Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach
| dc.contributor.author | Catalao, J. P. S. | |
| dc.contributor.author | Pousinho, H. M. I. | |
| dc.contributor.author | Mendes, V. M. F. | |
| dc.date.accessioned | 2017-07-13T15:11:48Z | |
| dc.date.available | 2017-07-13T15:11:48Z | |
| dc.date.issued | 2012 | |
| dc.date.updated | 2017-05-24T05:18:27Z | |
| dc.description.abstract | In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of one week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. © 2011 Elsevier Ltd. All rights reserved. | por |
| dc.identifier | 0142-0615 | en_US |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | nd | |
| dc.identifier.citation | Catalao, J. P. S.; Pousinho, H. M. I.; Mendes, V. M. F.Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach, INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 39, 1, 29-35, 2012. | por |
| dc.identifier.uri | http://hdl.handle.net/10174/21178 | |
| dc.language.iso | por | por |
| dc.rights | openAccess | por |
| dc.subject | Electricity market | por |
| dc.subject | Fuzzy logic | por |
| dc.subject | Neural networks | por |
| dc.subject | Price forecasting | por |
| dc.subject | Swarm optimization | por |
| dc.title | Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach | por |
| dc.type | article | por |