Listar por autor "Morales-Gonzalez, Juan Miguel"
Mostrando ítems 1-20 de 23
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A bilevel framework for decision-making under uncertainty with contextual information
Morales-Gonzalez, Juan Miguel
; Pineda-Morente, Salvador; Muñoz Díaz, Miguel Ángel (Elsevier, 2021-11-22)
In this paper, we propose a novel approach for data-driven decision-making under uncertainty in the presence of contextual information. Given a finite collection of observations of the uncertain parameters and potential ... -
A high dimensional functional time series approach to evolution outlier detection for grouped smart meters
Elias Fernandez, Antonio; Morales-Gonzalez, Juan Miguel; Pineda-Morente, Salvador (Taylor and Francis, 2022-01-01)
Smart metering infrastructures collect data almost continuously in the form of fine-grained long time series. These massive data series often have common daily patterns that are repeated between similar days or seasons and ... -
An exact dynamic programming approach to segmented isotonic regression
Bucarey, Víctor; Labbé, Martine; Morales-Gonzalez, Juan Miguel; Pineda-Morente, Salvador (Elsevier, 2021)
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 fitted curve is also constrained on the ... -
Chronological time-period clustering for optimal capacity expansion planning
Morales-Gonzalez, Juan Miguel; Pineda-Morente, Salvador (2018-07-12)
To reduce the computational burden of capacity expansion models, power system operations are commonly accounted for in these models using representative time periods of the planning horizon such as hours, days or weeks. ... -
Chronological Time-Period Clustering for Optimal Capacity Expansion Planning
Morales-Gonzalez, Juan Miguel; Pineda-Morente, Salvador (2018-07-06)
To reduce the computational burden of capacity expansion models, power system operations are commonly accounted for in these models using representative time periods of the planning horizon such as hours, days or weeks. ... -
Cost-driven screening of network constraints for the unit commitment problem
Porras, Álvaro; Pineda-Morente, Salvador; Morales-Gonzalez, Juan Miguel; Jimenez-Cordero, Maria Asuncion (The Institute of Electrical and Electronics Engineers (IEEE), 2022-03-16)
In an attempt to speed up the solution of the unit commitment (UC) problem, both machine-learning and optimization-based methods have been proposed to lighten the full UC formulation by removing as many superfluous line-flow ... -
Data-driven distributionally robust optimization with Wasserstein metric, moment conditions and robust constraints
Esteban-Pérez, Adrián; Morales-Gonzalez, Juan Miguel (2018-07-12)
We consider optimization problems where the information on the uncertain parameters reduces to a finite data sample. Using the Wasserstein metric, a ball in the space of probability distributions centered at the empirical ... -
Distributionally Robust Optimal Power Flow with Contextual Information
Esteban-Pérez, Adrián; Morales-Gonzalez, Juan Miguel (Elsevier B. V., 2022-10)
In this paper, we develop a distributionally robust chance-constrained formulation of the Optimal Power Flow problem (OPF) whereby the system operator can leverage contextual information. For this purpose, we exploit an ... -
Distributionally robust stochastic programs with side information based on trimmings
Esteban-Pérez, Adrián; Morales-Gonzalez, Juan Miguel (Springer, 2021-11)
We consider stochastic programs conditional on some covariate information, where the only knowledge of the possible relationship between the uncertain parameters and the covariates is reduced to a finite data sample of ... -
Electricity Cost-Sharing in Energy Communities Under Dynamic Pricing and Uncertainty
Gržanić, Mirna; Morales-Gonzalez, Juan Miguel; Pineda-Morente, Salvador; Capuder, Tomislav (IEEE, 2021-02-15)
Most of the prosumers nowadays are constrained to trade only with the supplier under a flat tariff or dynamic time-of-use price signals. This paper models and discusses the cost-saving benefits of flexible prosumers as ... -
Feature-driven improvement of renewable energy forecasting and trading
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 enhance both the quality of renewable energy ... -
Fostering the cooperative learning of mathematics in engineering schools through the "Teacher-Apprentice" group dynamics
Morales-Gonzalez, Juan Miguel; Olea, Benjamín; Atencia-Ruiz, Miguel Alejandro; Madrid-Labrador, Nicolas Miguel (2019-05-30)
In this presentation, we report on the experience gained and the results obtained from an educational innovation project that has sought to introduce cooperative learning into the mathematics subjects of the first year of ... -
Inverse optimization with kernel regression: Application to the power forecasting and bidding of a fleet of electric vehicles
Fernández-Blanco, Ricardo; Morales-Gonzalez, Juan Miguel; Pineda-Morente, Salvador; Porras, Álvaro (Elsevier, 2021-10)
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 proposed approach is based on a data-driven inverse ... -
Is learning for the unit commitment problem a low-hanging fruit?
Pineda-Morente, Salvador; Morales-Gonzalez, Juan Miguel (Elsevier, 2022-02-16)
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 in its wake, it is sometimes difficult to ... -
Is learning for the unit commitment problem a low-hanging fruit?
Pineda-Morente, Salvador; Morales-Gonzalez, Juan Miguel (Elsevier, 2022-06)
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 in its wake, it is sometimes difficult ... -
Learning the price response of active distribution networks for TSO-DSO coordination
Pineda-Morente, Salvador; Morales-Gonzalez, Juan Miguel; Dvorkin, Yury (IEEE, 2021)
The increase in distributed energy resources and flexible electricity consumers has turned TSO-DSO coordination strategies into a challenging problem. Existing decomposition/decentralized methods apply divide-and-conquer ... -
Partition-based distributionally robust optimization via optimal transport with order cone constraints
Esteban-Pérez, Adrián; Morales-Gonzalez, Juan Miguel (Springer, 2021)
In this paper we wish to tackle stochastic programs affected by ambiguity about the probability law that governs their uncertain parameters. Using optimal transport theory, we construct an ambiguity set that exploits the ... -
Predicting the electricity demand response via data-driven inverse optimization
Morales-Gonzalez, Juan Miguel; Saez-Gallego, Javier (2018-07-06)
A method to predict the aggregate demand of a cluster of price-responsive consumers of electricity is discussed in this presentation. The price-response of the aggregation is modeled by an optimization problem whose ... -
Prescribing net demand for two-stage electricity generation scheduling
Morales-Gonzalez, Juan Miguel; Muñoz, Miguel Ángel; Pineda-Morente, Salvador (Elsevier, 2023)
We consider a two-stage generation scheduling problem comprising a forward dispatch and a real-time re-dispatch. The former must be conducted facing an uncertain net demand that includes non-dispatchable electricity ... -
Prescriptive Analytics in Electricity Markets
(UMA Editorial, 2022-11-03)Decision making is critical for any business to survive in a market environment. Examples of decision making tasks are inventory management, resource allocation or portfolio selection. Optimization, understood as the ...