重庆大学雪峰山能源装备安全国家野外科学观测研究站,重庆市 400044
林莉(1974—),女,通信作者,博士,副教授,硕士生导师,主要研究方向:电力系统运行与控制。E-mail:linli@cqu.edu.cn
孙婷(2000—),女,硕士研究生,主要研究方向:储能并网运行与控制。E-mail:sunting0409@163.com
孙语韩(2004—),女,硕士研究生,主要研究方向:储能并网运行与控制。E-mail:3145721488@qq.com
收稿:2026-01-19,
修回:2026-04-09,
网络首发:2026-09-17,
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林莉,孙婷,孙语韩等.基于模态动态调整的混合储能系统双层功率协调控制[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20260119003.
LIN Li,SUN Ting,SUN Yuhan,et al.Bi-layer Power Coordinated Control of Hybrid Energy Storage System Based on Dynamic Modal Adjustment[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20260119003.
林莉,孙婷,孙语韩等.基于模态动态调整的混合储能系统双层功率协调控制[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20260119003. DOI:
LIN Li,SUN Ting,SUN Yuhan,et al.Bi-layer Power Coordinated Control of Hybrid Energy Storage System Based on Dynamic Modal Adjustment[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20260119003. DOI:
在风-储联合系统中,为在合理分配混合储能功率的同时优化储能元件运行状态,提出了基于模态动态调整的双层功率协调控制策略。首先,为在确保并网功率尽可能大的前提下提升固定模态分解对非平稳风电功率特征的适应性,提出了基于模态动态调整的储能功率获取方法。其次,计及功率的频率特征与储能单元的功率响应特性,构建了储能系统双层功率分配策略。在信号分解层,在改进灰狼优化算法的基础上提出了变分模态分解两个关键参数的自适应寻优方法,同时,以能量熵指标量化各本征模态函数的能量分布特性,确定计及蓄电池和超级电容频率响应特性的初始功率分配准则。在功率修正层,从充放电一致性与荷电状态运行区间两方面对蓄电池和超级电容的充放电功率进行二次校正,以抑制无效的能量交互和蓄电池的深度充放电风险。仿真结果表明,所提策略能够在风电波动场景下实现储能功率的合理分配,优化储能元件的运行状态,验证了所提策略的有效性。
In a wind-storage combined system
to rationally allocate the power of a hybrid energy storage system while optimizing the operating state of storage elements
a bi-layer power coordinated control strategy based on dynamic modal adjustment is proposed. Firstly
to improve the adaptability of fixed mode decomposition to the characteristics of non-stationary wind power on the premise of ensuring that the grid-connected power is as large as possible
a storage power acquisition method based on dynamic modal adjustment is proposed. Secondly
taking into account the frequency characteristics of power and the power response characteristics of storage units
a bi-layer power allocation strategy for the energy storage system is constructed. In the signal decomposition layer
based on an improved grey wolf optimization algorithm
an adaptive optimization method for the two key parameters of variational mode decomposition is proposed. Meanwhile
the energy entropy index is employed to quantify the energy distribution characteristics of each intrinsic mode function
and an initial power allocation criterion accounting for frequency response characteristics of the battery and supercapacitor is determined. In the power correction layer
the charging and discharging power of the battery and supercapacitor is secondarily corrected from two aspects of charging and discharging consistency and the operating range of the state of charge
so as to suppress invalid energy interactions and the risk of deep charging and discharging of the battery. Simulation results show that the proposed strategy can achieve reasonable allocation of storage power in wind power fluctuation scenarios and optimize the operating state of storage elements
verifying the effectiveness of the proposed strategy.
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