Ning Lu

From 2003 to 2012, Dr. Ning Lu was a senior research engineer with Pacific Northwest National Laboratory. She was a substation design engineer with the Shenyang Electric Power Survey and Design Institute from 1993 to 1998. She has conducted and managed research projects in modeling and analysis of power system load behaviors, wide area energy storage management systems, renewable integration, climate impact on power grids, and smart grid modeling and diagnosis. Dr. Lu is a Fellow of the Institute of Electrical and Electronics Engineers. She has authored or co-authored more than 60 publications, including journal articles, conference proceedings, and technical reports.

Research interests:

• Load modeling and control

• Wide-area energy storage

• Renewable integration

• Predictive defense model of the smart grid

• Climate change impacts on power grids

Education

2002 - Ph.D. in Electric Power Engineering, Rensselaer Polytechnic Institute, Troy, New York
1999 - M.S. in Electric Power Engineering, Rensselaer Polytechnic Institute, Troy, New York
1993 - B.Eng. in Electrical Engineering, Harbin Institute of Technology, Harbin, Heilongjiang, China

Recent Publications

• Operating a Commercial Building HVAC Load as a Virtual Battery Through Airflow Control (2021)
• A Data-Driven Pivot-Point-Based Time-Series Feeder Load Disaggregation Method (2020)
• Battery Model Parameterization Using Manufacturer Datasheet and Field Measurement for Real-Time HIL Applications (2020)
• PFR ancillary service in low-inertia power system (2020)
• Utility Rate Making: An Intersection of Economics and Social Good [Guest Editorial] (2020)
• A Real-Time Greedy-Index Dispatching Policy for Using PEVs to Provide Frequency Regulation Service (2019)
• A Supervised Machine Learning Approach to Control Energy Storage Devices (2019)
• Mode-based energy storage control approach for residential photovoltaic systems (2019)
• Optimal day-ahead scheduling for commercial building-level consumers under TOU and demand pricing plan (2019)
• Repurposing an energy system optimization model for seasonal power generation planning (2019)