本文提出一種多目標最佳化方法來解決配電系統日前電壓控制問題，主要目的是根據日前負載變動下來決定變電所有載分接開關(on load tap changer, OLTC)和可切換式電容器(switched capacitor, SC)設置的最佳排程。本研究中提出的目標函數考量OLTC和SC的切換限制：(1)最小化主變壓器匯流排上的電壓偏差，(2)最小化系統總功率損失。將多目標粒子群算法與柏拉圖前緣相結合，利用曼哈頓距離作為求解指標來評估多目標問題。此外，該方法進一步考慮分散式能源發電(distributed generation, DG)的不確定性。本文採用Digsilent-Powerfactory結合Matlab 2016a版。在模擬中研究不同的DG併網點和運轉情境對電壓控制調度的影響，之後再考慮結合智慧變流器的區域控制策略，最後通過 IEEE 33 BUS 測試系統驗證該方法的效率和性能。

In this thesis, a multi-objective optimization method is proposed to solve the day-ahead voltage control problems in distribution systems. The main purpose of this thesis is to determine the optimal schedule for on-load tap changer (OLTC) settings at the substation and the switched capacitors (SC) based on the day-ahead load forecasting. The objective functions presented in this study are: (1) minimizing voltage deviation at the main transformer bus, and (2) minimizing total power losses within switching limits of OLTC and SC. The multi-objective particle swarm algorithm is combined with the Pareto front and the Manhattan distance is applied as a solution index to assess these multi-objectives problems. In addition, the uncertainty of distributed generation (DG) is further considered in the proposed method. The Digsilent-Powerfactory combined with Matlab 2016a software packages are used in the thesis. In the simulations, the effects of different DG grid-connected points and operation scenarios on the voltage control scheduling are examined. Afterward, the regional control strategy combined with the smart inverter is taken into consideration. Finally, the efficiency and performance of this proposed method is verified by the IEEE 33 BUS test system.

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