基于光伏电站场景下的梯次电池储能经济性分析
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国家自然科学基金资助项目(51577065);国家重点研发计划资助项目(2017YFGX100110)


Economic Analysis of Echelon Battery Energy Storage Based on Artificial Fish Swarm Algorithm
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Project supported by National Natural Science Foundation of China (51577065)

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    摘要:

    大规模可再生能源并网时,通过配置储能系统平抑功率波动,可以实现能量的平稳转移。以某光伏电站为应用场景,分析梯次电池储能在平抑光伏功率波动这一应用模式下的优化规划并评估其经济性。建立光伏电站储能系统优化规划和经济性评估模型,以满足并网波动率限制下储能容量成本最小为目标函数,采用人工鱼群算法进行优化求解,并通过对比常规储能系统评估梯次电池的经济性。选取相关算例进行分析,结果表明模型具有一定的合理性和有效性。

    Abstract:

    Large scale renewable energy such as wind power grid, photovoltaic grid and others has brought great challenges to the grid's afety and stability. Energy storage system should be configured so as to stabilize the power fluctuation and achieve energy smooth transfer. Under the application scenario of photovoltaic power plant,the echelon battery storage' optimal planning is analyzed in the mode of stabilizing the photovoltaic power fluctuation . Economic evaluation is assessed. The optimal planning and economic evaluation model of the photovoltaic power plant energy storage system is established to meet the minimum storage capacity cost under the limit of the grid fluctuation ratio. The artificial fish swarm algorithm is used for solution optimization, and the economy evaluation of echelon battery is assessed and compared with conventional energy storage system. The results show the rationality and validity of the model.

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刘大贺,韩晓娟,李建林.基于光伏电站场景下的梯次电池储能经济性分析[J].电力工程技术,2017,36(6):27-31,77

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  • 收稿日期:2017-06-28
  • 最后修改日期:2017-08-20
  • 录用日期:2017-09-04
  • 在线发布日期: 2017-11-27
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