摘要
Jiles-Atherton (J-A)磁滞模型静态参数辨识结果直接影响其对变压器铁心磁滞特性的预测效果。针对目前单一智能算法存在的寻优能力差、计算时间长等问题,提出了一种人工鱼群算法与优化惯性权重线性递减粒子群优化算法相结合的混合算法。搭建变压器铁心磁性能测试系统,对正弦激励下变压器铁心的磁滞特性和损耗特性进行实验研究。对比分析了所提混合算法与其他单一智能算法对J-A模型的参数辨识速度与精度。结果表明,混合算法辨识结果的均方根误差仅为0.006 9,低于其他单一智能算法的相应结果,证明了该混合算法相较于其他单一智能算法,具有不易陷入局部最优解、收敛速度快、参数辨识精度高等优点。此外,考虑交变磁场下动态损耗分量对变压器铁心磁滞特性的影响,修正现有动态损耗系数求解方法,建立了J-A动态磁滞模型。通过对比动态磁滞回线模型预测结果与实验数据,验证了该方法的正确性与有效性。
The static parameter identification results of the Jiles-Atherton(J-A) hysteresis model directly affect the predictive effect of the model on the transformer core hysteresis characteristics. Aiming at the problems of poor optimization ability and long calculation time existing in current single intelligent algorithm, a hybrid algorithm combining artificial fish school algorithm and linearly decreasing particle swarm optimization algorithm with optimized inertia weight is proposed. A transformer core magnetic performance test system was set up to conduct the experiment research on the hysteresis and loss characteristics of the transformer core under sinusoidal excitation. The identification speed and accuracy of JA model parameters for the proposed hybrid algorithm and other single intelligent algorithms were compared and analyzed. The results show that the root mean square error of the hybrid algorithm identification result is only 0.006 9, which is lower than those of other single intelligent algorithms. The results prove that the proposed hybrid algorithm has the advantages of being not easy to fall into local optimal solutions, faster convergence speed and higher parameter identification accuracy compared with other single intelligent algorithms. In addition, considering the influence of the dynamic loss component on the hysteresis characteristics of the transformer core under alternating magnetic field, the existing dynamic loss coefficient solution method was modified, and a J-A dynamic hysteresis model was established. Comparing the forecast result of the dynamic hysteresis loop model with experiment data, the correctness and effectiveness of the proposed method are verified.
作者
赵志刚
马习纹
姬俊安
Zhao Zhigang;Ma Xiwen;Ji Jun'an(State Key Laboratory of Reliability and Intelligence of Electrical Equipment,Hebei University of Technology,Tianjin 300130,China;Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province,Hebei University of Technology,Tianjin 300130,China)
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2020年第1期26-34,共9页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(51677052)项目资助.
作者简介
赵志刚,分别在2004年,2007年和2010年于河北工业大学获得学士学位、硕士学位和博士学位,现为河北工业大学教授,主要研究方向为电工磁材料磁性能模拟与工程电磁场数值仿真及应用。E-mail:zhaozhigang@hebut.edu.cn;通信作者:马习纹,2018年于渤海大学获得学士学位,现为河北工业大学硕士研究生,主要研究方向为电工磁材料磁性能模拟与工程电磁场数值仿真及应用。E-mail:ma15131660295@163.com
