An Autonomous Fault Diagnosis and Isolation Recovery Algorithm for High Load Density Urban Distribution Network

The distribution network in the urban downtown area of Shanghai has the characteristics of high load density and serves many important consumers. The 10 kV distribution network has the most times of faults in full voltage level of power grid, which has a great impact on reliability. In order to ensure a safe and stable operation, this paper presents an autonomous fault monitoring, diagnosis and isolation recovery algorithm for distribution network in high load density downtown area. Firstly, the grid graph theory model is constructed to realize a fast fault location and the division of minimum outage area. Then the load transfer switch set and switch action sequence are generated to ensure a quick recovery of power supply in non-fault areas. Finally, simulation is built to based on an actual case for demonstration. The proposed algorithm can accurately locate faults and provide optimal power supply path, which greatly reduces the affected number of households during power outage. This can also contribute to a resilient distribution network.