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Wind storms such as hurricanes increase the outage rate of overhead transmission lines and hence can seriously affect the security of power systems. Therefore, it is very important to estimate the overhead transmission line outage rate for a power system that might be jeopardized by wind storms. In this paper, we propose a new method for estimating the outage rate of overhead transmission lines, with two primary advantages. First, the proposed method describes the relationship between the outage rate and the weather factors by a fragility curve customized for overhead transmission lines to ensure that the relationship is precisely represented. Second, the proposed method takes the conductor strength reduction and different physical properties of overhead transmission lines into consideration to increase outage rate estimation accuracy. We test the proposed method by estimating the outage rate of overhead transmission lines in a regional power system based on both historical and simulated wind storms. The test results show that the proposed method generates a more accurate estimation than the conventional approaches. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Truck-mounted mobile emergency generators (MEGs) are critical flexibility resources of distribution systems (DSs) for resilient emergency response to natural disasters. However, they are currently under-utilized. For better utilization, this paper proposes dispatching MEGs as distributed generators in DSs to restore critical loads by forming multiple microgrids (MGs). As the travel time of MEGs on road networks (RNs) can greatly influence the outage duration of critical loads, a two-stage dispatch framework consisting of pre-positioning and real-time allocation is introduced, and the traffic issue is considered via the vehicle routing problem. Pre-positioning places MEGs in staging locations prior to a natural disaster, while real-time allocation sends MEGs from staging locations to restore critical loads by forming MGs in DSs after the natural disaster strikes. Specifically, with the objective of minimizing the expected outage duration of loads considering their priorities and demand sizes, pre-positioning is done via a scenario-based two-stage stochastic optimization problem, in which the first-stage pre-positioning decisions are evaluated by numbers of second-stage real-time allocation problems corresponding to considered scenarios of DS damage and RN damage/congestion. A scenario decomposition algorithm is applied to solve this problem. Illustrative cases demonstrate the effectiveness of the proposed dispatch scheme and algorithm. [ABSTRACT FROM PUBLISHER]