Climate change is already producing observable effects on the environment, with heatwaves, rising temperatures, and extreme weather events increasingly impacting buildings.
The RESILIENT project addresses this challenge by assessing the impact of climate-resilient strategies on the Spanish building stock and developing a novel decision-making model to optimize the allocation of funds for climate-resilient retrofitting, both at the individual building and portfolio levels.
Unlike previous initiatives, this project adopts a comprehensive approach, exploring the untapped potential of building envelopes and systems in the implementation of climate-resilient strategies such as:
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Envelope-related strategies (insulation, PV-integrated façades and roofs, shading devices).
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Green strategies (green roofs and façades, urban agriculture combined with photovoltaics).
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Building systems strategies (replacing inefficient HVAC systems with renewable-integrated ones).
By clustering data and modelling representative buildings under current and future climates, and validating these through real-world testing, the project will deliver a validated decision-making model for optimized climate-resilient retrofitting.
The main objective of the RESILIENT project is to assess the impact of climate-resilient strategies on the Spanish building stock and to develop an innovative decision-making model for optimizing the allocation of funds in climate-resilient retrofitting, across both individual buildings and large portfolios.
Specific objectives include:
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Obj 1. To develop a set of future weather files for building simulations, based on regional climate projections.
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Obj 2. To design an automated method for identifying representative buildings through the integration of open data sources.
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Obj 3. To model and evaluate the impact of climate-resilient strategies on building resilience, energy performance, and thermal comfort.
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Obj 4. To develop a novel decision-making model to optimize fund allocation in climate-resilient retrofitting at both building and portfolio levels.
The project’s work plan is structured into six work packages (WP):
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WP1 and WP6 are transversal work packages that will ensure proper project coordination and maximize the societal impact of the results.
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WP2 will identify and model representative buildings by clustering national databases and developing accurate simulation models for the most common Spanish building typologies.
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WP3 will generate future weather files based on regional climate projections and simulate climate-resilient strategies under both current and future conditions.
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WP4 will test selected climate-resilient strategies in real buildings, validating simulation results through experimental monitoring campaigns.
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WP5 will carry out a comprehensive assessment of the strategies, analysing their technical feasibility, cost-effectiveness, environmental performance, and scalability. It will also develop an innovative decision-making model to optimize retrofitting investments at both building and portfolio levels.
The project is expected to make a significant contribution to the generation of new scientific and technical knowledge in the field of sustainable and climate-resilient buildings. By combining advanced climate modelling, data integration, and building performance analysis, the project will deliver innovative tools and insights to support the energy transition and climate adaptation of Spain’s building stock.
Key expected impacts include:
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Advanced Climate Data: Creation of updated and localized future weather files (EPW) for Spain, enabling more accurate building performance simulations under different climate scenarios.
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Reference Building Models: Development of a comprehensive set of Spanish reference buildings to support cross-sectional analysis of energy use, comfort, and resilience.
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Automated Data Integration: Implementation of an automated method for identifying representative buildings through open data sources, adaptable to different geographical scales.
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Evidence-Based Strategies: A detailed assessment of the effectiveness, feasibility, and cost of climate-resilient design and retrofitting measures, supporting informed decision-making.
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Decision-Support Tools: Design of a novel model to prioritize investment and funding allocation for climate-resilient renovation at both individual and portfolio levels.
Beyond the scientific and technical outcomes, the project will generate substantial socio-economic benefits:
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For policymakers: Guidance to support national and local strategies aligned with EU decarbonization and climate adaptation goals.
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For building occupants: Improved health, comfort, and safety, together with reduced energy costs and energy poverty. Public buildings designed under the project’s principles can also act as climate shelters during extreme weather events.
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For professionals and industry: New business opportunities and job creation by facilitating the integration of climate-resilient solutions into building design and renovation.
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For property owners: Increased asset value and operational savings, transforming resilience investments into long-term economic advantages.
Ultimately, the project will foster a more sustainable, resilient, and inclusive built environment capable of facing future climate challenges.
Title of the project: RESILIENT - Towards a climate-resilient future: modeling strategies for the Spanish building stock
Principal investigators: Prof. Marta Gangolells and Dr. Blanca Tejedor.
Beneficiary: Universitat Politècnica de Catalunya.
Funding body: Agencia Estatal de Investigación.
Funding program: Programa estatal de investigación científica y técnica y de innovación.
Reference: PID2024-160139OB-I00
Funding: 101,250 €.
Duration: 36 months.
Starting date: October 2025.
News
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The article has been published in the prestigious Journal of Building Engineering.
The RESILIENT project has developed an automated method for modelling national-scale reference buildings -
The article has been published in the prestigious journal Energy & Buildings.
The GRIC research group rethinks Building-Integrated Photovoltaics by evaluating their thermal trade-offs
