The invention discloses an assessment method for an impedance identification error index of a large photovoltaic inverter. The method comprises the steps that (1) a time sequence of an evolution system for the impedance identification error index of the large photovoltaic inverter is established according to parameters obtained through real-time monitoring; (2) a genetic neural network of measured data is subjected to optimization processing according to the time sequence of the evolution system; and (3) the impedance identification error index of the large photovoltaic inverter is calculated according to the optimization processing result of the genetic neural network. Through the method, the problem that in existing methods, only a regional power grid or all systems in a photovoltaic power generation system are adopted to perform parameter fluctuation analysis independently, and consequently assessment accuracy and photovoltaic utilization efficiency are not high is solved; the method has the advantages of improving assessment accuracy, avoiding problems concerning power quality caused by connection of a photovoltaic power station into a power distribution network system, remarkably increasing the photovoltaic utilization rate, remarkably improving the reliability of the power distribution network electric system and remarkably improving the economical efficiency of the power distribution network electric system.