Development and integration of intelligent auxiliary emergency disposal software for power grid faults

Under the current social background of high industrialization and informationization, the challenges faced by power grid as a key infrastructure and the countermeasures. Aiming at the problems of frequent power grid faults, expanding influence scope and low efficiency of traditional disposal methods, this study introduces in detail the overall architecture of intelligent auxiliary emergency disposal software for power grid faults, including the design of front-end, back-end and database. The front end pays attention to user experience and ease of use, the back end is responsible for data processing and algorithm operation, and the database provides data storage and management functions. The software includes real-time monitoring module, fault diagnosis module, emergency treatment module and historical data analysis module, which together constitute a complete software system, aiming at realizing intelligent auxiliary emergency treatment of power grid faults. Python is chosen as the main development language, and PyCharm is used as the development tool to support the efficient development and optimization of software. In the process of software development, Hadoop HDFS and Spark, a distributed storage system, are used to process and analyze massive power grid data to ensure the real-time and accuracy of the data. At the same time, machine learning algorithm is used for fault diagnosis and prediction. Through the integration with SCADA and GIS system, the real-time monitoring, rapid positioning and effective emergency treatment of power grid faults are realized, and the practicability and intelligence level of the software are improved. The performance of the software is tested in detail, and the problems found in the test are optimized to improve the stability of the system and the ability to handle high concurrent requests.