基于改进型VMD算法的充电控制的光伏功率平滑技术

蒙家彬

基于改进型VMD算法的充电控制的光伏功率平滑技术

引用本文：蒙家彬.基于改进型VMD算法的充电控制的光伏功率平滑技术[J].计算技术与自动化,2026,(1):171-177

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作者	单位
蒙家彬	（1.山东省水利勘测设计院有限公司,山东济南 250013）

中文摘要:为解决光伏发电系统因光照和温度变化导致的功率波动影响电网稳定性问题，提出了基于可靠单调充电控制策略的光伏功率平滑方法，该方法结合光伏输出功率预测技术与自适应变分模态分解算法，利用遗传算法优化的 Elman 神经网络预测功率激变阶段，通过自适应变分模态分解算法确定分解模式和并网模式数量以实现储能系统优化充放电控制，实验结果显示其平滑后的跟踪性能高达 0.99，储能系统 SOC 上下波动不超过 1%，此方法不仅减少了储能系统的容量需求，提高了光伏发电系统的能量利用效率，还能有效平滑光伏功率波动，满足电网稳定性需求。

中文关键词:光伏功率平滑可靠单调充电控制策略自适应变分模态分解储能系统优化光伏输出功率预测

Photovoltaic Power Smoothing Technology of Charge Control Based on Improved VMD Algorithm

Abstract:To address the issue of power fluctuations in photovoltaic (PV) generation systems caused by variations in irradiance and temperature, which affect grid stability, this study proposes a PV power smoothing method based on a reliable monotonic charging control strategy. This method integrates PV output power prediction technology with an adaptive variational mode decomposition (AVMD) algorithm. It utilizes a genetic algorithm-optimized Elman neural network to predict power surge stages. The AVMD algorithm is employed to determine the decomposition modes and grid-connected mode quantities, thereby achieving optimized charge-discharge control of the energy storage system. Experimental results demonstrate that the tracking performance after smoothing reaches as high as 0.99, with the state of charge (SOC) of the energy storage system fluctuating within no more than 1%. This method not only reduces the required capacity of the energy storage system, enhances the energy utilization efficiency of the PV generation system, but also effectively smooths PV power fluctuations, meeting grid stability requirements.

keywords:photovoltaic power smoothing reliable monotonic charging control strategy adaptive variational mode decomposition optimization of energy storage system photovoltaic output power prediction

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