What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Electrical engineering
- Algorithm
His main research concerns Mathematical optimization, Nonlinear programming, Control theory, Nonlinear system and Batch distillation.
In Mathematical optimization, Pu Li works on issues like Electric power system, which are connected to Probabilistic analysis of algorithms.
His biological study spans a wide range of topics, including Flexible battery, Solver, Model predictive control and Sequential quadratic programming.
His research in Control theory intersects with topics in Reactive energy, Battery storage, Simulation and Heuristic.
His Nonlinear system study combines topics from a wide range of disciplines, such as Computational complexity theory and Linear programming.
As a member of one scientific family, Pu Li mostly works in the field of Batch distillation, focusing on Process engineering and, on occasion, Chemical process, Computation, Scientific method and Fractional distillation.
His most cited work include:
- Active-Reactive Optimal Power Flow in Distribution Networks With Embedded Generation and Battery Storage (238 citations)
- Chance constrained programming approach to process optimization under uncertainty (232 citations)
- Chance Constrained Programming for Optimal Power Flow Under Uncertainty (199 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Mathematical optimization, Control theory, Nonlinear system, Nonlinear programming and Optimization problem.
His work in Mathematical optimization is not limited to one particular discipline; it also encompasses Wind power.
His work carried out in the field of Control theory brings together such families of science as Distillation, Fractionating column and Model predictive control.
In his research, Applied mathematics is intimately related to State variable, which falls under the overarching field of Nonlinear system.
His Optimization problem research incorporates themes from Discretization and Estimation theory.
His Stochastic optimization research is multidisciplinary, relying on both Robust optimization and Probabilistic-based design optimization.
He most often published in these fields:
- Mathematical optimization (37.04%)
- Control theory (24.69%)
- Nonlinear system (19.14%)
What were the highlights of his more recent work (between 2018-2021)?
- Mathematical optimization (37.04%)
- Automotive engineering (9.26%)
- Control theory (24.69%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Mathematical optimization, Automotive engineering, Control theory, Battery and Constrained optimization.
The study incorporates disciplines such as Wind power, Phase and Nonlinear system in addition to Mathematical optimization.
His studies in Automotive engineering integrate themes in fields like Energy storage, Renewable energy and Electronics.
His Control theory research is multidisciplinary, incorporating elements of Pressure regulator and Reduction.
The various areas that Pu Li examines in his Battery study include Reliability engineering and Microgrid.
His Constrained optimization research includes themes of Stochastic optimization and Applied mathematics.
Between 2018 and 2021, his most popular works were:
- Design Optimization of a Residential PV-Battery Microgrid With a Detailed Battery Lifetime Estimation Model (13 citations)
- Incrementally constrained dynamic optimization: A computational framework for lane change motion planning of connected and automated vehicles (10 citations)
- Predictive active-reactive optimal power dispatch in PV-battery-diesel microgrid considering reactive power and battery lifetime costs (9 citations)
In his most recent research, the most cited papers focused on:
- Electrical engineering
- Mathematical optimization
- Algorithm
His scientific interests lie mostly in Control theory, Stochastic optimization, Constrained optimization, Smoothing and Mathematical optimization.
Pu Li studies Control system which is a part of Control theory.
His Stochastic optimization study combines topics in areas such as Joint, State variable, Elliptic partial differential equation and Applied mathematics.
Constrained optimization combines with fields such as Convex optimization and Sequence in his work.
His Mathematical optimization research incorporates elements of Phase, Algebraic equation and Nonlinear programming.
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