| Summary: | 碩士 === 清雲科技大學 === 電機工程研究所 === 96 === At present, the development of ocean current generator technology is at the stage of
single-machine prototype design or test. The generation amount of each generator is small.
Hence, the ocean current farm will be created by aggregating many ocean current generators
in the future. There are two purposes in this thesis. One is, according to the distribution
characteristics of ocean currents, to obtain the optimal speed parameters, such as cut-in speed
and rated speed, of single generator by the Turbine Performance Index (TPI). Another is, in
the ocean current farm with fixed area, to obtain the optimal number and locations of the
generators under the considerations of wake effect, generator model and cost model. It can be
used to achieve the best profit of the ocean current farm.
In the study of the first purpose, the speed distributions of Taiwan's offshore ocean
currents are guaranteed as normal distribution and the closed form equation of TPI is
conducted. The average current speeds of Taiwan's offshore ocean currents are between 0.26
m/s and 1.17 m/s. The deeper the depths are, the slower the average speeds will be. The
optimal cut-in speeds are under 0.7 m/s and optimal rated speeds are between about 1.04m/s
and 2.24 m/s.
In the study of the second purpose, Simple Genetic Algorithm (SGA), Hybrid Distributed
Genetic Algorithm (HDGA), Binary Particle Swarm Optimization (BPSO) and Hybrid Binary
Particle Swarm Optimization (HBPSO) are used to obtain the optimal solutions of number
and locations of the ocean current generators. Test results show that BPSO and HBPSO are
better than that of SGA and HDGA in performance. Where the BPSO can obtain the best
accurate solution and executing speed is quite fast. However, if the faster speed is desirable,
the HPBSO can be suggested, but accuracy must be degraded a little.
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