在遮蔽效應下的太陽能電池會產生多個區域最大功率點,傳統的最大功率點追蹤法容易陷入局部最大功率點,無法找出全域最大功率點。因此本文提出組合式蛙跳演算法結合擾動觀察法之混合法找出全域最大功率點,應用於太陽能市電併聯系統,即太陽能電池的電力經由Boost轉換器和全橋式變流器轉換後併入市電,並利用類神經分數階PI進行全橋式變流器電流控制。最後,本論文使用Matlab軟體模擬,驗証最大功率點追蹤混合法可在遮蔽效應下太陽能系統操作在全域最大功率點。
The photovoltaic panels have plural operational regions for power generation under partial shading conditions, such that the traditional maximum power point tracking(MPPT) methods will lead to local maximum power generation. To obtain the global maximum power generation, this thesis proposes a hybrid method by combining Shuffled Frog Leaping Algorithm(SFLA) and Perturb and Observe(P&O) algorithm. A grid-tied PV power generation system is taken as the application, where a boost converter and a full-bridge inverter are used to transfer the PV power for grid-tied systems. Moreover, the neural network based on fractional-order PI current control is used for the current regulation of the full-bridge inverter. Finally, numerical simulation and experimental results show the expected performance of the global maximum power point tracking under partial shading conditions.