Reliability Assessment Method for Urban Distribution Network Based on Lightning Search Algorithm

With the gradual improvement of residential electricity reliability, the lower design strength of the distribution network makes it more prone to large-scale power outages in resisting natural disasters. Among them, the cold load start-up effect will significantly prolong the recovery time and affect reliability indicators. Based on this, this article proposes a reliability evaluation method for urban distribution networks based on a lightning search algorithm, which is used for optimal recovery planning and reliability calculation of urban power systems with highly concentrated load under constant temperature control. Firstly, a delay index model is used to establish a time-sharing power demand calculation model for cold load start-up events, and an optimal recovery model with the goal of minimizing recovery time and its corresponding constraints are proposed. Then, the cold load start-up event is incorporated into the Monte Carlo simulation platform for reliability assessment, and the lightning search algorithm is used to develop the optimal recovery plan. The recovery time and sequence are determined based on the duration of the power outage and the electricity demand at the time of recovery. Finally, the test distribution system was used to verify that the optimal recovery plan considering cold load start events does not violate the constraint conditions, and the stability and convergence robustness of the lightning search algorithm are stronger than the current mainstream algorithms. It can effectively improve the reliability of the distribution grid when considering cold load start events.