隨著國際間對於環境保護的重視，各國的能源政策均朝向再生能源發展，其中，又以太陽能與風力發電為主。針對這一類型以逆變器為框架的設備，美國電力協調委員會(Western Electricity Coordinating Council, WECC)開發了通用模型做為分析實際設備響應的模擬架構。本文提出一種通用模型參數設計的流程，結合拉丁超立方取樣及柏拉圖最佳化，使模型的響應能有效的擬合實際逆變器設備的輸出。本文考量逆變器設備在不同的設計情境下，以擬合不同時間區段之動態特徵為目標，透過多目標粒子群演算法結合柏拉圖最佳化，在柏拉圖前緣解集合中，挑選出一組滿足不同的系統運轉條件，且同時匹配設備預期響應的控制器參數。本文將於測試系統及IEEE 39 bus上新增一處大型光伏發電設備，根據預期的設備響應，驗證本文提出之參數設計流程的有效性。

With the increasing attention on worldwide ecological conservation, the energy policies of various countries are moving towards renewable energy systems, primarily with solar and wind as the main power sources. For the typical solar-wind generation system, the Western Electricity Coordinating Council (WECC) has developed a generic model as a simulation framework to analyze the response of the actual equipment. In this paper, we propose a parameter tuning process for the generic model controller that combines Latin hypercube sampling and Pareto optimization to enable the generic model to effectively match the output of the actual inverter device. Different operating scenarios are considered to match the dynamic characteristics of the inverter device by using the multi-objective particle swarm algorithm (MOPSO) along with the Pareto optimization. The effectiveness of the proposed parameter tuning process is verified on a user-defined test system and later on the IEEE 39 bus system with a large solar power facility.

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