Abstract:Techniques are described which have been employed to develop detailed, quantitive estimates of the available ocean wave energy flux. A summary of results for a region of particular interest to potential U.S. developers of wave energy systems — the U.S. Northwest Pacific Coast — is also presented. Comparisons with results of other studies are made. In addition, a method for predicting the amount of mechanical energy captured by a conversion device, based on a frequency domain technique, is presented. Results ar… Show more
“…Wave power extraction has long since been an alternative energy source being studied as far back as was conducted by Brown et al [4]. It is a low density resource, resulting in the requirement to have large structures to capture the energy [5]. Wave power is a predictable source of sustainable energy that has yet to be utilized to any significant extent anywhere in the world [2].…”
Section: Wave Power Technologies Consideredmentioning
Three individual wave power generation technologies were studied and evaluated using multicriteria decision analysis through the use of the PROMETHEE method. To evaluate the three technologies, data were collected from previously performed experimental testing on the performance of each wave power generation technology. These data were used to feed into seven different criteria; namely the capacity factor, rated power, capital cost, operation and maintenance (O&M) costs, cost of electricity (COE)for a JO year payback, maturity, and survivability. The associated data and criteria were used to determine the optimal technology. The results from the Decision Lab modeling ranked the Wave Dragon, AquaBuOY, and Pelamis technologies as 1,2, and 3, respectively, for ali three locations: Tofino/Ucluelet, Hibernia Oil Platform, and St. John's, Newfoundland. A sensitivity analysis of the threshold values determined for the baseline modeling indicated that the original ranking was essentially unaffected when the threshold values were modified (increased and decreased). The weights of the criterion were individually adjusted to evaluate any change in ranking order. A sizable increase in weighting of greater than 40% of any one criterion (while the others were weighed equally) resulted in a change of the overall ranking order of the three technologies. Final weightings on each of the criterion were assigned with preference on rated power, COE, and maturity stage. All other criteria were weighted equally and like the baseline modeling output, the results of the model ranked Wave Dragon, AquaBuOY, and Pelamis from most favorable to least favorable for all three of the locations analyzed.
“…Wave power extraction has long since been an alternative energy source being studied as far back as was conducted by Brown et al [4]. It is a low density resource, resulting in the requirement to have large structures to capture the energy [5]. Wave power is a predictable source of sustainable energy that has yet to be utilized to any significant extent anywhere in the world [2].…”
Section: Wave Power Technologies Consideredmentioning
Three individual wave power generation technologies were studied and evaluated using multicriteria decision analysis through the use of the PROMETHEE method. To evaluate the three technologies, data were collected from previously performed experimental testing on the performance of each wave power generation technology. These data were used to feed into seven different criteria; namely the capacity factor, rated power, capital cost, operation and maintenance (O&M) costs, cost of electricity (COE)for a JO year payback, maturity, and survivability. The associated data and criteria were used to determine the optimal technology. The results from the Decision Lab modeling ranked the Wave Dragon, AquaBuOY, and Pelamis technologies as 1,2, and 3, respectively, for ali three locations: Tofino/Ucluelet, Hibernia Oil Platform, and St. John's, Newfoundland. A sensitivity analysis of the threshold values determined for the baseline modeling indicated that the original ranking was essentially unaffected when the threshold values were modified (increased and decreased). The weights of the criterion were individually adjusted to evaluate any change in ranking order. A sizable increase in weighting of greater than 40% of any one criterion (while the others were weighed equally) resulted in a change of the overall ranking order of the three technologies. Final weightings on each of the criterion were assigned with preference on rated power, COE, and maturity stage. All other criteria were weighted equally and like the baseline modeling output, the results of the model ranked Wave Dragon, AquaBuOY, and Pelamis from most favorable to least favorable for all three of the locations analyzed.
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