風渦輪發電機存在著非線性的特性,故其最大功率點之位置將隨著風力狀況的改變而有所不同。本論文主要的目的是從風力發電系統追蹤最大的輸出功率點,之後再將功率輸出。本論文提出兩種新的最大功率追蹤技術應用於風力發電系統:模糊邏輯控制法與最佳點近似估測法。藉由追蹤理論改變昇降壓轉換器之責任週期,使風渦輪發電機之輸出功率與在最大功率點之功率相同。文中建立系統風速步階變化模型,用以設計控制程式及確認實驗之結果。電流型與電流頻率型擾動觀察法理論亦以實作的方式完成,以模糊邏輯控制法及最佳點近似估測法則相互比較。本論文使用數位訊號處理器(TMS320C240)估計最大功率點之位置,並控制風力發電系統中,昇降壓轉換器之責任週期,以達最大功率追蹤之目的。 為證實本論文所提出技術之可行性,所提之最大功率追蹤法將藉由一台三相、12極、400瓦的風渦輪發電機作實際的測試,並與現有之擾動觀察法比較。風渦輪發電機包括了三片直徑1.17公尺的風渦輪機與一台永磁式同步發電機。由實驗的結果得知,本論文所提出之最大功率法,即使在不同的風力情況下,皆能有效地追蹤至最大功率操作點,其中,最佳點近似估測法具有最佳之追蹤效果與穩定性。
The wind turbine generator exhibits a nonlinear characteristic and its maximum power point varies with changing atmospheric conditions. The objective of the thesis is to track maximum power point from wind energy conversion system (WECS) and transfer power to a resistive load or a battery.The thesis presents two novel maximum power point tracking (MPPT) techniques, fuzzy logic control and optimal point approximate estimate method, used in wind energy conversion system. The tracking algorithm changes the duty ratio of the converter such that the wind turbine generator power equals the power corresponding to the maximum power point. A wind speed step model was used in design and check phase. Current type and current-frequency type perturbation and observation (P&O) algorithm are also implemented to compare with fuzzy logic control and optimal point approximate estimate method. In this thesis, using digital signal processor (TMS320C240) to estimation the position of the maximum power point and rectify the duty ratio of buck-boost in WECS. To verify the effectiveness of the proposed approaches, these four MPPT methods have been tested on a practical three-phase, 12-pole, 400W, wind turbine generator. The wind turbine generator includes of a wind-turbine with three 1.17m diameter blades and a permanent magnet synchronous generator (PMSG). The experimental results show that these four MPPT methods have successfully tracked the maximum power operating point, even in case of different atmospheric conditions. And optimal point approximate estimate method has the best tracking efficiency and stability.