Siyuan Lu
Siyuan Lu
Xiaopeng Motors
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A suite of metrics for assessing the performance of solar power forecasting
J Zhang, A Florita, BM Hodge, S Lu, HF Hamann, V Banunarayanan, ...
Solar Energy 111, 157-175, 2015
The value of day-ahead solar power forecasting improvement
CB Martinez-Anido, B Botor, AR Florita, C Draxl, S Lu, HF Hamann, ...
Solar Energy 129, 192-203, 2016
A solar time based analog ensemble method for regional solar power forecasting
X Zhang, Y Li, S Lu, HF Hamann, BM Hodge, B Lehman
IEEE Transactions on Sustainable Energy 10 (1), 268-279, 2018
Unsupervised clustering-based short-term solar forecasting
C Feng, M Cui, BM Hodge, S Lu, HF Hamann, J Zhang
IEEE Transactions on Sustainable Energy 10 (4), 2174-2185, 2018
Photoluminescence characterization of a high-efficiency Cu2ZnSnS4 device
T Gershon, B Shin, N Bojarczuk, T Gokmen, S Lu, S Guha
Journal of Applied Physics 114 (15), 2013
Photocurrent induced by nonradiative energy transfer from nanocrystal quantum dots to adjacent silicon nanowire conducting channels: toward a new solar cell paradigm
S Lu, Z Lingley, T Asano, D Harris, T Barwicz, S Guha, A Madhukar
Nano letters 9 (12), 4548-4552, 2009
Nonradiative resonant excitation transfer from nanocrystal quantum dots to adjacent quantum channels
S Lu, A Madhukar
Nano Letters 7 (11), 3443-3451, 2007
PAIRS: A scalable geo-spatial data analytics platform
LJ Klein, FJ Marianno, CM Albrecht, M Freitag, S Lu, N Hinds, X Shao, ...
2015 IEEE International Conference on Big Data (Big Data), 1290-1298, 2015
Metrics for evaluating the accuracy of solar power forecasting
J Zhang, BM Hodge, A Florita, S Lu, HF Hamann, V Banunarayanan
National Renewable Energy Lab.(NREL), Golden, CO (United States), 2013
Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting
J Zhang, BM Hodge, S Lu, HF Hamann, B Lehman, J Simmons, ...
Solar Energy 122, 804-819, 2015
A high quantum efficiency preserving approach to ligand exchange on lead sulfide quantum dots and interdot resonant energy transfer
Z Lingley, S Lu, A Madhukar
Nano letters 11 (7), 2887-2891, 2011
Machine learning based multi-physical-model blending for enhancing renewable energy forecast-improvement via situation dependent error correction
S Lu, Y Hwang, I Khabibrakhmanov, FJ Marianno, X Shao, J Zhang, ...
2015 European control conference (ECC), 283-290, 2015
Scheduling cost efficient datacenter load distribution
AN Chatterjee, HF Hamann, KM Shankar, S Lu, KVRM Murali
US Patent 9,654,414, 2017
Method and system for crop type identification using satellite observation and weather data
MO Freitag, HF Hamann, L Klein, S Lu
US Patent 10,586,105, 2020
Relationship between Cu2ZnSnS4 quasi donor-acceptor pair density and solar cell efficiency
T Gershon, B Shin, T Gokmen, S Lu, N Bojarczuk, S Guha
Applied Physics Letters 103 (19), 2013
Predicting solar power generation using semi-supervised learning
JP Cipriani, I Khabibrakhmanov, Y Kim, S Lu, AP Praino
US Patent App. 15/083,661, 2017
Forecast of solar energy production-A deep learning approach
R Zhang, M Feng, W Zhang, S Lu, F Wang
2018 IEEE International Conference on Big Knowledge (ICBK), 73-82, 2018
A methodology for quantifying reliability benefits from improved solar power forecasting in multi-timescale power system operations
M Cui, J Zhang, BM Hodge, S Lu, HF Hamann
IEEE Transactions on Smart Grid 9 (6), 6897-6908, 2017
Real-Time Dynamics of Ca2+, Caspase-3/7, and Morphological Changes in Retinal Ganglion Cell Apoptosis under Elevated Pressure
JK Lee, S Lu, A Madhukar
PloS one 5 (10), e13437, 2010
IBM PAIRS curated big data service for accelerated geospatial data analytics and discovery
S Lu, X Shao, M Freitag, LJ Klein, J Renwick, FJ Marianno, C Albrecht, ...
2016 IEEE International Conference on Big Data (Big Data), 2672-2675, 2016
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