Abstract
In order to complete the function of power grid fault diagnosis accurately, rapidly and comprehensively, the power grid fault diagnosis system based on multi-data sources is proposed. The integrated system uses accident-level information, warning-level information and fault recording documents and outputs a complete diagnosis and tracking report. According to the timeliness of three types of information transmission, the system is divided into three subsystems: real-time processing system, quasi-real-time processing system and batch processing system. The complete work is realized through the cooperation between them. While a real-time processing system completes fault diagnosis of elements, it also screens out incorrectly operating protections and circuit breakers and judges the loss of accident-level information. Quasi-real-time system outputs reasons for incorrect actions of protections and circuit breakers under the premise of considering partial warning-level information missing. The batch processing system corrects diagnosis results of the real-time processing system and outputs fault details, including fault phases, types, times and locations of faulty elements. The simulation results and test show that the system can meet actual engineering requirements in terms of execution efficiency and fault diagnosis and tracking effect. It can be used as a reference for self-healing and maintenance of power grids and has a preferable application value.
Highlights
The transmission network is the main component of the power system and is responsible for large-capacity power transmission tasks
Reference [5] proposed an improved probabilistic load and distributed energy resources (DERs) modeling as pseudo-measurements, which has the ability to estimate the states of the power grid with high accuracy and short computational time
Considering the shortcomings of existing fault diagnosis and tracking methods and applications, this paper proposes a fault diagnosis system based on multi-data sources in order to achieve rapid, accurate and comprehensive effects of fault diagnosis and tracking
Summary
The transmission network is the main component of the power system and is responsible for large-capacity power transmission tasks. Reference [5] proposed an improved probabilistic load and distributed energy resources (DERs) modeling as pseudo-measurements, which has the ability to estimate the states of the power grid with high accuracy and short computational time These improved new technologies (especially the method proposed in reference [5]) enable the dispatching center to monitor and estimate the operating status of the entire power grid more accurately and quickly, providing feasibility for fault diagnosis. Traditional power grid fault diagnosis methods, including expert system [6], Petri net [7] and other diagnostic algorithms, are based on protection operation information and circuit breaker tripping information These methods could accurately diagnose faulty elements under the premise of complete information. Reference [12] used the inference chain and Bayesian network to track the faults of relay protection devices and achieved favorable results It did not fully consider the problem of partial alarm data information loss. A transverse comparison between this system and related technologies is made to prove the advantages of this system in terms of computational efficiency, reliability, and processing the problem of partial information loss
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