Alejandro Pena-bello
Senior Academic Associate
Sion, Wallis, Switzerland
Summary
👤
Senior🎓
Top SchoolAlejandro Pena-Bello is an electronic engineer and researcher with nine years of experience specializing in renewable energy, energy storage, and waste-to-energy technologies. He holds a PhD from the University of Geneva on PV adoption and low-carbon technologies and is a postdoctoral researcher at EPFL while serving as Senior Academic Associate at HES-SO Valais-Wallis. Alejandro blends technical modelling, techno-economic analysis, and environmental assessment to evaluate storage roles and prosumer–grid trade-offs, work that earned him publications including in Nature Energy. He has international training across Colombia, France, and Switzerland and contributes to community energy research initiatives and editorial processes, reflecting a rare mix of hands-on system modelling and policy-relevant insight. Notably, his background in both electronics and economics enables him to translate complex engineering results into actionable feasibility studies and decision-ready recommendations.
9 years of coding experience
5 years of employment as a software developer
Master's degree, Economics, Master's degree, Economics at Universidad Nacional de ColombiaPhD, Energy Storage, PhD, Energy Storage at University of GenevaDUT, Informatics, DUT, Informatics at Université Pierre Mendès-France (Grenoble II)Doctor of Philosophy - PhD Exchange student, Energy Management and Systems Technology/Technician, Doctor of Philosophy - PhD Exchange student, Energy Management and Systems Technology/Technician at EPFL (École polytechnique fédérale de Lausanne)
French, English, Italian, Spanish, German
Github Skills (15)
component-based10
battery10
consumption9
power-systems9
temporal9
optimization9
boolean9
electricity9
perfect9
optimizer9
forecast9
factor9
simulations9
energy9
solar9
Programming languages (1)
Github contributions (5)
alefunxo/Basopra
Dec 2018 - Mar 2022
BASOPRA - BAttery Schedule OPtimizer for Residential Applications. Daily battery schedule optimizer (i.e. 24 h optimization framework), assuming perfect day-ahead forecast of the electricity demand load and solar PV generation in order to determine the maximum economic potential regardless of the forecast strategy used. Include the use of different applications which residential batteries can perform from a consumer perspective. Applications such as avoidance of PV curtailment, demand load-shifting and demand peak shaving are considered along with the base application, PV self-consumption. Different battery technologies and sizes can be analyzed as well as different tariff structures. Aging is treated as an exogenous parameter, calculated on daily basis and is not subject of optimization. Data with 15-minute temporal resolution are used for simulations. The model objective function have two components, the energy-based and the power-based component, as the tariff structure depends on the applications considered, a boolean parameter activate the power-based factor of the bill when is necessary.
Contributions:47 commits, 1 PR, 37 pushes in 3 years 3 months
exogenousbatterytariffbatteriesday
alefunxo/Solar_communities
Nov 2018 - Nov 2020
Contributions:20 commits, 18 pushes, 1 branch in 2 years
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