Advanced Sensor Deployment for Distribution System State Estimation and Fault Identification
Distribution systems are currently facing steep operational challenges as a result of the rapidly increasing integration of renewables and other distributed energy resources (DERs) at both the primary and secondary circuit levels. Distribution utilities and system operators have traditionally had some visibility of their primary circuits using low-frequency supervisory control and data acquisition systems, and they have had very poor if not zero visibility of the secondary circuits where the presence of DERs is constantly increasing. Therefore, this paper presents simulation studies to demonstrate the benefits of an advanced, high-fidelity sensor technology, called as the MetaAlert System (MAS), developed by Electrical Grid Monitoring, Ltd. (EGM), on the distribution grid. First, a reliable model of the EGM sensors is developed, and then two use cases-distribution system state estimation (DSSE) and fault identification-are simulated to evaluate the performance of the MAS technology. Simulation results on the Electric Power Research Institute Jl feeder demonstrate that the MAS can effectively participate in system-level DSSE programs and can detect and locate faults faster than traditional distribution protection schemes.
- Research Organization:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE National Renewable Energy Laboratory (NREL), Shell Gamechanger Accelerator Power
- DOE Contract Number:
- AC36-08GO28308
- OSTI ID:
- 1922627
- Report Number(s):
- NREL/CP-5D00-85176; MainId:85949; UUID:7e730d83-1f62-4eff-b13b-7eba7e1e27be; MainAdminID:68597
- Resource Relation:
- Conference: Presented at the 2022 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 24-28 April 2022, New Orleans, Louisiana; Related Information: 80844
- Country of Publication:
- United States
- Language:
- English
Similar Records
Advanced Sensor Deployment for Distribution System State Estimation and Fault Identification: Preprint
Distribution System of the Future