Design And Implementation Of Regional Power Failure Discrimination System

With the rapid development of economy and the continuous improvement of people's living standard,people's normal production and life are more and more inseparable from the stable supply of electricity.However,power failure events occur from time to time,which seriously affects people's life and,more seriously,endangers people's life safety.Effective identification grid power is an important part of smart grid self-healing functions,when there was a power grid,monitoring system will be collected massive blackout information sending to collect the data center,power outage criterion system is able to quickly screen out from sending huge amounts of information blackout related data,timely discriminant power,auxiliary staff and maintenance personnel for the accident analysis and real-time processing,quickly restore power,to ensure safe and reliable operation of power grid.On the basis of massive data resources,this paper applies intelligent means such as big data analysis and mining to regional power failure discrimination,uses relevant algorithms to establish an accurate regional power failure discrimination model,and takes this as the support to establish a regional power failure discrimination system.Key information can be mined from massive data to accurately identify regional power outages,ensure the stability of the power system,improve the quality of users'electricity service,and ensure the safety,stability and economic operation of the power grid.In the current studies on regional power failure discrimination,experts and scholars mainly focus on large-scale power failure,and make advance prediction through line fault,power grid equipment performance and other aspects.But with the development of smart grid and the user demand for electricity service quality improving,power outage should not only focus on a wide range of power cuts and blackouts in advance warning of events,also should pay attention to the local small scale power cuts and blackouts timely detection and treatment after the incident,because of small scale power cut will also affect the life of people,and timely detection and treatment of the event reflects the power grid company's service quality and user experience,and relationship with social stability and orderly.It is the primary task and basis of regional power failure discrimination to establish a power failure discrimination model based on the massive data of power system.This system first carried on the detailed demand analysis,has carried on the outline design and the detailed design to the system,has carried on the modeling analysis to the system using the unified modeling language(UML).This paper analyzes and understands the business logic of regional power failure discrimination,deeply studies the main factors affecting regional power failure,collects the information of power consumption information collection system and marketing system,combines the weather information,and divides regional power failure into two types according to the business background analysis:power failure of key users and power failure of Taiwan region.For power failure discrimination of key users,the power failure discrimination rule base is established through big data statistical analysis and combining with the high reliability characteristics of key users.For area power outages,considering the business end rotation policy caused by power failure rules change,area power outages can be divided into two categories:1)to rotate after blackout area of data,using the difference autoregressive integrated moving average algorithm(ARIMA)algorithm,the generalized autoregressive conditional heteroscedasticity algorithm-difference autoregressive integrated moving average algorithm(GARCH-ARIMA)and the recursive neural network(RNN)algorithm to establish regional power outages discriminant model,generate electricity discriminant rules,and constantly updated over time;2)for the station area without power failure data after rotation,grey correlation analysis algorithm and the cosine similarity algorithm are selected to establish the regional power failure discrimination model.According to the established regional power failure discrimination model,the judgment accuracy of the system can be effectively improved,the time of judgment can be effectively reduced,the processing time of power failure can be accelerated,and the economic loss can be reduced.Based on the regional power outages discriminant model,based on the idea of software engineering,using the MVC architecture pattern,using the J2EE technology platform,using the Java language to write,and use B/S architecture design system,establish regional power failure criterion system,the system front-end part mainly intuitive display area power outage situation and all the details of the acquisition data.The back-end part is mainly based on the data collected for discrimination and timely detection of regional power failure,and the region may occur power failure warning,multi-angle multi-dimensional analysis of power failure or failure reasons,timely maintenance,improve the reliability of power supply.