本論文主要目的在於開發出基於二元樹搜尋法和RBFNN模型之配電系統三相電力潮流運算。首先，針對串聯型元件及並聯型元件等非線性元件，經由徑向基函式神經網路(Radial Basis Function Neural Network, RBFNN)訓練開發出新元件模型。其次，針對三相輻射狀配電系統，提出之基於二元樹搜尋之電力潮流法，以二元樹所創的T矩陣與前後掃描法運算結合。本論文皆利用商用套裝軟體Matlab 2016a版，開發新的三相電力潮流分析法以及新元件模型。最後，以IEEE測試系統為基準，在準確性、執行時間、疊代次數等項目來驗證所提出的方法。

The major purpose of this thesis is to develop the three-phase power flow calculations using the binary tree algorithm with radial basis function neural network (RBFNN) based network models for distribution systems. Firstly, for non-linear elements such as series element and parallel element, new network component models have been developed via RBFNN training. Secondly, for three-phase radial distribution systems, the proposed power flow method is combined with the T matrix obtained by the binary tree search algorithm, and forward and backward sweep approach. In this thesis, the new three-phase power flow analysis method and new network component models are developed by Matlab 2016a commercial software package. Finally, the IEEE test systems are used as benchmark to demonstrate the proposed method in terms of accuracy, execution time, and iteration number.

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