5 papers
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…
The Living Forecast: Evolving Day-Ahead Predictions into Intraday Reality
Kutay Bölat, Peter Palensky, Simon Tindemans
Accurate intraday forecasts are essential for power system operations, complementing day-ahead forecasts that gradually lose relevance as new information becomes available. This pa…
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…
Data Enrichment Opportunities for Distribution Grid Cable Networks using Variational Autoencoders
Konrad Sundsgaard, Kutay Bölat, Guangya Yang
Electricity distribution cable networks suffer from incomplete and unbalanced data, hindering the effectiveness of machine learning models for predictive maintenance and reliabilit…