基于MALW-SCHO-VMD的风电平抑策略

Wind Power Calming Strategy Based on MALW-SCHO-VMD

  • 摘要: 为解决风电出力的随机性、间歇性和难以预测性等关键技术问题,提出一种减小混合储能出力的风功率平抑和无风功率预测的混合储能功率分配策略。首先,分析了滑动平均滤波和限幅滤波的基本特性,提出了改进滑动平均限幅加权滤波分离并网功率与储能功率方法;其次,采用双曲正弦余弦算法优化的变分模态分解储能功率,考虑混合储能各自荷电状态约束与自身能量密度要求,设计了相应的并联混合储能模糊控制器,二次提升储能功率分配精度,建立混合储能系统年综合成本经济模型;最后,通过典型日数据仿真验证表明,所提平抑策略可以有效平滑并网功率,具备较高精度的功率分配能力,可以满足两类储能的充放电实际需求,解决储能的过充过放问题,提高系统整体经济效益。

     

    Abstract: In order to solve the key technical problems such as randomness, intermittency and unpredictability of wind power output, a hybrid energy storage power allocation strategy with reduced hybrid energy storage output and no wind energy prediction is proposed. Firstly, the basic characteristics of moving average filter and limiter filter are analyzed, and an improved moving average limiter weighted filter method is proposed to separate grid-connected power from energy storage power. Secondly, the variational mode decomposition of energy storage power optimized by hyperbolic sine and cosine algorithm is adopted, and the corresponding parallel hybrid energy storage fuzzy controller is designed to improve the energy storage power distribution accuracy twice, and the annual comprehensive cost economic model of the hybrid energy storage system is established. Finally, the simulation and verification of typical daily data show that the proposed calming strategy can effectively smooth grid-connected power and has a high precision power distribution capability, which can meet the actual requirements of charge and discharge of the two types of energy storage, solve the problem of over-charge and over-discharge of energy storage, and improve the overall economic benefits of the system.

     

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