10 años Energylab



Digital Industry - Big Data and Artificial Intelligence

Development of advanced data analysis projects in the field of the implementation of energy efficiency measures for their use in the deployment of expert systems based on massive data processing techniques (using sensors at consumption points and significant variables), to improving energy efficiency in all industrial sectors.

Through the use of disruptive technologies such as Big Data, Machine Learning, Deep Learning, mechatronic sensors and actuators or the Virtual Twin, we develop predictive mathematical models, adapt energy-consuming systems to their optimal operating point, reduce the gap between forecasted and actual consumption based on the use of statistical models, searches for correlations between energy and production parameters, identifies inefficiencies, prescribes actions to correct them and improves the energy efficiency of industrial equipment and processes.

Advanced mathematical modeling and simulation applied to the environment

Development of projects focused on the mitigation of climate change through the application of Artificial Intelligence, Machine Learning and Deep Learning, for the extraction and use of useful information from DB (satellite, government, meteorological, etc…), for the generation of predictive models, development of specific software tools and process optimization in the following areas:

  • Agricultural and forestry management
  • Air and water qualitya
  • Sustainability
  • Renewable energy
  • Emergency management and safety of natural disasters (floods, forest fires, etc.)

Industrial thermal efficiency

Study, analysis and development of technical solutions for the recovery of medium and low temperature heat in new facilities and existing processes, either for direct thermal use (plate exchangers, heat pump) or for renewable energy generation (Rankine cycle Organic – ORC, Peltier, Stirling engine, …).

Characterization of the existing energy potential through field measurements and laboratory tests, energy parameterization and modeling, energy simulation of thermal processes, design of energy recovery systems and verification of energy savings.

Application to the optimization of heat recovery in specific systems such as industrial cogenerations (improvement of equivalent electrical performance), mechanical compression equipment (refrigeration systems and air compressors), heat recovery from evaporative condensers, industrial ovens and other intensive thermal processes.