输电线路加权数据融合故障测距算法研究

高压输电线路故障测距具有多种不同的方法，如基于稳态量的单、双端测距和基于行波信号的单、双端测距等。由于电力系统存在许多不确定性因素及干扰，单一测距方法都有其固有的局限性。将多传感器数据融合技术引入电力系统故障测距，充分利用多测距源提供的冗余信息，提出自适应加权数据融合测距算法。该算法利用先验知识或仿真数据获取各单一测距算法在不同工况下的加权系数，然后对单一算法的测距结果进行加权融合，最终获得可靠精确的测距结果。应用PSCAD/EMTDC建立500 kV输电系统模型，通过模拟不同故障情况对算法进行了仿真验证。仿真结果表明，融合测距算法基本不受过渡电阻、故障位置、故障类型、分布电容等因素的影响，具有良好的可靠性、精确性和鲁棒性。

Transmission line fault location algorithm based on weighted data fusion

There are several algorithms for high-voltage transmission line fault location, such as steady state signal based one/two terminal algorithm, travelling wave based one/two-terminal algorithm. Due to many uncertainties and interference in transmission system, any single fault location method has its inherent limitations. By introducing multi-sensor data fusion technique, a self-adaptive weighted data fusion fault location algorithm is proposed, whose feature is fully using all the location information from multi-source. This new algorithm uses a priori knowledge or simulation data to obtain the weight coefficients of each single location algorithm corresponding to different fault conditions. The weight coefficients are then used to do calculation of weighted data fusion for all single location result. And finally the reliable and accurate location result will be obtained. This algorithm is tested under various fault conditions on a 500 kV transmission system model by using PSCAD/EMTDC. Simulation results show that the proposed algorithm is less influenced by fault resistance, fault position, fault type, system operation mode and distributed capacitance, and naturally possesses higher reliability, accuracy and robustness.