| During the development of electric power industry, popularization of power market in the whole country, optimal power flow of the power system plays an important role on solving the new problems that are caused by power market. In this paper, the mathematic model of the optimal power flow, with the minimum cost of power purchase as its object function, is firstly represented. Then particle swarm optimization that is used to solve optimal power flow is modified. Variables are disserted and inequality constraints are dynamically adjusted by non-stationary multi-stage assignment penalty function. The program is compiled by the language of MATLAB and the interface is created by LabVIEW. The IEEE-30 system is tested. 24 interval trades of one day are calculated and analyzed, the outputs and costs of every interval is determined. The validity of the algorithm has been testified through the test system.
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