郭倍源,尹雁和,阮志杰,周桂,刘劲,卢小海,阮大兵
GUO Beiyuan,YIN Yanhe,RUAN Zhijie,ZHOU Gui,LIUJin,LU Xiaohai,RUAN Dabing

• 1:广东电网有限责任公司中山供电局

摘要(Abstract)：

由蓄电池和超级电容器组成的HESS（混合储能系统）可以有效减小光伏出力随机性和波动性对并网的影响。为补偿预测误差与平抑波动，提出一种基于ICPO-VMD-HT（改进的冠豪猪优化-变分模态分解-希尔伯特变换）算法的混合储能容量优化配置方法。首先，以量化的功率预测误差与波动允许带宽建立综合目标域。然后，结合ICPO-VMD参数，并采用HT实现综合目标域内外功率的精准解析，进而分配低频与高频分量至蓄电池和超级电容器。最后，建立年综合成本经济模型，以河北某光伏电站实际数据为例验证了所提方法的有效性和优越性。
A hybrid energy storage system(HESS) composed of batteries and supercapacitors can effectively mitigate the impact of photovoltaic(PV) output randomness and fluctuation on grid connection. To compensate for prediction errors and suppress power fluctuations, this paper proposes a hybrid energy storage capacity optimization method based on the improved crested porcupine optimizer, variational mode decomposition, and Hilbert transform(ICPO-VMD-HT) algorithm. Firstly, a comprehensive target domain is established based on quantified power prediction errors and an allowable fluctuation bandwidth. Then, leveraging the parameters of the ICPO and VMD, the HT is employed to achieve precise decomposition of the power components inside and outside this comprehensive target domain. Subsequently, the low-frequency and high-frequency power components are allocated to the batteries and supercapacitors, respectively. Finally, an economic model for the annual comprehensive cost is established. Case studies using actual data from a PV plant in Hebei Province verify the effectiveness and superiority of the proposed method.

关键词(KeyWords)： 光储系统;混合储能;容量配置;功率预测;冠豪猪优化算法;变分模态分解;希尔伯特变换
photovoltaic-storage system;hybrid energy storage;capacity configuration;power prediction;CPO;VMD;HT

Abstract:

Keywords:

基金项目(Foundation): 南方电网公司科技项目（GDKJXM20240575）

作者(Author): 郭倍源,尹雁和,阮志杰,周桂,刘劲,卢小海,阮大兵
GUO Beiyuan,YIN Yanhe,RUAN Zhijie,ZHOU Gui,LIUJin,LU Xiaohai,RUAN Dabing

DOI: 10.19585/j.zjdl.202603012

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