Key data
Commissioning: in 2023
Partners: Kearney
Location: Brazil
About the project
At EDP, we are committed to innovation and excellence in energy distribution. Our project, R&D TOTEX 4.0, is a groundbreaking initiative that leverages Artificial Intelligence and Data Hyperautomation to transform the management of medium and low-voltage (MV/LV) distribution networks.
TOTEX 4.0 is equipped with an intelligent embedded system that orchestrates predictive and prescriptive maintenance actions. This advanced technology optimises resource allocation, enhances operational efficiency, ensures a more reliable grid, and significantly improves customer satisfaction.
One of the standout features of this project is its ability to predict interruptions and impacts in real-time. It prescribes the optimal corrective and preventive actions, taking into account various factors such as financial, operational, and regulatory impacts. This ensures that our resources are used efficiently without compromising service quality and network performance.
By integrating data from multiple sources, including fault history, weather conditions, and asset characteristics, TOTEX 4.0 provides a comprehensive view of the grid. This facilitates more accurate and rapid decision-making, directly contributing to the resilience and continuity of the energy supply. As a result, unexpected failures are minimised, and response times are optimised.
Aligned with EDP sustainability goals, the project utilises resources more efficiently, supporting our commitment to a greener future. The system has already been successfully implemented in pilot projects across Brazil, delivering impressive results and setting new standards in the energy sector.
Looking ahead, we plan to expand the scope of TOTEX 4.0 to include high-voltage (HV) networks and tailor implementations to meet the specific needs of EDP’s other geographical markets. This expansion will further modernise the management and maintenance of distribution networks, ensuring that we continue to lead the way in the energy transition.
Share on social media:
