The building sector in Europe accounts for 40% of the final energy demand of which more than half is used for space and water heating. This sector has tremendous untapped potential to accelerate decarbonisation by improving energy efficiency.
When it comes to energy efficiency, the state-of-the-art in existing building heating systems (especially in the residential sector) involves manual readings and observations while investigating faults. By doing so, only the grossest faults are typically uncovered, while significant performance shortcomings (although of lower magnitude) remain undiscovered unless an expert actually checks the installation (usually for other unrelated reasons). Here, making use of data with sufficient granularity (hourly or higher) over a longer horizon (days to months) unlocks considerable possibilities for identification of inefficiencies that would otherwise go unnoticed.
Another efficiency-related aspect is controller tuning. Legacy installations have controllers that are tuned only during the commissioning of the installation and rarely afterwards. Typically, they operate within an unnecessarily high margin. When using data-driven solutions, this margin can often be reduced by means of adaptive tuning. This results in energy savings without loss of comfort at user level. Based on my experience, energy savings potential is in the range of 10% and comes at a considerably lower cost than changes to the physical system (e.g. extra insulation on the building) and appliances, therefore providing an attractive return on investment.
Challenges in implementing data-driven solutions
The practical challenges are found in 3 levels: data collection, benefit quantification and market barriers.
Getting access to measured data can sometimes be difficult. In situations where building management systems (BMS) that gather data are already present, the complexity is mostly on the administrative end. On the other hand, where such systems are yet to be installed, cost is a major deterrent, especially when the end-user is yet to be convinced of their value.
A major pain point in the provision of energy efficiency services is the difficulty to build a representative and accurate baseline model. Data prior to the deployment of the solution is typically of low quality and resolution – often manual readings at irregular dates with monthly resolution or worse, if available at all. As building energy demand depends on variables (such as weather, number of occupants, et al), the baseline data needs to cover a long period resembling the test conditions and have a resolution that allows development of a reasonably precise baseline model. This is particularly difficult as such uncertainty is in a similar range of the savings that one tries to quantify, and tests must run on long periods (at least half a year) before being able to conclude on the gains.
There are several market barriers for data-driven solutions, such as those created by split incentives and the multitude of stakeholders involved in energy efficiency projects. An example of this in the residential building sector is found where a service needs to be contracted with the rental association (which results in higher operating costs, thereby increasing the rent) while the benefits of the lower energy demand is found at the end-user level who receives the energy bill. Here, business model development with network operators is difficult, and hurdles often boil down to the conservativeness of the industry meeting the relative novelty of data-driven solutions on the demand side (where benefits are not always quantified precisely enough to support a roll-out).
Future of energy systems
We can hope that the coming years will see accelerated transition to renewable sources, which requires a strong political commitment and societal backing. While this may seem hard to attain, citizens are calling for stronger climate action in many places around Europe and the world. Simultaneously, the industry is moving forward in cutting the costs and developing supportive technology.
As part of the energy transition, I hope that we will also put a strong emphasis in energy and resource efficiency, as well as flexibility, which are essential leverages on the demand side. These are often not given enough space in discussions that tend to focus more on the energy generation/production side.
And last but not least, I hope that future energy systems will be more user-centric, where people will be actively engaged in meeting their energy needs in a sustainable manner as it is their needs that are the reason why we have energy systems in the first place.
About the author
Dr. Pierre Vogler-Finck has a background in energy engineering, with a M.Sc. in Engineering from Supélec (now Centrale Supélec) in France, M.Sc. in Renewable Energy Engineering from Heriot-Watt University in Scotland and a Ph.D. in heating control in buildings from Aalborg University in Denmark. He has over 6 years of work experience in research and development within the energy sector in France and Denmark. His work in Denmark over the last 5 years has focused on making the demand side more energy-flexible and energy-efficient. He has primarily worked on heating of space and water as well as ventilation in buildings on the demand side, where the aim has been to unlock value from measurement data to support a greener operation of those systems.
The views expressed in this blog belong to the author.