本文以雲端運算服務、前端網頁服務及資料庫作為雲端基礎架構，並以軟體即服務(Software as a Service, SaaS)之概念規劃一種用於儲能系統之雲端資訊管理系統。其次，本文於雲端運算服務中導入人工智慧神經網路技術，使儲能系統資訊可透過神經網路進行分析，並將其資訊呈現於前端網頁，充分落實單一系統滿足儲能系統資訊之管理。再者，本文以物聯網技術實現主從式架構，以降低電池管理系統之複雜度，並透過網際網路隨時與雲端進行溝通，以實現即時監控及分析等功能。另外，本文將系統進行整合，並且透過軟體日誌及資料視覺化之方式，以驗證系統之成果。最後，本文將人工智慧神經網路技術於電池剩餘容量之預測與目前新型方法相比，證明本文所使用之方法誤差較低。

This thesis uses cloud computing services, front-end web services and databases as the cloud infrastructure, and plans a cloud information management system for energy storage systems with the concept of Software as a Service (SaaS). Secondly, this thesis introduces an artificial intelligence neural network technology into the cloud computing service, so that the energy storage system information can be analyzed through the neural network, and its information is presented on the front-end webpage, fully implementing a single system to meet the management of the energy storage system information. Furthermore, this thesis implements the master-slave architecture with the “Internet of Things” technology to reduce the complexity of the battery management system and communicate with the cloud at any time through internet to achieve real-time monitoring and analysis. In addition, this thesis integrates the system and verifies the results of the system through software log and data visualization. Finally, this thesis compares the prediction of the remaining capacity of battery by artificial intelligence neural network technology with now existing methods, confirming the validity of the proposed method with a lower prediction error.

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