Abstract
When a meteorological disaster occurs and equipment becomes damaged, a significant amount of time is required to repair the damaged components as it is impossible to repair several components simultaneously. Therefore, the determination of repair priority is a significant aspect of a distribution system’s resilience. This study proposes a technique to identify the unserved areas of a radial distribution system based on the bus injection to the branch current (BIBC) matrix, as opposed to a complex optimization technique, for evaluating the repair priority determination strategy for all the possible disaster scenarios. Generally, most resilience metrics include the concept of duration; therefore, the strategy for resilience enhancement must optimize the recovery priority using an objective function that consists of the recovered capacity increment, rather than the recovered capacity. To verify the proposed method, in this paper, the resilience is evaluated under all the disaster scenarios that can occur in contingencies from N-2 to N-5. Since complex restoration or repair strategies could be simplified using the proposed method, it is expected that this study will make a significant contribution to the resilience enhancement in distribution systems.
Highlights
Most definitions of power-system resilience focus on the capability for anticipation, absorption, and rapid recovery from an external high-impact, low-probability (HILP)event
In the scenario where a failure occurred in the components that have longer repair durations than the overhead line which accounts for the majority of the remaining components, RS1 failed to optimize the repair priority
A technique for identifying the unserved areas; Repair priority by recovered capacity increment (RCI) (=the increased amount of the available capacity of the entire system divided by the repair duration); Repair priority by comparing the RCIs due to the repair of two or more damaged branches
Summary
Most definitions of power-system resilience focus on the capability for anticipation, absorption, and rapid recovery from an external high-impact, low-probability (HILP). The time taken to reconfigure the system structure and to start or interconnect the available energy resources is less than that required to move repair crews for restoration-path optimization, in the repair of a distribution system, the time taken to repair the damaged components is the maximum compared to any other process. This study evaluates the resilience using this metric, which applies the active power that can be supplied by the distribution system to customers (‘available capacity’) as the system performance level To enhance this resilience metric that includes a time unit, the repair priority must be determined by comparing the increased available capacity through repair during the unit repair duration (‘recovered capacity increment’).
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