5 papers · 1 filter
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…
A Scenario-Spatial Decomposition Approach With a Performance Guarantee for the Combined Bidding of Cascaded Hydropower and Renewables
Luca Santosuosso, Simon Camal, Arthur Lett +3
This study develops a scalable co-optimization strategy for the joint bidding of cascaded hydropower, wind, and solar energy units, treated as a unified entity in the day-ahead mar…
What Are We Clustering For? Establishing Performance Guarantees for Time Series Aggregation in Generation Expansion Planning
Luca Santosuosso, Bettina Klinz, Sonja Wogrin
Generation expansion planning (GEP) is a prominent example of capacity expansion problems in operations research. Being generally NP-hard, GEP optimization models can become intrac…
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…
Optimal Virtual Power Plant Investment Planning via Time Series Aggregation with Bounded Error
Luca Santosuosso, Sonja Wogrin
This study addresses the investment planning problem of a virtual power plant (VPP), formulated as a mixed-integer linear programming (MILP) model. As the number of binary variable…