Areas of Expertise:

  • Power system dynamic stability and control;
  • Phasor Measurement Unit (PMU) application;
  • Integration of renewable generation and smart appliance;
  • Power market;
  • Real time voltage security analysis;
  • Signal processing/System Identification/Control System and their application in power systems.

Funded Projects (since August 2013):

  • Ning Zhou (CoPI), “Development of High IBR Penetration New York Power System Models for Operators,” funded by New York State Energy Research and Development Authority (NYSERDA), 2024-2026
  • Ning Zhou (PI), “Control Strategy Development for Inverter Based Resources to Improve Oscillation Modes,” Sponsored by DOE through Pacific Northwest National Laboratory, 2023-2025
  • Ning Zhou (CoPI), “Asynchronous Distributed and Adaptive Parameter Tuning (ADAPT) for Hybrid PV Plants,” SETO, Department of Energy (DOE), 2021-2025
  • Ning Zhou (PI), CAREER: Integrated Dynamic State Estimation for Monitoring Power Systems under High Uncertainty and Variation, Sponsored by National Science Foundation (NSF), Mar. 2019-Feb. 2025.
  • Ning Zhou, Algorithm Development for Robust Dynamic State Estimation, Sponsored by Department of Energy (DOE) through Pacific Northwest National Laboratory (PNNL), 2018-2020.
  • Ning Zhou (Co-PI), Development of a Low-cost Active DER System, funded by New York State Energy Research and Development Authority (NYSERDA), 2017-2019.
  • Ning Zhou, Algorithm Development for Dynamic State Estimation, Sponsored by DOE through Pacific Northwest National Laboratory (PNNL), 2014-2017
  • Ning Zhou, On-Line Validating and Calibrating Generator Dynamic and Electrical Parameters Using PMU and SCADA Data: Engine Development, Sponsored by NYSERDA through Bigwood System Inc. (BSI), 2016- 2017
  • Ning Zhou, BU Contributions to Data Integrity and Situational Awareness Tools (DISAT), Sponsored by DOE through Pacific Northwest National Laboratory (PNNL), 2014.
  •  Ning Zhou (PI), Mark Zhang (Co-PI), Xingye Qiao (Co-PI), Statistical Machine Learning Approach to Smart Grid Load Forecast based on Massive Datasets, Sponsored by Smart Energy Transdisciplinary Area of Excellence (TAE), SUNY Binghamton University, June 2015- Dec 2016.
  • Ziang Zhang (PI), Yong Wang (Co-PI), Ning Zhou (Co-PI), An Active Grid-Friendly Distributed Energy System Testbed, funded by Smart Energy Transdisciplinary Area of Excellence (TAE), SUNY Binghamton University, June 2016-May 2017