In recent years, electricity grids have undergone profound disruption transformation: from simple energy carriers they have become intelligent infrastructures thanks to the integration of digital systems, advanced sensors and data analysis tools. This progress allows not only react to failuresbut also of prevent themguaranteeing greater continuity of the service.
Predictive maintenance: how it was done before
Historically, energy management took one approach correctivewhich provided for the intervention only a failure occurred. In the past, failure prevention was still implemented and was mainly based on interventions scheduled maintenanceorganizing regular inspection campaigns carried out by specialized personnel. These activities made it possible to detect signs of wear, anomalies or possible critical issues on the systems before they turned into real failures. However, the effectiveness of these controls was conditioned by the observation skills of the operators, the frequency of the inspections themselves and above all by the fact that some portions of the network were still unreachable. Many sections of the network, being underground, can only be reached through excavations, an operation that is often impracticable unless the fault has occurred.
Today, however, the approach is radically different, and thanks to the implementation of automated solutions, intelligent sensors and advanced platforms for data analysis it guarantees continuous and highly accurate surveillance, even in sections of the network that are traditionally difficult to monitor. The benefits of these technologies compared to conventional methods are evident, in particular in relation to the reduction of operating costs.
From reaction to prevention: the paradigm shift in energy management
Key technologies supporting this evolution include IoT (Internet of Things) systems and intelligent sensors which collect strategic information on the state of the network. At the base of the system there are platforms for collecting and analyzing data provided by the numerous sensors distributed across the territory. These platforms, through advanced predictive analysis algorithms, make it possible to identify any changes in the functioning of the cables or devices that make up the network infrastructure, reporting possible anomalies and thus allowing maintenance to be planned before actual failures occur. THE remote control systems they also ensure continuous monitoring and make automated interventions possible which in some cases do not even require human intervention.
Turin and the model developed by IRETI
A concrete case of this evolution is found in Turin, considered a true “laboratory city” for innovation in the management of electricity networks. IRETI (the manager of the city’s electricity network) has introduced a advanced remote control and monitoring system coordinated by the Operational Center, which offers continuous supervision and a unified view of the network in real time throughout the year. Furthermore, IRETI has developed a specific software platform for predictive maintenance: this solution analyzes both the data collected in the field and historical data, allowing you to precisely identify the parts of the network at greatest risk of failure. Every strategic component of the network is scrupulously monitored.
To each switch is assigned a “health index“i.e. a score that reflects health status and reliability based on objective data and recorded events. Maneuvering operations are carefully monitored to ensure full efficiency. In the presence of anomalies or a high number of trips relating to a specific switch, the system automatically sends a signal for inspection and maintenance. Conversely, the system signals the need for intervention if a switch is not moved for a prolonged period (for example, more than 12 months), thus safeguarding its mechanical functionality. Finally, the operations carried out following a fault are also monitored, such as those due to a short circuit; if the pre-established threshold of trips under fault is exceeded, a preventive maintenance warning is generated.
THE transformersOn the other hand, key elements of the electricity system are equipped with a specific health index. This index is automatically updated over time based on the main operating parameters of the machine, such as temperature, electrical load, environmental installation conditions and the number of maintenance interventions carried out.
Even at medium voltage power lines (MT) a score is given. This index takes into account factors such as the age of the line, its length, the number of joints and recorded faults. This assessment helps to identify the most vulnerable network sections, facilitating the planning of targeted interventions.
Secondary and primary cabins also receive an overall rating from one perspective structuraltaking into consideration both the age of the building and that of the components installed, as well as the maintenance interventions carried out. This process helps plan structural renovation work before any problems arise.
Sensors and Data Acquisition
The advanced monitoring implemented by IRETI currently focuses on the Medium Voltage (MV) network. Data and alarm management occurs through the use of the communication protocol IEC 61850an international standard for communication in electrical networks. IRETI already plans to start the procedures necessary to extend these functions to the low voltage network in the near future, in order to guarantee coverage up to the last section that directly serves domestic users.
Data acquisition makes use of strategically installed sensors:
- In the secondary cabin: Specific terminals are used, installed at the ends of the medium voltage cables with integrated sensors that measure the electrical parameters (voltage and current) and are located inside the medium voltage switchboards. Additional sensors detect, for example, the opening of the cabin hatch door, the presence of smoke in the cabin or in the individual compartment, the temperature and the possible presence of water in the cabin (indicating potential flooding in progress).
- In the primary cabin: The monitoring focuses both on the constant sampling of the main physical and electrical quantities as in the case of secondary substations, more on specific monitoring such as the chemical composition of the insulating oils present in large-power transformers, rather than the presence of ozone, a gas with a typical pungent odor, a symptom of partial discharges or electric arcs in progress detectable with photosensitive sensors installed inside the switchboards.
Data acquisition occurs through a sophisticated acquisition and transport networkcomparable to a (closed) internet network, built to guarantee the secure and continuous transmission of strategic information relating to the functioning of the electricity grid. However, these networks are not limited to just data collection: they are structurally active and bidirectional. In fact, through the same infrastructure, commands are sent to field devices and automatisms are implemented that allow switches to be activated, power flows modulated and network structures modified in real time, significantly improving reaction times to faults and the prompt reduction of the users involved.
Managing this massive amount of data and commands requires collection, archiving, analysis and control systems extremely robust and reactive, capable of promptly filtering alarm signals and supporting immediate operational decisions. Precisely due to the critical nature of the information processed and the fundamental role that these data and commands play in the continuity and safety of the electricity service, the transport network is protected by advanced cyber security systems. These include encryption protocols, access authentication and continuous monitoring of any intrusion attempts, thus ensuring that sensitive data is not compromised and that the network remains resilient even in the face of increasingly sophisticated cyber threats.
It is clear that the technical figures involved in these processes, nowadays, must have skills not only in the field ofelectrical engineeringbut also in electronics, informaticsmanagement of data networks, communication protocols And big data. Precisely to respond to these needs, some Italian universities have begun to provide specific specialization or master’s courses on smart grid.
