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基于SA-PSO的风电消纳经济性动态规划分析

Research on Dynamic Economic Dispatch of Grid-connected Wind Power Based on SA-PSO Algorithm

  • 摘要:
      目的  电网运行规划研究在电力系统中具有十分重要的地位,对电源布局具有决策意义,其本质上是一个多约束组合优化问题,重点研究了风电运行成本的计算模型。
      方法  该模型对电源布局规划中需要重点考虑的约束问题进行了分析,采用粒子群算法用于解决此类目标优化问题,并结合模拟退火理论对传统粒子群算法进行了优化处理。
      结果  通过仿真计算,与遗传算法及粒子群算法进行了对比分析,证实了这种算法的优越性,可以找到满足各种约束条件的最优电网出力方案。最后,进一步分析了在不同风速下对风电并网运行成本影响。
      结论  该模型应用于电网规划分析是可行且有效的。

     

    Abstract:
      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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