Hybrid data-driven resilience assessment and enhancement of distribution system for cyclone susceptible zones

The sprawl of distribution system towards the need of smart grid, demands better sustenance and adaptation strategies to deal with high-impact low-frequency (HILF) events. One of the predominant causes of HILF events are natural calamities. Therefore, the resilience assessment of the distribution system is inevitable. The contributions majorly focuses on hybrid data driven approach using micro-phasor measurement unit (mu-PMU), for dynamic voltage, current phasors monitoring, and unmanned aerial vehicle (UAV) confirms structural vulnerability of nodes within network. Mesh grid approach, which analyses cyclone trajectory affecting the network, supplemented identification of most vulnerable part within network. However, priorities of vulnerable nodes are corroborated using complex network (CN) theory. This hybrid data driven approach and spatial parameters are used to estimate appropriate mitigation strategies against HILF scenarios. Hence, resilience analysis based on location parameters and dynamic network conditions are further analyzed based on degree of correlation of location dependent resilience with latitude, elevation, and probable water level. Based on susceptible vulnerable nodes, identification of optimum alleviation schemes is adopted and justified using resilience trapezoid. To validate efficacy of the proposed approach, the analysis is tested on IEEE 33-bus distribution network subjected to 5 cyclone prone geographical coordinates for 20 years cyclone data.