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  • 标题:Electrici models
  • 本地全文:下载
  • 作者:Fazil Gökgöz ; Fahrettin Filiz
  • 期刊名称:Investment Management & Financial Innovations
  • 印刷版ISSN:1810-4967
  • 电子版ISSN:1812-9358
  • 出版年度:2016
  • 卷号:13
  • 期号:3
  • 页码:150-158
  • DOI:10.21511/imfi.13(3-1).2016.01
  • 语种:English
  • 出版社:LLC “Consulting Publishing Company “Business Perspectives”
  • 摘要:The electricity market has experienced significant changes tow ards deregulation with the aim of improving economic efficiency. The electricity pricing is a major consideration for consumers and generation companies in deregulated electric markets, so that offering the right price for electricity has become more important. Various methods and ideas have been tried for electricity price forecasting. Artificial neural networks have received much attention with its nonlinear property and many papers have reported successful experiments with them. This paper introduces artificial neural network models for day-ahead electricity market in Turkey. Using gradient descent, gradient descent with momentum, Broydan, Fletcher, Goldfarb and Shanno (BFGS) and Levenberg-Marquardt algorithm with different number of neuron and transfer functions, 400 different models are created. Performances of different models are compared according to their Mean Absolute Percentage (MAPE) values;the most successful models MAPE value is observed as 9.76%.
  • 关键词:electricity price forecasting;neural networks;day-ahead electricity market;Turkey.
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