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系統識別號 U0026-1707201914095700
論文名稱(中文) 彰濱海域的海氣象及發電特性分析
論文名稱(英文) Analysis on Meteorology and Power Generation Characteristics in Chanbin Offshore Area
校院名稱 成功大學
系所名稱(中) 機械工程學系
系所名稱(英) Department of Mechanical Engineering
學年度 107
學期 2
出版年 108
研究生(中文) 張劭謙
研究生(英文) Shao-Chien Chang
學號 N16064111
學位類別 碩士
語文別 英文
論文頁數 107頁
口試委員 指導教授-林大惠
口試委員-余政達
口試委員-涂謙誠
口試委員-呂昭宏
中文關鍵字 測風塔  風力特性  季風  東北季風  颱風  發電量  年發電量  發電量波動 
英文關鍵字 Meteorological Mast  Wind Characteristic  Monsoon  Northeast Monsoon  Typhoon  Power Production  AEP  Power Fluctuation 
學科別分類
中文摘要 強勁的東北季風是台灣海峽天氣系統的一大特色。本研究將 2017
及 2018 年台電海氣象觀測塔量測的風資料圖像化並進行風速與風向 的基本統計分析。搭配 Vestas V-164 9.5MW 風機的功率曲線進行彰 濱地區的風力與發電量分析,並計算出年發電量以及發電量在一個小 時內的變化量,呈現了東北季風雖強勁但是風速變化劇烈此一現象。 發電量的急劇變化對於電力調度方面是一大挑戰。風機工作狀態的時 間佔比與東北季風時期的發電量佔比呈現了東北季風可觀的風資源。 同時,海上浮球量測的波高資料也進行了快速傅立葉分析,並將其結 果與風資料的傅立葉分析結果進行比對,得到風與浪有三處共同的週 期性此一結論。
颱風是台灣的另一個天氣特色。本研究使用了台電海氣象觀測塔 與固定式光達量測的梅姬颱風 (RSMC No. 1617) 風資料,計算其亂 流強度,並且與東北季風時期的資料進行比較,發現颱風的亂流強度 並未強過東北季風的亂流強度。
北海擁有良好的氣候條件,為歐洲地區離岸風電發展的先進地區 本研究匯整了 KNW (KNMI North sea Wind) 於 FINO1 之風資料、 MERRA-2 於丹麥 Horns Rev 風力發電廠之風資料以及台電海氣象
doi:10.6844/NCKU201900784
觀測塔量測的風資料,進行發電量分析以及發電量波動分析,結果顯 示台灣海峽的東北季風發電量波動確實較北海地區嚴重。
英文摘要 In this research, the wind data for 2017 and 2018 was measured by the Taipower meteorological mast. Wind speed and wind direction at heights of 10, 30, 50 and 95 meters were available. The resolution of the wind data is one second and that of the wave data is one hour. The wind and wave data for 2017 and 2018 were visualized and presented. The turbulent intensity for these years was plotted with the IEC61400-3 standard and the Weibull distribution was calculated and also presented in terms of seasons. The Fast Fourier Transform was applied to the wind and wave data to investigate if there were similar periodic variations.
The power production was estimated based on the ten-minutes resolution wind speed data and the power curve of the Vestas V-164 9.5MW turbine. The AEP (Annual Energy Production) was presented and the working status of the turbine was discussed in terms of the northeast monsoon (NE monsoon) season and the non-northeast monsoon (non-NE monsoon) season separately. The sudden power rise or drop will cause problems to the power management. If the power rise suddenly, there must have arrangements to smooth down the surges. On the contrary, if the power goes through a sudden drop, there must have some traditional generator sets which can launch as soon as possible to compensate for the power gap. This research is aimed to analyze the power fluctuation induced by the changeable wind in the NE monsoon season in Taiwan Strait and compare the phenomenon with that in the North Sea. To investigate severe variations in the NE monsoon wind, the power fluctuation during each one-
doi:10.6844/NCKU201900784
hour period were estimated and plotted together with the power output in the form of a time series.
Typhoons are another feature of Taiwan's weather system. The wind data of Typhoon Megi (RSMC No. 1617) which was measured with Taipower mast and the WindCube LiDAR were visualized. Another three periods in the NE monsoon season with relatively high wind speed were selected to compare with this typhoon.
The wind characteristic in Europe extremely applicable in terms of wind energy. The KNW data (a modified wind dataset provided by the Royal Netherlands Meteorological Institute) at FINO1 and the MERRA-2 data (a reanalysis wind dataset provided by NASA,) at the Horns Rev wind farm were chosen to investigate the similarities and differences between the wind characteristics of Taiwan and those of the North Sea area.
論文目次 Contents
List of Tables III
List of Figures V
1. Introduction 1
2. Literature Review 9
2.1. Betz limit 9
2.2. Power law and log law 10
2.3. Weibull distribution 12
2.4. Power curve 13
3. Experimental Method 15
3.1. Measurement Setup 15
3.1.1. TaiPower Meteorology Mast 15
3.1.2. Tower Distortion Factor 17
3.1.3. Leosphere WindCube V2 18
3.2. Datasets 21
3.2.1. Observational Data 22
3.2.2. MERRA-2 Data 22
3.2.3. KNW Data 23
3.3. Analysis Method 24
3.3.1. Statistical Analysis of Wind Data 24
3.3.2. Fast Fourier Transform Analysis 25
3.3.3. Power Analysis 26
4. Results and Discussions 31
4.1. Wind and Wave in Chanbin Area 31
4.1.1. Wind Analysis 31
4.1.2. Wave Analysis 46
4.1.3. FFT Analysis 52
4.1.4. Power Analysis 57
4.1.5. Wind Condition of Typhoon 71
4.2. Park Optimization 80
4.3. Comparison with the North Sea 87
5. Conclusions 99
6. Future Works 101
7. Reference 103
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