本研究應用增強型蚱蜢群聚演算法於儲能裝置選址與容量擇定，期以透過演算法之優異求解能力，協助儲能裝置之設置規劃，並在兼顧經濟考量下，有效提升現有配電系統運轉效能。本文所提之增強型蚱蜢群聚演算法經由觀察蚱蜢群體覓食行為建立完善求解機制，進而應用至本文之儲能裝置設置規劃。在規劃目標上，本文將總規劃成本、尖峰負載量及電壓偏差率納入規劃考量，並在滿足上述目標前提下，完成儲能裝置設置地點與裝置容量規劃之決策。而為驗證本文所提方法之成效，本文分別透過工業、住宅和商業類型配電系統進行模擬測試，證明本儲能裝置規劃確可提升系統供電與運轉穩定度，本文同時於測試情境中另加入太陽光電與電動車充電負載，用以驗證不同測試條件下之規劃可行性，規劃成果可提供配電工程規劃實務參考。

This study proposes the enhanced grasshopper algorithm to energy-storage device location and capacity determination. This algorithm assists the deployment of energy storage device through its satisfactory computational ability, by which the operational efficiency of distribution systems can be effectively improved. The solving mechanism of this algorithm for the planning of energy-storage device is derived based on the foraging behavior of grasshoppers. The investment cost, peak load, and voltage deviation are all included in the objective functions of the planning problem that is concerned. To verify this proposed method, the simulation is tested through industrial, residential and commercial distribution systems. Meanwhile, the photovoltaic system and electric vehicle charging scenarios are both taken into considerations for the feasibility assessment of the method. Test results gained from these scenarios are useful for practical distribution engineering planning studies.

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