Alarm information processing and faulty equipment location at the patrol and maintenance center based on big data

When a fault occurs in a power system, the master station at patrol and maintenance center can acquire a variety of alarm and status information concerning the fault from all the master stations at grid operation and control centers. This tends to bring huge stresses to the operators, and it´s also difficult to ensure the correctness of their judgment and treatment for the alarms. This paper introduces a patrol and maintenance center control cabin (operation and management system), which boasts alarm information processing and faulty equipment location functions. After the data of all the master stations is collected to the real-time database of integrated information platform at patrol and maintenance center, the fault features and its association with the equipment are extracted by using big data storage and data mining technology, and then in conjunction with the information of nearby substations, online real-time analysis and reasoning is made in respect of the operation status of the substation which initiates alarms. Finally, the specific equipment in fault or in danger and fault causes are identified by using decision tree to assist the operators to analyze and treat the incidents timely.