摘要
基于电场耦合的非接触式电压传感器应用于配网三相架空线路监测时,会受到各相输电线路之间电场的相互干扰,而目前非接触式测量大多也只是在单相线路上进行实验。为此,提出了一种改进的卡尔曼滤波(KF)方法提高其测量的准确性。首先,通过电场仿真分析叠加电场影响,然后结合算法理论建立系统状态空间模型,并对不同噪声水平的扰动信号进行测试。仿真结果表明:该组合模型滤波精度高于KF和自适应KF(AKF),均方根误差(RMSE)值分别下降了37.81%和14.2%,且随叠加电场干扰的增大其优势更加明显;麻雀搜索算法(SSA)在该模型下的性能也优于粒子群优化(PSO)算法和遗传算法(GA),证明了该方法在工程实际中有着较好应用前景。
When the non-contact voltage sensor based on electric field coupling is applied to the monitoring of threephase overhead lines in the distribution network,it will be interfered by the electric field between the transmission lines of each phase.At present,most of the non-contact measurement are only carried out on the single-phase line.Therefore,an improved Kalman filtering(KF)method is proposed to improve the accuracy of its measurement.Firstly,the influence of superimposed electric field is analyzed by electric field simulation.And then,the state space model of the system is established by combining the algorithm theory,and the disturbance signals with different noise levels are tested.The simulation results show that the filtering precision of the combined model is higher than that of KF and adaptive KF(AKF),and the root mean square error(RMSE)values are reduced by 37.81%and 14.2%respectively,and the advantages are more obvious with the increase of superimposed electric field interference.The performance of sparrow search algorithm(SSA)under this model is also better than that of particle swarm optimization(PSO)algorithm and genetic algorithm(GA),which proves that this method has a good application prospect in engineering practice.
作者
秦浩鑫
耿蒲龙
刘珂
QIN Haoxin;GENG Pulong;LIU Ke(National&Provincial Joint Engineering Laboratory of Mining Intelligent Electrical Apparatus Technology,Taiyuan University of Technology,Taiyuan 030024,China)
出处
《传感器与微系统》
北大核心
2025年第10期164-168,共5页
Transducer and Microsystem Technologies
基金
山西省重点研发计划项目(202003D111008)
国网山西省电力公司科技项目(52053023000G)。
