What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Electrical engineering
His primary areas of study are Mathematical optimization, Electric power system, Wind power, Simulation and Electricity.
His biological study deals with issues like Stand-alone power system, which deal with fields such as Power-flow study and Linear programming.
His Electric power system study incorporates themes from Extreme learning machine, Machine learning and Artificial intelligence.
Ke Meng has included themes like Battery energy storage system, Energy storage, Economic dispatch and Benchmark in his Wind power study.
His biological study spans a wide range of topics, including Battery and Reliability engineering.
His studies in Electricity integrate themes in fields like Fuzzy logic, Renewable energy and Radial basis function.
His most cited work include:
- Electric Vehicle Battery Charging/Swap Stations in Distribution Systems: Comparison Study and Optimal Planning (264 citations)
- Quantum-Inspired Particle Swarm Optimization for Valve-Point Economic Load Dispatch (225 citations)
- Optimal Allocation of Energy Storage System for Risk Mitigation of DISCOs With High Renewable Penetrations (215 citations)
What are the main themes of his work throughout his whole career to date?
Electric power system, Control theory, Mathematical optimization, Wind power and Renewable energy are his primary areas of study.
Ke Meng interconnects Electricity, Industrial engineering, Extreme learning machine, Simulation and Process in the investigation of issues within Electric power system.
His study looks at the relationship between Control theory and fields such as AC power, as well as how they intersect with chemical problems.
His Mathematical optimization study integrates concerns from other disciplines, such as Power system simulation and Economic dispatch.
His work carried out in the field of Wind power brings together such families of science as Control engineering, Turbine, Reliability engineering and Benchmark.
He studied Renewable energy and Energy storage that intersect with Automotive engineering.
He most often published in these fields:
- Electric power system (25.94%)
- Control theory (23.85%)
- Mathematical optimization (22.18%)
What were the highlights of his more recent work (between 2019-2021)?
- Control theory (23.85%)
- Mathematical optimization (22.18%)
- Renewable energy (19.25%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Control theory, Mathematical optimization, Renewable energy, Electric power system and Reliability engineering.
His Control theory study which covers Inverter that intersects with Admittance and Power flow.
His Mathematical optimization research is multidisciplinary, incorporating perspectives in Distributed generation, Nonlinear system, Economic dispatch and Backup.
His research integrates issues of Electricity, Energy storage, Energy management and Solar energy in his study of Renewable energy.
The various areas that Ke Meng examines in his Electric power system study include Key and Smart grid.
As a part of the same scientific study, Ke Meng usually deals with the Offshore wind power, concentrating on Genetic algorithm and frequently concerns with Wind power.
Between 2019 and 2021, his most popular works were:
- Thermal Inertial Aggregation Model for Integrated Energy Systems (21 citations)
- Hybrid approaches based on deep whole-sky-image learning to photovoltaic generation forecasting (18 citations)
- A comprehensive review of variable renewable energy levelized cost of electricity (14 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Electrical engineering
- Machine learning
His main research concerns Control theory, Renewable energy, Mathematical optimization, Microgrid and Voltage.
His Control theory research includes elements of Wind power, Induction generator, Doubly fed electric machine and Series compensation.
His Renewable energy research is multidisciplinary, incorporating elements of Probabilistic logic, Electric power system and Reliability.
His research ties Efficient energy use and Mathematical optimization together.
His Microgrid research includes themes of Islanding, Distributed generation and Resilience.
In his study, which falls under the umbrella issue of Voltage, Photovoltaic system is strongly linked to Electronic engineering.
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