85 citations · 116 across the 22 of their papers we have counts for
6 papers · 1 filter
Beyond the Neural Fog: Interpretable Learning for AC Optimal Power Flow
Salvador Pineda, Juan Pérez-Ruiz, Juan Miguel Morales
The AC optimal power flow (AC-OPF) problem is essential for power system operations, but its non-convex nature makes it challenging to solve. A widely used simplification is the li…
Practical Framework for Problem-Based Learning in an Introductory Circuit Analysis Course
Sebastian Martin, Salvador Pineda, Juan Perez-Ruiz +2
Introductory courses on electric circuits at undergraduate level are usually presented in quite abstract terms, with questions and problems quite far from practical problems. This…
Forecasting the Price-Response of a Pool of Buildings via Homothetic Inverse Optimization
Ricardo Fernández-Blanco, Juan Miguel Morales, Salvador Pineda
This paper focuses on the day-ahead forecasting of the aggregate power of a pool of smart buildings equipped with thermostatically-controlled loads. We first propose the modeling o…
Day-ahead Operation of an Aggregator of Electric Vehicles via Optimization under Uncertainty
Álvaro Porras, Ricardo Fernández-Blanco, Juan Miguel Morales +1
We pose the aggregator's problem as a bilevel model, where the upper level minimizes the total operation costs of the fleet of EVs, while each lower level minimizes the energy avai…
How Can Smart Buildings Be Price-Responsive?
Ricardo Fernández-Blanco, Juan Miguel Morales, Salvador Pineda
The prospective participation of smart buildings in the electricity system is strongly related to the increasing active role of demand-side resources in the electrical grid. In add…
Inverse Optimization with Kernel Regression: Application to the Power Forecasting and Bidding of a Fleet of Electric Vehicles
Ricardo Fernández-Blanco, Juan Miguel Morales, Salvador Pineda +1
This paper considers an aggregator of Electric Vehicles (EVs) who aims to learn the aggregate power of his/her fleet while also participating in the electricity market. The propose…