Jose Angel Velasco

I would like to contribute to the smart operation of renewable-based distributed resources and load demand in smart grids using machine learning and mathematical programming with cutting-edge technologies and tools

I am a Senior Data Scientist, especialized in optimization for decision-making and predictive modelling with a Ph.D. in Electrical, Electronics and Automation Engineering. My research interest include the optimal operation of LV smart grids under uncertianty using machine learning models and optimizaiton models with presence of distributed resources such as photovoltaics, Electric Vehicles and energy storage. Here you can find my updated resume

Education

Ph.D. in Electrical Engineering, Electronics and Automation

Universidad Carlos III de Madrid (UC3M)

Nov. 2017 - June. 2022

M.Sc. in Industrial Engineering

Universidad Carlos III de Madrid (UC3M)

Sept. 2014 - Sept. 2016

B.Sc. in Electrical Engineering

Universidad de Castila-La Mancha (UCLM)

Sept. 2010 - Sept. 2014

Internships

UCD Energy Institute (Dublin, Ireland)

Supervised by Andrew Keane and Alireza Soroudi

2018

Experience

Capgemini Engineering - Hybrid Intelligence

Senior Data Scientist

Energy Markets, Optimization of Logistics, Supply Chain and transport systems

April 2021 - present

Indra - Digital Labs

Data Scientist

Predictive modelling, simulation and optimization of multi-modal transport systems: bus, rail, airports, subway, road traffic (Transports market); sensors systems data fusion, synchronization and estate estimation (Defense market, FCAS project)

Sept. 2019 - April 2021

Universidad Carlos III de Madrid - Electrical Engineering Department

Researcher/ PhD Candidate/ Lab teacher

Smart Grids research: network modelling, uncertainty modelling, power losses estimation, optimal power flow, customers segmentation, feeders clustering, Photovoltaic hosting capacity, electric vehicle integration, battery energy storage applications, demand response with flexibility supply

Oct. 2015 - Sept 2019

Publications

Deep Learning Loss Model for Large-Scale Low Voltage Smart Grids

Jose Angel Velasco, Hortensia Amaris and Monica Alonso International Journal of Electrical Power and Energy Systems

Optimising Load Flexibility for the Day Ahead in Distribution Networks with Photovoltaics

Jose Angel Velasco, Valentin Rigoni, Alireza Soroudi, Andrew Keane and Hortensia Amarís 13th IEEE PES PowerTech 2019, Milano (Italy)

Energy Losses Estimation Tool for Low Voltage Smart Grids

Jose Angel Velasco, Hortensia Amaris and Monica Alonso 25th International Conference & Exhibition on Electricity Distribution (CIRED) 2019, Madrid (Spain)

Stochastic Technical Losses Analysis of Smart Grids Under Uncertain Demand

Jose Angel Velasco, Hortensia Amaris and Monica Alonso 53rd International Universities Power Engineering Conference (UPEC) 2018, Glasgow (Scotland)

Energy losses estimation in Low Voltage Smart Grids by using Loss Maps

Jose Angel Velasco, Hortensia Amaris and Monica Alonso International Conference on Energy, Environment and Economics (ICEEE) 2018, Edinburgh (Scotland)

Theses

Power losses Estimation in Low-Voltage Smart Grids

Jose Angel Velasco Ph.D. Thesis (June, 2022).

Pérdidas de energía en redes de distribución en Baja Tensión – Smart Grids

Jose Angel Velasco TFM (Sept, 2016).

Eficiencia Energética en La Edificación: Análisis energético y propuesto de mejoras para la edificio energética de un edificio residencial de 34 viviendas

Jose Angel Velasco TFG (Sept, 2014).

Software

Load Demand Estimation for Non-Telemeterd Customers

Markov-chain based High-Resolution Intra-hour Load demand profiles for Non-Metered Customers(contact for details)

Flexibilty Scheduling Robust Optimizer

Robust Unbalanced Optimal power flow for flexibility scheduling in Smart Grids< (contact for details)/p>

Power Losses Estimation in Large Scale Areas

Deep-learning based Power Losses Estimation in Large-Scale Distribution Areas< (contact for details)/p>

Contact

joseangel.velasco@yahoo.es

+34 618443816