基于分布参数模型的风电系统长距离送出线时域距离保护

传统工频原理距离保护易受风电系统故障特征的影响,基于集中参数模型的时域距离保护原理较适应于风电系统送出线。但考虑到该原理忽略分布电容的影响,当故障发生在风电系统长距离送出线时,可能造成距离I段保护发生暂态超越现象。因此,提出一种基于分布参数模型的风电系统长距离送出线时域距离保护原理。基于分布参数模型,通过保护安装处的电压、电流时域信息求得距离I段整定处的电压、电流时域信息,代入时域故障测距方程中,求得整定点与故障发生处的故障距离。通过与距离I段整定距离求和获得故障测量距离,实现保护动作。仿真结果表明,该原理不受长距离送出线分布电容的影响,具有较强的抗过渡电阻性能,优越于基于集中参数模型时域距离保护。

Time domain distance protection for long distance outgoing line of wind power system based on distributed parameter model

The traditional distance protection principle based on power frequency is easy to be affected by fault characteristics of wind power system. The time domain distance protection principle based on lumped parameter model is more suitable for the outgoing line of wind power system. However, considering the principle influence of distributed capacitance is neglected, when the fault occurs in the long distance outgoing line of the wind power system, transient transcendence may occur on the distance protection instantaneous relay protection zone. Therefore, this paper presents a time domain distance protection principle for long distance outgoing line of wind power system based on distributed parameter model. Based on the distributed parameter model, it uses the voltage and current time domain information of protection installation to obtain the time domain information of voltage and current at the distance protection instantaneous relay protection zone setting which are brought into time domain fault location equation, thereby the fault distance between the whole set point and the fault point is obtained. By summing the distance of the distance protection instantaneous relay protection zone setting, fault measurement distance is obtained, achieving the protection action. Simulation results show that the principle is not affected by the distributed capacitance of long distance outgoing line, and the performance of anti-transition resistance is good. The protection performance is superior to the time domain distance protection based on the lumped parameter model. This work is supported by National Natural Science Foundation of China (No.51467019).