چكيده به لاتين
In recent years, hurricanes, tornadoes, floods, and other severe weather events have caused devastating economic damage to society, and it is expected that with the current approach, these events will continue to have severe financial and human impact. The dependence of sensitive industries and enterprises and service centers that are directly related to the welfare and security of the people has also made electricity one of the irreplaceable foundations of human civilization. But in the last decade, the continued availability of this energy has been jeopardized by severe weather events and human threats, which has put studies on ensuring a continuous supply of this energy to subscribers on the agenda of researchers. Examining the strategies to reduce the vulnerability and reversibility of power systems against such accidents is discussed in the form of resilience of power systems.
In response to these challenges, this thesis examines the concept of resilience and prioritizes recovery by highlighting the role of short-term resilience measures, that is, rapid recovery measures with a valuation approach to assets and team planning. For this purpose, in this research, the prioritization of power distribution system lines in different scenarios is discussed. In this regard, the economic value of power distribution system lines is modeled as a measure of network sensitivity to storms. The basis of modeling is based on value in which the value of the load, the probability of failure of foundations, fragility curve, line repair time by the repair team and topology factor is considered to model the importance of demand side, failure rate and availability of lines, time and network layout. To be. Also, to optimize this valuation, scenarios related to hedging and the existence of scattered products in the network have been discussed. From this model, the priority of line repair is derived from low to high resilience, the number of crews required during the storm, the amount of carbon dioxide emitted by the repair crew, and the effect of corona status on the number of crews. This modeling is based on a hypothetical network consisting Three IEEE-33 bus feeders have been tested.
