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光储充一体化电站容量配置优化

Capacity configuration optimization of optical storage charging station

  • 摘要: 随着电动汽车的市占率越来越高以及充电技术的进步,加剧了电力系统的波动。本文以系统成本为目的,考虑光伏出力、电动汽车充电的不确定性、储能的电特性等特性,采用种群竞争机制与局部微扰策略,采用杂草入侵算法(InvasiveWeedOptimization,IWO)加快收敛速度。最后通过算例仿真,验证算法的全局搜索与收敛稳定性,实现经济性与光伏消纳的平衡。

     

    Abstract: With the increasing market share of electric vehicles and the progress of charging technology, the fluctuation of power system is aggravated. Aiming at the system cost, considering the characteristics of photovoltaic output, the uncertainty of electric vehicle charging and the electrical characteristics of energy storage, this paper adopts the population competition mechanism and local perturbation strategy, and adopts the Invasive Weed Optimization (IWO) algorithm to accelerate the convergence speed. Finally, through the example simulation, the global search and convergence stability of the algorithm are verified, and the balance between economy and photovoltaic consumption is realized.

     

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