MADRID, 19 May. (EUROPA PRESS) –
Enagás is applying digitization to convert the gas supply chain into an integrated, transparent and flexible ecosystem, as reported by the company, which uses ‘machine learning’ technologies to manage its infrastructures and uses the internet of things (IoT) and advanced analytics to optimize gas measurement.
Digitization allows Enagás to achieve greater efficiency throughout the value chain in an increasingly changing context, in which long-term energy demand forecasts no longer respond to the usual patterns.
The company maintains that, thanks to artificial intelligence and the IoT, advanced analytical models of demand, which can be in real time or close to it, “generate efficiency, agility and flexibility” and allow responding to customer demand in real time contributing to security of supply.
The Director of Digitization at Enagás, Olga Núñez, told Europa Press that these new technologies add value in operational terms, because with them you can “access information in real time and search for correlations, which facilitates the analysis of incidents and promotes predictive maintenance”.
But, in addition, they make it possible to improve efficiency in tactical terms, by helping to “optimize infrastructure maintenance work”, and offer an advantage in strategic terms thanks to “the creation of dashboards with information in real time”, which which helps in decision-making, “promoting a ‘data driven’ culture within the company”, he added.
The data that Enagás generates as an industrial company, by operating 11,000 kilometers of gas pipelines, six regasification plants and three underground storage facilities in Spain, are one of its key assets, as they allow it to improve the management and maintenance of the infrastructure network.
Based on a data governance program, data can be analyzed to facilitate decision-making or to increase efficiency. With the new platforms based on ‘machine learning’ and advanced analytics techniques, the systems that monitor the operation of infrastructures learn and are thus able to predict their behaviour.
The objective, according to the Director of Asset Management at Enagás, Rosa Nieto, is to achieve “more predictive and even proactive” maintenance. “We seek to be able, in the future, to optimize the maintenance that we carry out on our assets, adjusting them to their condition and reducing their corrective action. In this way, we will be able to guarantee maximum availability and security in our infrastructures, as we have done up to now,” she commented.
One of the new platforms used by Enagás to manage infrastructure data is Platiom, aimed at knowing the health of the main equipment at regasification plants and detecting possible incidents in advance through machine learning.
Enagás uses virtual reality techniques to train professionals in tasks required by liquefied natural gas plants, with a view to commissioning new installations or rotating professionals through different types of installation.
In the company’s transportation network, made up of more than 11,000 kilometers of gas pipelines, 19 compression stations and 416 regulation and/or metering stations, they also have digitization projects for their management and maintenance.
For example, the Neptuno platform is being developed which, through a data acquisition system and an advanced analytics program, helps to optimize the process of measuring the gas delivered from the Enagás transmission network.
In addition, Enagás applies analytical capabilities to calculate strategic indicators such as the carbon footprint, since it is committed to becoming a carbon neutral company by 2040.
In this case, digitization helps by automating and applying government in capturing the data that calculates this index, and Enagás hopes that in the future mathematical models can even be applied to help minimize it.
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