Power Flow Analysis to Improve Integrated Volt/Var Control (IVVC) and Energy Efficiency Programs3
The goal of this project is to develop a machine-learning-based approach to aid in the detection of power-flow discrepancies using the resources at NC State University (NCSU).
This project will focus on using artificial intelligence to identify which factors are relevant to the quality of a power flow solution, and which data is a good indicator of power flow success or failure. The goal is to develop a machine-learning-based approach to aid in the detection of power-flow discrepancies using the resources at NC State. This will allow utilities to more accurately conduct power flow analysis and could lead to improved grid reliability.
Sponsor
UNC - UNC Charlotte
The grant—running from December 20, 2021 to June 30, 2023—is for a total of $95,000.
Principle Investigators
Mesut E. Baran
More Details
Utilities conduct power flow analysis on a regular basis. This project will focus on using artificial intelligence to identify which factors are relevant to the quality of a power flow solution, and which data is a good indicator of power flow success or failure.