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AleaSoft, December 4, 2020. The environmental objectives of the European Union for 2030 and 2050 will require technological improvements both in the electricity generation and in its management in the interconnected electricity systems of all countries, especially in terms of the demand and its flexibility. The smartgrids and the smartmeters are examples of this deep digitalisation that is taking place in the energy sector in Europe.

One wonders how such a complex system as the electricity system of a country could be managed efficiently before the massive digitalisation of data and communications. Those were the times when the demand forecasts were made with templates, pencil and paper, and to transmit information it was necessary to pick up the phone and dial several numbers. And yet the electricity systems worked and the blackouts were very rare events.

But it is clear that those were other times. With the continued increase in energy demand, at least until the 2008 crisis, and the irruption of the renewable energies in the generation mix, it is clear that, without the technological improvements of the last decades, the manageability of the electricity system would not be possible. The inherent variability of the renewable energy generation technologies, such as the wind energy and the photovoltaic energy, makes the acquisition, processing and transmission of information necessary in large volumes and at high speeds.

The energy sector in the era of the Big Data and the Artificial Intelligence

The energy sector generates an immense amount of data every day. It is just necessary to think about each generation plant, each offer for each hour in each market, each meter in each home, each node of the electricity system. A quantity of information of this magnitude can only be managed and analysed with Big Data tools. Because the first step is to have and be able to collect and save all that information, but the next, and more important, is to know how to transform that information into useful and valuable knowledge to make responsible decisions.

This transformation of the information into intelligence and opportunities is one of the AleaSoft‘s missions for the energy sector. The use of the Artificial Intelligence requires a large amount of data so that the models can “learn” from it, draw conclusions, make forecasts and detect opportunities. That is why the energy sector is an unbeatable field for the Intelligence models and the Machine Learning algorithms to develop their full potential, and that is what the more than 400 AleaSoft models in operation have been doing during the last 21 years.

AleaSoft - AleaModel Machine Learning Artificial IntelligenceSource: AleaSoft.

It is important to see how the vision provided by the Artificial Intelligence models offers opportunities both in the short and in the mid and long term, and they are useful and necessary for any actor in the energy system, producers, retailers, traders, investors or large consumers.

The digitalisation and the energy transition

The environmental targets of reduction of greenhouse gas emissions that the European Union set for 2030 and 2050 pose a real technological challenge. In the first place, due to the increase in renewable capacity proposed by the Energy and Climate Plans. The integration of all this new renewable energy production in the generation mix, while maintaining the security of supply of the entire system, will require improvements in the electricity transmission grids and in the management systems to be able to monitor and respond adequately to an increasingly decentralised production. This is where the smartgrids will play an important role, and in them the use of Artificial Intelligence will be key.

But, on the other hand, it is clear that increasing the renewable energy production will not be enough to achieve the European objectives. On the demand side, it is necessary to increase the energy efficiency and make it possible for the demand to become more flexible and to respond to signals of price or variability of the renewable energy production. For this, information systems are required that can offer the customers simple and transparent information on their consumption, to improve their efficiency and also allow their active role in making the demand more flexible, essential for the integration of the renewable energies.

A clear example of the digitalisation on the part of the demand is the smartmeters. Making each supply point have a smart meter is a challenge in itself. But the most important thing is that it is necessary to be able to collect and analyse all that information so that it offers the intelligence and opportunities that were mentioned before.

The Artificial Intelligence in AleaSoft

As mentioned above, one of the AleaSoft‘s fundamental functions is to transform all this information from the energy markets in Europe into knowledge, intelligence, vision and opportunities. These analyses are available in a set of reports for the energy sector. These reports provide market intelligence resulting from processing the company’s historical databases of real data and forecasting.

In addition to its reports, AleaSoft also organises webinar series with the aim of providing useful information and knowledge to the professionals in the sector. These webinars have the participation of speakers from the most important companies in the energy sector in Europe and worldwide. The next webinar is scheduled for January 14 and will feature the participation of speakers from the consulting firm PwC Spain, to analyse the vision of the PPA contracts market for large consumers, its impacts and requirements, and of the need for future electricity market prices estimates.

Source: AleaSoft Energy Forecasting.