太陽能發電系統經常發生部分遮蔭情形，使得太陽能電池之功率-電壓特性曲線呈現多峰現象，因此開發一適用於部分遮蔭情形之全域最大功率追蹤技術顯得更為重要。對此，本文提出以兩階段法為基礎之全域最大功率追蹤技術，在第一階段根據模擬所得之結果追蹤至最大功率點附近，第二階段以Alpha因子擾動觀察法改善追蹤之精確度，並將操作點穩定控制在最大功率點上。
為了驗證本文所提方法之正確性與可行性，實際完成一600 W之最大功率追蹤電路。在遮蔭情形下，模擬結果與決定型杜鵑鳥搜尋法相比，在上升時間方面改善了34.67%，在穩定時間方面改善了25.18%，在平均追蹤電能損失方面減少35.68%，且穩態追蹤精確度可達99.99%。實測結果證明本文所提方法在不同遮蔭樣式下皆能追蹤到全域最大功率點，且在所測試的五種遮蔭樣式下其穩態追蹤精確度皆高於99.00%。

Photovoltaic generation systems (PGSs) frequently experience partial shading conditions (PSCs). Because PSCs will result in multiple peak values on the power-to-voltage characteristic curve, developing an algorithm that facilitates tracking global maximum power point (GMPP) is crucial. Therefore, a two-stage GMPP tracking algorithm is proposed in this thesis. In the first stage, the vicinity of the maximum power point is obtained by performing extensive simulations, while during the second stage, alpha factor perturb and observe (P&O) method is utilized to improve the tracking accuracy and stably control the operating point at the maximum power point.
To verify the correctness and feasibility of the proposed MPPT algorithm, a 600 W prototyping circuit is constructed. The simulation results compared with the deterministic cuckoo search (CS) method under partial shading conditions show that the rising time is shortened by 34.67%, the settling time is improved by 25.18%, the average tracking power loss is reduced by 35.68%, and the 99.99% steady-state tracking accuracy can be achieved. Experimental results also validate that the proposed method can obtain GMPP under different shading patterns, and above 99.00% steady-state tracking accuracy has been reached on the specific five PSC test cases.

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