Abstract: ‍ ‍In recent years， adaptive algorithms have been widely used in power system frequency estimation. Many scholars have tried to apply the classical adaptive filter theory to frequency estimation， and have achieved good results. However， under various complex power system operating conditions， the frequency estimation performance of traditional adaptive algorithms has the problem of deterioration. Therefore， in order to improve the frequency estimation performance of the algorithm， this paper proposes a distributed complex logarithmic hyperbolic cosine （DClncosh） algorithm and a distributed enhanced complex logarithmic hyperbolic cosine （DAClncosh） algorithm based on the lncosh cost function based on the diffusion topological network. Then， in MATLAB simulation， the power system imbalance conditions， Gaussian noise environment， non-Gaussian noise environment and the frequency estimation performance of the algorithm using measured data are simulated， and compared with the distributed complex minimum mean square （DCLMS） algorithm and distributed enhanced complex minimum mean square （DACLMS） algorithm， the simulation results verify the superiority of the frequency estimation performance of the distributed enhanced complex logarithmic hyperbolic residual algorithm.