【Technical Introduction】
     To meet the demands of advanced distributed green energy distribution and the transformation of the power system, the structure of power transmission and distribution lines is transitioning from uni-directional to bi-directional. The connectivity is shifting from static to dynamic structures, necessitating the enhancement of real-time monitoring and control of power line conditions to strengthen the resilience of the grid.
     Nowadays, the IEDs (Intelligent Electronic Devices) used in Taiwan power system belongs to multiple brands. As for acquiring data about faults, it is necessary to manually assess and locate the associated IEDs, and the exhausting data download and waveform graph productions are also manually executed. Accordingly, power system experts could make decisions, and respectively on-site personnel carry out relevant operations.
     The "Real-time Automatic Notification System for IED Event Waveforms (eWavePush)" developed by NARI is compatible with numerous brands of IEDs utilized in Taiwan power system. Its functionalities include data collection of IEDs events, signal conversions, waveform graph generation, and automatic push to the social media platform. Moreover, all aforementioned tasks could be done together within one second. An overview of this system is depicted in Figure 1.

【Project Planning/Technical Applications】
     In accordance with the national energy transition policy, the requirements for the coordination and stability of the power system are becoming increasingly challenging. Particularly, there is an urgent need for integration technology of information and communication systems for power transmission and distribution lines. NARI has developed a system capable of instantly collecting raw measurement data of IEDs events and integrating the return signals into a common data format, allowing waveform graphs to be automatically generated within one second and published to social media communication software.
     The generated event waveform graphs have been compared with the results of inspection using original manufacturer software, confirming their accuracy. Additionally, they have been verified in the working system to meet the requirements of the Taiwan power system. This enables maintenance personnel to promptly obtain information of the occurrence time, event waveform, and location of faults, facilitating swift response measures without the need for connecting to IEDs and downloading accident data. This significantly improves the efficiency of accident handling, accelerating the repair process, further enhancing the efficiency of scheduling and maintenance personnel in handling accidents, and strengthening the resilience and reliability of the power grid.
 
【Future Development】
     Future work includes the research and development of the "Intelligent Event Waveform Classification AI System," which utilizes advanced artificial intelligence algorithms to automatically analyze and identify fault types corresponding to electric post event waveforms. Additionally, NARI will develop the "Electric Post Basic Data Platform," which will provide users with the functionality to label event waveform graphs with corresponding event types and systematically organize historical event data of IEDs to form a training dataset for the intelligent event waveform classification AI program to train models. This will help establish a convergence and analysis system for IEDs status information and waveform data, allowing users to easily access historical information on the status of various IEDs and event waveform graph files on the platform. These systems will be integrated with the eWavePush to form a "Cloud-based Intelligent Decision Support System" with the function of converging and analyzing IEDs status information and waveform data continuously through automatic analysis of data returned by IEDs.
 
 
【Contact Information】
Name：Yen-Bor Lin
Tel：03-4711400  ext. 6229
E-mail：swallow915@nari.org.tw