What is he best known for?
The fields of study he is best known for:
- Algorithm
- Artificial intelligence
- Mechanical engineering
The scientist’s investigation covers issues in Environmental engineering, Heat recovery ventilation, Waste management, Exergy and Electricity generation.
In Environmental engineering, Jiangjiang Wang works on issues like Process engineering, which are connected to Combined cycle.
His Waste management research is multidisciplinary, relying on both Heat exchanger and Waste heat.
In the subject of general Exergy, his work in Exergy efficiency is often linked to Chemistry and Wood gas generator, thereby combining diverse domains of study.
Jiangjiang Wang interconnects Coefficient of performance, Primary energy and Sensitivity in the investigation of issues within Exergy efficiency.
The Electricity generation study combines topics in areas such as Automotive engineering, Electric power system and Water cooling.
His most cited work include:
- Review on multi-criteria decision analysis aid in sustainable energy decision-making (1245 citations)
- Optimization of capacity and operation for CCHP system by genetic algorithm (304 citations)
- Particle swarm optimization for redundant building cooling heating and power system (208 citations)
What are the main themes of his work throughout his whole career to date?
Process engineering, Electric power system, Exergy, Power and Electricity generation are his primary areas of study.
His studies deal with areas such as Work, Distributed generation, Environmental engineering and Hybrid system as well as Process engineering.
His Electric power system study also includes fields such as
- Automotive engineering which is related to area like Primary energy and Energy flow,
- Electrical load and related Battery.
The study incorporates disciplines such as Chilled water, Waste heat and Thermal energy storage in addition to Exergy.
His Power research includes elements of Genetic algorithm, Reliability engineering, Simulation and Sensitivity.
His research in Electricity generation intersects with topics in Multiple-criteria decision analysis, Operations research and Water cooling.
He most often published in these fields:
- Process engineering (39.39%)
- Electric power system (35.35%)
- Exergy (32.32%)
What were the highlights of his more recent work (between 2019-2021)?
- Electric power system (35.35%)
- Process engineering (39.39%)
- Grid (3.03%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Electric power system, Process engineering, Grid, Syngas and Primary energy.
Jiangjiang Wang has included themes like Multi-objective optimization, Energy supply, Thermal and Hybrid system in his Electric power system study.
Process engineering and Power are frequently intertwined in his study.
His Primary energy study frequently links to related topics such as Automotive engineering.
Distributed generation is closely connected to Collaborative optimization in his research, which is encompassed under the umbrella topic of Automotive engineering.
His research on Exergy efficiency concerns the broader Exergy.
Between 2019 and 2021, his most popular works were:
- Application of hybrid model based on double decomposition, error correction and deep learning in short-term wind speed prediction (24 citations)
- Hybrid solar-assisted combined cooling, heating, and power systems: A review (13 citations)
- Novel planning methodology for energy stations and networks in regional integrated energy systems (10 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Mechanical engineering
Jiangjiang Wang mostly deals with Electric power system, Imagination, Process engineering, Stochastic optimization and Energy management.
His Electric power system research includes a combination of various areas of study, such as Weighting and Grid.
His Imagination research incorporates elements of Network planning and design, Shortest path problem, Energy supply, Kernel density estimation and Search algorithm.
The various areas that Jiangjiang Wang examines in his Process engineering study include Thermal and Internal combustion engine.
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