From the 1 of 12 linked papers with an AI index.
12 papers
Scenario Reduction for Two-Stage Stochastic Mixed-Integer Programs
Yannick Werner, Juan Miguel Morales, Salvador Pineda +2
The paper proposes a new transportation cost function and a hybrid algorithm for reducing scenarios in two-stage stochastic mixed-integer programs, demonstrating high solution accu…
Towards time-variant scenario reduction for energy system optimization modeling under uncertainty
Yannick Werner, Juan Miguel Morales, Salvador Pineda +1
Stochastic programming has become a popular tool for supporting decision-making under uncertainty in the long-term planning of energy systems. Existing scenario reduction methods,…
Data-Boosted Optimization for AC Optimal Power Flow: Interior-Point and Spatial Branching Methods
Ignacio Repiso, Salvador Pineda, Juan Miguel Morales
The AC Optimal Power Flow (AC-OPF) problem is a non-convex, NP-hard optimization task essential for secure and economic power system operation. While interior-point methods are wid…
The Sweet Spot of Bound Tightening for Topology Optimization
Salvador Pineda, Juan Miguel Morales
Topology optimization has emerged as a powerful and increasingly relevant strategy for enhancing the flexibility and efficiency of power system operations. However, solving these p…
Scenario Reduction for the Two-Stage Stochastic Unit Commitment Problem
Yannick Werner, Juan Miguel Morales, Salvador Pineda +2
The two-stage stochastic unit commitment problem has become an important tool to support decision-making under uncertainty in power systems. Representing the uncertainty by a large…
Counterfactual optimization for fault prevention in complex wind energy systems
Emilio Carrizosa, Martina Fischetti, Roshell Haaker +1
Machine Learning models are increasingly used in businesses to detect faults and anomalies in complex systems. In this work, we take this approach a step further: beyond merely det…