| Summary: | [Introduction] The study of power grid operation planning plays an important role in power system and has decision-making significance for power distribution, which is a multi-constraint combinatorial optimization problem in fact. Research is mainly focused on the wind power cost calculation model. [Method] In view of various constraint conditions that generation expansion planning need to consider, particle swarm optimization (PSO) was used to solve this kind of objective optimization problem, and the traditional PSO was optimized based on simulated annealing theory. [Result] Numerical examples confirmed the superiority that can be found an optimal power output scheme to satisfy various constraints by comparison with the particle swarm algorithm and genetic algorithm. Finally, the influence on wind power grid connected operation cost under different wind speed were further analyzed. [Conclusion] It is feasible and effective to apply this model to power grid planning and analysis.
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