A novel hybrid algorithm for electricity price and load forecasting in smart grids with demand-side management
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- 作者：A. Ghasemia ; ghasemi.agm@gmail.com" class="auth_mail" title="E-mail the corresponding author ; H. Shayeghia ; b ; hshayeghi@gmail.com" class="auth_mail" title="E-mail the corresponding author ; M. Moradzadehc ; M. Nooshyara
- 关键词：DSM ; Demand-Side Management ; FWPT ; Flexible Wavelet Packet Transform ; CMI ; Conditional Mutual Information ; MIMO ; Multi-Input Multi-Output ; NLSSVM ; Nonlinear Least Square Support Vector Machine ; ARIMA ; Autoregressive Integrated Moving Average ; ABC ; Artificial Bee Colony ; GARCH ; generalized autoregressive conditional heteroskedastic ; DR ; dynamic regression ; TF ; transfer function ; MI ; mutual information ; WT ; wavelet transform ; LSSVM ; Least Square Support Vector Machine ; FNN ; fuzzy neural network ; R
- 刊名：Applied Energy
- 出版年：2016
- 出版时间：1 September 2016
- 年：2016
- 卷：177
- 期：Complete
- 页码：40-59
- 全文大小：3487 K
文摘
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Proposes a novel hybrid algorithm for price/load forecasting.
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Proposes a new conditional feature selection with inherent uncertainties of input data.
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Propose a new nonlinear LSSVM technique for learning and wavelet packet for signal decomposing.
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Used three real markets and models demand side management on price/load forecasting.
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Proposed a new modification for standard artificial bee colony optimization.