Zhifang Wang, Ph.D., joined the Department of Electrical and Computer Engineering faculty in August 2012. Dr. Wang is coming to VCU from the University of California, Davis. She received both the B.S. and M.S. degrees in Electrical Engineering from Tsinghua University, Beijing, China, and the Ph.D. degree in Electrical and Computer Engineering from Cornell University. She is a Senior Member of the IEEE, a member of IEEE Power & Energy Society, IEEE Communication Society, and IEEE Women in Engineering. Her current research focuses on cascading failures in power grids, energy system modeling and optimization, integration of renewable generation into power markets, and voltage stability and controls.
Industry Expertise (3)
Areas of Expertise (5)
Cascading Failures in Power Grids
Energy System Modeling and Optimization
Integration of Renewable Generation
Voltage Stability and Controls
Smart Grid Communication Architecture
HICSS'48 Best Paper Award 2015
For the paper entitled "On Bus Type Assignments in Random Topology Power Grid Models", coauthored with Dr. Robert J. Thomas.
IEEE Donald G. Fink Award 2013
For the paper entitled "For the Grid and Through the Grid: the Role of Power Line Communications in the Smart Grid," coauthored by Dr. Stefano Galli and Dr. Anna Scaglione.
IEEE Senior Member (professional)
In recognition of professional standing. Awarded by the Officers and Board of Directors of the IEEE.
Cornell University: Ph.D., Electrical and Computer Engineering 2005
Tsinghua University, Beijing,: M.S., Electrical Engineering 1998
Tsinghua University, Beijing,: B.S., Electrical Engineering 1995
- Assistant Professor, Electrical and Computer Engineering, VCU
- Director, EPES Lab, Electrical and Computer Engineering, VCU
Research Grants (1)
Synthetic Data For Power Grid R&D, June 2016 - June 2018
The University of Illinois at Urbana-Champaign, with partners from Cornell University, Virginia Commonwealth University, and Arizona State University will develop 10 open-source and synthetic transmission system models and associated scenarios that match the complexity of power grids. By utilizing statistics derived from real data, the team’s models will have coordinates based on North American geography with network structure, characteristics, and consumer demand that mimics real grid profiles. Much of the developed software will be open source and available on the MATPOWER software suite as well as the GRID DATA repository.
EGRE 471 Power System Analysis
Offered in spring semester. The course provides students with a comprehensive overview of electrical power system operation and design. It will develop models and tools for investigating system behavior, and provide opportunities for using the tools in design process.
EGRE 671 Power System Operation and Controls
This graduate level course covers the fundamental concepts of economic operation and controls of power systems, including real and reactive power balance, optimized generation dispatch, steady state an dynamic analysis, real-time monitoring and controls, and contingency analysis.
EGRE 573 Sustainable and Efficient Power Systems
The course covers distributed power generation system and renewable energy technologies. It develops models and tools for investigating electric power generation and efficiency analysis, the wind and solar power, energy storage, renewable integration and environmental impacts.
EGRE 336 Intro to Communication Systems
Introduction to the theory and application of analog and digital communications including signal analysis, baseband transmission, amplitude and angle modulation, noise model and effect, and design considerations.
EGRE 444 Communication Systems
The course covers the fundamental principles behind digital communications. The emphasis will be on the physical layer (i.e. digital transceiver design issues). The students are expected to gain a thorough understanding of digital communication systems, pulse modulation, digital modulation, detection and estimation for digital communications, information theory, as well as error control coding.
Selected Articles (5)
*Seyyed H. Elyas, Zhifang Wang
This paper presents our study results on the correlated assignment of generation, load, or connection buses in a given grid topology and the development of an optimized search algorithm to improve the proposed synthetic grid model, called RT-nestedSmallWorld.
*M. H. Athari, Z. Wang
In this study, the impacts of wind generation in terms of its penetration and uncertainty levels on grid vulnerability to cascading overload failures are studied. The simulation results on IEEE 300 bus system show that uncertainty coming from wind energy have severe impact on grid vulnerability to cascading overload failures. Results also suggest that higher penetration levels of wind energy if not managed appropriately will add to this severity due to injection of higher uncertainties into the grid.
*S. H. Elyas, Z. Wang,
With the help of Bus Type Entropy, a novel measure which provides a quantitative means to better represent the correlation of bus type assignments in a grid topology, we propose a multi-objective optimization algorithm for the bus type assignments in the random topology power grid modeling. The proposed search algorithm is able to locate the best set of bus type assignments for a given random "electrical" topology generated by RT-nested-smallworld.
*H. Sadeghian, *M. H. Athari, Z. Wang
This paper builds a simulation model for the local distribution network based on obtained load profiles, GIS information, solar insolation, feeder and voltage settings, and define the optimization problem of solar PVDG installation to determine the optimal siting and sizing for different penetration levels with different objective functions. The objective functions include voltage profile improvement and energy loss minimization and the considered constraints include the physical distribution network constraints (AC power flow), the PV capacity constraint, and the voltage and reverse power flow constraints.
Z. Wang, R. J. Thomas
This paper examined the correlation between the three bus types of G/L/C and some network topology metrics such as node degree distribution and clustering coefficient. We also investigated the impacts of different bus type assignments on the grid vulnerability to cascading failures using IEEE 300 bus system as an example. We found that (a) the node degree distribution and clustering characteristic are different for different type of buses (G/L/C) in a realistic grid, (b) the changes in bus type assignment in a grid may cause big differences in system dynamics, and (c) the random assignment of bus types in a random topology power grid model should be improved by using a more accurate assignment which is consistent with that of realistic grids.