基于粒子群-最小二乘混合算法的参数自适应故障测距方法

对于双端故障测距频域法，为了消除线路参数不确定性和双端数据不同步的影响，必须建立多维非线性故障测距观测方程进行求解，其求解方法的有效性将决定测距结果的成败，而目前采用的方法均存在着局限性。为此，利用粒子群优化算法的全局搜索能力与最小二乘迭代算法的快速精确收敛能力，提出一种基于粒子群—最小二乘混合算法的参数自适应故障测距方法。为了提高实用性，还针对前置低通滤波器和具有并联电抗器的输电线路等问题进行了研究。以1 000 kV特高压输电线路故障测距为例，进行全面仿真验证，证明了测距方案的正确性。

A parameter adaptive fault location scheme based on the combination of particle swarm optimization algorithm and least squares method

In order to eliminate the effects of transmission line parameter uncertainty and date unsynchronization for two terminals fault location schemes,a set of multidimensional nonlinear equations need to be set up,then solved by optimization algorithms. If the adopted optimal solving algorithm is unavailable,it could lead to fault location failure. For the limitations of conventional optimization algorithms,this paper proposes a novel fault location scheme which combines Least Squares Method(LSM) with Particle S...