Line Impedance Network Estimator (LINE) for Grid Mapping via Smart Meters

The Line Impedance Network Estimator (LINE) for Grid Mapping via Smart Meters project is a collaborative effort between the California Energy Commission and UC Lawrence Berkeley National Laboratory (LBNL). The primary objective is to design and develop a smart meter-based toolset that integrates machine learning, simulation, and decision support to map distribution line capacity and streamline utility load approvals. This initiative involves installing electric utility smart meters to passively monitor building usage and equipping advanced metering infrastructure with distributed machine learning algorithms to extrapolate the topology and capacity of secondary distribution lines. The project aims to validate a software tool suitable for large-scale utility deployment, including the use of over-the-air updates, and will include a paper study based on the acquired data. Work will be performed in San Francisco, California, and may extend to other locations such as San Jose and Oakland. The project is designed to advance building technology for improved energy savings, human health, and environmental performance at lower costs. It qualifies for categorical exemptions under the California Environmental Quality Act (CEQA) as it involves minor alterations, the replacement of existing utility systems, and basic data collection. All activities must be conducted by qualified technicians and researchers in accordance with applicable health, safety, and environmental regulations.