【目的】风速、环境温度和湿度等风资源参数具有显著的时变特性，其动态波动直接影响风力发电机的输出功率与温升。针对此问题，本文开展永磁风力发电机(PMWG)变负载工况下的特性研究，旨在实现对发电机温度状态的快速、精准监测。【方法】本文以一台以6 MW大功率PMWG为研究对象，采用有限元法建立其电磁仿真模型，得到绕组损耗、铁心铁耗和永磁体涡流损耗等关键损耗参数。然后，采用热网络法建立PMWG热网络模型。结合风电机组运行过程中风能载荷的随机变化特性，设计恒定负载工况和变负载工况，并进行相应工况的温升特性研究。最后，通过PMWG厂内型式试验数据和风电场运行测试数据对相关工况进行验证。【结果】对比PMWG厂内型式试验数据与仿真计算结果可得，额定负载工况下电机温升过程各采样点的平均相对误差为5%，验证了PMWG热网络模型的可靠性与准确性。对比风电场运行实测数据与仿真计算结果可得，变负载工况下平均温差百分比为4.5%。【结论】本研究揭示了大功率PMWG变负载工况下的温升特性，为PMWG在风电场运行场景下发电机各部件温升预测、预警及热管理系统控制参数设置提供参考。

[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.

湖南省自然科学基金(2024JJ8045);湖南省教育厅科学研究项目(25C1151, 25C1152);茂名市科技计划项目(2023013)