[Objective] Wind resource parameters such as wind speed, ambient temperature and humidity, exhibit prominent time-varying characteristics, and their dynamic fluctuations directly affect the output power and temperature rise of wind generators. Addressing this issue, this paper investigates the operating characteristics of permanent magnet wind generator (PMWG) under varying load conditions, aiming to realize fast and accurate monitoring of generator temperature state. [Methods] A 6 MW high power PMWG was taken as the research object. The finite element method was employed to construct the electromagnetic simulation model, and key loss parameters including winding loss, core iron loss and permanent magnet eddy current loss were obtained. Afterwards, thermal network model for the PMWG was established using the thermal network method. Considering the stochastic variation characteristics of wind load during wind turbines operation, constant load and varying load conditions were designed, and the temperature rise characteristics under corresponding conditions were investigated. Finally, the relevant operating conditions were validated using factory type test data and wind farm field test data of the PMWG. [Results] The comparison between the factory type test data of the PMWG and the simulation results showed that the average relative error of each sampling point in the motor temperature rise process under rated load operating condition was 5%, which verified the reliability and accuracy of the thermal network model for the PMWG. The comparison between the measured wind farm operation data and the simulation results indicated that the percentage of average temperature difference under varying load condition was 4.5%. [Conclusion] This study reveals the temperature rise characteristics of high power PMWG under varying load conditions, and provides a reference for temperature rise prediction, early warning of each generator component as well as the setting of control parameters for thermal management systems of PMWG operating in wind farm scenarios.