• maintenance management control factor (simulates windfalls and setbacks in
system failures, based on Mean Time Between Failure (MTBF) and Mean Time
To Repair (MTTR).
To simulate price changes for the wind power sales price and mussel sales price,
the prices can be adjusted by parameter setting of the trend diagram (Lagerveld
et al. 2014).
4.4 Conclusions
In line with Michler-Cieluch et al. (2009a), this article highlights the need for
collaboration between the different disciplines relevant for combining activities
offshore. We show that an asset management control model is useful for bringing
the relevant offshore disciplines together. Multi-use activities offshore do have an
effect on (the assessment of) risks arising from (multiple) combined O&M processes. The exact details of these processes are still unknown and hence estimations
are uncertain.
Simulations with the AMC model under different assumptions allow us to
estimate the benefits and costs of the interdisciplinary MUP approach, thus making
the approach more concrete and robust.
In summary, we conclude that there are opportunities for all actors (the government, the wind sector, and the aquaculture sector) to achieve their different
objectives by combining offshore wind energy production with offshore aquaculture. Lagerveld et al. 2014 suggest that an overall cost reduction on O&M activities
of approximately 10% is feasible, if offshore wind farms and offshore aquaculture
are combined.
Furthermore, running the Asset Management Control Model the return of
investment (ROI) for four different scenarios was simulated. Based on the chosen
economic parameter values and sales prices estimates, the model simulations show
that a ROI of 4.9% should be possible in unfavourable economic conditions when
synergy is absent. When 10% synergy can be achieved, a ROI of 5.5% seems
possible. The ROI is significantly higher when economic conditions are favourable.
Even when there is no synergy, a ROI of 8.3% should be feasible, and in case of
10% synergy the ROI is likely to reach 9.6%.
Recommendations
The mitigation of physical and chemical processes that pose a risk to the constructions should be investigated. In collaboration with all sectors involved, it
should be investigated in more detail what operational processes in a multi-use
setting can look like, thus enabling us to accurately quantify potential synergy
benefits. Only then will we be able to assess the reliability of our input values and
the robustness of the model results.
110
C. Röckmann et al.
system failures, based on Mean Time Between Failure (MTBF) and Mean Time
To Repair (MTTR).
To simulate price changes for the wind power sales price and mussel sales price,
the prices can be adjusted by parameter setting of the trend diagram (Lagerveld
et al. 2014).
4.4 Conclusions
In line with Michler-Cieluch et al. (2009a), this article highlights the need for
collaboration between the different disciplines relevant for combining activities
offshore. We show that an asset management control model is useful for bringing
the relevant offshore disciplines together. Multi-use activities offshore do have an
effect on (the assessment of) risks arising from (multiple) combined O&M processes. The exact details of these processes are still unknown and hence estimations
are uncertain.
Simulations with the AMC model under different assumptions allow us to
estimate the benefits and costs of the interdisciplinary MUP approach, thus making
the approach more concrete and robust.
In summary, we conclude that there are opportunities for all actors (the government, the wind sector, and the aquaculture sector) to achieve their different
objectives by combining offshore wind energy production with offshore aquaculture. Lagerveld et al. 2014 suggest that an overall cost reduction on O&M activities
of approximately 10% is feasible, if offshore wind farms and offshore aquaculture
are combined.
Furthermore, running the Asset Management Control Model the return of
investment (ROI) for four different scenarios was simulated. Based on the chosen
economic parameter values and sales prices estimates, the model simulations show
that a ROI of 4.9% should be possible in unfavourable economic conditions when
synergy is absent. When 10% synergy can be achieved, a ROI of 5.5% seems
possible. The ROI is significantly higher when economic conditions are favourable.
Even when there is no synergy, a ROI of 8.3% should be feasible, and in case of
10% synergy the ROI is likely to reach 9.6%.
Recommendations
The mitigation of physical and chemical processes that pose a risk to the constructions should be investigated. In collaboration with all sectors involved, it
should be investigated in more detail what operational processes in a multi-use
setting can look like, thus enabling us to accurately quantify potential synergy
benefits. Only then will we be able to assess the reliability of our input values and
the robustness of the model results.
110
C. Röckmann et al.