8 papers
Unlocking the Informational Value of Marginal Costs for Exact Time Series Aggregation in Generation Expansion Planning
Luca Santosuosso, Sonja Wogrin
This paper addresses the generation expansion planning (GEP) problem, formulated as a mixed-integer linear programming model with intertemporal storage constraints. Being generally…
Distributed Stochastic Model Predictive Control with Temporal Aggregation for the Joint Dispatch of Cascaded Hydropower and Renewables
Luca Santosuosso, Sonja Wogrin
This paper addresses the real-time energy dispatch of a hybrid system comprising cascaded run-of-the-river hydropower plants, wind, and solar photovoltaic units, operated under unc…
Surrogate Modeling of Interconnector Flows: A Machine Learning Alternative to Full-Scale Power System Simulations with Application to Cross-Border Electricity Exchange
Robert Gaugl, Eloy Insunza, José Portela +1
Cross-border electricity exchanges are crucial for operating and planning highly renewable power systems. Many studies reduce spatial granularity to keep the models tractable and p…
Machine Learning for Exact Time Series Aggregation in Generation Expansion Planning with Energy Storage
Jakub Rybka, Luca Santosuosso, Thomas Klatzer +1
This paper investigates a generation expansion planning (GEP) problem encompassing renewable, thermal, and storage technologies while simultaneously optimizing market participation…
Stochastic Virtual Power Plant Dispatch via Temporally Aggregated Distributed Predictive Control with Performance Guarantees
Luca Santosuosso, Fei Teng, Sonja Wogrin
This paper addresses the energy dispatch of a virtual power plant comprising renewable generation, energy storage, and thermal units under uncertainty in renewable output, energy p…
Towards Exact Temporal Aggregation of Time-Coupled Energy Storage Models via Active Constraint Set Identification and Machine Learning
Thomas Klatzer, David Cardona-Vasquez, Luca Santosuosso +1
Time series aggregation (TSA) aims to construct temporally aggregated optimization models that accurately represent the output space of their full-scale counterparts while using a…