Abstract
As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re-search of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset. The conferred results show that the prediction errors can be decreased, while the computation time is reduced.
Original language | English |
---|---|
Title of host publication | 11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012 (PSAM11 ESREL 2012) |
Volume | 2 |
Publisher | Curran Associates |
Publication date | 2012 |
Pages | 1505-1514 |
ISBN (Print) | 978-1-62276-436-5 |
Publication status | Published - 2012 |
Event | 11th International Probabilistic Safety Assessment and Management Conference and The Annual European Safety and Reliability Conference 2012 - Scandic Marina Congress Center, Helsinki, Finland Duration: 25 Jun 2012 → 29 Jun 2012 |
Conference
Conference | 11th International Probabilistic Safety Assessment and Management Conference and The Annual European Safety and Reliability Conference 2012 |
---|---|
Location | Scandic Marina Congress Center |
Country/Territory | Finland |
City | Helsinki |
Period | 25/06/2012 → 29/06/2012 |
Keywords
- Forecasting
- Neural networks
- Safety engineering
- Wind power