基于仿电磁学算法的电压暂降状态估计

Voltage sag state estimation based on electromagnetism-like mechanism

提出基于仿电磁学(electromagnetism-like mechanism,ELM)算法的高容错性电压暂降状态估计方法。通过抗干扰种群移动模型、自适应变异和精英策略等改进措施提升了仿电磁学算法的整体寻优性能。引入解析法和故障点法确定线路故障区间,利用冗余配置法确保观测矩阵的非奇异性。采用故障估计值与历史统计值之差构建了电压暂降状态估计模型。通过在IEEE24节点标准测试系统上的仿真计算,并与遗传算法的仿真对比,ELM在寻优效率和准确性方面具有明显优势。该方法适用于任一电网在对称、不对称故障时的电压暂降状态估计。

Based on electromagnetism-like mechanism （ELM） algorithm, a high fault-tolerant method for voltage sag state estimation is proposed. In this paper, the global optimization performance of the electromagnetic simulation algorithm is improved by the improvement of the anti disturbance population movement model, the adaptive mutation and the elite strategy. The analytic method and fault point method are introduced to determine the interval of line fauIt, and the redundancy collocation method is used to ensure the non singularity of the observation matrix. A voltage sag state estimation model is constructed by using the difference between the short circuit fault estimation and the historical statistics. Through the IEEE24 node Standard Test System Simulation and comparison with the genetic algorithm simulation, ELM has obvious advantages in the search efficiency and accuracy. This method can be applied to the voltage sag state estimation of a power system with symmetrical and unsymmetrical fault.