Mr. Luis Martin Pomares | Resource Assessment| Best Researcher Award
Dubai Electricity and Water Authority (DEWA) | United Arab Emirates
Luis Martín-Pomares is a leading expert in solar energy with extensive experience in solar resource assessment, remote sensing, and solar forecasting. He has held positions as Principal Scientist at the Dubai Electricity and Water Authority (DEWA) and as a Scientist at the Qatar Foundation’s QEERI, contributing to the development of regional solar atlases and advanced predictive models for photovoltaic and concentrated solar power plants. As President and Senior Project Developer at Investigaciones y Recursos Solares Avanzados S.L. (IrSOLaV), he led multi-disciplinary teams in the design and implementation of multi-MW solar projects worldwide, integrating satellite-derived irradiance data, statistical downscaling models, and deep learning for solar forecasting. His research encompasses solar irradiance estimation from geostationary and polar satellites, nowcasting systems, energy audits, and GIS-based solar resource mapping. Luis actively participates in international collaborations including the International Energy Agency (IEA) Solar Heating and Cooling tasks, COST Action 1002, and the FP7 DNIcast project. He is also a reviewer for journals such as Solar Energy, Journal of Solar Energy Engineering, and Atmospheric Measurement Techniques. His work has advanced predictive solar modeling and operational strategies for renewable energy integration, establishing him as a key contributor to the global solar energy community.
Profile: Google Scholar
Featured Publications
Martín, L., Zarzalejo, L. F., Polo, J., Navarro, A., Marchante, R., & Cony, M. (2010). Prediction of global solar irradiance based on time series analysis: Application to solar thermal power plants energy production planning. Solar Energy, 84(10), 1772–1781.
Perez, R., Lorenz, E., Pelland, S., Beauharnois, M., Van Knowe, G., et al. (2013). Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe. Solar Energy, 94, 305–326.
Polo, J., Wilbert, S., Ruiz-Arias, J. A., Meyer, R., Gueymard, C., Suri, M., … (2016). Preliminary survey on site-adaptation techniques for satellite-derived and reanalysis solar radiation datasets. Solar Energy, 132, 25–37.
Espinar, B., Ramírez, L., Drews, A., Beyer, H. G., Zarzalejo, L. F., Polo, J., & Martín, L. (2009). Analysis of different comparison parameters applied to solar radiation data from satellite and German radiometric stations. Solar Energy, 83(1), 118–125.
Lorenz, E., Remund, J., Müller, S. C., Traunmüller, W., Steinmaurer, G., Pozo, D., … (2009). Benchmarking of different approaches to forecast solar irradiance. Proceedings of the 24th European Photovoltaic Solar Energy Conference, 21–25.
Jahangiri, M., Shamsabadi, A. A., Mostafaeipour, A., Rezaei, M., Yousefi, Y., … (2020). Using fuzzy MCDM technique to find the best location in Qatar for exploiting wind and solar energy to generate hydrogen and electricity. International Journal of Hydrogen Energy, 45(27), 13862–13875.