What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Electrical engineering
Jie Zhang mainly investigates Wind power, Meteorology, Electric power system, Wind speed and Simulation.
His Wind power research is multidisciplinary, incorporating elements of Probability distribution, Stochastic process, Dynamic programming, Turbine and Renewable energy.
As a part of the same scientific family, he mostly works in the field of Meteorology, focusing on Reliability and, on occasion, Unavailability, Solar power forecasting and Statistical hypothesis testing.
In his work, Solar energy is strongly intertwined with Probabilistic forecasting, which is a subfield of Electric power system.
He interconnects Unimodality, Probability density function, Data set and Image resolution in the investigation of issues within Wind speed.
As part of one scientific family, Jie Zhang deals mainly with the area of Simulation, narrowing it down to issues related to the Marine engineering, and often Electricity generation, Wind tunnel, Rotor, Maximum power principle and Particle swarm optimization.
His most cited work include:
- Unrestricted wind farm layout optimization (UWFLO): Investigating key factors influencing the maximum power generation (227 citations)
- A data-driven multi-model methodology with deep feature selection for short-term wind forecasting (152 citations)
- Optimizing the arrangement and the selection of turbines for wind farms subject to varying wind conditions (151 citations)
What are the main themes of his work throughout his whole career to date?
Jie Zhang mostly deals with Wind power, Electric power system, Meteorology, Mathematical optimization and Wind speed.
The Wind power study combines topics in areas such as Electricity generation, Turbine, Simulation and Marine engineering.
His study in Electric power system is interdisciplinary in nature, drawing from both Reliability engineering, Probabilistic logic, Probabilistic forecasting, Artificial intelligence and Solar power.
His Reliability engineering research includes themes of Reliability and Reliability.
His work deals with themes such as Algorithm and Renewable energy, which intersect with Solar power.
His study explores the link between Meteorology and topics such as Solar energy that cross with problems in Photovoltaic system.
He most often published in these fields:
- Wind power (30.27%)
- Electric power system (25.41%)
- Meteorology (16.22%)
What were the highlights of his more recent work (between 2019-2021)?
- Electric power system (25.41%)
- Artificial intelligence (9.73%)
- Probabilistic logic (9.19%)
In recent papers he was focusing on the following fields of study:
Electric power system, Artificial intelligence, Probabilistic logic, Mathematical optimization and Deep learning are his primary areas of study.
Jie Zhang has researched Electric power system in several fields, including Reliability engineering, Harmonics, Reliability and Renewable energy.
The study incorporates disciplines such as Conditional probability distribution, Copula and Solar power forecasting, Solar power in addition to Probabilistic logic.
His Mathematical optimization research incorporates elements of Wind power, Robustness and Nonlinear system.
Many of his research projects under Wind power are closely connected to Metric with Metric, tying the diverse disciplines of science together.
Jie Zhang combines subjects such as Electricity generation, Plug-in, Distributed computing and Control engineering with his study of Deep learning.
Between 2019 and 2021, his most popular works were:
- Reinforced Deterministic and Probabilistic Load Forecasting via $Q$ -Learning Dynamic Model Selection (23 citations)
- Verification of deterministic solar forecasts (19 citations)
- Multi-distribution ensemble probabilistic wind power forecasting (17 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Electrical engineering
Jie Zhang spends much of his time researching Electric power system, Probabilistic logic, Artificial intelligence, Deep learning and Artificial neural network.
His Joint probability distribution research extends to the thematically linked field of Electric power system.
The various areas that Jie Zhang examines in his Probabilistic logic study include Load forecasting, Mathematical optimization and Solar power forecasting, Solar power.
His Mathematical optimization study incorporates themes from Smart meter, Q-learning, Wind power and Model selection.
His research in Probabilistic forecasting intersects with topics in Ensemble learning, Ensemble forecasting, Timestamp, Wind power forecasting and Surrogate model.
He interconnects Electrical conductor and Wind speed in the investigation of issues within Renewable energy.
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