Electric power transmission companies depend heavily upon their operational processes for performance and survival. Finding the cause for an event in the network through diagnosing electrical substations is extremely challenging, since it involves the management of a large amount of data from multiple sources found in geographically distant places. Hence, it is very time-consuming for process specialists to identify the equipment failure, the status of the power system protections and the mandatory procedures to carry out. In addition, many companies have limited technological resources to extract and analyze data, and manage equipment from various manufacturers which operate with multiple communication protocols and a variety of software.
The time requirement for this scenario puts the stability of the whole system at risk. Likewise, it implies many FTEs dedicated to downloading files from computers, limiting professionals from dedicating themselves to analysis tasks of greater value to the business. Through work in a co-creation scenario, MVM, along with one of its clients and a research group from one of the most important universities in Colombia, participated in the design and implementation of a technological solution that detects events from fault recording equipment and protection relays, analyze the information, and generate a timely automatic diagnosis on the causes of its occurrence. This solution allows technological convergence towards an intelligent electrical substation of the future since technological concepts are incorporated in the domain of expert systems, intelligent process automation, data science and advanced software development.
This solution has been implemented in more than fifty electrical substations in Colombia and five in Chile. The main benefits of this solution for electric power transmission companies are:
• Risk mitigation in operational processes through automatic centralized reporting of the events in the national transmission system network, thus optimizing the process of downloading fault records and settings.
• Near real-time analysis of information from protection equipment.
• Decision management from an advanced intelligent system for automatic fault diagnosis.
• Finally, the integration to the different SCADA, asset, inventory, and operation systems, among others.