4 papers · 1 filter
GUIDE-VAE: Advancing Data Generation with User Information and Pattern Dictionaries
Kutay Bölat, Simon Tindemans
Generative modelling of multi-user datasets has become prominent in science and engineering. Generating a data point for a given user requires employing user information, and conve…
MLMC-based Resource Adequacy Assessment with Active Learning Trained Surrogate Models
Ruiqi Zhang, Simon H. Tindemans
Multilevel Monte Carlo (MLMC) is a flexible and effective variance reduction technique for accelerating reliability assessments of complex power system. Recently, data-driven surro…
One Model to Forecast Them All and in Entity Distributions Bind Them
Kutay Bölat, Simon Tindemans
Probabilistic forecasting in power systems often involves multi-entity datasets like households, feeders, and wind turbines, where generating reliable entity-specific forecasts pre…
Clustering Rooftop PV Systems via Probabilistic Embeddings
Kutay Bölat, Tarek Alskaif, Peter Palensky +1
As the number of rooftop photovoltaic (PV) installations increases, aggregators and system operators are required to monitor and analyze these systems, raising the challenge of int…