The journey of digitalization: how Smart Digital Substations can drive the Industrial Internet of Things revolution
AUTORI: Alessandro Pedretti, Siddhanta Suryabanshi, Julian Deprez, Rodrigo Mateini, Lucio Urzedo, Antonio Lugarà, Mikhail Barros
DOI: 10.63111/QES-2025.1.0025
DOI RIVISTA: 10.63111/QES
SCARICA L’ARTICOLO (link attivo dal 6 marzo 2025)
ABSTRACT: This technical paper has been presented in the last CIGRE (Conseil International des Grand Réseaux Électriques) session in Paris, which took place in 2024, August 25th to 30th. This work, examined and approved by the technical commission within the Study Committee D2 (Information Systems & Telecommunication) and the Preferential Subject PS1 (IT/OT solutions to improve the efficiency and resilience of electric power systems), represents the natural prosecution of the experience described into the publication “How the Industrial Internet of Things is driving the Asset Management Digitalization: the implementation of an interconnected Asset Performance Management system in the electrical power distribution sector” presented in the CIGRE 2022 session in Paris.
The case study analyses three Smart Digital Substations, connecting wind farms to the grid, where both primary and secondary assets and wind turbines data are made available to a SCADA system. An APM (Asset Performance Management) solution is designed to potentially analyse all of these data, considering the offline (historical data, operators’ inspections, off-line reports) and on-line (interconnected sensors, protection
& control IEDs and SCADA parameters) data are ingested into the platform breaking the information silos, contributing to assess the risk level for each asset, in a user-friendly and easily- accessible cloud SaaS (Software as a Service) environment. Beyond analytics dashboards and customer reports, the implemented APM software delivers prescriptive recommendations, generated on the base of the asset health status evolution
by an expert system. This tool relies on a knowledge base populated by a vendor, acting the double-role of software house and substation assets manufacturer, and suitable to be integrated with the specific customer’s experience, becoming a safe and structured repository for the company’s knowledge. In the 2022 paper it was proven how the outcomes and recommendations from APM could support the customer to prevent a potential malfunctioning on a new transformer, due to an outstanding humidity rate into
the dielectric oil. This event has been diagnosed even though assets were brand new and only offline data from oil samples were available. In the latest system configuration, new off-line and on-line data will be available, thanks to the commissioning of an advanced dissolved gas analysis connected system, which is pulling data into the APM platform. Beyond this, secondary equipment’s performance models will be implemented providing
a more accurate indication of the asset health status. The APM application will then be able to produce more insights, of higher quality and level of detail. The combination of predictive analytics, advanced condition monitoring and technical expertise is clearly a benefit for asset managers, enabling the best information to be used to decide asset management actions.
This approach clearly defines how the IIoT (Industrial Internet of Things) can increase the value and the performance of existing assets without any need to replace or revamp in full the whole asset fleet. This is possible by leveraging subject matter expertise and specialized services to dig into existing and newly generated asset data turning them into information and then into action items, to be evaluated by the asset owners.
As a further step, this approach can be extended also blending structured and non-structured data, such as pictures, which through AI algorithms become suitable to feed an APM system. Leveraging image-recognition technology, which is well recognized as reliable and mature in many sectors, can foster the progress exchange between the industrial world to other business sectors, enabling a faster and more robust digitalization process
of the power transmission and distribution networks. Computer vision-based technologies can be applied not just to add an extra level of knowledge to Predictive Analytics, but also to improve operational efficiency of complementary areas within a Substation such as Health, Safety and Environment (HSE) enforcement, facility management, perimetral security, and much more.
