Marta Oliveira Panão


Departamento de Engenharia Geográfica, Geofísica e Energia

Sala/Gabinete 8.3.24
Ext. Principal 28330
Telefone Direto

Carreira Docente Universitário
Categoria Professor Auxiliar



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Currículo Resumido

Marta Panão, Eng. Physics (IST), MSc (IST), PhD in Mechanical Engineering (IST), is an Assistant Professor at FCUL. Her active research areas are performing indicators for Net Zero Energy Buildings, simplified and RC energy models, building stock energy models, demand energy flexibility, energy sufficiency. She published her work in 23 papers in international peer review journals with more than 300 Scopus citations (h-index 12). Since 2014, she is an assistant professor and chair of Heat and Mass Transfer, Energy Efficiency and Sustainable Buildings. She had participated in different research projects, more recently: SATO - Self Assessment Towards Optimization of Building Energy (2020-2024); SMILE - Sintra Motion & Innovation for Low Emissions (2021/2024); Urban data driven models for creative and resourceful urban transitions, SusCity (2015/2018); Solar potential in the urban environment, PVcity (2015/2108).

Scientific Interests

Buildings stock energy modelling;

Energy Performance Certification and Net-ZEB;

RC modelling of buildings thermal performance;

Demand Energy Flexibility;

Energy Sufficiency

Publicações selecionadas
  • Melo F.C., Carrilho da Graça G., Oliveira Panão M.J.N. (2023). A review of annual, monthly, and hourly electricity use in buildings, Energy and Buildings, 293, 113201.
  • Oliveira Panão M.J.N. (2021). Lessons learnt from using energy poverty expenditure-based indicators in a mild winter climate, Energy and Buildings, 242, 110936.
  • Oliveira Panão M.J.N., Mateus N.M., Carrilho da Graça G. (2019). Measured and modeled performance of internal mass as a thermal energy battery for energy flexible residential buildings, Applied Energy, 239, pp. 252-267.
  • Oliveira Panão M.J.N., Brito M.C. (2018). Modelling aggregate hourly electricity consumption based on bottom-up building stock, Energy and Buildings, 170, pp. 170-182.
  • Fonseca J.N.B., Oliveira Panao M.J.N. (2017). Monte Carlo housing stock model to predict the energy performance indicators, Energy and Buildings, 152, pp. 503-515

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