Group Energy Conservation

Dr Constantinos Balaras was recognized by ASHRAE and awarded the Louise and Bill Holladay Distinguished Fellow Award that honors Fellows of the Society for continuing preeminence in research work and engineering. The award was presented by ASHRAE President Bill McQuade during the 2026 Annual Conference in Austin, Texas on July 27, 2026.

REMED Interreg Euro-MED Final Conference it is time to pull it all together and present an overview of the accomplishments and deliverables of the ReMED project: TOWARDS CLIMATE RESILIENT URBAN CITIES. We have a couple of more months to put the final touches. Come September, all deliverables will be accessible and open for municipalities and interested professionals to get and use. Let's improve resillience of our built environment to climate change impacts, assess where we are currently, what are the priorities and how we can improve resillience for the benefit of people as building occupants and residents.
More information - Towards Climate Resilient Mediterranean Cities https://remed.interreg-euro-med.eu a collaborative effort of 9 partners from 5 EU countries.

REMED Interreg Euro-MED is getting ready for the FINAL JOINT WORKSHOP on June 23rd, from 15:45 to 17:00 CET.
Join us online - Free registration @ https://form.jotform.com/82961805184362
Get the latest insights on an innovative digital tool implementing the ReMED climate risk assessment system and decision-making model to support the analysis, selection and implementation of adaptation measures at neighbourhood and building scale.

A validated model for short-term prediction of cooling energy consumption in buildings - first step to forecast control of cooling, published in Journal of Building Engineering, 127: 116361. https://doi.org/10.1016/j.jobe.2026.116361
Smart control of energy supply for cooling in buildings can significantly improve energy efficiency. However, existing modelling methods are often complex and rely mainly on artificial neural networks (ANN) and other machine learning techniques, posing various difficulties for integrating them in forecast control of cooling. Moreover, accurate cooling energy models are generally more demanding to develop than heating models. To address this research gap, this study proposes a novel, simple and physically based method for creating building cooling energy models that also take into account the characteristics of the existing cooling system. The approach uses measured cooling energy consumption and meteorological data-outdoor air temperature, wind speed and solar irradiance - to derive an equivalent outdoor temperature that represents the real thermal behaviour of the building during cooling operation. Proper selection of operating and weather data is essential to minimise the influence of unrelated factors. The method is demonstrated on an office building in Poland and a university building in Cyprus. For both case studies, the developed cooling energy models were validated, achieving for outdoor temperatures above 26 °C mean absolute percentage error (MAPE) values of 13.15% for the office building and 17.87% for the university building. To further assess robustness, Multilayer Perceptron (MLP) ANN models were trained using the same hourly inputs-outdoor temperature, wind speed and solar radiation. The ANN models did not significantly improve prediction accuracy, yielding higher MAPE values of 19.6–24.7% for the office building and 29.4–34.9% for the university building. The results highlight that buildings must be considered individually and show that the proposed method can provide a practical, transparent and accurate tool for estimating cooling energy performance. Future work will address occupant influence and integration into predictive control of air-conditioning systems.