本研究主要分為兩部分，第一部分為模擬太陽能變化測試最大功率點追蹤演算法之追蹤評估比較，此兩種演算法分別二次式極值法(Quadratic Maximization)與最陡梯度法(Steepest Descent Method)，以LabVIEW軟體模擬三種變化測試:步階變化、Fast Ramp快速變化以及Slow Ramp緩慢變化，經由NI sb-RIO傳送模擬結果的虛擬電壓電流資訊給MPPT Controller進行最大功率點追蹤運算，計算每次從新追蹤至最大功率點需花費多少時間以及損失多少能量，對此結果分析其兩者優缺點。
第二部分為應用MPPT Controller於五片分散式太陽能發電系統中，並使用該系統進行遮陰實驗，將太陽能板進行手動遮陰使系統從新追蹤，並觀察追蹤至最大功率點所需時間，最後將兩者演算法實驗結果與模擬結果一同比較。
由第二部分確認MPPT Controller之穩定性後，使用該控制器至十片太陽能分散式系統中，以驗證該控制器運用於大型分散式發電系統中之可行性。

This study is divided into two parts, the first part of the simulation of solar energy change test maximum power point tracking algorithm to track the comparison, the two algorithms were quadratic polar method (Quadratic Maximization) and the steepest gradient method (Steepest Descent Method to simulate three changes in LabVIEW software: step changes, Fast Ramp rapid changes and Slow Ramp slow changes, through the NI sb-RIO to send simulation results of the virtual voltage and current information to the MPPT Controller for maximum power point tracking operation, calculate each How much time is spent and how much energy is lost from the new tracking to the maximum power point, and the advantages and disadvantages of the two are analyzed.
The second part is the application of MPPT Controller in five decentralized solar power generation system, and the use of the system for shading experiments, the solar panels to manually shade the system from the new tracking, and observe the time to track to the maximum power point, and finally The experimental results of the two algorithms are compared with the simulation results.
After confirming the stability of the MPPT Controller from the second part, use the controller to ten solar decentralized systems to verify the feasibility of the controller in a large decentralized power generation system.

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