首页|基于T-S模糊神经网络的光伏发电机组自动控制

基于T-S模糊神经网络的光伏发电机组自动控制

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光照情况变化会使光伏发电机组功率呈现不稳定性,加大光伏发电机组控制难度,为此,设计了基于T-S模糊神经网络的光伏发电机组自动控制方法.构建光伏阵列数学模型,分析在均匀和不均匀2种光照情况下光伏发电机组特性曲线.以分析结果为依据,采用T-S模糊神经网络构建光伏发电机组自动控制模型.为保证良好的控制效果,引入定比因子优化隶属度函数,输出最佳跟踪结果,结合最佳跟踪结果和自动控制模型实现光伏发电机组自动控制.测试结果显示,该方法能够完成光伏阵列特性分析,控制效果好.
Automatic Control of Photovoltaic Generator Set Based on T-S Fuzzy Neural Network
The change of illumination will make the power of photovoltaic generator set unstable,which increases the difficulty of photovoltaic generator set control.Therefore designs an automatic control method of photovoltaic generator set based on T-S fuzzy neural network.The mathematical model of pho-tovoltaic array is established,and the characteristic curve of photovoltaic generator set under uniform and uneven illumination is analyzed.Based on the analysis results,the T-S fuzzy neural network is used to construct the automatic control model of photovoltaic generator set.In order to ensure good control effect,the constant ratio factor is introduced to optimize the membership function,and the best tracking results are output.The automatic control of photovoltaic generator set is realized by combining the best tracking results and the automatic control model.The test results show that this method can complete the photovol-taic array characteristic analysis and the control effect is good.

T-S fuzzy neural networkphotovoltaic generator setautomatic controlcharacteristic curvemaximum power pointlighting conditions

杨振睿、沈主浮、孙辰、蔡斌、姜宽

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国网上海市电力公司市区供电公司调度控制中心,上海 200080

国网上海市电力公司市区供电公司总师室,上海 200080

T-S模糊神经网络 光伏发电机组 自动控制 特性曲线 最大功率点 光照情况

2024

机械与电子
中国机械工业联合会科技工作部 机械与电子杂志社

机械与电子

CSTPCD
影响因子:0.243
ISSN:1001-2257
年,卷(期):2024.42(2)
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