基于粒子群算法适应度的变压器匝间短路保护方案

Transformer protection scheme for turn-to-turn fault based on particle swarm optimization fitness

为了实现匝间短路的灵敏识别,根据匝间短路对变压器等效电路的影响,提出一种基于粒子群适应度的匝间短路保护方案。根据变压器有功损耗方程构建用于电阻参数辨识的适应度函数;采用粒子群算法展开辨识,得到寻优空间的最小适应度值;基于最小适应度值构造判据识别匝间短路。计及过渡电阻、测量噪声对保护有效性进行仿真验证的同时,分析影响保护灵敏度的因素,并与基于回路平衡方程、励磁电感的保护原理进行灵敏度对比,最后开展动模试验,得出结论:此方案用于匝间短路识别具有很高的灵敏度,并且可以避免参数计算误差的影响;识别效果不受负载影响,在一定大小过渡电阻影响下,灵敏度仍然较高;相比于上述其他两种保护,识别效果更优;动模试验验证了保护的实用性。

In order to detect turn-to-turn fault sensitively,a protection scheme for turn-to-turn fault based on the particle swarm optimization(PSO)fitness is proposed according to the influence of turn-to-turn fault on equivalent circuit of transformers.Firstly,the fitness function for resistance parameter identification is constructed on the basis of the active loss equation of a transformer.Then,the parameter identification is achieved by PSO,and the minimum fitness value of search space is obtained.Finally,based on the minimum fitness value,a criterion is constructed to identify turn-to-turn fault.Taking transition resistance and measurement noise into account,the effectiveness of this protection is verified in simulations.Moreover,the factors that possibly affect the sensitivity of this protection are analyzed.In addition,the sensitivity comparison of this proposed protection and the protection principle based on equivalent circuit equilibrium equation and excitation inductance is carried out.Some dynamic simulation experiments are accomplished at last.The conclusions can be drawn that this proposed protection scheme can achieve high sensitivity in turn-to-turn fault detection and avoid the impact of parameter calculation error;the identification effect is not affected by load condition,and the detection sensitivity is still high under the influence of a certain amount of transition resistance;the detection effect is better than the other two protections mentioned above.The dynamic simulation results verify the effectiveness of the proposed protection scheme.