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Données administratives

Jiannong Fang

jiannong.fang@epfl.ch +41 21 693 57 01

EPFL ENAC IIE WIRE
GR B2 390 (Bâtiment GR)
Station 2
1015 Lausanne

EPFL SCITAS
ME B2 444 (Bâtiment ME)
Station 9
1015 Lausanne

2025

Improving the accuracy and interpretability of neural networks for wind power forecasting

W. Liao; B. Bak-Jensen; Z. Yang; G. Zhang; J. Fang  et al.

International Journal of Electrical Power and Energy Systems. 2025. DOI : 10.1016/j.ijepes.2025.111027.

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Short-Term Solar Power Forecasting with Large Language Model

W. Liao; Y. Yang; Z. Yang; B. Bak-Jensen; J. Fang  et al.

2025. 2025 IEEE Kiel PowerTech, Kiel, Germany, 2025-06-29 - 2025-07-03. p. 1 - 6. DOI : 10.1109/powertech59965.2025.11180347.

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Explainable modeling for wind power forecasting: A Glass-Box model with high accuracy

W. Liao; J. Fang; B. Bak-Jensen; G. Ruan; Z. Yang  et al.

International Journal of Electrical Power and Energy Systems. 2025. DOI : 10.1016/j.ijepes.2025.110643.

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TimeGPT in load forecasting: A large time series model perspective

W. Liao; S. Wang; D. Yang; Z. Yang; J. Fang  et al.

Applied Energy. 2025. DOI : 10.1016/j.apenergy.2024.124973.

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2024

Evolution of Turbulent Boundary Conditions on the Surface of Large Barchan Dunes: Anomalies in Aerodynamic Roughness and Shear Velocity, Aeolian Threshold, and the Role of Dune Skewness

M. Y. Louge; A. Valance; J. Fang; S. J. Harnett; F. Porté-Agel  et al.

Journal of Geophysical Research: Earth Surface. 2024. DOI : 10.1029/2023JF007599.

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Can we trust explainable artificial intelligence in wind power forecasting?

W. Liao; J. Fang; L. Ye; B. Bak-Jensen; Z. Yang  et al.

Applied Energy. 2024. DOI : 10.1016/j.apenergy.2024.124273.

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2023

A Fast Hybrid Pressure-Correction Algorithm for Simulating Incompressible Flows by Projection Methods

J. Fang

Algorithms. 2023. DOI : 10.3390/a16060287.

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2021

Numerical Weather Prediction and Artificial Neural Network Coupling for Wind Energy Forecast

L. Donadio; J. Fang; F. Porté-Agel

Energies. 2021. DOI : 10.3390/en14020338.

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2019

Wind Energy Prediction in Highly Complex Terrain by Computational Fluid Dynamics

D. Tabas; J. Fang; F. Porté-Agel

Energies. 2019. DOI : 10.3390/en12071311.

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2018

Shifts in wind energy potential following land-use driven vegetation dynamics in complex terrain

J. Fang; A. Peringer; M.-S. Stupariu; I. Pǎtru-Stupariu; A. Buttler  et al.

Science of The Total Environment. 2018. DOI : 10.1016/j.scitotenv.2018.05.083.

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2017

Direct numberical simulation of turbulent slope flows up to Grash of number Gr=2.1 x 10(11)

M. G. Giometto; G. G. Katul; J. Fang; M. B. Parlange

Journal of Fluid Mechanics. 2017. DOI : 10.1017/jfm.2017.372.

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2016

Intercomparison of Terrain-Following Coordinate Transformation and Immersed Boundary Methods for Large-Eddy Simulation of Wind Fields over Complex Terrain

J. Fang; F. Porté-Agel

Journal of Physics: Conference Series. 2016. DOI : 10.1088/1742-6596/753/8/082008.

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2015

Large-Eddy Simulation of Very-Large-Scale Motions in the Neutrally Stratified Atmospheric Boundary Layer

J. Fang; F. Porté-Agel

Boundary Layer Meteorology. 2015. DOI : 10.1007/s10546-015-0006-z.

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2013

Flow over Hills: A Large-Eddy Simulation of the Bolund Case

M. Diebold; C. Higgins; J. Fang; A. Bechmann; M. B. Parlange

Boundary-Layer Meteorology. 2013. DOI : 10.1007/s10546-013-9807-0.

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2012

A MLS-based lattice spring model for simulating elasticity of materials

G.-F. Zhao; J. Fang; J. Zhao

International Journal of Computational Methods. 2012. DOI : 10.1142/S0219876212500375.

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Interaction between large wind farms and the atmospheric boundary layer

F. Porte-Agel; H. Lu; Y.-T. Wu

2012. 23rd International Congress of Theoretical and Applied Mechanics (ICTAM), Beijing, China, August 19-24, 2012. p. 307 - 318. DOI : 10.1016/j.piutam.2014.01.026.

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A coupled distinct lattice spring model for rock failure under dynamic loads

G. Zhao; N. Khalili; J. Fang; J. Zhao

Computers and Geotechnics. 2012. DOI : 10.1016/j.compgeo.2011.12.006.

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2011

A 3D distinct lattice spring model for elasticity and dynamic failure

G.-F. Zhao; J. Fang; J. Zhao

International Journal for Numerical and Analytical Methods in Geomechanics. 2011. DOI : 10.1002/nag.930.

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Towards oscillation-free implementation of the immersed boundary method with spectral-like methods

J. Fang; M. Diebold; C. Higgins; M. Parlange

Journal of Computational Physics. 2011. DOI : 10.1016/j.jcp.2011.07.017.

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2009

Improved SPH methods for simulating free surface flows of viscous fluids

J. Fang; A. Parriaux; M. Rentschler; C. Ancey

Applied Numerical Mathematics. 2009. DOI : 10.1016/j.apnum.2008.02.003.

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Enseignement et PhD

A dirigé les thèses EPFL de

Marco Giovanni Giometto

A co-dirigé les thèses EPFL de

Gaofeng Zhao