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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yuan-Kang Wu Ching-Yin Lee Chao-Rong Chen Kun-Wei Hsu Huang-Tien Tseng |
| Copyright Year | 1972 |
| Abstract | The interest in the utilization of offshore wind power is increasing significantly worldwide. A typical offshore windfarm may have hundreds of generators, which is outspread in the range of several to tens of kilometers. Therefore, there are many feasible schemes for the wind turbine location and internal line connection in a wind farm. The planner must search for an optimal one from these feasible schemes, usually with a maximum wind power output and the lowest installation and operation cost. This paper proposes a novel procedure to determine the optimization wind turbine location and line connection topology by using artificial intelligence techniques: The genetic algorithm is utilized in the optimal layouts for the offshore wind farm, and the ant colony system algorithm is utilized to find the optimal line connection topology. Furthermore, the wake effect, real cable parameters, and wind speed series are also considered in this research. The concepts and methods proposed in this study could help establish more economical and efficient offshore wind farms in the world. |
| Sponsorship | IEEE Industry Applications Society |
| Starting Page | 2071 |
| Ending Page | 2080 |
| Page Count | 10 |
| File Size | 1649725 |
| File Format | |
| ISSN | 00939994 |
| Volume Number | 50 |
| Issue Number | 3 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-01-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wind turbines Wind farms Equations Mathematical model Rotors Genetic algorithms Optimization Wake effect Offshore Wind Power Artificial Intelligent Genetic Algorithm Ant Colony System wake effect Ant colony system (ACS) artificial intelligence genetic algorithm (GA) offshore wind power optimization |
| Content Type | Text |
| Resource Type | Article |
| Subject | Industrial and Manufacturing Engineering Control and Systems Engineering Electrical and Electronic Engineering |
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