LAURE ITARD

Laure Itard is Professor of Building Energy Epidemiology at Delft University of Technology. From 2010 to 2017 she was Professor of Applied Sciences at The Hague University of Applied Sciences, research group Energy in the Built Environment. Previously, she was a researcher at DUT and a consulting engineer at Deerns in the field of energy and buildings. Her field of expertise spans energy modelling in buildings, data-driven energy policies, (big & smart) data analysis, statistics, building stock energy models, Energy performance of buildings Directive (EPBD), fault diagnosis models, heating, ventilation & air conditioning systems (HVAC), thermal comfort and post-occupancy evaluation.

About renovation

Energy use in buildings is a main contributor to the depletion of natural resources and responsible for numerous emissions affecting the quality of global, regional, local and indoor environments. As new-build rates are very low (and with regard to circularity should be kept as low as possible), the vast majority of future building stock has already been built and the main challenge is to increase its energy efficiency, both by decreasing its energy demand and by deploying renewable energy conversion systems.

Two main developments are rapidly changing today’s (research) landscape.First, the complexity of buildings’ energy systems has increased a lot and is still increasing. On the one hand, this is a consequence of the on-going transition from either autonomous local systems (e.g. a home boiler) or strongly centralised systems (e.g. a power plant or district heating) to distributed systems in which nodes (e.g. buildings) act as both supplier and consumer, leading to the socalled smart electrical and thermal grids. On the other hand, this increase in complexity relates strongly to the needs for multiple integrated conversion, distribution and buffering systems inherent to the use of renewable energy

'Energy management systems (BEMS) are becoming a necessary part of buildings' energy systems'

Second, the fast growing availability of cheaper sensors, smart meters, building management systems, cloud and internet of things frees up huge potential for feedback on actual operational performance, useful for theoptimisation and design of systems, as well as for the monitoring of energy policies. While a couple of years ago direct energy monitoring was still considered too costly, it is now starting to be recognised as a main component of energy efficiency. However, the more data we have, the more the lack of suitable analysis methods becomes burdensome. Unlike industrial systems, buildings’ energy systems work in strong interaction with the building and its occupants, are essentially variable partial load systems and are also responsible for the quality of the indoor climate, making multiobjective performance analysis a must. However, the use of data analytics for system optimisation is still in its infancy.

'Quickly growing availability of smart meters frees a huge potential for feedback on actual operational performances of buildings and the monitoring of energy policies'

The recent development of new methods for the assessment of the effectiveness of energy policies at building stock level, using actual energy data, has led to the discovery of huge discrepancies between modelled and actual values of energy consumption and energy-saving potentials in the Dutch residential sector, findings that were later reported in other countries, leading recently to the foundation by the International Energy Agency of IEA-EBC-Annex 70, 'Building energy epidemiology'.

However, while these data-mining activities based on statistical approaches led to numerous new insights, they do not allow for a better understanding of the causes of the discrepancies between models and reality, nor for the understanding of the complex relationships between energy system, building system and occupant behaviour. This understanding, however, is a necessity when it comes to the realisation of energy-saving measures, the transition to sustainable systems and demand/ supply matching in smart grids. To study these complex relationships and causalities, much more detailed and specific monitoring is needed. In the past, monitoring activities were always carried out at the level of labs, climate chambers or at single project level, making the extrapolation of the results to building stock impossible and leading to a bias in behavioural aspects as people being observed under lab circumstances are likely to behave in a completely different way than in a familiar home or office environment. That is why large monitoring campaigns in dwellings in use, using a sensor-rich measurement environment, are necessary. This fits very well with the trend of home automation and internet of things, and would allow for the study of the huge possibilities of data-driven modelling and machine learning for automated inspection of buildings and automated energy-saving recommendations per household.

There are more developments in energy management and building automation systems in non-residential buildings because there are more incentives for maintaining a continuous high level of indoor comfort as it relates to productivity. The heating, ventilation and air conditioning (HVAC) systems in this sector have therefore become very complex, also due to developments in the field of commissioning and energy-performance contracting and to the increased use of renewables like geothermal energy. Consequently, building and energy management systems (BEMS) are becoming a necessary part of buildings’ energy systems. Where buildings have been equipped with multiple sensors, these BEMS deliver an enormous amount of data, the potential of which is currently largely unexploited. Here, too, there is a need to develop analysis methods, entailing combinations of statistics with thermodynamic models, control models, systems dynamics’ theory and expert systems and to develop diagnosis and optimisation methods. Diverse studies have shown that by applying continuous energy diagnoses methods, 10-30 % energy savings could be achieved. That’s well worth doing.