Optimization of power system path restoration is a combinatorial optimization problem

the time needed for computation is increasing exponentially with system scale. Therefore

speeding up the computation is one of the research hotspots in this field. Considering the connectivity constraint in existing research has not been analyzed as yet

the optimization of power system path restoration cannot be formulated as a mixed-integer programming model. Therefore

the blackout system is translated into a single-source multiple-sinks network. Then the bus operation state and amount of network flow in the transmission path are set as decision variables

while flow conservation and capacity constraints for each bus constitute the analytic expressions of connectivity constraint. According to the fundamental principle that the path between nodes of flow injection and arrival is connective. On this basis

a mixed integer linear programming model for optimization of path restoration is built through the analytic expressions of connectivity constraint and by translating the objective function into linear terms. The optimal path restoration is solved by CPLEX. Finally

the proposed linear model is validated by the IEEE test systems and Jiangsu power grid.