Biography:
Luis Montero is a researcher and energy models consultant at the Institute for Research in Technology (IIT). Besides, he is a lecturer at the ICAI School of Engineering. Luis obtained a Ph.D. in Power Systems from the Comillas Pontifical University, Madrid, Spain, in 2024. Previously, he received a M.Sc. degree in Chemical Engineering from the University of Salamanca, Salamanca, Spain, in 2017 and completed a B.Sc. degree in Chemical Engineering from the University of Granada, Granada, Spain, in 2015. Luis has also worked as a freelance project engineer and energy markets analyst at Enagas. Regarding research, Luis collaborated with the Nanostructured Materials Research Group of the University of Salamanca during the 2016-2017 academic year, and he has been a member of the Energy Systems Models Area (SADSE) at the IIT since 2018.
Areas of interest:
Operation, regulation and planning of power and natural gas systems. Modeling and optimization techniques, artifical intelligence and forecasting techniques.
Experience:
Project engineer, energy markets analyst, researcher, energy models consultant.
Skills:
Optimization techniques and Data analysis. Representation and modeling of power and natural gas systems. Programming in GAMS, Matlab and VBA.
Current research interests:
Models to manage the hydrothermal generation in real-size multi-area electricity markets. Enhance the operational detail when power and natural gas systems are represented in a medium-term horizon. Application of machine learning techniques to the management of assets belonged by market players whose decisions are characterized by a competitive behavior.
L. Montero, G. Morales-España, A. Bello, J. Reneses, "Tight and compact MILP formulation for a high-resolution of start-up costs in the medium-term unit commitment", Sustainable Energy, Grids and Networks, Vol. 44, pp. 101935, December 2025. [Online: August 2025] doi: 10.1016/j.segan.2025.101935
JCR-JIF: 5,700 Q1 (2025); - SJR: 1,239 Q1 (2025); 
L. Montero, A. Bello, J. Reneses, "Analyzing the computational performance of balance constraints in the medium-term unit commitment problem: tightness, compactness, and arduousness", International Journal of Electrical Power & Energy Systems, Vol. 160, pp. 110080, September 2024. [Online: June 2024] doi: 10.1016/j.ijepes.2024.110080
JCR-JIF: 5,000 Q1 (2024); 5,300 Q1 (2025) - SJR: 1,714 Q1 (2024); 1,482 Q1 (2025) L. Montero, A. Bello, J. Reneses, M. Rodríguez, "A computationally efficient formulation to accurately represent start-up costs in the medium-term unit commitment problem", IEEE Transactions on Power Systems, Vol. 38, nº. 6, pp. 5623 - 5634, November 2023. [Online: December 2022] doi: 10.1109/TPWRS.2022.3232029
JCR-JIF: 6,500 Q1 (2023); 8,700 Q1 (2025) - SJR: 3,827 Q1 (2023); 4,217 Q1 (2025) L. Montero, A. Bello, J. Reneses, "A review on the unit commitment problem: approaches, techniques, and resolution methods", Energies, Vol. 15, nº. 4, pp. 1296, February 2022. [Online: February 2022] doi: 10.3390/en15041296
JCR-JIF: 3,200 Q3 (2022); 3,900 Q3 (2025) - SJR: 0,632 Q1 (2022); 0,748 Q1 (2025) L. Montero, A. Bello, J. Reneses, "A new methodology to obtain a feasible thermal operation in power systems in a medium-term horizon", Energies, Vol. 13, nº. 12, pp. 3056, June 2020. [Online: June 2020] doi: 10.3390/en13123056
JCR-JIF: 3,004 Q3 (2020); 3,900 Q3 (2025) - SJR: 0,598 Q2 (2020); 0,748 Q1 (2025) 
