From the 1 of 4 linked papers with an AI index.
4 papers
Constructing Deployment Scenarios for Reserve Deliverability via Adaptive Robust Optimization
Guillaume Van Caelenberg, Akylas Stratigakos, Elina Spyrou
The paper proposes a two‑stage adaptive robust optimization model that generates deployment scenarios of forecast errors to improve reserve deliverability under grid congestion, us…
End-to-End Pseudo-Measurement Learning for State Estimation under Limited Observability
J. G. De la Varga, S. Pineda, A. Stratigakos +1
Distribution System State Estimation (DSSE) is becoming increasingly important with the integration of Distributed Energy Resources (DERs) and the active operation of distribution…
Learning Data-Driven Uncertainty Set Partitions for Robust and Adaptive Energy Forecasting with Missing Data
Akylas Stratigakos, Panagiotis Andrianesis
Short-term forecasting models typically assume the availability of input data (features) when they are deployed and in use. However, equipment failures, disruptions, cyberattacks,…
Predict+Optimize Problem in Renewable Energy Scheduling
Christoph Bergmeir, Frits de Nijs, Evgenii Genov +25
Predict+Optimize frameworks integrate forecasting and optimization to address real-world challenges such as renewable energy scheduling, where variability and uncertainty are criti…