13 papers
Is learning for the unit commitment problem a low-hanging fruit?
S. Pineda, J. M. Morales
The blast wave of machine learning and artificial intelligence has also reached the power systems community, and amid the frenzy of methods and black-box tools that have been left…
Learning the price response of active distribution networks for TSO-DSO coordination
Juan Miguel Morales, Salvador Pineda, Yury Dvorkin
The increase in distributed energy resources and flexible electricity consumers has turned TSO-DSO coordination strategies into a challenging problem. Existing decomposition/decent…
An exact dynamic programming approach to segmented isotonic regression
Víctor Bucarey, Martine Labbé, Juan M. Morales +1
This paper proposes a polynomial-time algorithm to construct the monotone stepwise curve that minimizes the sum of squared errors with respect to a given cloud of data points. The…
A novel embedded min-max approach for feature selection in nonlinear support vector machine classification
Asunción Jiménez-Cordero, Juan Miguel Morales, Salvador Pineda
In recent years, feature selection has become a challenging problem in several machine learning fields, such as classification problems. Support Vector Machine (SVM) is a well-know…
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…
An Efficient Robust Approach to the Day-ahead Operation of an Aggregator of Electric Vehicles
Álvaro Porras, Ricardo Fernández-Blanco, Juan M. Morales +1
The growing use of electric vehicles (EVs) may hinder their integration into the electricity system as well as their efficient operation due to the intrinsic stochasticity associat…