its value, the better its financial
performance. Where it is greater than 100%, then the costs are more
than the revenue. Its value depends on the sell price of the product,
which is different to LCOE where value is dependent only on the cost of
product. LCOO is a measure of profit and it is relatively simple to show
that (1-LCOO) is mathematically equivalent to net margin. The Maribe
project steering committee decided not to use ‘industry-standard com-
parator’ for each of the technologies in the combination (e.g. LCOE for
Fig. 2. Generic business model for ocean renewable energy technology developer [78] ( image created by BMI Netherland (http://www.businessmodelsinc.com/ for
Maribe project for use in dissemination).
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
345
the energy conversion devices), with the shared costs of the platform or
marine space divided between the technologies for the numerator of
each, as this approach is only feasible for MUS combinations. One of the
paper's cases studies is a MUP, and dividing costs like ‘allocating
overhead costs in a business’ is not so simple. An investor is faced with
investing in one project and LCOO as a way of measuring the whole
project and not based on an arbitrary spilt. It may well be that one of
the combinations is poorer than typical of its sector but by combining
with another sector the overall combination is a better investment.
3.2.2. Cost comparator
The ‘Cost Comparator’
35
method has been modified by Maribe
modellers for the purpose of this project. It compares the project LCOO
against that of the project's closest competitor at Commercial phase.
The Cost Comparator logic is based on the premise that it is likely that
the investors will not invest if the LCOO is not “At Least as competitive as its
Fig. 3. Maribe Flowchart describing methodology for selection of most favourable Blue Growth sectors, leading to selection of final 3 case studies for the paper.
Table 3
Standard financial metrics definitions (Dalton et al. [81]).
Metric Definition
Cost of finance The amount of money needed to provide the return to debt and equity investors. Calculated using WACC.
WACC ‘Weighted average cost of capital’ resulting from all sources of investment and ownership.
Simple payback The time it takes for the project CAPEX and OPEX spend to be recovered from the revenue, ignoring the cost of finance.
Payback The time it takes for the discounted project CAPEX and OPEX to be recovered from the discounted revenue.
Net present value (NPV) The difference between the present values of all the cash inflows and outflows. The NPV varies according to the year that is assumed to be
'present'.
NPV (yr −4) NPV at a point 5 years before the start of operation, where CAPEX spending has commenced without revenue generation
NPV (yr 0) NPV at the point the project finishes construction work (end of year 0), just before the start of operation (beginning of year 1).
IRR ‘Internal rate of return’ is the return generated on the CAPEX invested (including costs of capital during construction) by the undiscounted
cash flows during project operation. It is also the discount rate at which NPV(yr 0) equals €0.00. hence it provides the maximum financial
cost affordable by the project without entering into losses, IRR is recommended to be above 10% to be attractive to bank finance.
Levelised cost of electricity (LCOE) In some of the Maribe case studies where combination of sectors are energy only (wave+floating offshore wind), LCOE will be used, which
is derived independently of any price or tariff
a
. A central scenario for LCOE for fixed foundation offshore wind with FID in 2016 is €
2016
131/MWh [79]. This corresponds with the baseline LCOEs in DECC Simple Levelised Cost of Energy Model [80].
b
Levelised Cost of Energy
(LCOE) is calculated as "average annual spend"/"average annual energy". Annual spend is the average repayments for CAPEX and any
annual costs. LCOE represents the charge to be levied on each Kwh produce in order to recover the total costs involved.
a
Using LCOE as a comparison indicator should be conducted with care, as explained by Dalton et al. [81], due to the many varying factors inherent in the indicator
calculation.
b
DECC Simple Levelised Cost of Energy Model is designed to show the impact of innovation so its baseline LCOEs are those for FID 2020 if no innovation occurred.
They are effectively those for FID 2016.
35
http://onlinelibrary.wiley.com/doi/10.1002/gas.21809/full.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
346
competitor”. For example, a project with a specific type of wave device
may have an economic performance that looks good against projects
with other wave devices but it needs to perform well against the market
leading projects producing renewable generated electricity such as
offshore wind to actually warrant investment. The Cost Comparator is
in %, and values below 100% are positive for the combination showing
it to be better performing than its comparator, while those above 100%
show it to be worse.
3.2.3. Jobs/km
2
This metric provides a purely socio economic metric, and measures
the spatial density of jobs arising from marine space. The space itself is
becoming increasingly precious and public funding and investment ever
more competitive. Jobs/km
2
(jobs per square km) features infrequently
in the literature and data are presented in Table 5. These are job den-
sities for cities. No references could be found for job densities for pro-
jects.
3.2.4. Jobs/CAPEX
A search by the authors did not reveal any reference where Jobs/
CAPEX metric was used, or statistic results were available.
3.2.5. Profitability Index (NPV/CAPEX)
NPV/CAPEX is another metric not often used in the literature,
sometimes referred to as Profitability Index (PI) or Investment
Efficiency (IE). In the Maribe project, NPV is normalised against
CAPEX, thus allowing comparison of NPV profit returns across a range
projects. It is expected that large CAPEX expenditure projects will ex-
pect large NPV returns, while smaller CAPEX projects will naturally
derive smaller NPV results. Therefore, using NPV solely as a comparison
metric between projects of varying size, is disadvantageous to smaller
projects. The metric is described amongst a list of other metrics in the
following references [87–95]. Unfortunately, accessing the hard data in
the papers was difficult, and NPV/capex results could not be sourced for
this review. The deep sea and oil industry seem to use the metric more
frequently that other sectors. Dalton et al. [96] used a related metric:
NPV/MW.
3.2.6. Business plan score
Business plans were rated out of 5: 5 = best, 0 = not good. The
ratings were based on assessments made of the submitted plans, rated
by Maribe Business plan team in MaREI. The Business plans were based
on the Business Model canvas method (https://strategyzer.com/
canvas). The canvas consists of 9 blocks, with 2 extra sections added
by Maribe. These were: Value proposition, Customers, Channels,
Relations, Revenue, Resources, Activities, Partners, Management,
Competition, Markets. All three of the paper case studies started the
business plan preparation from scratch.
3.2.7. Risk score
A risk matrix was used based on the likelihood and impact (Fig. 4).
The 6 risk categories considered were (quoted by Maribe report):
1. “Operation -all stages”
2. “Economic & Political”
3. “Financial”
4. “Environment”
5. “Socio-Economic”
6. “Health & Safety”
The risk % was calculated as an average of the % of red critical risks
to the overall spread of risks of the 6 risk categories.
Each risk was assessed pre-mitigation, and then post-mitigation
mitigation. Limitations on risk assessment included risk appetite and/or
understanding and/or experience of risk assessment in the offshore by
individual companies involved in the Maribe risk identification and risk
response strategy (published in Williams et al. [77]).
3.2.8. Advisory Panel score and Consortium Partner score
The Maribe project held one project consultation session in Brussels
(called the Advisory Session). Maribe invited 14 advisors to review
pitches made by the companies involved in each combination, based on
their business plans. The Advisory Panel rated each project pitch based
on Business Plan content and delivery of the pitch. The Advisory Panel
scores were scored out of 10: lowest 1; highest 10. Details of the panel
are available.
36
At the end of the Maribe project, the Maribe consortium
partners assigned a review score to each of the case study projects. The
scores submitted by the Maribe consortium partners were based on the
overall rating of the full Business Case report for each project combi-
nation, consisting of the 5 sections of their reports: technical, financial,
business, and risk sections. Similar to the rating score method of the
Advisory Panel, as above.
Table 4
Economic tariff input rates and other revenue sources.
Item Reference Values used in case study modelling
Electricity price sold (wind energy) (€/MWh)
a
[82] 140.0
Electricity price sold (wave energy) (€/MWh)
b
[83] 312.7
Aquaculture finfish (€/ton) Price provided by Aquabiotech
c
5000
Aquaculture seaweed (€/ton)
d
1000
Desalinated water (€/m
3
)
e
2.5
a
The base FiT for offshore wind is €108.30/MWh in Greece in 2012. A 30% increase is possible on a per project basis (hence FiT=€140/MWh).
b
UK Renewables Obligation bands list wave below a 30 MW cap as support of 5 ROCs/MWh in 2016/17. A ROC is worth about £ 43/MWh and electricity about
£ 50/MWh. Assuming that the generator is a licensed electricity supplier, 1 MWh of wave generated electricity is worth 5 * 43 + 50 = 265.0 £ /MWh (€312.7/
MWh). Assume exchange rate is £ 1 = €1.18.
c
Aquabiotech https://www.aquabt.com/.
d
Price provided by Seaweed energy solutions (SES www.seaweedenergysolutions.com/en). Conservative, due to modelling future commercial project. Price
contains several demand uncertainties. Current prices would be rather close to 2000 EUR/ton.
e
EcoWindWater proposes to set a sale price of 2.5 EUR/m3 to sell the desalinated water. Price covers CAPEX and profit required.
Table 5
Jobs/km
2
from referenced sources.
Reference Location and details Jobs/km
2
[84] Employment Centres and the Journey to Work in
Sydney: 1981–2001
2470
[85] “Tokyo has one of the largest Central Business District
(CBD) of the world with 3 million jobs,
58,600
[86–88] Spain (average jobs/km
2
) 293.7
Barcelona 7828
36
http://maribe.eu/2016/05/24/maribe-advisory-sessions-15-16-june-2016-
brussels-belgium/.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
347
4. Three case studies: company description, data inputs and case
study results
4.1. Results of filtering process
Following macro assessment, nine companies agreed to take part in
micro assessment and to provide nine case study combination con-
cepts
43
. For the purposes of this paper, the three most commercially
advanced projects were selected to be presented in the paper,
37
(CS 1,
2, 3) as outlined in Table 6. Only the commercial business cases are
presented in this paper.
38
4.2. Case study 1 (CS1): Wave Dragon and SES
4.2.1. Company descriptions
The project is composed of two companies, Wave Dragon and
Seaweed Energy Solutions (SES), and the independent organisation
Bellona Foundation. Wave Dragon
39
is a private Danish/UK based
company working towards the commercialisation of wave energy con-
verter (WEC) technology to extract electricity directly from ocean
waves. Seaweed Energy Solutions (SES)
40
is a Norway-based seaweed
innovation and business development company. Bellona Foundation is
an independent environmental NGO that aims to mitigate challenges of
climate change through identifying and implementing sustainable en-
vironmental solutions”.
Wave Dragon has deployed a grid connected 1:4 scale pilot 237 t
wave energy converter (WEC) plant in Nissum Bredning,
41
Denmark.
The technology is a floating, slack-moored energy converter of the
overtopping type. The current status of the technology is at TRL 6.
Wave Dragon features regularly in research literature, with many of the
paper topics exploring multiple use [97–105]. The costs and LCOE for
these MUP concepts are given in Table 7.
SES features in the following research publications [106–108]. SES
has proven capacity to cultivate brown seaweed (Saccharina latissima
and other kelp genus) on a large scale (long-lines). It provides a plat-
form for the further development of cultivation technology. An in-
dustrial scale hatchery was built, and it successfully supplied seeds for
100–150 t wet weight biomass. A pilot farm in Frøya
42
is one of the
largest seaweed cultivation farms to date in Europe. Current products
are distributed to a niche food industry market. The technology current
status is TRL 9 for seaweed cultivation in SES.
4.2.2. Strategic roadmap to commercialisation for Case study 1
combination
The combination is planned to be in Welsh offshore waters (Fig. 5).
Wave Dragon will provide calmer waters in its lee for the seaweed farm
as well as provide power for a storm submergence system, which will
increase the operational days and thus make kelp production feasible in
exposed waters (Fig. 6). Wave Dragon has plans for further technology
development at commercial farm scale. SES is looking to improve fur-
ther its harvesting technologies, including mechanisation, and to help
increase harvest volumes. The processed seaweed can be sold as a high
value material for food and health products (nutraceuticals), cosmetics,
animal feed markets, among others.
The commercial development and growth plan for the MUS com-
bination is summarised in Table 8. The pre-commercial pilot project at
TRL7 will be a single WEC overtopping platform incorporating 16
turbines (4 MW) deployed in front of a small 4-hectares seaweed farm
(approx. 80 t/y). The 1st commercial farm at TRL9 will see the project
expanding to 9 WECs with seaweed capacity increased 50-fold. A 2nd
commercial farm will likewise include 9 WECs with a 4000 t/y seaweed
capacity farm at a new site. The business case described here is for the
3rd commercial project at the same site which will see subsequent ex-
pansion into 5 farms of 9 WECs (180 MW) and 20,000t/y of seaweed at
total investment of €661 M (Fig. 6). The project will be located: 13 km
from shore of Pembrokeshire coast in a water depth of 40–60 m and
covering a combined footprint of approx. 3200 × 1700 m. The project
will be cable connected to shore by 33 kV cable with inter array con-
nection of 10–33 kV. The moorings for Wave Dragon will be catenary
chains/ropes; seaweed string will use chains+ropes. The project tech-
nologies will be fabricated at the nearby Port of Milford Haven.
4.2.3. Company perceptions of the advantages of combination
The combination will benefit from an easier licensing process due to
the multiple use of space and will also benefit from positive public
perception due to the combination of two environmentally friendly
products. The seaweed part of the project gains the most from the
partnership due to calmer water provided by wave devices as well as
ready access to power for storm submergence. Expected cost reductions
for either technologies due to synergies in installation, inspection and
maintenance operations will be minimal.
Advantages to Wave Dragon
“Sale of electricity power to seaweed farm”
“Reduction in operational cost by using the same vessel for both
activities”.
“More frequent activities on site: better detection of potential
anomalies”.
Advantages to Seaweed Energy Solutions
The WEC farm allows more days of operation for the aquaculture
venture due to:
“WEC farm will provide calmer waters by nature of the dampening
effect of the devices, which extract energy from the ocean”.
Fig. 4. Risk matrix- Likelihood and Impact.
Table 6
Details of the three Maribe case studies of Blue Growth combinations presented
in the paper and links.
Case
Study
Company 1 Technology 1 Company 2 Technology 2
CS1 WaveDragon Wave Energy Seaweed Energy
Solutions
Seaweed macro
AlgaeDenmark
CS2 Albatern Wave Energy Aquabiotech Aquaculture
FinfishScotland
CS3 EcoWindWater Desalination Same as
Company 1
Floating wind
Greece
37
Another equally important factor contributing to the selection of the 3 case
studies was the fact that all 5 companies were agreeable to have their financial
as well as their case study results published.
38
The pilot business cases were also produced by the Maribe project for each
combination, but for sake of length are not discussed in this paper.
39
http://www.wavedragon.net/ and http://www.wavedragon.co.uk.
40
www.seaweedenergysolutions.com/en.
41
http://www.wavedragon.net/index.php?option=com_content&task=
view&id=12&Itemid=14.
42
http://www.seaweedenergysolutions.com/en/commercial-projects/pilot-
farm-norway.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
348
“Electricity from the WECs can be used to winch the seaweed farms
lower into the water, protecting them from any ill-effects. This will
enable them to be located in areas further offshore which would not
normally be viable. - larger areas, with deeper and cleaner waters,
fewer environmental issues and less conflict of space”.
4.3. Case study 2 (CS2): Albatern and Aquabiotech
4.3.1. Company description
“AquaBioTech Group
43
is an international aquaculture consulting
and technology supply company located on the island of Malta, oper-
ating with clients and projects in over fifty-five countries [109–111].
AquaBioTech uses the Subflex
44
submersible cages technology, as it
considers it as well suited to the offshore application in the Medi-
terranean due to their use of a single mooring point supporting a series
of linked cages, resulting in minimised space use and environmental
impact, as well as the ability to be submerged below the destructive
energy zone of the waves during a storm”.
“Albatern
45
is a Scottish based company. Albatern's wave energy
device is called the WaveNET
46
(Fig. 7)[112,113]. The energy pro-
duced by the WaveNet is relatively small, but is ideal to service small
energy project requirements, as well as projects that require autono-
mous energy supply. Aquaculture farms are an example of an ideal
customer.”
The current status of both technologies is considered to be at TRL 7.
It is based on:
the proven ability of the SubflexTM cage farming technology used
by Aquabiotech and
the level of testing of the Albatern wave energy devices in Scotland
“Albatern is already testing its device in combination with an
aquaculture company Marine Harvest in Isle of Muck, Scotland, at pre-
pilot scale (called the Pathfinder project
47
). WaveNET device is posi-
tioned slightly away from the cages but in a protected environment. The
aim of this installation is to prove the functionality of the system and
give a level of confidence that the WaveNET is a secure system and
there is minimal risk to the cages, as well as to identify any unforeseen
problems that need to be resolved. The technology is yet to be verified
in the less energetic Mediterranean where performance is expected to
be reduced. A “Hybrid” storage system that will convert and store the
wave energy offshore and provide the necessary power on demand is
currently also being developed”.
4.3.2. Strategic roadmap to commercialisation for case study 2
“The two companies have come together to form a Special Purpose
Vehicle (SPV) to provide a one-stop-shop for wave energy enabled
aquaculture solutions to provide electricity for energy intensive aqua-
culture installations”, facilitating commercial cage farming further
offshore. The SPV's value proposition will be to provide autonomous
wave energy power to both existing and new cage farming operations.
“Fish can be produced with a vastly reduced environmental impact by
utilising the renewable electricity provided by the WaveNET devices. It
is envisaged that the WaveNET will also be utilised on more large scale
projects, providing power (and potentially potable water) to shore
based marine aquaculture facilities in areas where wave energy is sui-
tably abundant and supply of grid-based electricity is expensive or
unavailable”.
The targeted market stretches across the globe with the SPV initially
Table 7
LCOE for Wave Dragon case studies.
Source Ref LCOE
Performance and economic feasibility analysis of 5 wave energy devices off the west coast of Ireland. [96] 1–5 MW €0.30/kWh
100 MW €0.15/kWh
Feasibility and LCA for a Wave Dragon platform with wind turbines (at location of 36 kW/m) [104] 7 MW 1 device €0.083/kWh
700 MW 100 devices €0.04/kWh
7 MW Wave Dragon+ 2× 2.3 MW of Wind [104] €0.05/kWh
Fig. 5. Location of the combination of Wave Dragon with SES in South Wales,
UK.
Fig. 6. 2nd commercial farm layout: Wave Dragons at the top and seaweed
farm in lee of Wave Dragons.
43
www.aquabt.com/.
44
https://www.subflex.org/.
45
http://albatern.co.uk/.
46
www.waveenergyscotland.co.uk/news-events/wave-energy-first-for-
scottish-aquaculture/.
47
https://marineenergy.biz/2016/10/21/scottish-waves-to-power-a-
working-fish-farm/.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
349
focussing on the Mediterranean and broader European sea basins where
space for inshore aquaculture farming is fully utilised and now requires
movement offshore. Fig. 8 presents the possible locations for deploy-
ment at various stages of commercial offshore aquaculture development
in Malta. “The SPV's intention is to initially deploy a pilot combination
of one full Subflex cage system able to produce 1000 t of fish serviced
by a WaveNET system and associated Hybrid plant housed in the farm
service vessel. Once proven to be successful, a full commercial scale of
6000 t will be deployed and serviced by a much larger WaveNET grid
and associated Hybrid plant service vessel, which will then be the
commercial demonstrator utilised for the approach to the market”.
The Technical Specs of 3rd commercial scale farm for case study 2
comprises of 96 x Series 6 Wavenet Albatern: (7.5 kW) plus Hybrid
Plant (total 720 kW rated capacity). The WaveNETs will service 48
Subflex cages (each of 7240 m
3
) with target output of 6,000MT per
annum 500 MT/Month. The total footprint of the cages will be
34,560 m
2
, and the WaveNET of 48,000 m
2
. The project would be lo-
cated 5–8 km South-East of Malta Mainland in a water depth of
50–70 m. Power from the WaveNETs will be connected to Service
Vessel by a cable, with Diesel Back-Up. The WavenNETs and the Subflex
cages will have separate moorings: Albatern devices and moorings will
be fabricated by made by Albatern. The Subflex Cages and respective
moorings will be made by Aquabt/Gili Ocean Tech. Ltd./Marine
Contractor.
4.3.3. Company perceptions of advantage of combination
Cost savings are expected to be the big advantage and incentive for
both sectors, technologies and companies. These will come primarily in
“Installation and Commissioning and O/M due to shared vessels”, as
well as “Cost savings on Technical Support Team and Overhead
(Skippers, engineers, workshop, maintenance, Support/Operational
base facilities, Moorings, Key Executives (CEO, MD admin staff)”.
The benefits for Aquaculture company are
“Cost savings on energy due to energy supplied by sustainable
power from on site wave resource”.
“Reduced handling diesel fuel in rougher waters offshore”,
“Wave farm to provide protected calmer water for aquaculture cages
from rough seas, enabling the aquaculture farm to be further off-
shore where clean nutrient rich water exists, higher stocking den-
sities due to the depth and limited environmental impact. It is ex-
pected that the offshore location will vastly increases aquaculture
production capacity and enables the propagation of a wider range of
species farmed in the Mediterranean”.
“Farm serviced by wave-energy has marketing edge of renewably
powered farm produce with sustainable margin at least in the
medium term”.
The benefits for Wave energy company are
“Guaranteed sale of electricity to aquaculture customer”.
“Low electrical losses and cabling costs due to proximity of cus-
tomer”.
“At full commercial scale, the wave energy farm could provide
electricity provision for onshore enterprises and national grids,
which are in constrained grid environment with high power costs
enabling earlier parity achievement”
4.4. Case study 3 (CS3): EcoWindWater
4.4.1. Company description
EcoWindWater
48
(EWW) is a Greek clean-tech company. EWW
value proposition is in addressing the scarcity of freshwater and energy
commodities in identified domestic and global markets by delivering
both fresh water and electricity in a dynamic configuration meeting
customer needs including catering for seasonal fluctuations. EWW's
domestic market focuses around several Greek islands especially in the
Cyclades complex that experience water stress during the high tourism
season and having to import fresh water to meet their needs. The global
market stretches to other island locations in the Caribbean and Canaries
but also to countries of the Middle East that face extremely high levels
of water stress as underground aquifers are depleted and where water
management is becoming increasingly costly.
EWW has trialled the Ydriada MUP platform since 2010 at 1:2 scale
located offshore environment of Heraclea (Fig. 9)[115–121] and de-
livered desalinated water to the grid via a pipe at 70 m
3
/day maximum
capacity. The technology current status is at TRL 6. The corresponding
Fig. 7. Concept Drawing of WaveNET Array Configuration (image permission
from Albatern).
Fig. 8. Planned and existing aquaculture zones of Malta: “Green zone Area 8 is
designated for the transfer cages plan, Red zone area F designated as a future
aquaculture zone for the offshore cages” [114].
Table 8
Wave Dragon/SES project roadmap of deployments to full commercialisation.
Company TRL 8 pre-commercial farm (Pilot) TRL 9 1st commercial farm TRL 9 2nd commercial farm TRL9 3rd commercial farm (Case Study)
Wave Dragon 1 WD @ 4 MW = 4 MW 9 WD; 30 MW 9 WD; 30 MW 45WD@ 4 MW = 180 MW
SES 80 t seaweed/y 4000 t/y 4000 t/y 20,000 t/y
48
www.ecowindwater.gr/ViewShopStaticPage.aspx?ValueId=1995.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
350
Technology Performance Level (TPL) is considered to be at TPL7+ and
the Investment Readiness Level (IRL) positioning is at IRL 4+.
4.4.2. Strategic roadmap to commercialisation for case study 3
The commercial development plan for the technology has three key
stages, currently planned off the coast of Chios Island (Fig. 10):
(I) The first stage is a 800 kW demonstration MUP platform.
(II) The next stage will see the construction of a 2 MW Pilot MUP (2nd
generation MUP).
(III) At commercial level, the 2 MW MUP will be optimised with a
maximum output of 3360 m
3
per day.
Chios Island offers a few ideal sites with water depths of between 50
and 100 m within few kilometres of shore, which allows extra flexibility
to avoid conflicts with other active sectors such as tourism. The
Technical Specs of 3rd commercial scale farm for case study 3 com-
prises of 1 MUP, 250 m × 250 m, consisting of one 2 MW wind turbine
and one desalination unit with 3360 m
3
/d potable water capacity. The
project will be located 2 km off the coast of Chios, Greece in a water
depth of 60–100 m. The electricity will be exported to grid via 33 kV/
2 MW cable (capacity can increase for multiple MUPs). The moorings
for the MUP will be a standard anchor and chain mooring system (e.g.
Stevshark Mk5). The MUP and all assembly will be fabricated and in-
stalled at Eleusis Port, Athens.
4.4.3. Company perceptions of advantage of combination
Cost reduction are the major tangible benefit, saving space costs,
maintenance and power costs. Construction costs savings arise from
fabrication and assembly in its upright position at shipyard and towed
to offshore location. Its major value proposition offer is that the MUP
technology is not geographically/morphologically site-specific, it is
mobile and can be moored at various locations avoiding conflicts with
other sectors (such as fishing, aquaculture, tourism, leisure (marinas)
and port/shipping). The dynamic configurations of the MUP is also
totally flexible maximising either water and/or electricity production
depending on seasonal needs. Finally, the MUP offers 100% renewable
power source with low carbon footprint.
The benefits for Desalination company are (quoted by Maribe
report)
“Lower costs than land-based conventional desalination, due to
cheaper wind power than diesel”.
“Environmentally friendly chemical-free renewable powered
desalination system compliant with EU directives”
“Mobile site selection process on case-by-case basis working closely
with local stakeholders”.
The benefits for Wind company are (quoted by Maribe report)
“Energy used at source, therefore low losses”.
“Guaranteed customer for electricity purchase”
4.5. Results
Table 9 presents the essential case study financial inputs. A sum-
mary of all the results is presented in Table 14. The following sections
give the results for each of the metrics described in Section 3, for each
of the 3 case studies, and compares the results to the literature pre-
sented in Section 3, if the figures are available.
4.5.1. Levelised Cost of Output
The summary of the Levelised Cost of Output of the combination for
each case study is presented in Table 10. CS1 combination with Wave
Dragon and SES has the lowest LCOO, 40.2% so, well under the 100%
threshold for an attractive project. The results were driven by the two
positive factors in the calculation: The Capex cost per MW of the Wave
Dragon is comparatively low, benefiting from economy of scale in the
large 4 MW unit construction costs, and learning gained in reaching
commercial level. The revenue earned over the 25 years of the project
was also high, for two reasons:
The commercial farm contained 45*4 MW Wave Dragon, totalling
180 MW. This is a relatively large amount of electricity in MW for
export.
The use of the highly favourable old UK wave ROC equivalent of
€312.7 MWh (see Table 5).
CS2 had a LCOO result of 75%, comfortably below the 100%
threshold. The project size is generally smaller in scale, and with all
smaller scale projects, CAPEX costs are relatively higher (not benefiting
from economies of scale, as in CS1), while revenue is relatively lower,
resulting in a less favourable LCOO than CS1. The major player in the
combination is aquaculture, contributing to the majority of the capital
expenditure costs and the revenue earned. The results indicate that
revenue derived from Aquaculture are substantial and are sufficient to
cover expenditure and still make a return.
Fig. 9. Ydriada platform with 35 kW wind turbine in Heraclea (image permission
from Ecowindwater).
Fig. 10. Chios Island: two possible sites for TRL7 and TRL8 deployments.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
351
CS3 also had a similar LCOO result to CS2 of 76%, an attractive
result, again comfortably below the 100% threshold. The majority of
the revenue is derived from the sale of desalinated water (only a small
amount of electricity is exported), sufficiently profitable to support the
annual costs.
4.5.2. Comparator
1) CS1: Wave and Seaweed
CS1 project's revenue was mostly from the wave energy export, and
was thus the basis of the comparator. The wave energy LCOE was
compared to its rival fixed wind. The LCOE for the Wave Dragon was an
attractive €139/MWh (Table 11), The extremely positive CS1 LCOE
result was due to:
3rd Commercial scale project, a future predicted scenario
large economy of scales,
large MWh produced and
economical CAPEX/MW.
2) CS2 project Wave and Aquaculture finfish
Similar to the method used in CS1, the wave energy production and
resultant LCOE were used in the Comparator determination for CS2.
The case study is modelling an autonomous project, non-grid con-
nected, therefore alternative power supply would be via diesel.
LCOE figures were readily available for wave and its competitor
diesel. The comparison of Aquaculture with comparator would be
much more difficult, thus the choice of using energy LCOE as
comparator for CS2. The LCOE for Albatern wave energy device
modelled in the Malta location was very high at €542/MWh (espe-
cially compared to CS1 LCOE), due to high installation cost, and low
wave energy resource (same FIT was used as in CS1 case). The
Albatern LCOE was of similar range to the other published papers of
their results. However, in favour for the Albatern device and MUS
combination, Malta is an island, and currently has very high costs
and LCOE for imported diesel (€ 530/MWh). Thus the result com-
parator was quite favourable at 102%.
3) CS3 project floating wind and desalination
EWW techno-economic modelling used a sale cost price for 3rd
commercial scale production of desalinated water at €2.5/m
3
, which is
half of the cost of imported water used as a reference. This results in the
best comparator of the 3 projects (and of the entire Maribe case stu-
dies), at 55%.
4.5.3. Jobs/km
2
The jobs statistics used in the 3 case studies are presented in
Table 12
The 3 case studies varied immensely in their results for jobs/km
2
,
reflecting the diversity of value proposition they offer.
CS1 had the lowest result, at 3.6 jobs/km
2
. The project combines an
energy farm and seaweed. Regarding energy farms, besides their initial
construction (offsite), they have low maintenance onsite. Wave Dragon
in particular forecast high device reliability, due to basic design. Wave
Dragon is also an extremely large device, the farm size is large with 45
devices each spaced apart at least 0.5 km distance between devices.
Seaweed farms are similar, in requiring very low maintenance: besides
initial seeding, only once a month inspections and harvest after 1 year.
The combination therefore has the lowest result.
CS2 had a medium result of 205 jobs/km
2
. The aquaculture finfish
has much different job intensities than seaweed production. Finfish
require daily feeding, and monthly sea lice conditioning. Nets are also
Table 9
Summary of the Maribe case study inputs and indicator results for LCOE and LCOO.
CS1 CS2 CS3
Item Value Value Unit Item Value Unit
Project rating, WAV 180 0.72 MW Project rating, FLW_DES 2 MW
Project rating, AQ 20,000 6000 tonnes / year
CAPEX 661 26.3 €million CAPEX 12.9 €million
OPEX 289 287 €million OPEX 17.2 €million
DECEX 3 0.9 €million DECEX (net of scrap value) 0 €million
Cost of finance 832 24.4 €million Cost of finance 15.4 €million
Energy generated 10,800 31.4 GWh Fraction of water intentionally exported 100%
Product produced 400,000 90,000 tonnes Energy intentionally not exported (wind) 130 GWh
Water exported 23,179,044
Electricity price sold 312.7 €/MWh Electricity price sold (wind) 140 €/MWh
Fish or Seaweed price sold 1000 5000 €/tonne Water price sold 2.5 €/m³
Energy exported (wind) 10 GWh
Simple payback 3.5 2.5 years Simple payback 6.1 years
Discount rate or WACC 8.9% 8.9% Discount rate or WACC 7.9%
Operating for 20 15 years Operating for 20 years
Payback 5 3 years Payback 10 years
(WAV=Wave Energy, AQ=Aquaculture, FLW_DES=Floating Wind Desalination).
Table 10
Levelised Cost of Output calculation of the 3 combinations (M= Millions).
CS1 CS2 CS3
Annual Cost €/yr €76 M €22.5 M €1.13 M
Annual revenue €/yr €189 M €30 M €1.485 M
LCOO 40.2% 75% 76%
Table 11
Comparator calculation for three case studies.
Maribe Competition Comparator %
CS1 Wave energy LCOE Fixed wind LCOE 108%
€139/MWh €126/MWh
a
CS2 100% wave energy LCOE 100% diesel energy
LCOE
102%
€ 542/MWh € 530/MWh
a
CS3 Price of desalinated water
provided by MUP 100% wind
Cost of imported water
discounted 50%
55%
€2.5 /m³
b
€5.1 /m³
c
a
Modelled by Maribe.
b
Sale price €/m price determined during Maribe project interview process
with EWW to make a profitable case.
c
Water transportation price for 2017 is €10.3 + (VAT 24%) for transpor-
tation of 320.000 m
3
to anhydrous islands [122]. Maribe decided to halve the
value in order to produce a competitive rival cost.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
352
high maintenance. Fish are transferred from hatchery to various pond
sizes as they mature. Despite finfish farms being spread over a large
area, their job intensity remains high. The combination of finfish and
wave therefore has a medium job intensity.
CS3 has the highest result of 562 jobs/km
2
. The Ecowindwater is a
floating platform, 20 m × 20 m, however a single unit will still require
1/2 km space surrounding it; in comparison to the other two case stu-
dies it is relatively small in total area. The technologies on board do not
require a large job intensity in operations and maintenance.
Desalination process is mostly automated; water created and pumped to
shore. Floating wind power generation only requires monthly main-
tenance. Despite the low operations required, the small square km value
used in the modelling resulted in the combination of floating desali-
nation powered by wind as a very high job intensity (Table 13).
4.5.4. Jobs/CAPEX
For CS1, the high jobs created in the large commercial project was
offset by the large CAPEX expenditure, producing a medium jobs/
CAPEX result.
For CS2, the project fared the worst; the relatively low annual jobs
created and relatively high CAPEX expenditure created low Jobs/
CAPEX result.
For CS3 faired the best of the 3 projects; the higher jobs required
that aquaculture, with the lower CAPEX cost resulted in the most
favourable result of the three.
The jobs/CAPEX has a less extreme variation than Jobs/ Km sq, and
thus perhaps a more robust metric. Unfortunately, there are no litera-
ture review figures to compare results.
4.5.5. Profitability Index (NPV/CAPEX)
When considering the normal indicators of NPV and IRR, all three
projects had a positive NPV and over 10% IRR. However as explained in
Section 3.2.5, these results do not easily show which of the projects
would be most profitable and so the profitability index allows the case
studies to be compared more equally. Results are presented in Table 14.
CS1 gave rise to a medium result for NPV/CAPEX. Although the NPV
was high and recorded a favourable IRR of 22.4%, the very high
CAPEX of almost €0.5B, reduced the overall profitability index
compared to the other two projects.
CS2 had the best NPV/CAPEX. Moderate NPV returns, together with
moderate CAPEX, resulted in 2.3 times return.
CS3 returned a low result for the NPV/CAPEX indicator. The project
did not return a high NPV, as revenue for the water sale was modest.
The CAPEX was relatively high, together with the relatively low
NPV returns resulted in the lowest NPV/CAPEX of the 3 projects.
Unfortunately, as no raw data result figures were available for the
literature of NPV/CAPEX as explained in Section 3.2.5, it is not possible
in this paper to compare the Maribe results and discuss whether fa-
vourable or not against other projects.
4.5.6. Business Plan score
The 3 cases studies had similar medium ratings, ranging from 3.25
to 3.82. CS3 Ecowindwater had the highest rating, in part due to close
connection and networking with the Business model team, where ex-
tensive time was committed by the company in preparing the plan.
4.5.7. Risk score
All three projects received a medium-low Risk score of between 19%
and 22% (Fig. 11). Common to all three was the high risk of funding
and economic viability. Also common to all was the health and safety
issues. CS1 was rated harshest on its operations risk, due to the size of
the device and weather windows concerns.
4.6. Summary of results
All three of the case studies have favourable economic potential
when examining the conventional indicator results of LCOE, NPV and
IRR. However, the vastly divergent technologies involved in the three
combinations make comparison of the economic performance difficult.
Consequently, one novel economic indicator and four other rarely used
indicators were applied to each case study, to enable a more balance
comparison of the projects performance, these are summarised in
Table 14 (four other minor indicators were presented in the results
section, but will not be discussed in the Discussion section: Business
Plan score, Risk, Consortium and panel score).
The first and novel indicator was LCOO, with parallels with LCOE
for electricity commonly used for comparing energy projects. All of the
three projects fared well in this indicator. The second interesting in-
dicator was the ‘Comparator’, which determined how the combination
fared economically compared to its nearest competitor or rival tech-
nology. The CS3 desalination project fared best here, due to the com-
petitive cost of desalinated water via renewable energy in comparison
to the existing very expensive costs of importing fresh water via boat to
remote islands in Greece.
The third interesting indicator was Jobs/km
2
. This indicator will
perhaps be most important in the future, as marine space becomes more
restrictive and public funding more competitive. CS3 fared best in this
indicator, as it was the most economical in space, whilst still providing
relatively good employment. Results compared favourably with
European city averages. The fourth indicator was Jobs/CAPEX.
Creating jobs is an imperative in Europe, but the expense to society
must be critically assessed. Unfortunately, this indicator is rarely used,
so comparison to other projects was not possible in this paper. Of the 3
cases studies, CS3 again fared the best with low CAPEX costs producing
the most favourable result.
The fifth and final indicator is NPV/CAPEX expenditure. This in-
dicator made it possible to compare vastly different scales in project
size, without the distortion of the capital sums invested. CS2 fared best
under this indicator. The relatively high CAPEX costs for the CS1 pro-
ject penalised the CS1 project. It was the only metric where CS3 fared
badly.
Table 12
Jobs inputs and Jobs/km
2
results for 3 cases studies.
CS1 CS2 CS3
Jobs Years Jobs Years Jobs Years
Construction Construction Construction
2240 5 30 3 53 5
OPEX OPEX OPEX
801 20 9 15 64 20
DECEX DECEX DECEX
0 0 0 1 0 1
Total Total Total Total Total Total
3041 25 39 19 117 26
Annual Jobs 3041/25= 122 39/19= 2.05 117/26= 4.5
km
2
36 0.01 0.008
Jobs/km
2
3.4 205 562
Table 13
Jobs/Capex inputs and results for 3 case studies.
CS1 CS2 CS3
Annual Jobs 122 2.05 4.5
CAPEX €m 661 26 13
Jobs/CAPEX 0.18 0.07 0.346
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353
5. Discussion
5.1. Discussion of the review section
The economy of the sea can be divided in two: the mature Blue
Economy industry sectors and the emerging innovation of the Blue
Growth sectors. The global value of the established Blue Economy is
enormous; the OECD [129] estimates that the global gross value added
(GVA) of the whole Blue economy is estimated by to grow to more than
US$3 trillion (at 2010 prices) by 2030, about 2.5% of total global GVA.
In 2010 it was recorded at about US$1.5 trillion when it was dominated
by the established industries of offshore oil and gas (34%) and maritime
tourism (26%). Ship transport and shipbuilding accounted for 9% with
a further 13% attributed to port activities and 11% for marine
equipment. Catch fisheries featured at only a 1% share of the ocean
economy with a further 5% in fish processing.
It is recognised that two of the four traditional mature Blue
Economy sectors (Catch Fisheries and offshore Oil and Gas) have
reached peak capacity and are in decline. Shipping continues to grow
along with growth in global trade and tourism continues to expand
along with disposable income in emerging economies. However, the
Blue Growth innovation sectors are targeted in policy to be the main
drivers of the new maritime economy. However, in the OECD report
[129], the new Blue Growth industries are currently minimal, with only
aquaculture and offshore wind showing at less than 1% each. Offshore
wind shows the most energetic growth to 2030, rising to 8% of the
whole. There has been a concerted drive in public policy to stimulate
the potential for Blue Growth. Section 2.1 described 20 years of Global
and EC policy and regulation mechanisms with both push and pull
policy drivers. In a European context this is based around MSFD and
MSP strategies being implemented nationally, regionally and by each
sea basin.
Simultaneous to regulation policies, there have been a raft of public
funding schemes (both EU and national) to drive Blue Growth. The
success of these schemes for Blue Growth is as yet not proven, except in
the offshore wind sector where a number of factors have catapulted it to
success. A recent initiative of the EC, the Blue Invest platform, is per-
haps signalling the sector to be innovative in the sourcing of its future
funding. Blue Invest has accumulated an impressive list of investors,
and the platform is experimenting in the latest techniques of match-
making and project promotion – similar to a Dragons Den style format.
The multi-use concept is designed both to be a catalyst for marine in-
dustries and a way to make efficient use of space and facilities with
reduced environmental harm. Section 2.3 presented a state for the art
review of the various combinations of Blue growth technologies and
their degrees of success.
Fig. 11. Risks before mitigation for 3 case studies: CS 1,2,3.
Table 14
Summary table of results for 3 cases study.
Indicator Metric WD+SES Albatern+ABT Ydriada+EWW
Maribe CS1 Maribe CS2 Maribe CS3
CAPEX (€M) 661 26 13
NPV (€M) 916 59 7
IRR (%) 22.4 34.5 13
Jobs 122 2.05 4.5
Occupied area (km
2
) 36 0.01 0.008
LCOO ((€/€)%) 41 76 78
Cost Comparator (%) 108 102 60
Jobs/km
2
3.4 205 562
Jobs/CAPEX 0.18 0.07 0.34
NPV/CAPEX (€) 1.4 2.3 0.5
Business plan score (1–5) 3.25 3.79 3.83
Risk score (%) 22 19 22
Panel score 5.81 7.6 7.3
Consortium score 6.3 6.6 7.2
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
354
Aquaculture is a rapidly expanding sector responding to the ex-
panding global demand for protein and food fish. Currently it mainly
refers to nearshore aquaculture, which is well established and mature,
and in some cases in decline. Aquaculture in Blue Growth is defined as
offshore aquaculture which holds large promise, with removal of space
constraints, cleaner seas, and much reduced environmental impact. It is
an emerging sector facing many barriers, both technological and cost
related. It also faces competition from other sources of food protein in
the form of wild fish, meat and vegetables. There is also controversy
with regards to environmental concerns, and pressure to produce stock
both organically as well as sustainably - such as with renewable power.
Offshore aquaculture will benefit tremendously by combining techni-
cally as well as commercially with other Blue Growth sectors: sharing of
the space will provide much needed protection from extreme resource,
as well as shared facilities and operating costs.
Offshore Wind Energy is the most rapidly expanding sector in the
ocean economy. The technology has advanced rapidly over ten years,
increasing output of individual turbines from 3 MW capacity to 10 MW
capacity or more combined with increased efficiencies of generating
electricity direct to grid. This technology development and economies
of scale has meant that the levelised cost of electricity (LCOE) from
offshore wind has tumbled from over €300 per MWh to some recent
(2017) strike prices below €75 per MWh. In July 2016 ∅rsted Energy
(formerly DONG) won the Netherlands auction for an offshore wind
farm at Borssele I & II at a price of € 72.7 /MWh (LCOE about €68/
MWh) [126]. This excludes transmission costs and development costs
were paid by the government. Adding the transmission connection at a
(fairly modest) €14/MWh to the costs, giving a total project LCOE of
about €82/MWh. In December 2016 Shell and partners won the latest
Netherlands auction for an offshore wind farm at Borssele III & IV at a
price of €54.5/MWh (25% lower than that achieved by ∅rsted in July
2016 for Borssele I & II). Adding the transmission connection brings
project LCOE close to the price of electricity [127,128]. Clearly, off-
shore wind is approaching a fully competitive level with other forms of
electricity generation including fossil and nuclear. Constraints on ex-
pansion of the industry are suitable sites for fixed turbine towers and
the large areas of marine space needed in possible conflict with other
activities. Visual intrusion on seascapes has also been a significant
factor in objections to some proposals. The innovation of floating tur-
bines is progressing which, if successful and commercial, will release
the industry from many of the site constraints. Floating wind has
overcome some crucial technology problems, as well as the very large
reduction in development costs for prototypes. Floating wind has now
moved past the ‘valley of death’, and into TRL8 prototype array de-
ployments. The need for offshore wind to share space or combine on
platforms is minimal. Yet the benefit it would contribute to other Blue
Growth sectors will be significant.
Wave and Tidal Technologies (covered by the term ocean energy)
are still at an early stage TRL despite 40 years of development.
Examples of fully commercial enterprises are some years away. Tidal
stream devices are more advanced with the first arrays installed but
their ultimate capacity is relatively small compared to wind and wave
with the majority of potential concentrated into a few suitable loca-
tions. Tidal barrage systems have been operating for decades (e.g. the
La Rance barrage) and are cheap in the long term, but the high CAPEX
and extensive civil engineering works are a barrier to investment.
Research is still ongoing in this area [130]. The size and apparently
ubiquitous nature of wave resource has to date been a key driver in
research. Wave energy has failed so far to achieve a potentially com-
mercial power take off (PTO) technology (except for Wave Dragon,
which utilizes standard type hydro turbines), and drivers to develop the
technology are diminishing, partly because the market for significant
renewable energy to the grid is being met by offshore wind. The 2016
JRC Oceans report [124] states that current LCOE of wave energy
ranges between €600/MWh and €1100/MWh, with a reference value of
about €850/MWh. At the extreme, values can reach up to €1390/MWh
in case of a poor resource and can go down to about €440/MWh in case
of a good resource. Whilst wave and tidal held equal promise to off-
shore wind energy 15 years ago, this is not now the case. Confidence in
floating wind to fill the remaining gap of remote high energy in deep
waters is high, where wave is still yet to succeed in a successful TRL 6
prototype deployment. Thus, the ‘valley of death’ scenario is increasing
becoming a large barrier for the sector, where financial investors either
will not fund or withdraw funds when ocean technologies reach this
stage. In the light of these difficulties for the sector, ocean energy is
diversifying and seeking other partners in Blue Growth to add to its
value proposition and help reduce costs and risk. Thus wave energy is
combining with aquaculture and even with its rival floating wind, to
explore multi-use, with aims to reduce its costs, as well as learn from
these more mature sectors. EC funding is particularly favouring this
initiative with a number of funding schemes.
The search for synergies between different Blue Growth sectors is
hoped to enhance the economic performance of these struggling Blue
Growth activities, promoting at the same time a more efficient use of
infrastructure and logistical resources. Furthermore, the grouping and
combination of activities enables marine spatial planning to facilitate
an efficient and environmentally sustainable management of maritime
industries, reducing conflicts over the use of marine space and the as-
sociated environmental harm. In most cases of multi-use, it is offshore
wind which is providing the practical lead in the concept. Active re-
search and trials are underway to combine wind farm areas with catch
fisheries and aquaculture. This is largely in response to the need to
offset opposition created by displacing established fisheries from such
large areas of sea. Offshore wind is setting the standard in community
benefit payments to the coastal communities affected by their opera-
tions. Unfortunately, many types of multi-use combinations may simply
add complexity and hence reduce profitability.
5.2. Discussion of Maribe case study results
Section 3 of this paper presented the results for three of the nine
Maribe case studies exploring the viability of multi-use of space and
multi-purpose platforms. Each case study presented a combination of
two or more Blue Growth sectors. The Maribe project succeeded in
securing the cooperation of companies active in the field to provide real
data for each of the case studies. The results section of the paper pre-
sented the financial data and results using the Maribe metrics. This
discussion section compares the results to other research conducted in
the field, already described in the Literature review section.
5.2.1. Comparison to Oceans of Tomorrow (OoT)
The Oceans of Tomorrow (OoT) projects were reviewed by Díaz-
Simal [48] on behalf of Maribe. It will first be noted that none of the
technologies or companies from any of the OoT projects were part of
the Maribe studies, as already explained, due to a lack of advancement
in the concepts.
49
All the OoT projects conducted their own techno-
economic assessment of the concepts, each one concluding that the
costs of operations were not viable in the current form. This contrasts to
the positive commercial case for the three Maribe case studies pre-
sented in this paper, as well as the remaining six in Maribe. The proof of
viability is largely due to the economic and commercial expertise
contained in the Maribe consortium. The advice from industry resulted
in improvements to feasibility by identifying more accurate estimations
of CAPEX and OPEX and in refining the project structures.
49
Only one of the OoT concepts was explored by Maribe, fixed wind sharing
with aquaculture, on the basis that a general business case assessment would be
performed without the contribution of data by companies. It is worth noting
that this case study received one of the higher Maribe ratings, and has been
presented in van der Burg [76].
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
355
5.2.2. Comparison to other literature case studies
This section will compare the three Maribe case study results with
similar case studies found in the literature as presented in Section 2.3.
Comparison is only possible for some of the metrics as many used in this
paper are infrequently used in academic publications, but they are well
established.
Levelised Cost of Output cannot be compared to other studies as the
metric is unique to the Maribe study.
When the results for jobs/km
2
are compared to the literature review
results in Table 5, CS2 and CS3 are similar to the average for jobs/
km
2
for Spain. They do not compare to the job density of cities.
There are no statistics available to compare to the intensity of other
projects. The use of jobs/km
2
metric has to be carefully used, as the
area involved can vary immensely and distort results. The CS3 single
unit deployment demonstrates how easily the figure can be skewed.
The comparator metric was the main metric which enabled com-
parison to other literature sources as it used euro costs per unit
quantity; either Euro per kWh for energy, or Euro per m
3
for water.
These two metrics are commonly used.
1) CS1: Wave and Seaweed: The Maribe case study LCOE for Wave
Dragon is similar to Dalton's [96] LCOE results for 100 MW of Wave
Dragon resulting in €150/MWh (Table 7) but higher than Sorenson
et al. [123] who quoted a very low LCOE for commercial stage Wave
Dragon (as low as €30/MWh). Sorenson et al. also model a 7 MW
wave Dragon with two 2.3 MW wind turbines in MUS (LCOE €51/
MWh). On the other hand, this is far more positive than that pre-
dicted by JRC Oceans report [124] as discussed above. The attrac-
tive LCOE for CS1 is in-line with BVGA predictions for 2030,
whereby, assuming a LCOE at 2016 of £ 200/MWh, using a LCOE
learning rate of 12%, and market growing from 10 MW in
2016–2000 MW in 2030, LCOE could reduce to £ 75/MWH by 2030
[125]. For the fixed wind LCOE, Maribe used the 2016 LCOE of
€126.
50
This comparator LCOE resulted in a comparator result with
wave energy of 108%. However, the offshore wind LCOE used in the
Maribe study is rapidly superseded in a downward spiral as offshore
wind costs continue to fall. Despite wave energy resulting in a very
attractive LCOE of €139/MWh, it suffers in comparison to its rival
offshore wind, which is likely to be as low as €50/MWh. Using these
low LCOE, the comparator could increase drastically up to 200% or
more.
2) CS2: Wave and Aquaculture Finfish: The LCOE for Albatern wave
energy device modelled in the Malta location was €542/MWh
(especially compared to CS1 LCOE), due to the proportionally larger
cost of installing a small array of devices, and low wave energy
resource (same FIT was used as in CS1 case). The Albatern LCOE was
of similar range to the other published papers of their results.
However, in favour for the Albatern device and MUS combination,
Malta is an island, and currently has very high costs and LCOE for
imported diesel (€ 530/MWh). The LCOE of €542/MWh compares
in magnitude to other very early TRL ocean energy technologies, or
technologies with very high initial Capex costs. In a paper by
O’Connor et al. [131], the Wavestar and Pelamis had similar LCOE
for low wave energy locations of Denmark and Greece (€450/MWh).
However, the differences between the two value propositions could
not be greater: Wavestar was a 2 MW device, and had a strategy of
driving to reliability first, incurring huge Capex costs, and dealing
with cost reduction later. Thus, Wavestar prototype had very large
LCOE of similar magnitude to Albatern. As stated in the review
section, a TRL7 deployment in multiuse of space with fixed wind did
not proceed, due to a withdrawal of private funding and licencing
problems. EC funding was in place. The failure to progress in this
case is a key negative result for the multi-use sector - either the
technology is wrong or the market drivers are not strong enough.
Albatern, are at the opposite end of the power spectrum providing
only 7 kW of generating capacity. Although their LCOE is large, the
non-grid connected aquaculture market it caters for can afford it.
The diesel alternative costs are the same. Therefore, the comparator
result CS2 was quite favourable at 102%.
3) CS3: Floating Wind and Desalination: Statistics for costs for con-
ventionally produced desalinated water are readily available and
make comparison to renewable powered desalination viable.
Imported water via boat is currently very expensive for non-grid
connected Greek islands, at €10.3/m
3
. Maribe used half this price as
the comparator €5.1/ m
3
. EWW techno-economic modelling used a
sale cost price for third party commercial scale production of de-
salinated water at €2.5/m
3
, which is half of the cost of imported
water used as a reference. Table 2 list costs of production costs of
producing desalinated water. The production costs quoted ranging
from €0.3–3.3/m
3
are similar to the sale price quoted for EWW of
€2.5/ m
3
. These costs of production do not include transport costs,
other energy costs, or a profit margin. Therefore, the expected sale
costs for the water produced should be necessarily higher than the
range from €0.3–3.3/m
3
. consequently, the comparator figure result
of 55% could be considered a worst case result for Ecowindwater
and this is an attractive business proposition.
6. Conclusions
This paper has reviewed the policy interventions and supported
projects to promote Blue Growth projects and multiple use of space and
multi-purpose platforms. The paper demonstrated that there has been a
consistent push from the EU to drive the agenda of Blue Growth, and
the development of MUS and MUP. At a first glance the idea behind
MUS/MUPs is rather simple: two (or more) maritime industries sharing
the same space and/or infrastructure. MUSs and MUPs are novel con-
cepts, and as such their development will require either the creation of
new business models or the participation and investment from both
public and private agents. In order to optimise these investments and
make MUS/MUPs commercially viable, a good knowledge of the mar-
itime industries involved becomes crucial. The knowledge of their op-
erational methods, strengths, weaknesses and potential for growth is
not only useful for management planning, but also it opens the door for
the consolidation of emerging maritime sectors. However, no com-
mercial projects have yet emerged. The common barrier faced by the
projects in the review section was that the large scale complex MUP
solutions proposed can only be funded with significant subsidy. The
high CAPEX and additional costs associated with operation offshore
makes many of these systems non-competitive with land based com-
petitors. Furthermore, lack of access to hard data and estimated fi-
nancial performance creates uncertainty in determining the best value
propositions. Moreover, data and results are often presented using
economic indicators that make comparison difficult.
Therefore, this paper proposes a novel methodology to filter the
many competing concept ideas of Blue Growth, MUS and MUP down to
a handful of viable concepts that have made significant efforts to create
a robust business case.
The paper then presented the results of three of the case studies
conducted by the Maribe H2020 project, which successfully accessed
hard financial data, with permission to publish results, and presented
the results using a suite of normalised indicators, facilitating the pro-
jects comparison. The three cases presented concentrated on the Blue
Growth sectors of wave energy, offshore wind energy, aquaculture and
desalination. It is interesting to observe that all of the case study
business propositions are relatively small niche market propositions.
The results indicate that financial support for MUP and marine re-
newable technologies should prioritise small market technology cases,
50
https://cleantechnica.com/2016/11/01/offshore-wind-costs-22–126mwh-
bnef/.
G. Dalton, et al. Renewable and Sustainable Energy Reviews 107 (2019) 338–359
356
initially, with the future ambitions of achieving economies of scale and
cost reduction in the same way as offshore wind over the last 20 years.
Alternatively, policy and investment should support “bottom up”
market driven approaches.
Maribe succeeded in economically assessing and comparing di-
vergent Blue Growth combinations by using a suite of economic in-
dicators (metrics) especially suited to comparison of non-related tech-
nologies. All three case study projects had economic merits and excelled
under different indicators. Based on all the positives and negatives, CS3
project had the most promising results, as reflected in Table 14 where
CS3 had the greatest number of highest scoring indicators. The con-
sortium and panellists also rated CS3 as the most promising. The paper
concludes that a carefully structured Blue Growth multi-use business
can create a profitable operation and provide the jobs and value that
Blue Growth aims to provide.
The methodology presented is robust and can be applied in other
contexts where private and public organisations wish to invest in
companies via grants or venture investments. It is hoped that this paper
has demonstrated the scientific benefit of using these metrics, in par-
ticular from the perspective of allowing comparison. The macro and
micro assessment methods will be particularly useful in other Blue
Economy contexts and in other multiple product contexts.
Acknowledgments
The authors would like to thank the 5 companies participating in
the Maribe case studies, for providing the valuable CAPEX, OPEX, and
DECEX figures for the economic modelling and agreeing to allow both
these figures as well as the results to be publish in this paper. (Hans
Christian Soerensen, Erik Friis-Madsen, Frank Neumann, Gareth
Lawrence, David Campbell, Nikitas Nikitakos, Theodore Lilas).
Thanks are also expressed to the administration staff of the Maribe
project, Noirin, and Hester, and to the H2020 Project Officer for
Maribe.
The contributions of Gordon Dalton is supported by Marine
Renewable Energy Ireland (MaREI), the SFI Centre for Marine
Renewable Energy Research - (12/RC/2302).
All authors wish to acknowledge the European Energy Research
Alliance (EERA).
The Maribe project has received funding from the European Union's
Horizon 2020 research and innovation programme under the Grant
Agreement No. 652629. This work was financially supported by the UK
EPSRC project United Kingdom Centre for Marine Energy Research (EP/
P008682/1).
Data access
Summary data is included in the paper, detailed data is the property
of the respective companies and cannot be shared due to contractual
restrictions.
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