针对静电荷逃逸电子式电压互感器(electronic voltage transducer,EVT)电场边缘效应引入的附加电容影响其测量准确性的问题,提出一种粒子群优化算法(particle swarm optimization,PSO)、风驱动优化算法(wind driven optimization,WDO)、最小二乘支持向量机(least squares support vector machine,LSSVM)结合的电场优化方法.首先,采用WDO-LSSVM构建描述EVT电场分布的数学模型,其中用WDO优化LSSVM的参数选择.其次,采用PSO算法求解上述数学模型,获得EVT电场分布最优时的物理参数组合.同时,提出一种电极结构优化方法,将电极边缘切削成圆弧或斜面以改善电场局部集中现象.最后,采用COMSOL仿真软件构建EVT的三维模型,对EVT进行电流-电路耦合场仿真.仿真结果表明,所提方法减小了边缘效应引入的附加电容和EVT的测量误差.
Electric field optimization method of electrostatic charge escape electronic voltage transformer
Addressing the issue of additional capacitance induced by electric field edge effects in electrostatic charge escape electronic voltage transformers,which impair measurement accuracy,this study proposes an integrated electric field optimization method combining particle swarm optimization(PSO),wind driven optimization(WDO),and least squares support vector machine(LSSVM).Initially,a mathematical model depicting the EVT's electric field distribution is established using WDO-LSSVM,with WDO optimizing the selection of LSSVM parameters.Subsequently,PSO is employed to solve this model,yielding the optimal physical parameter set for EVT electric field distri-bution.Further,an electrode structure optimization strategy is introduced,involving chamfering electrode edges into arcs or slopes to alleviate local field concentration.Lastly,COMSOL simulation software is utilized to construct a 3D model of the EVT and conduct current-circuit coupled field simu-lations.Simulation outcomes demonstrate that the proposed approach effectively reduces the additional capacitance from edge effects and minimizes the measurement error of the EVT.
electronic voltage transformerelectric field optimizationartificial intelligence algorithmCOMSOL simulationstructural improvement
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