Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Forecasting Day-Ahead PV Generation and Load Demand for an Individual Residential Consumer
Elias Mandefro Getie, Geert Deconinck
KU Leuven,Belgium
A comparison of machine learning algorithms for the optimization of a day-ahead photovoltaic power forecast
Katrin Schulte, Lars Engel, Lars Quakernack, Fynn Liegmann, Jens Haubrock
Bielefeld University of Applied Sciences and Arts, Germany
Forecasting vertical grid load using machine learning algorithms
Marie-Louise Kloubert
Amprion GmbH, Germany
The Impacts of the Effective Load Data Preprocessing in Long-Term Load Forecasting
Airam Perez Guillen, Jovica V. Milanović
The University of Manchester, United Kingdom
Multi-step ahead wind power forecasting based on N-BEATS model
Luis Fernando Rodrigues Agottani1, Matheus Melara Girardi2, Wendel Rafael de Souza Chaves1, Lucas de Azevedo Takara3, Leandro dos Santos Coelho3, Viviana Cocco Mariani1
1Graduate Program in Mechanical Engineering, Federal University of Parana, Brazil; 2Department of Computer Science, Pontifical Catholic University of Parana, Brazil; 3Graduate Program in Electrical Engineering, Federal University of Parana, Brazil
Ultra short term power prediction of offshore wind power based on ICEEMD-KPCA-LSTM
Lingling Huang, Zhangjie Fu, Yang Liu, Shurong Wei, Feixiang Ying
Shanghai university of electric power, China, People's Republic of
