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Gerard Laguna [Challenges in energy efficiency]: "To get good data to model the buildings and the implementation of the model predictive control into existing facilities"

Published: 21/10/2020

Gerard Laguna

Gerard Laguna has joined recently to Building Energy and Environment research group of CIMNE as a Severo Ochoa PostDoc Trainee. We have interviewed him to know his point of view about energy efficiency as well as what implies for him its new position.

-What new challenges does this position imply for your research career?

This position is a big challenge because after my PhD in which a microelectronics cooling device was designed, modelled and experimentally tested now I am going into data analytic focused on energy efficiency in buildings. However, this position is an opportunity to do high-quality research meanwhile I am developing my data analytic knowledge.

-What do you think energy efficiency building can bring to society?

Energy efficiency buildings target is to reduce the energy consumption, or at least reduce the environmental footprint of buildings meanwhile they are maintaining or improving the comfort indoors. Therefore, energy efficiency in buildings contributes to society improving the standard of living by boosting the comfort in buildings and reducing its environmental impact. Moreover, by reducing the energy consumption in buildings, the living costs decrease so energy poverty also should decrease.

-What does it mean for a researcher to work in a Severo Ochoa Center of Excellence?

I appreciate being awarded with this position and I feel it is a great opportunity to grow as a researcher.

-What topics are you focusing your research on?

My research nowadays is focused on characterizing the energy behaviour of buildings by using statistical learning methods and applying model predictive control to improve energy efficiency and reduce operating costs.

-What are the challenges at energy efficiency building in the coming years?

The bigger challenges are to get good data to model the buildings and the implementation of the model predictive control into existing facilities.