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Technology Product and Service
Energy Data Space

Funded by

Anticipate risks in the electrical grid before they become incidents

DATASTRUC is a real-time analysis and monitoring platform for medium-voltage energy infrastructures. It combines data captured by IoT sensors with meteorological information to identify anomalies, anticipate potential failures, and provide a more accurate view of the state of the energy grid using artificial intelligence techniques. The service centralizes the visualization of data, events, and analytical results, facilitating asset operation and maintenance, as well as more efficient data-driven decision-making.

Vista del mapa de monitorizacin de centros de transformacin en Espaa

Caractersticas principales

Resilience to cyberattacks

Data encryption ensures the integrity of the data obtained by the sensors and its subsequent transmission.

Interoperability and collaboration

Encourages collaboration and data sharing among stakeholders within the Data Spaces.

Scalability and flexibility

An economic model that facilitates the implementation of the platform and interaction with other Data Spaces.

Funcionalidades

Predictive maintenance and real-time contextual analytics

DATASTRUC combines real-time data capture with artificial intelligence algorithms to identify behavioral patterns and anticipate failures before they occur. The platform not only analyzes sensor data but enriches it with contextual information from the environment, providing a more complete view of the assets' status. This facilitates data-driven decision-making, reduces downtime, and proactively optimizes maintenance plans.

Vista detallada de monitorizacin de un centro de transformacin

Features

Panel de administracin mostrando configuracin de sensores

Fire and overheating prevention

Flood detection in transformer substations

Early identification of electrical faults

Detection of intrusions or unauthorized access

Monitoring of sensor and connectivity failures

Sensors

Air quality

Continuous monitoring of air quality in transformer substations and technical rooms using sensors capable of measuring suspended particles, volatile compounds, CO2 concentration, and other environmental parameters. It helps detect conditions that could affect equipment operation, prevent risks to personnel, and optimize the ventilation and maintenance of the facilities.

Partial discharges

An early detection system for partial electrical discharges in medium and high-voltage equipment, such as transformers, switchgear, or wiring. These discharges are often indicative of deterioration in electrical insulation and can cause critical failures if not corrected in time. Continuous monitoring allows for predictive maintenance and a reduction in unplanned outages.

Gas

Sensors designed to detect the presence of harmful, flammable, or hazardous gases, such as methane, hydrogen, carbon monoxide, or SF6. Their function is to alert to potential leaks or accumulations that could compromise the safety of individuals, the state of the equipment, or the regulatory compliance of the facility.

Humidity

Monitoring of relative humidity levels in electrical and industrial environments to prevent problems caused by condensation, corrosion, or the degradation of electronic components. Humidity control helps maintain optimal operating conditions and extends the lifespan of the equipment.

Presence

Human presence detection systems using motion, radar, or artificial vision sensors to identify unauthorized access in transformer substations, technical rooms, or restricted areas. This contributes to strengthening the physical security of the facility and allows for real-time alerts to be generated in the event of an intrusion.

Temperature

Continuous temperature monitoring in electrical panels, transformers, batteries, and other critical assets. The early detection of abnormal temperature increases prevents overheating, minimizes the risk of breakdown or fire, and improves operational efficiency through preventive maintenance.

Thermal camera

Capture and analysis of thermal images to identify hot spots, thermal imbalances, or anomalies invisible to the human eye. This technology facilitates the remote and continuous inspection of electrical and industrial installations, allowing action to be taken before serious failures or performance losses occur.

Ultrasound

Anomaly detection via the analysis of ultrasounds generated by leaks, electrical discharges, friction, or mechanical defects. Ultrasonic sensors allow incidents to be identified early even in noisy environments, facilitating predictive maintenance tasks and increasing equipment reliability.

Water level

Monitoring of the water level in inspection chambers, underground rooms, transformer substations, or sensitive areas to detect flooding or leaks. The system allows automatic alerts to be generated and safety protocols to be activated before the water affects critical infrastructure or causes damage to the equipment.

Technologies

Data capture directly in critical infrastructures

DataStruc relies on IoT to capture data from transformer substations, capturing data on temperature, humidity, pressure, flow, etc.

Real-time data platform

Processing and management of large volumes of operational data. The solution uses a scalable data platform capable of handling continuous information flows, structuring data, and making it available for analysis and operational exploitation processes.

Advanced analytics and artificial intelligence

Early anomaly detection beyond simple thresholds. DataStruc incorporates advanced analytics and machine learning techniques to identify anomalous patterns, reducing false positives and enabling an early response to potential incidents.

Interoperability and Data Spaces

Data prepared for secure reuse and collaboration. The DataStruc architecture is designed following interoperability principles, preparing data and metadata for its integration into energy sector Data Spaces, fostering reuse, collaboration, and new data-driven services.

Participating entities

The DATASTRUC project is led by Technology 2 Client (T2C), which is supported by various specialized technological partners for the development of the different system components, combining capabilities in sensing, validation in real-world environments, and integration into Data Spaces.

The Universitat Politècnica de Catalunya (UPC) participates as an expert entity in advanced data analysis and artificial intelligence, collaborating in defining models for anomaly detection, signal interpretation, and analytical validation of results.

Masense, participating in the project as an entity subcontracted by T2C, provides specialized knowledge in the field of sensing and data capture, including IoT technologies, signal definition, and sensor deployment in industrial infrastructures. Its contribution focuses on the technical aspects associated with field data acquisition.

Specialist in laboratory testing of sensors, collaborating in defining models for anomaly detection, signal interpretation, and analytical validation of results.

This combination of technical capabilities allows the project to be approached from a multidisciplinary perspective, coherently covering the aspects of data capture, processing, analysis, and exploitation.

Documentation

Algorithms

Economic model