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Yamin Wang
Yamin Wang
General Electric
Verified email at clarkson.edu
Title
Cited by
Cited by
Year
Wind speed forecasting based on the hybrid ensemble empirical mode decomposition and GA-BP neural network method
S Wang, N Zhang, L Wu, Y Wang
Renewable Energy 94, 629-636, 2016
6352016
A fully-decentralized consensus-based ADMM approach for DC-OPF with demand response
Y Wang, L Wu, S Wang
IEEE Transactions on Smart Grid 8 (6), 2637-2647, 2016
2462016
Robust optimization for load scheduling of a smart home with photovoltaic system
C Wang, Y Zhou, B Jiao, Y Wang, W Liu, D Wang
Energy Conversion and Management 102, 247-257, 2015
1442015
Distributed optimization approaches for emerging power systems operation: A review
Y Wang, S Wang, L Wu
Electric Power Systems Research 144, 127-135, 2017
1392017
On practical challenges of decomposition-based hybrid forecasting algorithms for wind speed and solar irradiation
Y Wang, L Wu
Energy 112, 208-220, 2016
1062016
A novel wind speed forecasting method based on ensemble empirical mode decomposition and GA-BP neural network
Y Wang, S Wang, N Zhang
2013 IEEE Power & Energy Society General Meeting, 1-5, 2013
412013
A fully distributed asynchronous approach for multi-area coordinated network-constrained unit commitment
Y Wang, L Wu, J Li
Optimization and Engineering 19 (2), 419-452, 2018
242018
Improving economic values of day-ahead load forecasts to real-time power system operations
Y Wang, L Wu
IET Generation, Transmission & Distribution 11 (17), 4238-4247, 2017
192017
Hourly Solar Irradiation Prediction Based on Empirical Mode Decomposition and ELM
S Wang, Y Wang, Y Liu, N Zhang
Electric Power Automation Equipment 34 (8), 7-12, 2014
14*2014
Robust load scheduling in a smart home with photovoltaic system
Y Zhou, C Wang, B Jiao, Y Wang
Energy Procedia 61, 772-776, 2014
112014
Optimal bidding strategy for day-ahead power market
J Li, Z Li, Y Wang
2015 North American Power Symposium (NAPS), 1-6, 2015
102015
Challenges in applying the empirical mode decomposition based hybrid algorithm for forecasting renewable wind/solar in practical cases
Y Wang, L Wu, S Wang
2016 IEEE Power and Energy Society General Meeting (PESGM), 1-5, 2016
52016
Wind speed forecasting modelling by combination of masking signal based empirical mode decomposition and GA-BP neural network
N ZHANG, S WANG, Y WANG
Electric Power 47 (5), 129-135, 2014
22014
Parallel Gaussian Elimination on Single-chip Cloud Computer
Y Wang, C Dai, C Liu, L Wu
2015 North American Power Symposium (NAPS), 1-5, 2015
2015
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Articles 1–14