Trans RINA, Vol 157, Part C1, Intl J Marine Design, Jan –Dec 2015
An area for investigation is whether, for a vessel such as a WFSV, some decision-making can be coded into the model to reduce the time taken to search for an acceptable set of dimensions.
5.3 THE OVERALL ANALYSIS PROCESS
Considering the range of inputs to the O&M system shown in Figure 2, and the range of characteristics of the WFSV and other supporting craft shown in Table 3, the multi-dimensional “problem space” and “solution space” can be explored in different ways, depending on which of the use scenarios listed in Section 5.1 is of interest. Future UCL developments of the O&M tool and DBBA models will have to address this issue, as it is key to optimising the computing time required to run the models.
Selecting from the list of scenarios, some example usage concepts can be outlined:
Optimisation of vessel designs for a specific array; The O&M model could be run for a range of plausible vessel costs and capabilities to develop a meta-model which could then be used to drive the optimisation of the parametric models. This could be used for a broader O&M vessel fleet consisting of different types.
Development of a flexible vessel design that can be marketed to arrays using different O&M concepts; The
vessel model could be run for a range of
requirements to develop accurate meta-models for cost and capability. These could then be used in a wider O&M model exploration of different array concepts.
3.
Both of these make use of “meta-models”, these are simplified representations of results from more complex analysis, such as response surfaces, Artificial Neural Networks or even a look-up table of possible design variants. It may be the case that in some analysis scenarios, it is more desirable to run the vessel sizing model directly, however.
6. CONCLUSIONS AND FUTURE WORK
With projected expansion of the offshore renewable energy sector in terms of capacity, water depth and distance support
from shore, the strategies more
development of effective difficult.
Operation and
maintenance costs represent a high proportion of the cost of electrical power generated by wind turbines and so there is a current focus on reducing O&M costs and thus electricity production cost. Of particular interest is the improvement of availability, extending the range of sea states in which a turbine may be safely accessed. Three main options have been proposed for the marine support strategy for an offshore windfarm, and within these options there are a range of vessel types and capabilities that may be optimal for a given development.
4. 5.
6.
Working from this general background, a 6 month UCL MSc project examined the issue of modelling different O&M strategies for offshore windfarms. A Matlab based tool was developed that utilised a range of inputs describing the wind farm arrangement and location, reliability of turbine components and individual costs for repair activities. Applying a selected maintenance strategy within external constraints such as weather conditions, the tool
production and support vessel specified
calculates the costs, energy requirements for the
wind farm. The UCL O&M model was
validated against published data for UK Round 1 windfarms.
To further develop this concept, a baseline CTV has been designed using the Design Building Block approach (DBBA). This exercise has demonstrated the applicability of the approach to this type of vessel, and will form the basis for continuing research to integrate the high level O&M modelling with parameterised vessel models to allow a more sophisticated analysis of the marine support strategy. Applying the configurationally centred DBBA to develop the vessel models will permit a wider range of innovative solutions to be assessed with higher confidence than a method employing a purely numerical model.
7. REFERENCES 1.
2.
http://www.ucl.ac.uk/mecheng/research/marine
CORBETTA G., “The European Offshore Wind Industry - Key Trends and Statistics 1st half 2013”, European Wind Energy Association (EWEA), 2013
“Electricity Generation Costs 2013”, Department of energy & Climate Change (DECC), 2013
RAO, B.K.N (editor), “Handbook of Condition Monitoring”, Comadem International, 1996.
RIBRANT, J, “Reliability Performance and Maintenance: A Survey of Failures in Wind Power Systems”, Masters Thesis, KTH School of Electrical Engineering, 2005.
YAN-RU WU & HONG-SHAN ZHAO, “Optimization Maintenance of Wind Turbines Using Markov Decision Process”, International Conference on Power System Technology, 24-28 October, 2010, Hangzhou, China.
7. 8. 9.
DING, FF, “Comparative Study of Maintenance Turbine Systems”. Thesis (Ph.D), Concordia Institute, 2010.
SALHA, A, “Operation and Maintenance Strategy for Offshore Windfarms”, MSc Thesis, University College London, 2013.
DINWOODIE, I & MCMILLAN, D, “Sensitivity of Offshore Wind Turbine Operation & Maintenance Costs to Operational Parameters”, 42nd ESReDA Seminar: Risk and Reliability for Wind Energy and other Renewable Sources, Glasgow, 2012
C-144
© 2015: The Royal Institution of Naval Architects
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92 |
Page 93 |
Page 94 |
Page 95 |
Page 96 |
Page 97 |
Page 98 |
Page 99 |
Page 100 |
Page 101 |
Page 102 |
Page 103 |
Page 104 |
Page 105 |
Page 106 |
Page 107 |
Page 108 |
Page 109 |
Page 110 |
Page 111 |
Page 112 |
Page 113 |
Page 114 |
Page 115 |
Page 116 |
Page 117 |
Page 118 |
Page 119 |
Page 120 |
Page 121 |
Page 122 |
Page 123 |
Page 124 |
Page 125 |
Page 126 |
Page 127 |
Page 128 |
Page 129 |
Page 130 |
Page 131 |
Page 132 |
Page 133 |
Page 134 |
Page 135 |
Page 136 |
Page 137 |
Page 138 |
Page 139 |
Page 140 |
Page 141 |
Page 142 |
Page 143 |
Page 144 |
Page 145 |
Page 146 |
Page 147 |
Page 148 |
Page 149 |
Page 150 |
Page 151 |
Page 152 |
Page 153 |
Page 154 |
Page 155 |
Page 156 |
Page 157 |
Page 158 |
Page 159 |
Page 160 |
Page 161 |
Page 162 |
Page 163 |
Page 164 |
Page 165 |
Page 166 |
Page 167 |
Page 168 |
Page 169 |
Page 170 |
Page 171 |
Page 172 |
Page 173 |
Page 174 |
Page 175 |
Page 176 |
Page 177 |
Page 178 |
Page 179 |
Page 180 |
Page 181 |
Page 182 |
Page 183 |
Page 184 |
Page 185 |
Page 186 |
Page 187 |
Page 188 |
Page 189 |
Page 190 |
Page 191 |
Page 192 |
Page 193 |
Page 194 |
Page 195 |
Page 196 |
Page 197 |
Page 198 |
Page 199 |
Page 200 |
Page 201 |
Page 202 |
Page 203 |
Page 204 |
Page 205 |
Page 206 |
Page 207 |
Page 208 |
Page 209 |
Page 210