摘要 發展乾淨再生能源是我國能源政策的目標。近年來全球風力發電機組裝置容量增加,預期風力發電機組未來將會穩定快速成長,並扮演著逐漸重要的能源角色。 風力發電機運轉所產生的噪音來源可分為兩種:(1) 機械噪音,是由機艙內的發電設備運轉所產生之噪音,(2) 空氣動力噪音,是因氣流通過葉片轉動時所產生風切之噪音。 本論文主要探討兩種不同型式的風力發電機運轉時所產生之噪音,進而比較風速與發電量之關係。再利用類神經網路系統,以量測較少的次數進行分析,產生數學式。往後便可利用此數學式,即可得知風速或發電量的預估值。因此吾人希望藉由量測風力機噪音,能更深入了解風力發電機的原理。
Abstract Developing clean recycle energy source is our goal. In the recent years, the worldwide wind turbine installed capacity has increased dramatically. The global wind turbine market is expected to continue growing rapidly and stably, making wind turbine an increasingly important energy source. The sources of sounds emitted from operating wind turbines can be divided into two categories: 1) Mechanical sounds, from the interaction of turbine components, and 2) Aerodynamic sounds, produced by the flow of air over the blades. This thesis investigates these two different kinds of the sounds in order to compare the relationship between the wind speed and the power. Moreover, there is a mathematics formula produced after analyzing the sounds and using the neural network. Afterwards, the estimated data can be known by using this formula. Therefore, I hope I can firmly understand the theorem of the wind turbine through this study.