![]() ・ Time-varying resilience at the network level, ・ Randomness and dynamics (i.e., non-stationarity) of failures and recoveries, Resilience of power distribution under severe weather poses unique challenges: Hence, the resilience of power distribution requires significant study. Damages from such hazards as severe storms to power distribution can profoundly impact a large number of users. For example, a utility (dis- tribution system operator) can serve millions of customers in America. As the demand for energy grows, the edge of the grid becomes more and more important. However, the majority of the failures occurred during severe storms are often at power distribution rather than transmission networks. For example, cascading failures at transmission networks have been studied widely. Until now, tremendous efforts have been directed to resilience of the core that consists of the major power generation and transmission of high voltages. Here, resilience corresponds to the ability of power distribution to reduce failures and recover rapidly when failed. Ī fundamental research issue pertaining to this real problem is the resilience of power distribution to large- scale external disruptions. Thus power distribution is particularly susceptible to external disruptions from severe weather. About 90% of total failures occurred at power distribution. Many such components are distributed in the open and exposed to external hazards such as hurricanes, derechoes, and ice storms. ![]() Distribution networks consist of a large numbers and diverse types of components, such as substations, power lines, poles, feeders, and transformers. Power distribution provides medium and low voltages to residences and organizations. ![]() Power distribution system lies at the edge of the power grid. ![]() The power grid is a vast interconnected network that delivers electricity to customers. Received accepted 26 February 2016 published 29 February 2016 Our results show non-stationary evolution of failure rates and recovery times, and how the network resilience deviates from that of normal operation during the hurricane. We use the real data from the electric grid to learn time-varying model parameters and the resilience metric. Third, we apply the non-stationary model and the resilience metric to large-scale power failures caused by Hurricane Ike. The resilience metric characterizes the ability of power distribution to remain operational and recover rapidly upon failures. Second, we define time-varying resilience based on the non-stationary model. Transient Little’s Law then provides a simple approximation of the entire life cycle of failure and recovery through a queue at the network-level. First, we derive non-stationary random processes to model large-scale failures and recoveries. This work studies the resilience of power distribution from three aspects. However, the problem of large-scale power failure, recovery and resilience has not been formulated rigorously nor studied systematically. Large-scale power failures often occur, resulting in millions of people without electricity for days. Power distribution, the edge of the energy infrastructure, is susceptible to external hazards from severe weather. This work applies non-stationary random processes to resilience of power distribution under severe weather.
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