Ensemble Prediction Model with Expert Selection for Electricity Price Forecasting
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- Ying-Yi Hong & Ching-Ping Wu, 2012. "Day-Ahead Electricity Price Forecasting Using a Hybrid Principal Component Analysis Network," Energies, MDPI, vol. 5(11), pages 1-15, November.
- Antonio Bracale & Pasquale De Falco, 2015. "An Advanced Bayesian Method for Short-Term Probabilistic Forecasting of the Generation of Wind Power," Energies, MDPI, vol. 8(9), pages 1-22, September.
- Francisco Martínez-Álvarez & Alicia Troncoso & Gualberto Asencio-Cortés & José C. Riquelme, 2015. "A Survey on Data Mining Techniques Applied to Electricity-Related Time Series Forecasting," Energies, MDPI, vol. 8(11), pages 1-32, November.
- Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2008. "Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm," Energy Economics, Elsevier, vol. 30(5), pages 2623-2635, September.
- Sergey Voronin & Jarmo Partanen, 2013. "Price Forecasting in the Day-Ahead Energy Market by an Iterative Method with Separate Normal Price and Price Spike Frameworks," Energies, MDPI, vol. 6(11), pages 1-24, November.
- He, Kaijian & Yu, Lean & Lai, Kin Keung, 2012. "Crude oil price analysis and forecasting using wavelet decomposed ensemble model," Energy, Elsevier, vol. 46(1), pages 564-574.
- Weron, Rafał, 2014.
"Electricity price forecasting: A review of the state-of-the-art with a look into the future,"
International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
- Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
- Jurado, Sergio & Nebot, Àngela & Mugica, Fransisco & Avellana, Narcís, 2015. "Hybrid methodologies for electricity load forecasting: Entropy-based feature selection with machine learning and soft computing techniques," Energy, Elsevier, vol. 86(C), pages 276-291.
- Tan, Zhongfu & Zhang, Jinliang & Wang, Jianhui & Xu, Jun, 2010. "Day-ahead electricity price forecasting using wavelet transform combined with ARIMA and GARCH models," Applied Energy, Elsevier, vol. 87(11), pages 3606-3610, November.
- Li, Song & Goel, Lalit & Wang, Peng, 2016. "An ensemble approach for short-term load forecasting by extreme learning machine," Applied Energy, Elsevier, vol. 170(C), pages 22-29.
- George P. Papaioannou & Christos Dikaiakos & Anargyros Dramountanis & Panagiotis G. Papaioannou, 2016. "Analysis and Modeling for Short- to Medium-Term Load Forecasting Using a Hybrid Manifold Learning Principal Component Model and Comparison with Classical Statistical Models (SARIMAX, Exponential Smoot," Energies, MDPI, vol. 9(8), pages 1-40, August.
- Ferruzzi, Gabriella & Cervone, Guido & Delle Monache, Luca & Graditi, Giorgio & Jacobone, Francesca, 2016. "Optimal bidding in a Day-Ahead energy market for Micro Grid under uncertainty in renewable energy production," Energy, Elsevier, vol. 106(C), pages 194-202.
- Bangzhu Zhu, 2012. "A Novel Multiscale Ensemble Carbon Price Prediction Model Integrating Empirical Mode Decomposition, Genetic Algorithm and Artificial Neural Network," Energies, MDPI, vol. 5(2), pages 1-16, February.
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- Umut Ugurlu & Oktay Tas & Aycan Kaya & Ilkay Oksuz, 2018. "The Financial Effect of the Electricity Price Forecasts’ Inaccuracy on a Hydro-Based Generation Company," Energies, MDPI, vol. 11(8), pages 1-19, August.
- Ciaran O'Connor & Joseph Collins & Steven Prestwich & Andrea Visentin, 2024. "Electricity Price Forecasting in the Irish Balancing Market," Papers 2402.06714, arXiv.org.
- Zoran Gligorić & Svetlana Štrbac Savić & Aleksandra Grujić & Milanka Negovanović & Omer Musić, 2018. "Short-Term Electricity Price Forecasting Model Using Interval-Valued Autoregressive Process," Energies, MDPI, vol. 11(7), pages 1-17, July.
- Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2017. "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Neural network models," HSC Research Reports HSC/17/03, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
- Grzegorz Marcjasz & Tomasz Serafin & Rafał Weron, 2018.
"Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting,"
Energies, MDPI, vol. 11(9), pages 1-20, September.
- Grzegorz Marcjasz & Tomasz Serafin & Rafal Weron, 2018. "Selection of calibration windows for day-ahead electricity price forecasting," HSC Research Reports HSC/18/06, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
- Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał, 2019. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1520-1532.
- Chai, Shanglei & Li, Qiang & Abedin, Mohammad Zoynul & Lucey, Brian M., 2024. "Forecasting electricity prices from the state-of-the-art modeling technology and the price determinant perspectives," Research in International Business and Finance, Elsevier, vol. 67(PA).
- Emmanuel Kipchumba Korir & Jane Aduda & Thomas Mageto, 2020. "Forecasting Electricity Prices Using Ensemble Kalman Filter," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(1), pages 1-2.
- Lehna, Malte & Scheller, Fabian & Herwartz, Helmut, 2022. "Forecasting day-ahead electricity prices: A comparison of time series and neural network models taking external regressors into account," Energy Economics, Elsevier, vol. 106(C).
- Umut Ugurlu & Ilkay Oksuz & Oktay Tas, 2018. "Electricity Price Forecasting Using Recurrent Neural Networks," Energies, MDPI, vol. 11(5), pages 1-23, May.
- Ethem Çanakoğlu & Esra Adıyeke, 2020. "Comparison of Electricity Spot Price Modelling and Risk Management Applications," Energies, MDPI, vol. 13(18), pages 1-22, September.
- Javier Contreras, 2017. "Forecasting Models of Electricity Prices," Energies, MDPI, vol. 10(2), pages 1-2, January.
- Ping-Huan Kuo & Chiou-Jye Huang, 2018. "An Electricity Price Forecasting Model by Hybrid Structured Deep Neural Networks," Sustainability, MDPI, vol. 10(4), pages 1-17, April.
- Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
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Keywords
electricity price forecasting; ensemble model; expert selection;All these keywords.
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