Abstract:

In this paper , the problem of the load restoration was studied and it was modeled as a combinational optimization problem with many constraints. Then , according to the high efficiency of genetic algorithm for solving large-scale combinational optimization problems , a coarse-grain parallel genetic algorithm is presented. In the parallel virtual environment based on message passip.g , the calculation can be efficiently speeded up by using the master/ slave mode of parallel programming. Moreover , by combining the constraints with the objective functions , an order relation is constructed to deal with the constraints in load restoration. As the constraints of load restoration cannot be violated in the solving process , the power system security can be effectively ensured. Simulated results show that the proposed algorithm can effectively speed up the calculation and restart the load as much as possible.

Key words: power system, load restoration, parallel genetic algorithm, combinational optimization, coarse grain