参数自适应SFS算法多逆变器并网孤岛检测技术
Islanding Detection Technology for Multiple Grid-connected Inverters Based on Adaptive Parameters SFS Algorithm
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摘要: 针对传统Sandia频率偏移(SFS)算法在多逆变器并网条件下孤岛检测性能的不足,提出了一种基于参数自适应的改进SFS算法。该算法利用数字相关原理检测公共耦合点电压与逆变器输出电流间相位差,根据测到的相位差对SFS算法中的初始斩波系数cf0及正反馈增益K随逆变器频率检测误差及负载品质因数的不同做相应调整,以消除稀释效应及高品质因数负载所导致的孤岛检测失败。理论分析及仿真实验结果表明,所提出的改进SFS算法在出现稀释效应及负载条件较恶劣的情况下,孤岛检测性能明显优于传统算法。Abstract: In view of the inadequate performance of islanding detection of the traditional Sandia frequency shift(SFS)method for multiple grid-connected inverters,an improved SFS algorithm based on adaptive parameters is proposed.The algorithm uses the digital correlation theory to detect the phase difference between the voltage of the point of common coupling and the output current of the inverter.According to the phase difference,the initial chopping coefficient cf0 and positive feedback gain Kof the SFS algorithm are adjusted accordingly with respect to the detection error of frequency and load quality factor,so as to eliminate the failure of islanding detection caused by the dilution effect and high quality factor of load.Theoretical analysis and simulation experiment results show that the improved SFS algorithm is evidently superior to the traditional algorithm in the case of dilution effect and bad load conditions.