近年來由於計算科學的發展，藉由各種分析法探討極端事件可能造成的衝擊是目前相當熱門的研究主題，內容包含天然災害的發生與人為的蓄意攻擊對於民生問題的影響，而重要基礎建設受到破壞將產生不可預期的連鎖效應。民生重要基礎建設常被視為典型的複雜系統，近年來以電腦模擬輔助分析這類重點基礎建設的研究也越來越多。綜觀文獻中所提出之重要基礎建設弱點分析的架構，基本上多包含兩個步驟：(1) 以拓樸方式過濾分析重要基礎建設中的弱點 (2) 以系統動力學方式了解基礎建設之弱點的成因。在本計畫中，我們將嘗試以電力供應網路為例，藉由拓樸連結與可靠度的網路分析，以系統動力學模擬方式及時間序列預測平台，進行過濾、實驗、及分析的工作。由於現今電力供應系統與通信資訊系統的關係密切，非常適合當作重要基礎設施的例子。本計畫希望能透過科學計算的技術，建立國家重要基礎建設的分析模型與研究方法，以做為後續研發及重要決策的參考。 Owing to the development of the computational science in recent years, the impacts of various extreme events could be studied as well as estimated. Many approaches have been proposed to study the impacts of our modern life due to the appearance of natural disasters or intentional attacks by people. It is known that important national infrastructures can be considered as a typical complex adaptive system. In recent years, it has become a trend to use the technologies developed in computer simulations to assist the analysis of the vulnerability of critical infrastructures. Typically, there are two successive stages in the framework of such an approach: a topological screening analysis for identifying its vulnerability of the critical infrastructure and a detailed modeling of the system dynamics of the identified parts for gaining insights about the vulnerability. In this project, we will attempt to use the network of electric power supply as an example to discover the vulnerability embedded in critical infrastructures. In such a system, analysis is based on measures of topological interconnection, reliability efficiency, and forecasting nonlinear time-series whereas the screening task is to capture the detailed dynamics of the operational scenarios involving the most vulnerable parts of the critical infrastructure. In this project, we hope that by making use of the technologies developed in computational sciences, we can build a good analytical model and a new research method for the study of national infrastructure. And as a result, the conclusions drawn in this study can be used as an important reference for decision making by the government.