碩士 / 國立臺灣科技大學 / 電機工程系 / 105 / Clean wind energy has become an important energy option, with the Kyoto Protocol carbon reduction, the Paris climate agreement to curb the temperature rise and the PM2.5 issue. Therefore, it is critical to estimate wind energy accurately, in order to reduce capital cost, power capacity and operations & maintenance (O&M) costs. In general, there are more savings on total generation cost with a decrease in estimating errors for wind energy forecasts and with an increase in estimating accuracy for the day-ahead unit commitment schedule.
This study is mainly aimed to establish the method of estimating wind speeds, wind power and the profits for offshore wind farms by using Measure-Correlate-Predict (MCP), wind speed frequency distributions and wind turbine power curves. First of all, the main idea of MCP methods lies essentially in the correlation established between the wind data recorded at the target site and those simultaneously recorded at one or several different nearby weather stations as reference stations and where the long-term data are also estimated. Secondly, in order to upgrade the estimating accuracy for both the long-term wind speeds and the wind power at offshore wind farms, we will check the differences between the real results at the target site and the estimating results at reference stations. The maximum absolute error rates between the real results and the estimating results for the average wind speed and for the wind power are 0.00983% and 1.89% respectively. Finally, the research results will be applied to evaluate the investment efficiency for a specific offshore wind farm.
| Identifer | oai:union.ndltd.org:TW/105NTUS5442098 |
| Date | January 2017 |
| Creators | Hwai-Wen Wu, 吳懷文 |
| Contributors | Hong-Chan Chang, 張宏展 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 62 |
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