Ultra-short-term wind power forecasting based on personalized robust federated learning with spatial collaboration
Author
Abstract
Suggested Citation
DOI: 10.1016/j.energy.2023.129847
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Liu, Yixing & Liu, Bo & Guo, Xiaoyu & Xu, Yiqiao & Ding, Zhengtao, 2023. "Household profile identification for retailers based on personalized federated learning," Energy, Elsevier, vol. 275(C).
- Dai, Xiaoran & Liu, Guo-Ping & Hu, Wenshan, 2023. "An online-learning-enabled self-attention-based model for ultra-short-term wind power forecasting," Energy, Elsevier, vol. 272(C).
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Hu, Shuai & Xiang, Yue & Zhang, Hongcai & Xie, Shanyi & Li, Jianhua & Gu, Chenghong & Sun, Wei & Liu, Junyong, 2021. "Hybrid forecasting method for wind power integrating spatial correlation and corrected numerical weather prediction," Applied Energy, Elsevier, vol. 293(C).
- Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
- Gonçalves, Carla & Bessa, Ricardo J. & Pinson, Pierre, 2021. "A critical overview of privacy-preserving approaches for collaborative forecasting," International Journal of Forecasting, Elsevier, vol. 37(1), pages 322-342.
- Li, Yang & Wang, Ruinong & Li, Yuanzheng & Zhang, Meng & Long, Chao, 2023. "Wind power forecasting considering data privacy protection: A federated deep reinforcement learning approach," Applied Energy, Elsevier, vol. 329(C).
- Wang, Lei & He, Yigang, 2022. "M2STAN: Multi-modal multi-task spatiotemporal attention network for multi-location ultra-short-term wind power multi-step predictions," Applied Energy, Elsevier, vol. 324(C).
- Wang, Yun & Zou, Runmin & Liu, Fang & Zhang, Lingjun & Liu, Qianyi, 2021. "A review of wind speed and wind power forecasting with deep neural networks," Applied Energy, Elsevier, vol. 304(C).
- Sun, Shaolong & Du, Zongjuan & Jin, Kun & Li, Hongtao & Wang, Shouyang, 2023. "Spatiotemporal wind power forecasting approach based on multi-factor extraction method and an indirect strategy," Applied Energy, Elsevier, vol. 350(C).
- Amir Beck & Shoham Sabach, 2015. "Weiszfeld’s Method: Old and New Results," Journal of Optimization Theory and Applications, Springer, vol. 164(1), pages 1-40, January.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Wang, Xiaodi & Hao, Yan & Yang, Wendong, 2024. "Novel wind power ensemble forecasting system based on mixed-frequency modeling and interpretable base model selection strategy," Energy, Elsevier, vol. 297(C).
- Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020.
"Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss,"
Journal of International Money and Finance, Elsevier, vol. 104(C).
- Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2019. "Forecasting Realized Oil-Price Volatility: The Role of Financial Stress and Asymmetric Loss," Working Papers 201903, University of Pretoria, Department of Economics.
- Dal Bianco, Marcos & Camacho, Maximo & Perez Quiros, Gabriel, 2012.
"Short-run forecasting of the euro-dollar exchange rate with economic fundamentals,"
Journal of International Money and Finance, Elsevier, vol. 31(2), pages 377-396.
- Marcos dal Bianco & Maximo Camacho & Gabriel Perez-Quiros, 2012. "Short-run forecasting of the euro-dollar exchange rate with economic fundamentals," Working Papers 1203, Banco de España.
- Maximo Camacho & Marcos Dal Bianco & Gabriel Perez Quiros, 2012. "Short-run forecasting of the euro-dollar exchange rate with economic fundamentals," Working Papers 1201, BBVA Bank, Economic Research Department.
- Máximo Camacho & Rafael Doménech, 2012.
"MICA-BBVA: a factor model of economic and financial indicators for short-term GDP forecasting,"
SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 3(4), pages 475-497, December.
- Maximo Camacho & Rafael Domenech, 2010. "MICA-BBVA: A Factor Model of Economic and Financial Indicators for Short-term GDP Forecasting," Working Papers 1021, BBVA Bank, Economic Research Department.
- Goodness C. Aye & Stephen M. Miller & Rangan Gupta & Mehmet Balcilar, 2016.
"Forecasting US real private residential fixed investment using a large number of predictors,"
Empirical Economics, Springer, vol. 51(4), pages 1557-1580, December.
- Goodness C. Aye & Stephen M. Miller & Rangan Gupta & Mehmet Balcilar, 2013. "Forecasting the US Real Private Residential Fixed Investment Using Large Number of Predictors," Working Papers 201348, University of Pretoria, Department of Economics.
- Goodness C. Aye & Rangan Gupta & Stephen M. Miller & Mehmet Balcilar, 2014. "Forecasting US Real Private Residential Fixed Investment Using a Large Number of Predictors," Working papers 2014-10, University of Connecticut, Department of Economics.
- Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024.
"Daily growth at risk: Financial or real drivers? The answer is not always the same,"
International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
- Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2022. ""Daily Growth at Risk: financial or real drivers? The answer is not always the same"," IREA Working Papers 202208, University of Barcelona, Research Institute of Applied Economics, revised Jun 2022.
- Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2015.
"The out-of-sample forecasting performance of nonlinear models of regional housing prices in the US,"
Applied Economics, Taylor & Francis Journals, vol. 47(22), pages 2259-2277, May.
- Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working Papers 201226, University of Pretoria, Department of Economics.
- Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working Papers 1209, University of Nevada, Las Vegas , Department of Economics.
- Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working papers 2012-12, University of Connecticut, Department of Economics.
- Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working Papers 15-27, Eastern Mediterranean University, Department of Economics.
- Jonathan Berrisch & Florian Ziel, 2023. "Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices," Papers 2303.10019, arXiv.org, revised Feb 2024.
- Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-33.
- Massimiliano Marzo & Paolo Zagaglia, 2010.
"Volatility forecasting for crude oil futures,"
Applied Economics Letters, Taylor & Francis Journals, vol. 17(16), pages 1587-1599.
- Marzo, Massimiliano & Zagaglia, Paolo, 2007. "Volatility forecasting for crude oil futures," Research Papers in Economics 2007:9, Stockholm University, Department of Economics.
- Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.
- Lahiri, Kajal & Yang, Liu, 2013.
"Forecasting Binary Outcomes,"
Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106,
Elsevier.
- Kajal Lahiri & Liu Yang, 2012. "Forecasting Binary Outcomes," Discussion Papers 12-09, University at Albany, SUNY, Department of Economics.
- Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
- Naser, Hanan, 2016. "Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach," Energy Economics, Elsevier, vol. 56(C), pages 75-87.
- Vosen, Simeon & Schmidt, Torsten, 2012.
"A monthly consumption indicator for Germany based on Internet search query data,"
EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 19(7), pages 683-687.
- Simeon Vosen & Torsten Schmidt, 2012. "A monthly consumption indicator for Germany based on Internet search query data," Applied Economics Letters, Taylor & Francis Journals, vol. 19(7), pages 683-687, May.
- Schmidt, Torsten & Vosen, Simeon, 2010. "A monthly consumption indicator for Germany based on internet search query data," Ruhr Economic Papers 208, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
- Marian Vavra, 2015. "On a Bootstrap Test for Forecast Evaluations," Working and Discussion Papers WP 5/2015, Research Department, National Bank of Slovakia.
- Rumler, Fabio & Valderrama, Maria Teresa, 2010.
"Comparing the New Keynesian Phillips Curve with time series models to forecast inflation,"
The North American Journal of Economics and Finance, Elsevier, vol. 21(2), pages 126-144, August.
- Fabio Rumler & Maria Teresa Valderrama, 2007. "Comparing the New Keynesian Phillips Curve with Time Series Models to Forecast Inflation," EcoMod2007 23900080, EcoMod.
- Fabio Rumler & Maria Teresa Valderrama, 2008. "Comparing the New Keynesian Phillips Curve with Time Series Models to Forecast Inflation," Working Papers 148, Oesterreichische Nationalbank (Austrian Central Bank).
- Giot, Pierre & Petitjean, Mikael, 2007.
"The information content of the Bond-Equity Yield Ratio: Better than a random walk?,"
International Journal of Forecasting, Elsevier, vol. 23(2), pages 289-305.
- GIOT, Pierre & PETITJEAN, Mikael, 2006. "The information content of the Bond-Equity Yield Ratio: better than a random walk?," LIDAM Discussion Papers CORE 2006089, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- GIOT, Pierre & PETITJEAN, Mikael, 2007. "The information content of the Bond-Equity Yield Ratio: Better than a random walk?," LIDAM Reprints CORE 1982, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Parigi, Giuseppe & Golinelli, Roberto, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
- Hakan Kara & Pinar Ozlu & Deren Unalmis, 2015.
"Turkiye icin Finansal Kosullar Endeksi,"
Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 15(3), pages 41-73.
- Hakan Kara & Pinar Ozlu & Deren Unalmis, 2015. "Turkiye icin Finansal Kosullar Endeksi," Working Papers 1513, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
More about this item
Keywords
Wind power forecasting; Federated learning; Privacy-preserving; Spatio-temporal correlation;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:288:y:2024:i:c:s0360544223032413. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.