Whether at home, in a study center, or in an office, we’re usually aware of how we feel temperature-wise. If the room temperature feels uncomfortable, we try to adjust it by changing the climate control settings. We probably don’t stop to think about whether we’re using renewable energy or what impact our demand for thermal comfort has on the grid. What’s interesting is that a building that’s part of a smart grid can handle this management automatically, anticipating the availability of resources and deciding how to respond to our comfort needs to provide us with a pleasant environment in which to go about our daily activities.
More than just a connected building
The transition of buildings toward digital monitoring through the installation of devices capable of recording various variables is becoming increasingly evident. This equipment provides data that helps interpret the status of different areas and forms the basis for high-level decision-making mechanisms. Sensors thus represent the first layer upon which a building’s intelligence is built, although they alone are not sufficient for the building to actively interact with the network.
To do this, we need to take it one step further: measure, anticipate, decide, and act. The building can monitor what is happening through its sensors, anticipate demand, weather conditions, or the availability of renewable energy, use that information to decide how to manage its energy resources, and, finally, take action on flexible assets such as storage, specific loads, or HVAC systems.
Decisions made at this supervisory level are typically linked to the concepts of efficiency and flexibility: making better use of available resources and deciding when, how much, and how to consume energy. But this ability to adapt truly comes into its own when it also takes into account the needs of those who use the buildings. That is where HVAC becomes one of the main points of intersection between energy management and the user.
In the context of technology development and transfer for the use of energy resources, thermal comfort offers precisely that opportunity: to explore optimization techniques while keeping the needs of the people who occupy the buildings as a guiding principle.
ADCONTROL: Prediction and Supervisory Control for Smart Energy Management
The ADCONTROL project has allowed us to apply this approach to energy management in a real-world setting. In collaboration with GEnergy, CARTIF has worked on developing a solution designed to manage a building’s thermal comfort and energy resources by combining prediction, optimization, and control.
In this context, forecasting involves estimating how energy demand and photovoltaic production will evolve, for which machine learning techniques, among other approaches, have been used. These predictions, along with variables such as environmental conditions and building temperatures, feed into an optimization-based supervisory controller. The challenge lies not only in identifying the most energy-efficient operation but also in balancing various potentially conflicting objectives, such as making better use of available resources and maintaining adequate comfort conditions for occupants. Based on this information, the system determines how to operate the energy resources and translates the result into temperature setpoints that can be implemented by the HVAC systems.
Coming up with a feasible solution is only part of the challenge. For these decisions to actually be implemented in the building, prediction and control services must be integrated with the monitoring and actuation infrastructure. The solution developed is based on a distributed architecture in which local devices collect information and execute commands, while prediction and optimization services run in the cloud.
Implementing a solution like this in a real-world setting also demonstrates that no two buildings are exactly alike and that adaptability is just as important as the algorithms themselves.
From Algorithm to Actual Building: Data, Adaptation, and Learning
ADCONTROL also allowed us to study what it takes to transition a solution from a demonstration environment to a real building. The system, initially designed for deployment in CARTIF’s Energy Living Lab, later had to be adapted for an office building. This change not only required a review of the monitoring and control infrastructure but also meant dealing with new operating conditions, data availability, and energy performance.
During the adaptation process, it was necessary to review the instrumentation requirements and make adjustments to the prediction models and the control algorithm. Among the challenges encountered were, for example, initial difficulties in accessing photovoltaic production data and obtaining disaggregated information on energy consumption.
It might seem that an energy management and thermal comfort service like the one developed at ADCONTROL could be directly applied to other spaces with similar characteristics. However, the transfer of this technology depends on the actual condition of the buildings and the extent of intervention permitted. As service developers, at CARTIF we continue to gain insights that enable us to address environments as diverse as offices, homes, daycare centers, and even historic buildings, where energy and comfort challenges are compounded by the need to preserve the heritage that adds value to our cities.
An opportunity for users, operators, and the energy system
Smarter energy management can add value at various levels. For users, it means maintaining optimal comfort levels without having to deal with the complexity behind the scenes. For managers, communities, and property owners, it means having new tools to make better use of energy resources, integrate renewable energy generation, and automate part of the decision-making process. And, on a larger scale, adaptable buildings can contribute to a more flexible relationship with the grid and a more efficient use of available resources.
For service developers, the opportunity lies in ensuring that these technologies are seamlessly integrated into spaces—in some cases, almost imperceptibly to users—while decisions consistent with their needs and available energy resources are made in the background.
At CARTIF, we continue to explore precisely this path: how to apply these solutions to real buildings, learn from each context, and adapt the technology to the needs of those who use them.
Two years ago, I wrote on this very blog about phase-change materials (PCM) and heat pumps: how to efficiently generate heat, store it, and use it later. In the THUMBS UP project, we’ve continued to build on that idea. Once thermal storage is already integrated into the building, the next question is how to use it and how to verify that the control system is delivering the results we’re looking for.
From Thermal Storage to Building Energy Management
One of the cases we have studied is the HSB Living Lab in Gothenburg, a multifamily building connected to a district heating network. The system combines heat pumps, water tanks, and FractLES thermal storage based on PCM. The pilot design provides a total of 101 kWh of nominal storage capacity, with one portion dedicated to domestic hot water and the other to heating.
Before implementing a strategy in an actual building, we can test it in a dynamic model. At CARTIF, we use TRNSYS to simulate the building’s behavior and study what happens when the way the storage is charged and discharged changes. The BEMS (Building Energy Management System) is then responsible for coordinating those decisions within the facility, using the available signals and adhering to its operating limits.
Thermal Storage System Monitoring Interface
In the study, we compared a baseline system without PCM and two different strategies for controlling the same system. In both cases, the storage system is used for both domestic hot water and heating. The results show, however, a different response during operation, especially when the PCM is charged for the domestic hot water (DHW) system. We wanted to know whether a similar improvement in the power indicator of the rate actually meant that the two strategies were performing equally well.
Power Peaks: When the Daily Average Doesn’t Tell the Whole Story
To evaluate storage, we used, among other indicators, one related to the District Heating rate in Gothenburg. It is calculated based on the average power output on days of peak demand. Using this criterion, the two strategies appeared to be virtually equivalent: both reduced the indicator by about 4% compared to the scenario without storage.
But that 4% refers to a daily average. The maximum power the building draws over a short interval is a different metric. One tells us how the day plays out as a whole; the other lets us see what’s happening within that day. That’s why we review the same simulations using data collected every 15 minutes.
The difference was clear. In the simulation without storage, the maximum power observed in the 15-minute interval was about 22 kW. With the first strategy, during some PCM charging periods, demand came close to 79 kW. With the second strategy, the maximum power remained around 22 kW, practically at the same level as the building without PCM.
The explanation lies in the time scale. A short-term increase in power barely affects the 24-hour average, even though it is very noticeable when we look at the data every 15 minutes. Furthermore, both strategies completed an equivalent number of DHW storage charges. The second strategy achieved those charges with a much more moderate power response.
Energy Consumption and Costs: What Happens When You Analyze a Full Year
When the analysis was expanded to cover the entire year, the two strategies once again diverged. The first strategy reduced the average daily power indicator but increased the energy imported from the heating network by 2.6%. The second strategy maintained virtually the same improvement in that indicator and reduced the annual energy imported by about 4%.
The effect was also reflected in the cost. In the scenario used in the study—based on the rate published by Göteborg Energi—the estimated savings were about 0.5% with the first strategy and close to 3% with the second. This comparison is based on a common rate benchmark, not the building’s actual bill.
The daily indicator was fulfilling its function, but it could not, on its own, describe how the facility was performing. When looking at the same system at different time scales, the assessment of control changes substantially.
What Can We Take Away from This Analysis?
This case helps explain why the BEMS is a key component when integrating energy storage into a building. A load decision can change the demand at that moment, affect subsequent consumption, or result in more or less energy being available a few hours later. The control system must coordinate these interactions within the limits of temperature, charge status, and equipment operation.
That is why, at THUMBS UP, we evaluate the control system using more than one time scale. The indicators associated with the tariff are compared with short-term behavior and with the energy balance for the entire period. We also maintain traceability of the operation: which signals were used, which version of the control was active, and which setpoints were applied. Without that information, it is difficult to explain later why the system responded in a certain way.
This concept is useful beyond thermal storage. Something similar can happen with heat pumps, batteries, photovoltaic self-consumption, or flexible industrial processes: improving the metric we’re tracking doesn’t guarantee that the entire system is behaving as we expect.
At CARTIF, we work precisely on this process. We use models to test strategies before implementing them at the facility, develop the necessary controls to apply them, and analyze operational data to verify the results. The goal is to ensure that the flexibility provided by storage can be measured, explained, and improved using traceable information.
Thermal storage makes it possible to shift energy over time. The control system determines how to do this. The case of Gothenburg offers a very practical lesson: to determine whether a strategy works, you have to measure the results at the appropriate scale.
Energy retrofitting of buildings faces a twofold challenge: improving the efficiency and sustainability of the building stock and accelerating the digital transformation of a sector that remains highly fragmented. Technologies such as BIM, openBIM, and digital twins are opening up new possibilities for connecting data, materials, energy consumption, and decision-making throughout the entire life cycle of buildings.
From Brick to Data: How Digitalization and the Use of BIM Models Are Changing the Energy-Efficient and Circular Renovation of Buildings
The way we design, build, renovate, and manage buildings in Europe is changing… but not fast enough. The building sector remains responsible for nearly half of energy consumption and a large share of the materials and waste generated. Added to this is a less visible but equally important problem: low productivity, fragmentation within the sector, and difficulty in adopting new technologies—especially among small and medium-sized enterprises (SMEs) in the sector.
It is against this backdrop thatDTERBIM(Driving the Transformation toward Energy-efficient and Circular Renovation through BIM) was launched—a European project coordinated by CARTIF that began in October 2025 with a clear objective: to accelerate the transition toward energy-efficient and circular building renovation by leveraging open, interoperable, and user-friendly digital tools.
Fragmentation and Low Digitalization in the Construction Industry
The building sector is a cornerstone of the European Green Deal and initiatives such as the Renovation Wave and the Energy Performance of Buildings Directive (EPBD). However, the AEC/FM (Architecture, Engineering, Construction, and Facility Management) sector faces very clear structural challenges.
An initiative by the European Commission to at least double the rate of building renovation in the European Union by 2030, with the goal of reducing greenhouse gas emissions through measures such as the decarbonization of heating and cooling systems, energy retrofits of public buildings such as hospitals and schools, and efforts to combat energy poverty in less-efficient buildings.
On the one hand, fragmentation: 99% of companies in the sector are SMEs, which use different tools, have poorly coordinated processes, and rely on disconnected information flows. This leads to errors, rework, cost overruns, and data loss throughout the building’s life cycle.
On the other hand, there is a lack of digital interoperability. Although the use of BIM (Building Information Modeling) is growing, many tools do not “communicate” with one another. Data is duplicated, lost, or arrives late, making it difficult to make informed decisions. International studies estimate that this lack of interoperability costs billions of euros each year.
Added to all this is the challenge of integrating sustainability and circularity into current digital processes. Most tools focus on the design phase and energy efficiency, but they overlook key aspects such as the reuse of materials, deconstruction planning, and tracking environmental impacts throughout the entire life cycle.
From “linear” buildings to circular and digital buildings
DTERBIM is based on a simple yet powerful idea: it’s not enough to simply digitize what we already do; we must change the way we work. The project proposes moving from a linear model (design–build–use–demolish) to a circular, digital, and collaborative model, where the principles of Reduce, Reuse, and Recycle guide the building from its conception through its potential dismantling and reuse.
The circular economy and sustainability are, therefore, central pillars of DTERBIM. From this perspective, circularity is present in all stages of a building’s life cycle (design, construction, operation, and deconstruction) through the development of tools to:
Design buildings intended to be adaptable, dismantled, and reused.
Create Material Passports, which provide information on what materials are in a building, their condition, and how they can be reused.
Standardize the handover and documentation process through the Digital Building Logbook, eliminating mountains of paper and facilitating future building management..
Thanks to these solutions, circularity is no longer just a theoretical concept but has become an integral part of day-to-day project work.
To this end, DTERBIM combines three main pillars:
1. An open and interoperable BIM process based on openBIM standards.
2. A suite of 12 digital tools and smart services that are easy to use and designed for large, medium, and small businesses.
3. Two digital twins that link digital models to real building data.
All of this is integrated into a shared ecosystem, without forcing companies to abandon the tools they already use.
openBIM: Interoperability to Improve Building Renovation
One of the major challenges addressed by DTERBIM is the rigidity of traditional BIM approaches, which are based on a single, centralized “source of truth.” This approach tends to work well in large organizations, but it excludes many small and medium-sized enterprises due to its cost and complexity.
DTERBIM is committed to an open, flexible, and federated model, where each stakeholder can continue to use their usual tools, provided they comply with open standards such as IFC, BCF, IDS, or bSDD. In this way, architects, engineering firms, construction companies, building managers, and government agencies can share information without technical barriers or vendor lock-in.
This openBIM approach not only improves collaboration, but also reduces errors, saves time, and improves data quality—all of which are essential for making sustainable decisions from the earliest stages of the project.
Digital Twins to Improve Energy Efficiency in Buildings
Another major advancement in DTERBIM is the integration of Digital Twins. While BIM represents the building in a static manner, Digital Twins incorporate real-time data from sensors, management systems, and digital platforms.
DTERBIM develops two types of digital twins:
Digital Construction Twin, which helps plan, monitor, and manage construction projects, improving quality and reducing delays.
Digital Twin of the Building in Operation, which helps optimize energy consumption, comfort, and maintenance over time.
The big news is that these twins aren’t limited to energy; they also incorporate sustainability and circularity criteria, such as emissions, materials, reuse, and life-cycle costs.
Accessible Digitalization for Construction SMEs
One of the aspects that most sets DTERBIM apart is its clear focus on small businesses, which account for 99% of the entities involved in the construction sector. The project not only develops technology but also works closely with industry stakeholders through participatory methodologies, training, and real-world pilot projects in Spain, Poland, and Greece.
The goal is clear: to lower barriers to entry, facilitate learning, and demonstrate that digitalization and circularity are not a cost, but rather an opportunity to improve competitiveness.
Another step toward the rehabilitation of the future
DTERBIM does not promise magic solutions, but it does propose a profound and realistic change in the way building renovation and construction are approached in Europe. By embracing open standards, accessible tools, and a full life-cycle approach, the project lays the groundwork for a more efficient, sustainable, and inclusive sector.
In the coming years, DTERBIM’s results will be validated through real-world projects and will serve as a benchmark for future policies, regulations, and business models. Because transforming the construction industry is not just a matter of technology—it is a matter of collaboration, long-term vision, and a commitment to a more sustainable future.
Nowadays both air quality and climate change are two themes that are of interest and cause concern to municipalities. Even they are closely related, it´s a case of different problems that requires analysis tools and specific action strategies.In order to design policies tailored to the actual situation in each city, there are no generic measures or decisions to be taken; rather, it is essential to have objective numerical values in order to act efficiently and justifiably.essential to count with nu
In both cases are involved issued gases by the human activity, although not all has the same effect. In one side, atmospheric pollutants affect directly to air quality (nitrogen oxides, carbon monoxide, sulphur dioxide, ammonia or even particulate matter, which, although not gases, have a significant impact on health). On the other side, greenhouse gases, such as carbon dioxide, methane, nitrous oxide or fluorinated gases, which main effect is contribute to global warming.
But les us now focus on the gases that need to be taken into account in local authority policies to combat climate change and move towards climate neutrality, without forgiven that other pollutants are crucial to air quality and health protection policies.
How to measure the emissions of a municipality: the base to design efficient climate policies
If we look at it at the molecular level and we analyse the properties of these gases, we see that some atmospheric pollutants has direct effects over human health, while some certain greenhouse effect gases has an elevated capacity to mantain heat at the atmosphere and contribute to global warming. But if we focus on urban inventories linked to energy consume, emissions volume and by presence on the main emissions sources, the reference gas it is usually the carbon dioxide. In fact, when all greenhouse effect gases are considerer together, their emissions are usually expressed such as equivalent CO2 (Co2eq), a unit that takes into account the different Global Warming Potential (GWP) of each gas and allows them to be compared against a single benchmark.
The prevalence of carbon dioxide in the energy sectors means that it is the predominant gas in most urban emissions inventories. However, in sectors such as waste management, wastewater treatment and certain agricultural and livestock activities, methane and nitrous oxide can account for a significant proportion of emissions.
What is a Reference Emissions Inventory (IER)?
To know where these emissions originate and reduce them in an efficient way, municipalities elaborate a Reference Emissions Inventory (IER). These tools allow quantify emissions associated with different activities developed on the city and constitute the starting point to design climate policies based on data.
In the methodology we use at CARTIF, the inventory organiza the information in three main areas: city council area, PACES analysis area and municipal area. First one evaluate emissions of different areas of the own city council, such as, transport, own fleet, own energy production, etc. Second one is maned in that way because the clasification is inherited fromPlans of Action for the Climate and Energy Sustainable (PACES), an estrategy boost on the framework of Convenant of Mayors that help municipalities to reduce emissions, improve energy efficiency and adapt to climate change. And finally municipal area, which consists of everything not included in the previous one, such as industry or agricultural and livestock (primary), even we have to take into account isn´t a rigid clasification.
What is a Reference Emissions Inventory (IER)?
A municipal emissions inventory is a tool that quantifies the greenhouse gas emissions generated by a city’s activities. It enables the identification of the main sources of emissions and the design of data-driven climate policies to move towards climate neutrality.
How is a municipal emissions inventory calculated?
Inside the sector of each area, the calculations of these emissions should face two major obstacles: on the one hand, the availability of the needed data, where for example city council data is directyl accesible while data such as fossil fuel consume in industry or in residencial buildings requires estimation and stadistical disaggregation processes, as they are not usually available at the required level of municipal detail. On the other hand, for some areas such as transport, it is necessary to work with information such as street network or a selection of communication nodes to generate data in an indirect way that allows realizing a coheretn statistical evaluation. All of this highlights the importance of counting with specialised equipments able to combine data from different sources, apply international recognised methodologies and obtain consistent inventories and comparable in time.
In most urban sectors, particularly those related to energy consumption, emissions are estimated on the basis of the energy consumed (or produced). However, there are sectors such as waste management, certain industrial processes or some agricultural activities where emissions are calculated using other specific parameters. Each energy source or activity has a specific emission factor that relates the unit of consumption or activity (kWh of electricity, litres of fuel, Nm³ of natural gas, tonnes of waste, etc.) to the emissions generated, expressed in tonnes of the corresponding gas or, when different greenhouse gases are aggregated, in tonnes of CO₂ equivalent (tCO₂eq).
Within each sector, consumption and emissions figures are normally broken down by energy source used and, where appropriate, by further sub-categories, such as vehicle types in the transport sector or municipal areas in the utilities sector. Furthermore, it is useful to present aggregated figures by sector and by year, as this allows the trends in consumption and emissions over time to be visualised from the reference year (known as the ‘baseline’) to the most recent year for which data is available.
From data to action: how an inventory helps reduce emissions
At CARTIF, we have carried out various emissions studies for towns and cities, both as part of the Covenant of Mayors initiative — as in the case of Logroño — and through specific studies for local councils, such as Ponferrada. This work provides an objective snapshot of each municipality’s starting point and forms the basis for developing Action Plans, assessing climate risks, prioritising investments and measuring the actual impact of public policies on climate change mitigation and adaptation.
👉 Does your local authority need to draw up or update its emissions inventory? At CARTIF, we help local authorities quantify their emissions, define decarbonisation strategies and design climate plans based on scientific evidence. Get in touch with our team to find out how we can help you.
In recent years, energy prices have become a central variable for industry, thermal networks and, more broadly, for any heat decarbonisation strategy. In this context, a simple but very useful indicator for interpreting market trends is the electricity to gas price ratio, meaning the relationship between electricity and natural gas prices expressed in the same energy unit.
This ratio does not replace a full techno economic assessment, but it does help answer a very practical question: in which contexts can heat electrification, for example through heat pumps, be more attractive than gas based solutions.
What the electricity to gas ratio means
In simple terms, the ratio is defined as:
ratio = electricity price / gas price
If the ratio increases, electricity is relatively more expensive than gas. If it decreases, electricity becomes relatively more competitive.
The key point is that this indicator should be read alongside technology performance. For a heat pump (HP), the cost of useful heat depends on the electricity price, but also on its COP. Therefore, the higher the electricity to gas ratio, the higher the performance required from an electric technology to compete economically with a conventional solution.
Even so, it is best seen as a first contextual signal rather than a final decision: the ratio does not account for investment, operation and maintenance, integration constraints, waste heat availability or regulatory frameworks. That is why it works best when combined with technical results and more detailed analyses, helping to steer innovation, exploitation and transfer strategies without losing sight of market reality.
How the data were collected
For this analysis, electricity and gas price data were collected for different European countries, using Eurostat1 mainly as the reference source for the historical series and for 2025. Based on these inputs, both prices were harmonised into the same energy unit to calculate the ratio consistently.
In this type of exercise, it is important to be clear that the outcome depends on several assumptions: customer category, treatment of taxes, consumption band, and the availability of national data. In some cases, particularly for countries outside Eurostat’s1 standard coverage, it may be necessary to use complementary national sources.
A first look, the 2025 European map
A very intuitive way to represent the ratio is through a European map. Figure 1 shows the distribution of the electricity to gas ratio for 2025.
Fig 1. European map of the electricity to gas ratio in 2025
The first takeaway is clear: Europe does not behave uniformly. Some countries show relatively low ratios, especially in the Nordic region, while others show significantly higher ratios, such as the United Kingdom and some countries in southern and eastern Europe.
The European Union average in 2025 is around 2.96, which already provides a useful reference for interpreting each country’s relative position. Countries such as Sweden or Finland show clearly lower values, suggesting a more favourable environment for electrification. By contrast, high values such as those observed in the United Kingdom, Italy or Greece indicate that, in those contexts, the economic competitiveness of electric solutions depends even more on achieving high performance.
A table to see the evolution in more detail
While Figure 1 provides a global snapshot, the time evolution tells another part of the story. For this reason, Table 1 includes five country cases with very different profiles, plus the European Union average; it covers 2007, 2015, 2025 and a simple extension of the trend to 2035.
Figura 2. Evolution of the electricity to gas ratio in Sweden, France, Spain, Germany and the United Kingdom for 2007, 2015, 2025 and 2035.
In the table, the green shading marks cases where, assuming an average HP COP of 3 and a gas boiler efficiency of 0.9, the price context is more favourable for an HP than for a gas boiler, meaning the electricity to gas ratio is less than or equal to 3/0.9, approximately 3.33, without considering investment or operation.
What trends emerge from the results
Several interesting observations can be drawn from the historical series. First, the ratio has not been stable over time. The evolution between 2007 and 2025 shows significant volatility, confirming that market context can change substantially and directly affect the economic viability of electrified technologies.
Second, the 2025 map confirms strong regional differentiation. Northern Europe generally shows lower ratios, while other countries exhibit more strained relationships between electricity and gas prices. This means the same technological solution does not start from the same economic baseline across countries.
Third, cross country comparison makes it clear that the ratio can be used as a quick reading tool to identify where certain solutions, such as industrial heat pumps, could find a more favourable market entry point.
Finally, the 2035 value should not be interpreted as a prediction. It is a simple extension of the trend observed in the historical series, included only to facilitate reading and to open a discussion on possible trajectories. It can still be useful to explore how market conditions might evolve and what that could imply for the future exploitation of clean heat technologies.
Link to PUSH2HEAT, why this matters for the project
Within PUSH2HEAT, CARTIF is working on the analysis and preparation of exploitation routes and adoption pathways for heat decarbonisation solutions, with a clear focus on industrial contexts and on bringing technologies to market with realistic criteria.
One of the project’s goals is that solutions do not remain as “something that works”, but that they make sense in real world scenarios, with market signals, operational constraints and replicability needs. In that framework, the electricity to gas ratio is a simple but very practical piece to contextualise opportunities by region, and to support exploitation messages with a quantitative basis that is easy to communicate.
How to support vulnerable households through passive solutions
The energy transition is progressing rapidly, but not always in an equitable manner. In Europe, millions of households still struggle to access basic energy services.
In this context, several key questions arise:
· How can we design energy-efficiency renovation strategies that effectively help to reduce vulnerability, bearing in mind that many households cannot afford conventional heating and cooling systems?
· How can we ensure that energy-efficiency renovation projects reach the most vulnerable groups?
To address these challenges, CARTIF took part as a speaker at the Energy Poverty Advisory Hub (EPAH) Annual Conference 2026, during the session entitled ‘How Integrated Energy Renovations Can Reach Vulnerable Households: Practical Approaches to Financing, Engagement, and Demand Reduction’, presenting some of the work carried out as part of the SUPERSHINEproject.
Beyond technology: the role of social innovation in energy retrofitting
Energy-efficient refurbishment now benefits from well-established technical solutions. However, its implementation in disadvantaged neighbourhoods does not depend solely on its technical effectiveness. Factors such as households’ financial capacity, social acceptance of the works, political pressure or the complexity of administrative procedures can become significant barriers to the viability of any intervention.
EPAH 2026 Workshop: Simulating real-world decisions in vulnerable contexts
During the conference, CARTIF led an interactive workshop based on role-play, designed to replicate the real-world complexity involved in decision-making for energy-efficiency renovation projects targeting vulnerable households.
The exercise was based on a typical urban setting, in which participants were tasked with implementing measures in a district characterised by high levels of energy poverty and low energy efficiency in the building stock.
Passive measures: much more than just energy savings
During the project, the focus was on implementing as many passive solutions as possible, with the aim of reducing the district’s energy demand and improving the indoor comfort of the homes.
This approach served to convey a key idea: in vulnerable contexts, improving living conditions cannot depend on the use of active systems, but rather on the quality of the building itself.
People: When technology meets reality
To introduce the social dimension, each participant was assigned a role representing a person with specific characteristics, needs and limitations. This enabled the various profiles involved in the process to face real-life situations. As a result, decisions were no longer purely technical but came to be influenced by social, economic and political factors.
Making decisions under real-world constraints
In addition to the participants, the group was given a set of constraints that introduced real-world limitations into the process. These constraints forced them to continually rethink their decisions, shifting from a focus on technical optimisation to one centred on practical feasibility.
Key takeaways: how to tackle energy poverty
The exercise revealed that, in situations of energy poverty, the priority is not to optimise energy consumption, but to reduce the need for energy.
This approach led to a number of key lessons:
Energy poverty is a multifaceted problem. It cannot be solved by technical solutions alone.
Decisions are influenced by context: what is optimal from an energy perspective may not be so within the social and economic context.
Coordination between stakeholders is essential, particularly when integrating solutions at building and district level
There is no one-size-fits-all solution: each situation requires a balance between efficiency, cost and social acceptance.
Materiales sobre el workshop desarrollado en la conferencia
