How artificial intelligence can help the energy sector

14 January, 2022

One third of companies have already incorporated technological solutions of this type that favour business efficiency.

Technological development has revolutionised industries and businesses. Progress is unstoppable and the new solutions that are developed have a direct positive impact on business activity. In particular, the energy sector is one in which artificial intelligence (AI) will bring about the most changes in the way it relates to customers.

The range of possibilities offered by AI has grown exponentially thus far in the 21st century. More and more powerful technologies are becoming available to manage large volumes of data and algorithms that help humans automate processes and improve decision making.

Increasingly widespread

The use of this type of technology in the energy sector is growing. This is revealed in a report by Infosys, which quantifies the number of companies in the sector that use these solutions at 30%. In addition, there is a further 20% that admit they intend to resort to it and are planning to do so.

Cost savings is one of the reasons why many businesses are turning to AI. But its real contribution goes far beyond that. And it has a very positive impact on the efficiency of any activity.

And what do these specific benefits translate into? These are some of the “triumphant” applications in the energy sector:

– Anticipate demand: it is possible to adjust to needs knowing that they will vary significantly at any given time. Having real-time information and historical data, combined with other variables, becomes a powerful tool for predicting behaviour. In Spain, thanks to a database that goes back three decades and the analysis of up to 14 variables, it has been possible to forecast consumption one year in advance.

– Improve the customer experience: it allows the strategy of all customer relationship channels to be improved, not only digital. AI acts as yet one more agent that helps resolve customer incidents, offer services or products more appropriate for each type of customer, thanks to the volumes of data that we have about them, and all this in a 24/7 service that learns from each interaction.

– Predictive maintenance: another great advantage provided by AI, which, in this case, makes it possible to stay one step ahead of possible network incidents. Having a monitored system and receiving alerts in advance allows you to intervene before a fault occurs. It increases safety and sometimes avoids stopping the activity with the ensuing cost.

– Energy efficiency: better management of supply and consumption, both domestic and industrial, is now possible with smart systems. This promotes energy efficiency and, as a result, we are making progress in reducing emissions and becoming more environmentally friendly, one of the major challenges worldwide.

– Renewable energies: together with the foregoing, renewable energies play a decisive role in the climate emergency. Although they have the major advantage of being infinite, they are conditioned by the weather (sun, wind, etc.). Production depends on this and, to avoid uncertainty, AI is an ally in prediction and enables us to have an estimate of the amount of energy that can be generated.

Enagás’ experience      

Enagás, as an energy infrastructure operator, is applying technological solutions in this area based on machine learning and advanced analytics techniques. “This digitalisation process, framed within the company’s culture of innovation, is a necessary impulse to complete the energy transition”, the company points out.

“The adaptation of systems and infrastructures make better management and maintenance possible thanks to monitoring and the ability to obtain real-time data. We are optimising the operation of our network, which in Spain comprises some 11,000 kilometres of gas pipelines, six regasification plants and three underground storage facilities”, they say.

One practical example can be seen in its LNG tanks. Enagás uses AI, combined with real-time drone imagery and cloud computing, to track maintenance more effectively. Or, to mention another specific innovation, it has introduced a platform that optimises maintenance of critical plant equipment and detects faults in advance using machine learning.

This is a small sample of the utility of AI in the energy sector. Its present value is undeniable and the evolution in this field promises much room for improvement in the future. So much so that the consulting firm Gartner concludes in one of its latest reports that this area will spearhead the technological investment of companies in 2025.