计及水电机组运行状态的水光储互补系统功率平滑方法

王冉旋, 孙子龙, 周鹍, 李渊

太阳能学报 ›› 2026, Vol. 47 ›› Issue (4) : 61-73.

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (4) : 61-73. DOI: 10.19912/j.0254-0096.tynxb.2024-2154

计及水电机组运行状态的水光储互补系统功率平滑方法

  • 王冉旋, 孙子龙, 周鹍, 李渊
作者信息 +

POWER SMOOTHING METHOD FOR HYDROELECTRIC-PHOTOVOLTAIC-ENERGY STORAGE SYSTEM CONSIDERING OPERATING STATUS OF HYDROELECTRIC UNITS

  • Wang Ranxuan, Sun Zilong, Zhou Kun, Li Yuan
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文章历史 +

摘要

为提高光伏发电系统的可靠性和稳定性,减少对电网功率波动的影响,提出计及水电机组运行状态的水光储互补系统功率平滑方法。根据水电机组实际运行数据,提取表征水电机组性能的特征指标,采用改进的复杂信息指标客观赋权法结合逼近理想解排序法(CRITIC-TOPSIS)得到水电机组运行状态的初始评估,将评估结果作为卷积神经网络(CNN)-灰狼优化的支持向量机(GSVM)模型的标签输出,建立基于CNN-GSVM的水电机组运行状态在线识别模型。利用自适应局部加权回归算法和小波分解算法将光伏功率信号分解为低频并网功率和由不同性能水电机组和储能承担的高频波动功率,制定水光储互补系统协调控制策略,实现光伏功率的平滑控制。通过某区域水光储互补系统实际运行数据仿真验证了所得方法的有效性。算例分析结果表明,根据水电机组实时运行状态调整水电机组和储能系统出力,在保证平抑光伏功率波动的同时兼顾了水电机组的安全性。

Abstract

In order to improve the reliability and stability of photovoltaic power generation systems and reduce the impact on grid power fluctuations, this paper proposes a power smoothing method for a hydroelectric-photovoltaic-energy storage complementary system considering the operating status of hydroelectric units. Based on the actual operating data of hydropower units, the feature indicators that characterize the performance of hydropower units are extracted. The improved CRITIC-TOPSIS method is used to obtain the initial evaluation of the operating status of hydropower units. The evaluation results are used as the label output of the Convolutional Neural Network (CNN)-Grey Wolf Optimization Support Vector Machine (GSVM) model to establish an online recognition model for the operating status of hydropower units based on CNN-GSVM. Using local weighted regression algorithm and wavelet decomposition algorithm, the photovoltaic power signal is decomposed into low-frequency grid connected power and high-frequency fluctuating power borne by different performance hydropower units and energy storage. A coordinated control strategy for the hydroelectric-photovoltaic-energy storage complementary system is formulated to achieve smooth control of photovoltaic power. The effectiveness of the proposed method is verified through simulation of actual operating data of the hydroelectric-photovoltaic-energy storage complementary system in a certain region. The simulation analysis results show that adjusting the output of the hydroelectric unit and energy storage system based on the real-time operating status of the hydroelectric unit not only ensures the smoothing of photovoltaic power fluctuations but also considers the safety of the hydroelectric unit.

关键词

卷积神经网络 / 支持向量机 / 小波变换 / 灰狼算法 / 水光储互补 / 改进CRITIC-TOPSIS

Key words

convolutional neural networks / support vector machines / wavelet transforms / grey wolf algorithm / water-solar-storage complementarity / improving CRITIC-TOPSIS

引用本文

导出引用
王冉旋, 孙子龙, 周鹍, 李渊. 计及水电机组运行状态的水光储互补系统功率平滑方法[J]. 太阳能学报. 2026, 47(4): 61-73 https://doi.org/10.19912/j.0254-0096.tynxb.2024-2154
Wang Ranxuan, Sun Zilong, Zhou Kun, Li Yuan. POWER SMOOTHING METHOD FOR HYDROELECTRIC-PHOTOVOLTAIC-ENERGY STORAGE SYSTEM CONSIDERING OPERATING STATUS OF HYDROELECTRIC UNITS[J]. Acta Energiae Solaris Sinica. 2026, 47(4): 61-73 https://doi.org/10.19912/j.0254-0096.tynxb.2024-2154
中图分类号: TK519   

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