本論文提出一個用來改善低電壓穿越性能的智慧型控制之雙級太陽光發電系統去處理在弱電網情況下之故障。一般電網的強度與短路比有密切關係，當短路比越低電網的強度越弱。本文太陽光發電系統包含一個交錯式直流至直流轉換器與一個三階層中性點箝位變流器所組成。此外，太陽光發電系統具有智慧型變流器功能，其中太陽光電變流器的輸出實功、虛功是根據電網規範所計算的。為了提高太陽光發電系統的控制性能來處理在弱電網情況下之故障，本文提出了一種線上學習的遞迴式小波模糊類神經網路，用來取代傳統的比例積分控制器用於智慧型變流器的實虛功控制。此外，本文提出的太陽光發電系統的控制器是透過PSIM軟體來模擬。另外，所提出的控制器是使用浮點運算數位訊號處理器的兩個控制平台來實現。從模擬結果與實驗結果可以看出，利用智慧型變流器的智慧型控制，可以實現在弱電網情況下發生故障時實功控制與虛功控制的優良性能。;An intelligent control method is proposed to improve the low-voltage-ride-through (LVRT) performance of a two-stage photovoltaic (PV) power plant to deal with grid faults under weak grid condition. Generally, the strength of the grid is closely related to the short circuit ratio (SCR). When the SCR is lower, the strength of the grid is weaker. The PV power plant is composed of an interleaved DC/DC converter and a three-level neutral-point clamped (NPC) inverter. Moreover, the PV power plant possesses the smart inverter function, in which the output active and reactive powers of the inverter are calculated according to the grid codes of the utilities. In order to improve the control performance of the PV power plant to handle grid faults under weak grid condition, an online trained recurrent wavelet fuzzy neural network (RWFNN) is proposed to replace the traditional proportional-integral (PI) controller for the active and reactive powers control of the smart inverter. Furthermore, the proposed controllers of the PV power plant are simulated via PSIM software. In addition, the proposed controllers are implemented by two control platforms using floating-point digital signal processor (DSP). From the simulation and experimental results, excellent control performance for the active and reactive powers control under grid faults and weak grid condition can be achieved by using the intelligent control of the smart inverter.
