Publicação
Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach
| Resumo: | In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 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. (C) 2012 Elsevier Ltd. All rights reserved. |
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| Autores principais: | Pousinho, Hugo Miguel Inácio |
| Outros Autores: | Mendes, Victor; Catalão, João Paulo da Silva |
| Assunto: | Electricity Market Price Forecasting Swarm Optimization Neural Networks Fuzzy Logic Neural-Network ARIMA Models System |
| Ano: | 2012 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Politécnica de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Científico da Universidade Politécnica de Lisboa |
| Resumo: | In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 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. (C) 2012 Elsevier Ltd. All rights reserved. |
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