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可再生能源微网电源小信号稳定性分析

Analysis of Small Signal Stability of Micro-grid Power Supply with Renewable Energy
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摘要 为了提高可再生能源微网电源的输出稳定性,进行电源输出小信号的稳定性测试和分析,提出基于匹配滤波和相关性检测的可再生能源微网电源小信号稳定性分析模型。采用匹配滤波检测器进行小信号检测,结合噪声抑制方法对小信号进行干扰抑制和自适应调节的预处理,通过相关性检测方法进行信号的输出稳定性检测,建立信号的高阶统计特征分析模型,再通过对小信号的高阶统计特征量提取结果进行信号的输出转换控制,结合输出均衡性控制和抗干扰性测试方法,进行电源小信号的稳定性分析和测试。仿真结果表明,采用该方法进行可再生能源微网电源小信号测试的稳定性较好,检测准确度较高,提高了电源的可靠性。 To improve the output stability of a micro-grid power supply with renewable energy,the small signal stability test and analysis of the output from the power supply were carried out,and a small signal stability analysis model of the micro-grid power supply with renewable energy based on matched filtering and correlation detection was proposed.The matched filter detector was used for small signal detection,and the small signal preprocessing was performed by combining the noise suppression method for interference suppression and adaptive adjustment.The correlation detection method was used for the detection of signal output stability,and a high-order statistical feature analysis model of the signal was established.Through the signal output conversion control of the small signal high-order statistical feature quantity extraction results,the small signal stability analysis and test of the power supply were carried out with the combination of the output balance control and anti-interference test methods.Simulation results show that the small signal test of the micro-grid power supply with renewable energy has a better stability and a higher detection accuracy when using the proposed method,which improves the power supply reliability.
作者 马一峰 杨乐 贾晟 段新东 MA Yifeng;YANG Le;JIA Sheng;DUAN Xindong(Marketing Department,State GridAnhui Electric PowerCo.,Ltd.,Hefei 230022,China;School of Computerand Information Engineering,Nanyang Institute of Technology,Nanyang 473000,China)
出处 《电源学报》 CSCD 北大核心 2023年第3期70-75,共6页 Journal of Power Supply
基金 河南省科技厅基础与前沿研究规划课题“云储存安全关键技术研究”资助项目(142300410108)。
关键词 可再生能源 微电网 小信号 稳定性 检测 renewable energy micro-grid small signal stability detection
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