Optimization study of post-disaster resilience enhancement and resource scheduling of distribution networks in coastal cities based on mixed-integer linear programming

In this paper, a two-stage robust optimization model based on mixed-integer linear programming is proposed for the problem of resilience enhancement and resource scheduling optimization of distribution networks in coastal cities under extreme disasters.The optimization model of active distribution network power supply restoration is constructed to realize multi-resource cooperative scheduling by combining linearized tidal current constraints.A line maintenance team scheduling model is established to optimize the fault repair path and sequence.Design the two-stage robust optimization framework, and realize the master-slave problem iteratively solved by the column constraint generation algorithm.The simulation results show that under the three fault scenarios, the SRCL indexes of Case3 are improved by 31.108%,39.321% and 27.42%, and the RRCL is improved by 4.355%, 19.853% and 6.703%, respectively, compared with that of Case2, and the voltage overrun problem can be effectively suppressed.The robustness analysis verifies the adaptability of the model to the uncertainty of line maintenance time, and provides decision support for the formulation of post-disaster recovery strategies.