AI in the energy sector: main use cases

Jose Luis Escobar

Director of Strategy and Business Development, GAMCO

There is a consensus among executives of the world's leading companies about the crucial impact that Artificial Intelligence (AI) in the energy sector will have on all the sectors. There are multiple studies available that reflect this. 

main cases ia energy sector

These are not changes that will come in the distant future, but factors that are already changing the competitive landscape of more and more industries and companies.  

The ways in which AI is going to help businesses are manifold and not all of them yet fully explored. However, we can look at industry sectors and review what major developments are occurring with AI.

In the case of the energy sector, there are already very clear trends in the use of Artificial Intelligence, which we will summarize below. 

Given that this is a traditional and mature sector, where infrastructures in the energy business - whether in production, transportation or distribution - have a high level of criticality due to their enormous impact on society and the economy, much is expected from AI as a business transforming factor. In fact, Gamco has already had successful experiences in this sector.

Examples of AI in the energy sector

Intelligent Networks

In recent years, a new concept has emerged: the concept of the smart gridsThe company's products and services are mainly driven by artificial intelligence capabilities.

These automated networks are capable of real-time intelligent analysis, balancing energy supply and demand, or detecting potential errors or fraud along the entire supply chain.

Also, thanks to the AI technology incorporated in smart grids, energy suppliers can manage service outages more efficiently, optimize voltage or detect demand peaks, as well as parameterize the specific behavior of certain customers or cities.

In addition, it is important to note that these smart grids will also enable progress to be made in production and distribution to bring it closer to the end consumer. By considering different production alternatives, consumers will be able to benefit from the use of the most efficient models in each case.

Anticipating demand

The incorporation of artificial intelligence into the energy environment also allows suppliers to anticipate electricity demand in urban or industrial environments, so that production can be adjusted to each particular need. 

Predictive maintenance

Another of the great revolutions that AI promises in this area involves the predictive maintenance of electrical distribution networks.

Every point in the entire supply network is monitored in real time and can alert when components are about to fail. In this way, the potential incident can be resolved before a serious failure occurs.

Every point in the entire supply network is monitored in real time and can alert when components are about to fail. In this way, the potential incident can be resolved before a serious failure occurs.

Energy efficiency

If it is possible to anticipate demand, monitor infrastructures and balance the energy load, it is also possible to reduce electricity consumption through the application of artificial intelligence. 

For example, Google uses machine learning algorithms to reduce electricity consumption in its data centers by 15% to 40%. These predictions make it possible to anticipate the load on data center cooling systems and control equipment more efficiently.

artificial intelligence ia in the energy sector

AI and renewable energies

Renewable energies are the big bet The main concern of governments around the world today is both the scarcity of resources and the possible climate impacts of other, more environmentally harsh energies.

But even though they are infinite resources (wind, sun), they are, above all, intermittent. It is difficult to forecast demand because certain climatic conditions must be assumed.

AI is therefore essential to help predict weather conditions, so that it can anticipate how much energy will be available at any given time.

Given the undeniable importance of the use cases mentioned above, as well as the results that are being obtained, and given the particularities of the electricity sector within the energy sector, it seems clear that the contributions of AI in terms of knowledge and forecasting will set the pace for the future of the sector.

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