8 papers · 1 filter
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…
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…
Feature-driven Improvement of Renewable Energy Forecasting and Trading
Miguel Á. Muñoz, Juan M. Morales, Salvador Pineda
Inspired from recent insights into the common ground of machine learning, optimization and decision-making, this paper proposes an easy-to-implement, but effective procedure to enh…
Data-Driven Screening of Network Constraints for Unit Commitment
Salvador Pineda, Juan Miguel Morales, Asunción Jiménez-Cordero
The transmission-constrained unit commitment (TC-UC) problem is one of the most relevant problems solved by independent system operators for the daily operation of power systems. G…