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Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates

E-Mail:

Date of Employment:2003-04-01

School/Department:School of Automation and Electrical Engineering

Administrative Position:professor/Doctoral supervisor

Education Level:With Certificate of Graduation for Doctorate Study

Business Address:Room 307 School of Automation and Electrical Engineering No. 88, Anning West Road, Anning District, Lanzhou City

Gender:Female

Degree:Doctoral degree

Status:Employed

Academic Titles:professor

Alma Mater:Lanzhou Jiaotong University

Discipline:Electrical Power System and Automation

Wang Guo

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Gender:Female

Education Level:With Certificate of Graduation for Doctorate Study

Alma Mater:Lanzhou Jiaotong University

Research Field

Current position: 王果 / Scientific Research / Research Field

  1. Rail Transit Power Supply System
    Analysis and calculation of power quality issues in power systems, including rail transit power supply systems, such as harmonics, reactive power, and negative sequence components, along with their influencing factors. Analysis, calculation, simulation, and design of power quality compensation devices and their control systems, including thyristor-switched capacitors, controllable reactors, active power filters, and reactive power generators. Analysis of traction power supply methods: covering the design of power supply schemes, calculation of power supply capacity, modeling and simulation analysis of various power supply methods, optimization of power supply schemes, and proposal of new power supply methods.

  2. Power Electronics Technology and Applications
    Analysis, calculation, simulation, and design of power electronic devices such as rectifiers, inverters, choppers, and AC converters, including their circuit topologies, parameters, control strategies, and control systems. Research on the analysis and evaluation of traction power supply systems, distribution networks, and related power quality issues.

  3. Multi-Source Information Fusion Detection and Analysis in Substations
    Focusing on key electrical equipment in substations, this research integrates noise signals with deep learning algorithms to build a noise-based acoustic fingerprint recognition system for key substation equipment. The goal is to achieve noise level assessment in ultra-high voltage substations and fault diagnosis of critical electrical equipment. The work primarily involves substation noise acquisition systems, noise data processing techniques, and acoustic fingerprint recognition technology for electrical equipment.

  4. Carbon Accounting and Collaborative Carbon Reduction Research
    This area focuses on the coupling relationship between "electricity and carbon" in power systems and rail transit power supply systems, the conversion between "power data and energy consumption data," refined assessment and prediction models for electricity-based carbon emissions in high-energy-consuming enterprises, and research on key technologies for collaborative carbon reduction through new energy solutions.

  5. Active Distribution Network
    Research on stable control, line loss analysis, low-carbon control, and power quality management in active distribution networks.