Hongyan Dui , Heyuan Li , Xinghui Dong , Shaomin Wu
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An energy IoT-driven multi-dimension resilience methodology of smart microgrids
Smart microgrids are significant in promoting clean energy development and improving microgrid security and reliability. However, harsh environments make them exposed to various hazards, including natural hazards such as hail and wildfire and digital hazards such as cyberattacks. Due to these complex challenges, performing performance evaluation and resilience analysis for smart microgrids in different periods (e.g., before, during, and after the hazards) and different layers (e.g., a data layer and a physical layer) is difficult. To reduce this research gap, this paper develops a new multi-layer failure and multi-dimension resilience methodology in the energy Internet of Things (IoT). This paper analyses a multi-layer failure mechanism of smart microgrids in energy IoT with the synergy of the “physical layer, perception layer, communication layer, and application layer”, establishes a multi-stage performance model for smart microgrids based on operation loops, and develops a multi-dimension resilience methodology for smart microgrids with consideration of four performance evolution processes (i.e., prevention, degradation, restoration, and reconstitution). A case adopted from the Shandong province in China is used to demonstrate the proposed method under normal operating conditions and different types of disasters.
期刊介绍:
Elsevier publishes Reliability Engineering & System Safety in association with the European Safety and Reliability Association and the Safety Engineering and Risk Analysis Division. The international journal is devoted to developing and applying methods to enhance the safety and reliability of complex technological systems, like nuclear power plants, chemical plants, hazardous waste facilities, space systems, offshore and maritime systems, transportation systems, constructed infrastructure, and manufacturing plants. The journal normally publishes only articles that involve the analysis of substantive problems related to the reliability of complex systems or present techniques and/or theoretical results that have a discernable relationship to the solution of such problems. An important aim is to balance academic material and practical applications.