Expressions of interest (EoI) related to Sustainable Energy Systems - research activities having an impact in the medium and longer term

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Nov 7, 2013 (7 years and 10 months ago)


Expressions of interest (EoI) related to Sustainable Energy Systems

activities having an impact in the medium and longer term

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Organisation details

Organisation name:

Aalborg University

Organisation activity:


Legal status of the


Contact details

Family name:


First name:

John Dalsgaard






Sohngaardsholmsvej 57 DK
9000 Aalborg



Telephone number:

+ 45 96 35 85 81

Fax number:

+ 45 98 14 82 43


Description of the suggested activity

(The following questions will help us to understand the purpose, content and pertinence of your
suggested activity.)

e of EoI:

Harmonised and cost optimal safety level of wind turbines



Select the most relevant Medium to Long Term Energy Activity Codes.

If your EoI is relevant to more than one, please list the activity codes in descending order of rel


To which of the other FP6 Thematic Priorities (TP) is your proposal also relevant, if any?

Please indicate which Type of Action you feel is most appropriate for your EoI:


Indicative range of requested EC Funding in M Eu

less than 1 M Euro

Potential Impact and Relevance to the achievement of objectives of the addressed thematic priorities of
the Euratom programme. (Please see point 3.A of the Guide of Submitters):

A basic requirement for wind energy to be competi
tive compared to other energy production methods is
that wind turbines are cheap and reliable in the expected lifetime. Safety levels for wind turbines are
traditionally established individually for each component / part of the wind turbine, blades, tower,

generator, foundation, etc. In order to optimise the cost
benefits for wind turbines all costs and benefits
in the expected lifetime should be accounted for. This includes construction costs, maintenance and
repair costs, eventual failure costs and

income form electricity production. Further all uncertainties
related to loads, strengths, models and production should be accounted for. Using risk based decision
theoretical models all these costs
benefits and uncertainties can be accounted for.

For la
based wind turbines the risk and safety level is influenced significantly by the risk aversion due
to risk of fatalities in case of failure. For offshore wind turbines this risk aversion is not important, and
therefore the safety level can be reduced.

The main objectives of the project are to formulate a risk based decision model, collection of typical
data for large offshore wind turbine parks, and estimating the cost
optimal safety level for wind
turbines in such a way that a harmonised safety level i
s obtained for all parts of the wind turbine, and
of a wind turbine park.

The methodology can be used to optimise the safety level for specific wind turbine projects and for
different parts of the wind turbine. The methodology can be used both from a soci
ety point of view, and
from investor point of view to establish the safety requirements. It is expected to result in lower safety
levels than used today but also in significant reductions in building and maintenance costs for wind
turbines. The optimal saf
ety level is basically found as a trade
off between increased risk of failure of
the wind turbine and reductions in building and maintenance costs.

Scientific and Technical Objectives (Please see point 3.B of the Guide of Submitters):

The following obj
ectives are identified:

1. Formulation of cost

benefit model: based on wind turbine types, which are expected to be used the
next 5
10 years in large offshore wind power parks. Different foundation concepts are included.

2. The main failure modes are i
dentified. This includes failure in all parts of the wind turbine, including
blades, mechanical parts, tower, foundations etc.

3. Uncertainties related to parameters in the failure modes are identified, and described statistically.

4. A systematic risk a
nalysis is performed for the whole wind turbine (park), identifying all significant
failure events and how they are dependent. Bayesian networks, failure and event trees are to be used.

5. To quantify the stochastic model and the risk analysis, data are c
ollected for typical loads (wind,
wave, current, ice, and operational) and strengths of the different materials. The data will be collected
from wind turbine producers, operators, etc. The data will be statistically analysed and recommended
stochastic mode
ls for general use will be established.

6. The identified failure modes, uncertainties and risk models are integrated in the cost
benefit decision
model. The decision model is used as a rational decision support system for selection of main wind
turbine d
esign and reliability level of all parts of the wind turbine. The main goal is to minimize the total
expected cost for production of wind energy.

7. The decision mode is implemented in a software system, which mainly should be based on existing
software m
odules. The decision support system is to be verified and documented by several example

8. The decision tool can be used to quantify the effect on the cost of energy produced by wind turbines
o if uncertainties are reduced (better models and /
or more site measurements), and thereby reduced
safety factors in design o if inspection and monitoring are performed

Outline implementation plan (Please see point 3.C of the Guide of Submitters):

The partners in the consortium, see below, have expert k
nowledge both in the technical design of wind
turbines, and in the production process. The implementation will be divided in the following items:

∙ Identification of the main needs in the above described decision support system

∙ Research and technical i
mplementation of the steps described above.

∙ Dissimilation of knowledge through exchange of scientist, PhD students and Post
docs, seminars in
cooperation with industry

Envisaged Consortium (Please see point 3.D of the Guide of Submitters):

The partne
rs in the proposed project include the partners in the newly established EAWE (European
Academy of Wind Energy). The members in EAWE are:

∙ CRES, NTUA, University of Patras


∙ ECN, Delft University of Technology

The Netherlands

∙ ISET, Univers
ity of Kassel


∙ RISØ, Technical University of Denmark, Aalborg University, DHI


Further, one or two large wind turbine producers are included in the consortium.

All members have long experience in wind energy research and in dissimila
tion of wind energy research
results to industry.

Publication of this EoI

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together with my contact details.