In March, the Spanish magazine Revista Energética has published the article “IoT Technology to provide the intelligence to the prefabricated substation, improve its maintenance in real-time and guarantee the quality of the network” written by Lourdes Martínez, Communication and Marketing at amplía))). Click here to read the article in Spanish.
IoT Technology provides the intelligence to the prefabricated substation, improve its maintenance in real-time and guarantee the quality of the electrical network
The creation of a monitoring system for this network element together with intelligent vibration and frequency sensors has made it possible to have an accurate understanding of its operation to improve its maintenance and detect anomalies in real-time.
For these 17 years of working with electrical companies at amplía))), a technology company that has developed assets monitoring software, we have seen that electrical operators don’t have data in real-time to monitor the majority part of domestics equipment in the energy prefabricated substation. These elements are responsible for transforming the medium and low voltage energy to go to homes and the industries in an accurate and correct way.
The new European and National regulations that require a great use of renewable energies to replace coal and reduce gas emissions have carried out to start their first steps with the modernization of intelligent measurement equipment, such as smart meters, an adaptation of the old ones with the incorporation of new heat and temperature sensors, the sensorization of all the network elements and a balanced installation of systems that greatly overload the network. These overloads on electrical components or conductors cause network failures and installations age prematurely due to these anomalies.
In this electrical scenery, we start working with our partner Inael, a manufacturer of High and Low Voltage electrical equipment in Europe and LATAM, we saw the lack of awareness that existed in the general conditions of the performance of network elements. These have a direct relation with the risk of incidents and the lack of availability of electricity for the users.
In several studies and proof of concept with Inael, we have detected that exist certain critical points in a prefabricated substation. The overloads and the increases in temperature generate a deterioration in these parts and elements of the prefabricated substation. For example, the dielectric inside that is normally oil, when it is overstressed, is chemically altered. This affects performance capacity and is one of the main causes of failure in the prefabricated substation.
With the incorporation of vibration and frequency sensors to analyse the electromagnetic emissions and OpenGate monitoring system, it obtains historical data of the situation about when has happened and how it has affected this change even though the type of detected incident. All the data is collected, identified and categorized in this system. We can visualize the information according to user interest (technical operator or project manager) and create operations and generate alerts when for example, the vibration is higher between certain parameters.
When we carried out thousands of maneuvers on the cells of the prefabricated substation, we have detected a series of behaviors in the resonance of the structure that affects the life cycle of the equipment involved.
Therefore, it becomes vitally important to know that abnormal behavior in a component can generate resistance and cause an excess temperature in the line.
With all this, it is possible to improve energy efficiency by knowing the faults and anomalies that occur in the prefabricated substation elements, knowing how the variations of some elements affect others that made the network supply impossible and how often they occurred.
Now, it allows managing maintenance tasks, reducing gas emissions because many of these tasks are done remotely from the OpenGate IoT platform, or specialized staff does it in less time knowing where and why the failures occur. In addition, we can optimize the investments and operations of the network itself by having exact and precise knowledge of its behavior.
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