For ISA Intercolombia and its companies dedicated to the transmission of electric energy, reliability in monitoring power system signals is crucial to ensuring the safe and efficient operation of their assets.  Monitoring faces various challenges, such as measurement errors, communication latency, cybersecurity vulnerabilities, and hardware failures.  Addressing these issues with advanced technologies and good management practices is essential to maintain the stability and efficiency of the grid.

In line with the business strategy for 2030, the implementation of the PI System in ISA and its companies was initiated as an effective tool for data storage.  This platform meets operational requirements by providing real-time historical information, as well as offering add-ons that facilitate the creation of analytical models and graphical data presentation.  Through the capabilities of PI AF, a dynamic model was developed using attributes from each monitoring signal obtained from SCADA via an interface with PI.  These data are processed to establish the reliability indicator in monitoring.  The resulting signals are stored in the Data Archive and used for decision-making in operations and maintenance.  Additionally, the model allows for the configuration of alert events through triggers, which send email notifications to those responsible for monitoring management.  This provides early information that contributes to meeting regulatory indicators related to monitoring reliability.

• The implementation of the PI System in ISA and its companies not only improves reliability in electrical signal monitoring but also optimizes the management, operation, and maintenance of electrical assets, thus contributing to a more efficient and safe operation of the power system.
• The configuration of alert events through triggers in the PI System provides early notification of potential problems, allowing for a quick and effective response from the maintenance team, thereby minimizing operational impact.
• The PI System's ability to process and analyze large volumes of data in real-time enables the early detection and prevention of failures, reducing the risk of monitoring loss and non-compliance with regulatory aspects.