The goal of this project is to develop a platform (C3) for advanced knowledge in REE to make construction works safer, more efficient and sustainable. C3 will process and exploit the data to improve efficiency and create automation and controls for decision-making. This digital transformation initiative offers a decisive advantage in making energy transition and the smart network of the future a reality.

The roots of this project lie in predictive maintenance. It goals to improve the estimates required to improve the quality of condition-based maintenance, which consists of anticipating faults in assets to avoid them becoming unavailable and the high costs of repairing them. In this context, the “partial discharges” are small currents that appear in insulated facilities (cables, insulated GIS sub-station compartments, power transformers, etc.) prior to the failure of the element in question. The goal of the project is to create a platform that does not currently exist in the market that can detect and diagnose “partial discharges” automatically, based on artificial intelligence, to classify them by seriousness and provide information that enables the right decision and maintenance action to be taken.

Red Eléctrica is deploying a new model for managing the vegetation growing near its power lines. Until now, the plant species were identified manually using photograph interpretation techniques.

This project created a series of algorithms to automate the interpretation of photos of tree species and scrubland using satellite images and those of the National Plan for Aerial Orthophotography (PNOA).

The goal of this project is to switch from a reactive/preventive model to a predictive model in the area of occupational health and safety. We make use of the traceability and digital footprint of the data and information provided by the management tools and applications of the Red Eléctrica Group to make analyses with descriptive (what happened), predictive (what could happen) and prescriptive models (what can we do to stop it happening) The first goal of the project is to use Artificial Intelligence methods to create a probability indicator of the risk of accidents and issues associated with any maintenance and construction work.

We want to show the feasibility of making an inventory of photovoltaic panels by using very high resolution satellite images and artificial intelligence. To do this we will be running tests in various parts of Spain with different features and variables to extract the guidelines for implementing a precise and operative global service in the future. The goal of the project is essentially to be able to precisely detect the panels automatically and locate them on the ground, distinguishing, where possible, the different types of panels so that we can make a reasonable estimate of their installed capacity.

We developed this project to strengthen and to create efficiencies in the maintenance of overhead power lines by making our knowledge systematic and standardising our remote detection and classification of possible visual anomalies. The project covers the redefinition of current technical practices, information flow and the procedures for handling work in the field.

The project aims to develop a transmission grid based on local and remote monitoring and sensors, operating with transmission categories calculated in real time. These capacities are calculated using a thermal model of the line and data obtained from the monitoring of immediate atmospheric conditions and/or the physical parameters of the installation along its full length. This will enable us to access the capacity that has so far been blocked by the circuits, giving us better knowledge of their real conditions. The result is more flexible and safer operations.

Newton is Red Eléctrica’s calculation programme. It is easy to extend, integrate and maintain. It is state-of-the-art in power flow, linear calculations and other essential functions. Newton’s architecture is designed for the desktop as much as the cloud, capable of massive calculations and integration with AI for the planning and operation of electricity systems.

Together with Orange, Huawei and the Red Eléctrica Group, we have developed a pilot project for the remote inspection of facilities using artificial vision in different spectrums and the detection of SO2/SF6 gas (indicator of faults in the sub-station and greenhouse gas leakages) both in electricity sub-stations and the channels within them.

To do this, we deploy a network of specific cameras and sensors, both in fixed and mobile points, with a system for monitoring different wavelengths that makes the detection of faults more efficient, increasing the safety of field operators and enabling us to develop more powerful tools for predictive maintenance.

This solution will enable us to recover the SF6 leaked from our GIS installations using absorbent materials (modified or synthesized commercial compounds).

The system developed will make an effective contribution to reducing greenhouse gas emissions into the atmosphere caused by equipment leakages in the transmission grid that use SF₆.

In this project, low-cost IoT devices that are minimally invasive are developed, in order to monitor the dynamic response of safety elements and detect unsafe behaviours when carrying out work on transmission grid elements.

In the present, sub-station automation systems are distributed systems where specific software is executed in specific hardware. The application of new algorithms is then conditioned by software-hardware equipment of each supplier.

With this project, a software platform executed on diverse hardware, based on concepts of micro-services, will be designed to implement the functions of the sub-station automation system.

Its goal is to see the real level of small-scale self-supply (P <1MW) because there is no plan for real-time measurements or metering for the amount generated. The information, however, is available in the IoT and the cloud. The platform makes monitoring possible in real time, enabling us to estimate production in the system and to make forecasts.

This project is intended to ensure the safety of people and facilities in discharge operations, removing situations of risk for operators associated with their work in protected zones and accompanying tasks, as part of the Red Eléctrica Group’s strategic goal of “zero accidents”.

The objective of the SLISE project is to mitigate the vulnerabilities that the new virtualization technologies adopted massively at the core of the 5G architecture (and which are already part of the technical drafts of the sixth generation) have dragged into the new paradigm of communications as a service. Specifically, research into new algorithms is proposed: incident analysis, encryption, radio attack detection identification and automated response; in a more flexible context to face the risks inherent to virtualization technologies: Network Function Virtualization (NFV), Software Defined Networks (SDN) and Network Slicing (NS). All this will be studied, defining demanding indicators that broadly cover these objectives, in a set of use scenarios that present different protection priorities and that include the use of communications in the context of critical infrastructure management, as well as the use of communications in the manufacturing industry.

Together with Orange, Huawei and the Red Eléctrica Group, we are working to develop a pilot that can analyse the potential of 5G technology for protection, control and automation systems. The pilot will show the potential of 5G for these systems: they will become independent from the means of access to the communications network (fibre optics or 5G), which makes it possible to make new designs and optimise the infrastructure required, making it suitable to the needs, criteria and philosophy of the different agents. There are 3 different scenarios proposed to replace usual communications via fibre optics with 5G radio solutions:

• 5G for WAMPAC
• 5G for line protections
• 5G to deploy the process bus outside the sub-station
• Replace the line protection by its digital twin

Together with Orange, Huawei, Arbórea Intellbird and Hispasat we are implementing 5G technology to make real time analyses of accident scenarios in critical infrastructures, enabling us to carry out inspections of critical aspects of our infrastructures using remotely controlled and robotic systems.

This will improve our response time by incorporating inspection processes and the analysis of critical infrastructures, increasing their safety. It is also proposed to include communication satellites as backup for the terrestrial 5G network via Network Slicing in different situations.

The goal of this project is to validate the electricity infrastructures of Red Eléctrica as vehicles for 5G systems. This will enable the creation of a roadmap with the preparation of various minimum viable products (MVP) to acquire experience in the installation of 5G systems in networks (requirements, special needs, etc.) and to test the possible impact on the environment of the infrastructures.