Publicacións

@article{rodriguez-alvarez_litheum_2025,

title = {LITHEUM. A web-based lighting and thermal urban model for city energy assessment},

author = {Jorge Rodríguez-Álvarez and Miguel Ángel Rodríguez-Luaces and Tirso Varela-Rodeiro and Natalia Alvaredo-López and Víctor Lamas-Sardiña},

url = {https://www.sciencedirect.com/science/article/pii/S2210670725004779},

doi = {10.1016/j.scs.2025.106603},

issn = {2210-6707},

year  = {2025},

date = {2025-07-01},

urldate = {2026-03-23},

journal = {Sustainable Cities and Society},

volume = {130},

pages = {106603},

abstract = {This study presents Litheum (LIghting and THErmal Urban Model), an online urban building energy modelling (UBEM) tool that integrates morphological sensitivity analysis with interactive scenario development. By leveraging Geographic Information Systems and open-source technologies, the model addresses the accessibility challenges of previous UBEM tools, offering an intuitive web-based application suitable for diverse users, from homeowners to planners and policymakers, without requiring prior energy modelling expertise. Litheum applies a novel algorithm to calculate solar obstruction, optimizing computational requirements while capturing the spatial and temporal dynamics of urban contexts, an area where data-driven models often fall short. The energy calculation methods follow the EN ISO 52016–1 standard, balancing precision, flexibility, and reproducibility for large-scale applications. Unlike detailed dynamic building simulation tools, Litheum is optimized for urban energy planning and policy development. Pilot studies in three Spanish cities—Pontevedra, A Coruña, and Madrid—demonstrated the model's adaptability across varying urban scales. Feedback informed enhancements, including a solar control mode functionality for warmer climates. The online platform's design enables seamless interaction and rapid deployment in diverse urban settings. Future efforts will focus on expanding the platform's deployment in additional cities, integrating artificial intelligence to infer key building characteristics, such as glazing ratios, to improve robustness and processing efficiency. Litheum exemplifies the potential of open-source UBEM tools to facilitate energy assessment, fostering widespread adoption and better informed planning decisions.},

keywords = {Computer simulation, Energy assessment, UBEM, Urban building energy models, Urban morphology, web-GIS},

pubstate = {published},

tppubtype = {article}

}

@article{rodriguez-alvarez_urban_2023,

title = {Urban Building Energy Modelling for the Renovation Wave: A Bespoke Approach Based on EPC Databases},

author = {Jorge Rodríguez-Álvarez},

url = {https://www.mdpi.com/2075-5309/13/7/1636},

doi = {10.3390/buildings13071636},

issn = {2075-5309},

year  = {2023},

date = {2023-07-01},

urldate = {2026-08-13},

journal = {Buildings},

volume = {13},

number = {7},

pages = {1636},

publisher = {Multidisciplinary Digital Publishing Institute},

abstract = {In 2020, domestic buildings represented 27% of the energy consumption in the European Union. The EC Renovation Wave concluded that the annual renovation rate should be doubled, from 1% to 2%, over the next decade in order to meet the 2030 energy efficiency targets. Funding programs are being implemented at national and European levels to accelerate this process. These aim to prioritize large-scale interventions and the most efficient energy conservation measures by including strict performance targets as eligibility conditions. However, these programs are coordinated by local authorities, and they struggle to generate reliable energy estimates for large areas, not least predict potential savings at both aggregated and individual levels. This paper presents a bespoke energy retrofit analysis methodology based on urban building energy modelling, which is defined and calibrated with the Energy Performance Certificate Database. We apply this method to the case study Barrio das Flores. The model adopts a hybrid approach, defining and simulating representative typologies to extrapolate the results to the whole district according to each dwelling’s specific parameters. This methodology will be used to predict the potential energy savings in the study area and support the grant application for the funding renovation program.},

keywords = {building renovation, Energy efficiency, Urban building energy models},

pubstate = {published},

tppubtype = {article}

}