L
Lei Wu
Researcher at Stevens Institute of Technology
Publications - 726
Citations - 12064
Lei Wu is an academic researcher from Stevens Institute of Technology. The author has contributed to research in topics: Medicine & Chemistry. The author has an hindex of 49, co-authored 206 publications receiving 7997 citations. Previous affiliations of Lei Wu include Mississippi State University & Chinese Ministry of Public Security.
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Stochastic Security-Constrained Unit Commitment
TL;DR: Numerical simulations indicate the effectiveness of the proposed approach for solving the stochastic security-constrained unit commitment and introduce the scenario reduction method for enhancing a tradeoff between calculation speed and accuracy of long-term SCUC solution.
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Real-Time Price-Based Demand Response Management for Residential Appliances via Stochastic Optimization and Robust Optimization
TL;DR: The numerical results show attributes of the two approaches for solving the real-time optimal DR management problem for residential appliances via stochastic optimization and robust optimization approaches.
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Wind speed forecasting based on the hybrid ensemble empirical mode decomposition and GA-BP neural network method
TL;DR: The proposed hybrid method based on improved empirical mode decomposition and GA-BP neural network can improve the forecasting accuracy and computational efficiency, which make it suitable for on-line ultra-short term (10 min) and short term (1 h) wind speed forecasting.
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Hourly Coordination of Electric Vehicle Operation and Volatile Wind Power Generation in SCUC
TL;DR: The coordinated integration of aggregated plug-in electric vehicle (PEV) fleets and renewable energy sources (wind energy) in power systems is studied by stochastic security-constrained unit commitment (Stochastic SCUC) model, which minimizes the expected grid operation cost while considering the random behavior of the many PEVs.
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Robust Co-Optimization Scheduling of Electricity and Natural Gas Systems via ADMM
TL;DR: In this paper, a robust co-optimization scheduling model was proposed to study the coordinated optimal operation of the two energy systems, while considering power system key uncertainties and natural gas system dynamics.