A Rapid Location Method for Relay Protection Faults in Main Network Substation Based on Time Series Q-learning Algorithm
The relay protection faults of the main network substation are usually sudden and does not last for a period of time.The transient property is not obvious,and the rapid location effect is limited.Based on these factors,a rapid fault location method based on the time series Q-learning algorithm is proposed.In time series Q-learning,different polynomial function pa-rameters are used to represent the relay protection actions of different main network substations.Greedy strategy is used to se-lect the relay protection actions of main network substations.The weights are updated according to the relay protection status feedback results,and time series Q-learning algorithm is used to train parameters.The node admittance matrix of fault transi-ent network is constructed,the branch voltage and current are calculated,and the fault correlation domain is determined.Ac-cording to the graph theory the rapid location topology structure is built according to the time series Q-learning algorithm.By analyzing the distance between the branch current and the fault current,the fault correlation is calculated to complete the rapid location of the fault.From the experimental results,it can be seen that the fault phase sequence of this method is consistent with the actual situation,which can analyze the transient characteristics of relay protection in the main network substation,and is suitable for complex and changeable relay protection devices.
time series Q-learning algorithmrelay protectionrapid fault locationfault correlation domain
万方数据
维普
