Distribution system model calibration with big data from AMI and PV inverters
Efficient management and coordination of distributed energy resources with advanced automation schemes requires accurate distribution system modeling and monitoring. Big data from smart meters and photovoltaic (PV) micro-inverters can be leveraged to calibrate existing utility models. This paper presents computationally efficient distribution system parameter estimation algorithms to improve the accuracy of existing utility feeder radial secondary circuit model parameters. The method is demonstrated using a real utility feeder model with advanced metering infrastructure (AMI) and PV micro-inverters, along with alternative parameter estimation approaches that can be used to improve secondary circuit models when limited measurement data is available. Lastly, the parameter estimation accuracy is demonstrated for both a three-phase test circuit with typical secondary circuit topologies and single-phase secondary circuits in a real mixed-phase test system.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- Grant/Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1259833
- Report Number(s):
- SAND-2015-7430J; 603404
- Journal Information:
- IEEE Transactions on Smart Grid, Journal Name: IEEE Transactions on Smart Grid; ISSN 1949-3053
- Publisher:
- Institute of Electrical and Electronics Engineers (IEEE)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
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