Retrofit Scenarios Research Articles

Comparative study of greenhouse gas emission calculations and the environmental impact in the life cycle assessment of buildings in China, Finland, and the United States

The building sector is considered a leading contributor to global greenhouse gas (GHG) emissions. With the implementation of China's 2030 carbon peak and 2060 carbon-neutral strategy, significant quantitative research regarding low-carbon buildings is crucial. However, a considerable discrepancy remains between the low-carbon building development in China and other advanced countries; the calculation method of GHG emissions lacks international integration. Based on the life cycle assessment (LCA) theory, a comparative empirical analysis was conducted among residential and public building sets in China, Finland, and the United States considering the life-cycle GHG emissions, which demonstrated notable differences in the Product stage (A1–A3), Maintenance and material replacement stage (B1–B5), and Energy use stage (B6) between each building set. Different building retrofit scenarios were then established to study the emission reduction methods. The results suggest that clean energy sources, materials with low global warming potential, engineered wood structures, and steel structural beams in long-span buildings are conducive to reducing GHG emissions throughout the life-cycle of buildings.

The collaborative pollutants and carbon dioxide emission reduction and cost of ultra-low pollutant emission retrofit in China's cement kiln

Promoting the ultra-low pollutant emission retrofit of the cement industry, as the third largest industry in terms of air pollutants and carbon dioxide (CO2) emissions in China, has become an important part of achieving carbon peaking and carbon neutrality. In this work, the current status of pollutant emission in cement industry and the pollutant emission limit value of ultra-low emission retrofit in typical provinces were analyzed. And, the collaborative air pollutants and CO2 emission reduction potential and cost-benefit were assessed in six types of ultra-low pollution emission retrofit scenarios. The results indicate that the emission reduction of particulate matter (PM)，sulfur dioxide (SO2) and nitrogen oxides (NOx) in six scenarios are 10%–15%, 1%–5% and 26%–64%, respectively. The construction investment of 43.8 billion Yuan is needed to complete the retrofit of production lines when the pollutant emission limit value is set as 10 mg/m3, 35 mg/m3 and 50 mg/m3 for PM, SO2 and NOx, which is 6 times of that when the pollutant emission limit value is set as 10 mg/m3, 50 mg/m3 and 100 mg/m3. However, the cost per unit equivalent of pollutant abatement of the former is only 36% of the latter. The emission reduction potential of CO2 in six scenarios is 0.4%–0.6%, indicating that the ultra-low pollutant emission retrofit in cement kiln has limited effect on CO2 emission reduction potential. Comprehensive analysis of emission reduction potential and cost-benefit, it is more economical and reasonable for China cement kilns to choose the path of ultra-low emission retrofit in scenario 4.

Combining CAD Modeling and Simulation of Energy Performance Data for the Retrofit of Public Buildings

The retrofit of the most energy-intensive buildings represents an opportunity to improve their energy efficiency or to reduce their energy demand. This paper proposes combining computer-aided design (CAD) modeling and the use of energy efficiency software to build a methodology for calculating, visualizing and analyzing building parameters in order to provide retrofit scenarios. Five retrofit scenarios were implemented using the energy software, including the initial operating cost, capital cost and payback period to be evaluated. At the same time, a three-dimensional CAD model was created to perform daylighting and shading simulations to visualize and design the role of building orientation under actual use conditions. These retrofit scenarios were evaluated individually and then combined to examine their performance in terms of cost-effectiveness and energy efficiency. The simulation results show the importance of the building’s orientation, as this directly affects the thermal properties of the walls and openings, as well as the daylighting areas. The simulation results were also used to define the parameters that affect the interoperability of the retrofit solutions. Finally, in addition to the significant reduction in calculation time, the coupling of the CAD software with the energy efficiency software allowed access to information that was not available at the outset.

Investigation of different resilience-based optimisation strategies for retrofitting curved bridges

Recent natural or manmade hazards highlighted the pressing need for allocating enough financial resources for the enhancement of the resilience of infrastructure in our society. In this regard, bridges play a pivotal role in transportation networks, where any reduction in their performance can influence the functionality of the whole network. Bridge retrofitting is a common strategy for enhancing transportation network resilience. Composite reinforcement with different thicknesses and concrete seat extenders with different widths have been used to retrofit an existing curved bridge in Iran. A novel hybrid algorithm called NSGAII-SA was proposed and compared against a simple optimisation strategy, a traditional genetic algorithm solver (NSGA-II), and pure simulated annealing (SA). These optimisation strategies identify the optimal retrofit scenarios set in terms of maximum resilience index, minimum recovery time, and minimum retrofitting cost. For this problem, NSGAII-SA outperforms the traditional NSGA-II. The comparison shows that for this particular application, SA has the best overall performance. However, the proposed NSGAII-SA algorithm has satisfactory performance too, it is a clear improvement over NSGAII and it has the potential to be very useful and better suited than SA for problems with large design spaces and many local minima.

Seismic vulnerability assessment and retrofitting design of Italian public buildings

Rina Consulting, between 2019 and 2021 was involved in the seismic vulnerability assessment and retrofit design of a large public buildings stock in Italy. The project includes several buildings built between the 40′s and the 90′s located in regions prone to very high seismic hazard and characterized by strategic uses. The buildings included in the portfolio span from masonry structures to reinforced concrete structures, including precast buildings. All the structures were submitted to linear and nonlinear analysis to define their seismic vulnerability and identify their structural deficiencies; then a retrofit design was performed to guarantee the increase of the building's seismic capacity according to the requirements of National code. Alternative retrofitting scenarios were investigated, and compared by means of cost-benefit analysis, with the aim to guarantee a good balance between the costs and the structural efficiency of the interventions.The main aim of the paper is to present practical considerations regarding the main issues related to the data gathering, the seismic input definition and the seismic vulnerability index obtained for the different building typology. The study aims also to investigate the comparison between the seismic requirements assumed for the original design and the seismic requirements assumed for the seismic vulnerability according to the current national code and its influence on retrofit interventions costs. The collected data form part of a database which scope is to provide a criterion for predicting retrofit strategy and costs as a function of the seismic vulnerability index. Final purpose of the study is to provide possible improvement of the methodologies to be applied to similar projects that include large building stock to define a possible efficient framework to be proposed to the different stakeholders.

Operational energy and embodied impacts of retrofitting the window frames of mixed-mode office buildings

Design decisions normally consider the building's operational phase as the main criterion to reduce energy expenses in a building. In less efficient buildings, reducing the operational energy becomes the most important aspect to address in the design, construction and operational phases, for it represents the highest life cycle energy flow. However, energy-efficient solutions often reduce operational energy demand by increasing the building's embodied energy and greenhouse gas emissions, which have been overlooked in energy performance analyses. This work aims at investigating the operational energy and the consequent embodied impacts resulting from the retrofit of the window frame of mixed-mode office buildings located in a hot climate, with a focus on reducing the cooling energy demand. The method consists of an experimental study based on a case study, in which the EnergyPlus and the SimaPro software tools are used to evaluate the operational energy and the environmental impacts. Results showed that reducing the WWR and increasing the window opening factor conveyed operational energy savings but in some retrofit scenarios tested, these retrofit measures were counterproductive from the CED and GWP perspective. The main scientific contribution of this work is understanding the importance of the building analysis from a life-cycle approach. The results obtained can assist companies and designers to make their decisions from a broader environmental perspective.

A Systematic Literature Review of Physics-Based Urban Building Energy Modeling (UBEM) Tools, Data Sources, and Challenges for Energy Conservation

Urban building energy modeling (UBEM) is a practical approach in large-scale building energy modeling for stakeholders in the energy industry to predict energy use in the building sector under different design and retrofit scenarios. UBEM is a relatively new large-scale building energy modeling (BEM) approach which raises different challenges and requires more in-depth study to facilitate its application. This paper performs a systematic literature review on physics-based modeling techniques, focusing on assessing energy conservation measures. Different UBEM case studies are examined based on the number and type of buildings, building systems, occupancy schedule modeling, archetype development, weather data type, and model calibration methods. Outcomes show that the existing tools and techniques can successfully simulate and assess different energy conservation measures for a large number of buildings. It is also concluded that standard UBEM data acquisition and model development, high-resolution energy use data for calibration, and open-access data, especially in heating and cooling systems and occupancy schedules, are among the biggest challenges in UBEM adoption. UBEM research studies focused on developing auto-calibration routines, adding feedback loops for real-time updates, future climate data, and sensitivity analysis on the most impactful modeling inputs should be prioritized for future research.

Dynamic modelling of indoor environmental conditions for future energy retrofit scenarios across the UK school building stock

UK schoolchildren spend on average 30% of their waking lives inside schools. While indoor environmental quality (IEQ) is critical for their health and attainment, school buildings are also a key part of the UK's carbon emissions reduction strategy. To address conflicts between energy efficiency and IEQ, predictive models of UK classroom stock should incorporate energy and IEQ performance criteria across dynamic scenarios comprising energy retrofit and IEQ improvement measures. On this basis, we have developed a novel approach for auto-generation, simulation, post-processing and analysis of EnergyPlus UK classroom archetype models. Such modelling facilitates the multi-parameter evaluation of school building performance, whilst incorporating stock-wide heterogeneity and longitudinal dynamic changes.As extent of retrofit increases, decreasing incremental energy demand reduction was quantified and increasing effectiveness of passive ventilation at mitigating overheating was identified. Negative impact of South facing orientation on overheating was reduced after applying a range of IEQ improvement methods. However, low ceiling heights in 1945–1967 era classrooms impact the efficacy of these IEQ mitigations on calculated attainment, requiring design rather than mitigation strategies as a remedial solution. Strategies preventing NO2 pollution ingress could be more-effective than PM2.5, with night-time ventilation avoiding ingress during daily peaks and greater sensitivity to location. Future work shall incorporate multiple criteria into a single tool based on stakeholder preferences to improve quality of retrofit decision making.

The impact of energy-efficiency upgrades and other distributed energy resources on a residential neighborhood-scale electrification retrofit

Ambitious targets for carbon emissions reductions are highlighting new challenges for electrification strategies, leading to an increased focus on building load flexibility and energy management to complement the variability inherent in renewable energy generation. Over the next decade millions of existing homes could undergo electrification retrofits, and there is an urgent need to understand the potential impacts of electrifying major residential loads such as water and space heating on community load characteristics, resident energy bills, and the utility’s distribution system. Behind-the-meter distributed energy resources (DERs), including efficiency measures, photovoltaics (PV), battery storage, managed electric vehicle (EV) charging, and controls such as home energy management systems (HEMS), can significantly alter a neighborhood’s load profile and provide benefits to both the residents and the grid. We present a novel approach to characterizing the impact of a hypothetical neighborhood-scale residential retrofit program on individual homes’ energy use profiles, associated utility bills, and the local distribution system. We modeled a mixed-fuel community of 30 single-family homes in Denver, Colorado, and compared the effects of retrofit scenarios ranging from conventional energy-efficiency upgrades to full electrification with and without more advanced DER technologies. We analyzed which packages of DERs most reliably enable demand flexibility in response to a time-of-use (TOU) rate for this and similar neighborhoods. Our buildings-to-grid co-simulation framework includes a generic secondary distribution feeder model to capture voltage profiles, transformer loading, and other grid impacts in each case. We also calculated the carbon emissions associated with energy use in the community. The methodology developed here can be broadly applied to community-scale beneficial electrification studies in other regions, climates, utility infrastructures, and building typologies to make specific, targeted recommendations based on quantified projections of energy demand in any given community. Our findings indicate that residential electrification can be achieved without negatively impacting the monthly utility bill, and that a combination of conventional energy-efficiency measures, PV, battery, controls, and managed EV charging to maximize a community’s demand flexibility is a promising strategy. Adding DERs (especially PV) as part of efficient electrification produces much bigger savings than efficient electrification without DERs. A key barrier is that upgrades require upfront costs, and modest utility bill savings result in long payback periods.

A multi-aspect approach to energy retrofitting under global warming: A case of a multi-apartment building in Montenegro

Global warming will seriously affect buildings, and the Montenegrin building stock is no exception. Since the country is one of the most inefficient energy users in Europe, improving the energy efficiency of buildings is essential. Therefore, the study implemented a novel multi-aspect approach to energy retrofitting, linking building thermal performance, occupant interaction and climate change. A representative existing multi-apartment building in Podgorica was selected, and a survey among occupants was conducted to identify their satisfaction with indoor thermal comfort and to evaluate the acceptability of the proposed energy retrofit measures. Next, the thermal performance of the building was simulated under current and future climate conditions. Finally, a comprehensive parametric analysis was performed by applying different retrofit scenarios. The selected retrofit measures were evaluated based on their impact on energy efficiency and occupant acceptability. The results showed that the most impactful retrofit measure would be thermally insulating the building envelope, followed by a lower shading set-point and natural ventilation cooling. Applying the best retrofit combinations would reduce the total energy demand by 75% under the current climate and by 66% and 59% at the end of the 21st century under the RCP4.5 or RCP8.5 scenarios, respectively. However, the occupant survey results disclosed that beyond thermally insulating the building, occupants have limited awareness about the potential of energy retrofit actions, while summer thermal discomfort is the dominant issue. Therefore, building energy retrofit and climate adaptability actions should also address occupant views.

Applying the response surface methodology to predict the energy retrofit performance of the TABULA residential building stock

Recent advances in computing software have enabled the development of calibrated building energy simulations tools that allow retrofit-related analysis including optimization and energy-efficient building design. However, to create a national energy and climate plan, using these tools may imply a great deal of effort (time, cost, and human resources) to carry out simulations for the full set of different building types, construction, geometries, design parameters, and retrofit scenarios. Because of this, simplified approaches that can reliably estimate the impact of energy-efficiency retrofit alternatives based on averaged building stock characteristics could offer a significant advantage, especially in middle-income countries such as Bosnia and Herzegovina. This study aims to explore the energy reduction potential of a representative building from the national residential building stock by utilizing the response surface methodology (RSM). In this study, RSM is combined with the energy simulation tools EnergyPlus and DesignBuilder to model the energy savings associated with energy-efficient retrofit measures for a residential building from the national TABULA registry in Bosnia and Herzegovina. This study introduces a novel energy consumption model that can be applied to optimize energy-efficient retrofit design solutions for reducing the energy consumption for heating and cooling in the residential building sector. Moreover, the model developed was validated by using the results of a national survey on energy consumption in Bosnia and Herzegovina. Therefore, the use of the model developed is versatile and suitable for rapid prediction of energy-efficient retrofit-related energy consumption and energy savings of the residential building stock.

Simulation-Based Decision Support System for Energy Efficiency in Buildings Retrofitting

The implementation of building retrofitting processes targeting higher energy efficiency is greatly influenced by the investor’s expectations regarding the return on investment. The baseline of this work is the assumption that it is possible to improve the predictability of the post-retrofit scenario, both in energy and financial terms, using data gathered on how a building is being used by its occupants. The proposed approach relies on simulation to estimate the impact of available energy-efficient solutions on future energy consumption, using actual usage data. Data on building usage are collected by a wireless sensor network, installed in the building for a minimum period that is established by the methodology. The energy simulation of several alternative retrofit scenarios is then the basis for the decision support process to help the investor directing the financial resources, based on both tangible and intangible criteria. The overall process is supported by a software platform developed in the scope of the EnPROVE project. The platform includes building audit, energy consumption prediction, and decision support. The decision support follows a benefits, opportunities, costs, and risks (BOCR) analysis based on the analytic hierarchy process (AHP). The proposed methodology and platform were tested and validated in a real business case, also within the scope of the project, demonstrating the expected benefits of alternative retrofit solutions focusing on lighting and thermal comfort.

Estimating Space-Cooling Energy Consumption and Indoor PM2.5 Exposure across Hong Kong Using a City-Representative Housing Stock Model

High-quality data on building energy use and indoor pollution are critical to supporting government efforts to reduce carbon emissions and improve the population’s health. This study describes the development of a city-representative housing stock model used for estimating space-cooling energy use and indoor PM2.5 exposure across the Hong Kong housing stock. Archetypes representative of Hong Kong dwellings were developed based on geographically-referenced housing databases. Simulations of unique combinations of archetype, occupation, and environment were run using EnergyPlus, estimating the annual space-cooling energy consumption and annual average PM2.5 exposure concentrations under both non-retrofit and retrofit scenarios. Results show that modern village houses and top-floor flats in high-rise residential buildings, on average, used 19% more space-cooling energy than other archetypes. Dwellings in urban areas had lower exposure to outdoor-sourced PM2.5 and higher exposure to indoor-sourced PM2.5 compared to those in rural areas. The percentage decrease in space-cooling energy consumption caused by energy efficiency retrofits, including external wall insulation, low-e windows, and airtightening, varied significantly based on archetype. The implementation of external wall insulation in the housing stock led to an average decrease of 3.5% in indoor PM2.5 exposure, whilst airtightening and low-e windows resulted in 7.9% and 0.2% average increases in exposure, respectively.

Identifiability study of an RC building model based on the standard ISO13790

This paper presents the construction of a RC building model with a good identifiability and a good predictive ability. The identifiability refers to the convergence of a calibration algorithm towards parameters that correspond to the physical properties of the building. This property allows accurate parameterization of the models and robust calibration. The calibrated RC models can be used for predictive control and the non-calibrated RC models are appropriate for urban energy simulation platforms for the analysis of flexibility and retrofit scenarios. From the state of the art, a modified RC model based on the standard ISO 13790 is proposed and then studied on a simplified mono-zone case study. A Bayesian calibration method has highlighted a problem of correlation between the parameters. A selection of parameters and the re-parameterization of the model have been successfully proposed to reach a good identifiability of the model.

Coupling of the electricity and district heat generation sectors with building stock energy retrofits as a measure to reduce carbon emissions

This study examined how the carbon dioxide emissions can be reduced in an energy system with coupling of the electricity and district heat generations, while considering different paths for the building stock development. As the building sector and the energy sector are interdependent on one another, it is important to consider them as a whole, to understand to what extent emission mitigation measures should be conducted in each of them, to avoid unnecessary costs. The problem was applied to a Finnish context and formed as a mixed-integer linear programming problem, which was used to minimize the emissions from highly renewable electricity and district heat generations, by using the flexible properties in both. A scenario-based analysis was performed, where simulations were conducted for the year 2050 and the effects to the emissions and energy system costs were examined over 30 years up to 2050. The set target of 90 % emission reductions in annual emissions, from the 2020 level, was attained with several combinations of wind power, deep heat well heat pumps, and thermal storage as part of the energy generation, for each of the energy retrofit scenarios of the building stock. However, both the building stock and energy system measures were required to reach the target. The amount of wind power had a major impact on the results, and in general the more wind power was utilized the less the other measures were required. Moreover, when the building stock was retrofitted to a lower environmental impact level, the costs to reach the target emissions were less than half compared to retrofitting them to a higher impact level. However, there was no major difference whether the building stock developed more towards household heat pumps or district heating. The least costly set of options to reach the target emissions for 2050, 1.83 Mt of carbon dioxide annually, attained them with a cost increase of 10.18 billion euros from the reference over 30 years. The emissions for the same period decreased by 56 %, from 488 to 217 Mt of carbon dioxide, resulting in a unit cost of 37.6 € per ton of carbon dioxide for the emission reductions.

Multi-technology building system retrofits for utility incentive programs: Savings, costs and baseline considerations

Utility incentive programs are an important channel to support the deployment of energy efficiency in buildings. To date, these programs have largely been limited to single-component strategies. However, many utilities are now motivated to identify and develop multi-component system retrofits to achieve deeper energy savings, which are essential to achieving broader energy and greenhouse gas reduction goals in the buildings sector. In this paper we present the energy savings, demand reductions, and cost-effectiveness of 16 systems retrofit packages in six utility regions in the United States. These results are being used by these utilities to inform and develop incentive programs for systems retrofits. Our analysis shows that packages with proven lighting and HVAC measures can provide 5–22% whole building annual energy savings, and 13–22% annual energy costs savings, using utility incentive program baselines (code and existing building). The packages are reasonably cost effective for replace-on-burnout but generally not for a retrofit scenario prior to end of equipment life. Demand response can increase both the energy savings and energy cost savings, further improving the cost effectiveness of these packages. We analyzed the impact of using existing building vs. code baselines for calculating savings, showing that the choice of baseline in developing utility incentive programs has a substantial impact on the attributable energy savings to a program, with significant implications for the overall viability of a program (generally savings against existing building condition are higher and improve project and program cost-effectiveness).

Assessing energy demands of building stock in railway infrastructures: a novel approach based on bottom-up modelling and dynamic simulation

In this paper the implementation and application of a novel methodology for the estimation of the energy demand of the railway building stock is presented. To this aim, a bottom-up modelling approach implemented in a simulation tool is developed to assess the energy footprint and potential savings of railway buildings. The tool is intended to support operators and decision-makers in the planning of systematic energy retrofit necessary to up to date the railway infrastructure.The developed methodology is applied to the Italian railway building stock with a bottom-up approach, identifying several groups of similar stations (archetypes) that are clustered according to real data collected. Afterwards, a data-driven model is derived from the detailed dynamic simulations of physic-based models representing the whole building heritage. As a demonstration of the validity of the proposed methodology and its capability to be exploited in real applications, some energy-saving strategies are simulated, and a comprehensive analysis is conducted on the considered stations.The surrogate data-driven model shows R2 coefficients always above 0.93 compared to physic-based model in predicting heating, cooling and electricity demand. Depending on the size of the stations, the mean relative error is in the range 5.9–15.0%. Furthermore, the surrogate model turns out to be an easy-to-use tool to analyse retrofit scenarios and take informed decisions, while the methodology is easily extensible and scalable to other contexts.As demonstrated, the most impactful measure among the ones investigated is the adoption of high-performance lighting systems which entail an overall primary energy saving up to 26%, with very low pay back periods (∼1 year).

Re-considering the energy efficient retrofitting approach to question cost-optimality and nZEB under COVID-19 measures

The building energy performance has been highly studied in the last decades considering the indoor environmental quality, and sustainability indicators to examine energy-efficient cost-optimal, and nZEB building levels for different building typologies. However, since the start of the COVID-19 pandemic in 2020, the usage and operation of public spaces and buildings have evolved according to COVID-19 measures produced by the authorities. Social distancing measures and HVAC system measures affecting energy performance and indoor environmental quality of the public buildings are consequently necessary for building energy performance studies. Thereby, it is aimed at re-considering an energy-efficient cost-optimal retrofitting approach for a primary school building case, under the COVID-19 measures to recast an energy-efficient cost-optimal level and apply a cost-efficiency criterion to search for the measures adapted nZEB scenarios. COVID-19 measures affecting building energy performance, such as social distancing and IEQ requirements, were analysed. Then, probable ventilation rates were controlled by the infection probability method to satisfy the limit number for infection. Thus, pre-COVID-19 and post-COVID-19 variables regarding occupancy density and HVAC operation were determined for the calculation process. Besides, retrofit scenarios were shaped to improve optic and thermophysical properties of the façade, lighting, and HVAC systems performance. Then, energy, LCC, thermal comfort and IEQ performance of retrofit scenarios were calculated with a calibrated model. Results were evaluated by applying the cost-efficiency criterion to find out nZEB scenarios. It can be stated that distinct LCC and energy use increments occurred in the cost-optimal range and nZEB level.

Failure Modes of RC Structural Elements and Masonry Members Retrofitted with Fabric-Reinforced Cementitious Matrix (FRCM) System: A Review

Much research has been conducted and published on the examination of the behavior of reinforced steel and concrete structures with a FRP system. Nevertheless, the performance of FRP differs from that of FRCM, particularly at high temperature and ultimate strength. The present study provides a review of previous research on structural elements (viz. beams, columns, arches, slabs, and walls) retrofitted with FRCM systems, taking account of various parameters, such as layers, composite types, configurations, and anchors for controlling or delaying failure modes (FMs). Additionally, this paper discussed the details of different FMs observed during experimental tests, such as crushed concrete or bricks, fiber debonding from substrate materials, slippage, fiber rupture, and telescopic failure for strengthened specimens. Moreover, this paper investigated where and how fractures may develop in structural elements retrofitted with the FRCM system under various retrofit scenarios. To this end, in addition to the review of the relevant literature, a large dataset has been compiled from different (RC) structural elements and masonry members. Next, a relationship is developed between failure modes (FMS) and influential parameters, i.e., the number of layers and the type of composite, based on this dataset. This can be used as a benchmark example in future studies, as there is no such basis available in the literature, to the best of the authors’ knowledge.

Data-driven decision support system for building stocks energy retrofit policy

In most European countries, residential assets account for as much as 85% of the building stock floor area and are, on average, very outdated and energy inefficient. Moreover, the European Commission published the EU Green Deal invigorating higher retrofit of private and public buildings. Nowadays, public authorities collect extensive datasets to analyze the existing building stock; however, the complex and diverse scenario makes the definition of retrofit policies cumbersome. The biggest hurdle is often linked to the high cost of acquiring information. The presented research tries to overcome these issues by introducing a decision support system for retrofit policymaking from low-cost data-driven approaches. The method is based on: i) clustering techniques to divide building assets into groups with similar characteristics and energy consumption, and ii) Montecarlo simulation to compute each cluster's energy savings based on different retrofit scenarios. The proposed method has been successfully applied to an extensive portfolio of residential assets in Lombardy Region in Italy, called the CENED database, with over one million assets. As a result, the introduced method defines the optimum retrofit scenario with a low cost of information (e.g., without expensive surveys to gather data on existing assets' characteristics and performance indicators) and determines the number of assets to be retrofitted along with the expected energy savings. This data-driven approach can be easily updated given new renovations and status changes in the built environment, making it useable for the long term or in different regions. To summarize, data-driven solutions are now required to accomplish the European Union's decarbonization ambitions, and the proposed method helps decision-makers choose better energy retrofit policies for the built environment.