What is he best known for?
The fields of study he is best known for:
- Statistics
- Electrical engineering
- Artificial intelligence
His scientific interests lie mostly in Electric power system, Mathematical optimization, Control theory, Wind power and AC power.
His Electric power system study combines topics in areas such as Reliability engineering and Probabilistic logic.
His research integrates issues of Microeconomics, Economic dispatch and Electricity market in his study of Mathematical optimization.
His Control theory research includes elements of Maximum power point tracking, Microgrid, Induction generator and Energy storage.
His Wind power research incorporates elements of Wind speed, Control engineering, Turbine, Optimization problem and Demand response.
His work deals with themes such as Power factor, Distributed generation, Voltage regulation and Power control, which intersect with AC power.
His most cited work include:
- Smart Transmission Grid: Vision and Framework (701 citations)
- Next-Generation Monitoring, Analysis, and Control for the Future Smart Control Center (263 citations)
- DCOPF-Based LMP Simulation: Algorithm, Comparison With ACOPF, and Sensitivity (260 citations)
What are the main themes of his work throughout his whole career to date?
Fangxing Li mainly investigates Electric power system, Mathematical optimization, Control theory, Wind power and AC power.
His Electric power system research includes themes of Electricity, Reliability engineering, Control, Probabilistic logic and Simulation.
His research investigates the connection between Mathematical optimization and topics such as Electricity market that intersect with issues in Demand response, Microeconomics and Transmission.
Fangxing Li interconnects Power, Phasor, Control engineering and Voltage in the investigation of issues within Control theory.
His Wind power research integrates issues from Wind speed, Turbine, Energy storage, Optimization problem and Renewable energy.
His study in AC power is interdisciplinary in nature, drawing from both Power factor, Distributed generation, Voltage regulation and Electronic engineering.
He most often published in these fields:
- Electric power system (31.88%)
- Mathematical optimization (26.81%)
- Control theory (23.19%)
What were the highlights of his more recent work (between 2018-2021)?
- Electric power system (31.88%)
- Demand response (9.42%)
- Mathematical optimization (26.81%)
In recent papers he was focusing on the following fields of study:
Fangxing Li spends much of his time researching Electric power system, Demand response, Mathematical optimization, Control theory and Power.
The study incorporates disciplines such as Probability distribution, Sensitivity, Probabilistic logic, Computer simulation and Convolutional neural network in addition to Electric power system.
His research in Demand response intersects with topics in Load management, HVAC, Smart grid and Flexibility.
His Linear programming study in the realm of Mathematical optimization interacts with subjects such as Sizing.
His study focuses on the intersection of Power and fields such as Control with connections in the field of Automatic frequency control.
He studied Electricity and Wind power that intersect with Bidding.
Between 2018 and 2021, his most popular works were:
- 5G network-based Internet of Things for demand response in smart grid: A survey on application potential (44 citations)
- Intelligent Multi-Microgrid Energy Management Based on Deep Neural Network and Model-Free Reinforcement Learning (38 citations)
- Clustering Load Profiles for Demand Response Applications (31 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Electrical engineering
- Artificial intelligence
His primary areas of study are Electric power system, Demand response, Power, Wind power and Renewable energy.
Fangxing Li brings together Electric power system and Physical system to produce work in his papers.
The concepts of his Power study are interwoven with issues in Automatic frequency control, Control theory and Mathematical optimization.
His Mathematical optimization research is multidisciplinary, relying on both Range and Interval.
His work carried out in the field of Wind power brings together such families of science as Encoding and Computer data storage.
His studies deal with areas such as Dynamic simulation and Electricity as well as Renewable energy.
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