How artificial intelligence encourage energy sufficiency

By ENGIE - 24 February 2023 - 14:37

In the context of everyday life, our business, local authority and private customers can find energy sufficiency to be a real headache, financially, organisationally and technically speaking. But our digital data analysis tools based on artificial intelligence are making better, lower and more timely energy consumption a reality. Jean-Pierre Pélicier, Chief Data Officer at ENGIE, analyses and explains the Group's digital solutions adopted by our customers.


Jean-Pierre Pélicier

How do data and artificial intelligence encourage sufficiency and help accelerate the energy transition? 

Jean-Pierre Pélicier: We collect masses of data from our facilities – solar and wind farms, etc. – located all over the world. With new infrastructure being developed to meet the needs of a world without carbon energy, there will be even more data available. By combining this data with meteorological, satellite and mapping data, we are taking direct action to help the energy transition. 
Firstly, because this data helps us determine how efficient facilities are by identifying which have the best exposure to sunlight, wind and other weather conditions. We are therefore better informed when it comes to building efficient renewable energy production plants. Secondly, because the data we collect from our facilities in real time helps us optimise our equipment by scheduling maintenance operations or repair of faulty parts as quickly as possible. This remote monitoring capability is even more useful when our facilities are hard to reach. 
Finally, the data is widely used to monitor ENGIE's decarbonization process. It measures the consistency of our operational actions in relation to our Group commitments to meet our target for Net Zero Emissions by 2045.


In concrete terms, how do we manage an energy facility using data?

J.-P. P.: Take the example of a solar panel in one of ENGIE's more isolated photovoltaic plants. Using data, we can monitor its electricity production by the hour. Data is also widely used to anticipate renewable, and by definition alternative, energy production. Using AI models applied to weather forecasting data, we can predict the amount of energy that will be produced and reduce the use of other energy production sources accordingly.
We can also predict the quantity of electricity that a panel can produce in normal conditions, by analysing satellite and meteorological data in real time. If there is a drop in performance, our teams are informed immediately and can take action quickly. Without artificial intelligence, we would be less efficient and less agile. Maintenance teams would be obliged to check all the panels in the solar farm on a regular basis and would run the risk of missing maintenance requirements between checks. Artificial intelligence makes us extremely responsive and saves us valuable human resources. 


In concrete terms, how does data enable companies and individuals to use energy in a more responsible way ?

J.-P. P.: Our digital solutions enable our industry customers to monitor energy consumption at their production plants. We install Energy Management Systems – software based on data collection – to analyse machine consumption profiles and suggest improvements. If they produce electricity, for example by installing solar panels on their buildings, our solutions enable them to monitor their production in detail and manage it better on a day-to-day basis.
For private customers, our solution measures the consumption of a household's principal electrical appliances (boilers, radiators, ovens, etc.) in real time, again with the aim of optimising energy use (for example, by using a dishwasher's "eco" mode). It's simple but highly effective. The eCare solution, for example, enables users to control their household appliances remotely using machine learning algorithms. Today eCare is connected to over 145,000 objects in four European countries. We also help our private customers determine their homes' potential for solar production, either on an individual basis or for a set of homes (like our Harmon’Yeu project).


Three key digital solutions by ENGIE

Darwin to manage large-scale production plants

  • A solution to collect data in real time from wind, solar, hydroelectric and biogas plants. 
  • The goal is to help operational teams improve their revenues and control their costs, in order to accelerate the transition to a low-carbon energy mix.

Nemo for heating and cooling networks 

  • A solution to optimise district heating and cooling network management to improve environmental performance.
  • The goal is to heat and cool a city while minimising its environmental impact, and to help local authorities meet their commitments regarding renewable energy use. 
  • This has resulted in: - a 3 to 5% reduction in heating and cooling networks' primary energy consumption in France and abroad. Find out more.

eCare for private customers