A Model-free Approach for Estimating Service Transformer Capacity Using Residential Smart Meter Data

Azzolini, Joseph A.; Reno, Matthew J.; Yusuf, Jubair

doi:10.1109/jphotov.2023.3335889

Title: A Model-free Approach for Estimating Service Transformer Capacity Using Residential Smart Meter Data

Journal Article · 04 December 2023 · IEEE Journal of Photovoltaics

DOI: https://doi.org/10.1109/jphotov.2023.3335889 · OSTI ID:2228378

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Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Before residential photovoltaic (PV) systems are interconnected with the grid, various planning and impact studies are conducted on detailed models of the system to ensure safety and reliability are maintained. However, these model-based analyses can be time-consuming and error-prone, representing a potential bottleneck as the pace of PV installations accelerates. Data-driven tools and analyses provide an alternate pathway to supplement or replace their model-based counterparts. In this article, a data-driven algorithm is presented for assessing the thermal limitations of PV interconnections. Using input data from residential smart meters, and without any grid models or topology information, the algorithm can determine the nameplate capacity of the service transformer supplying those customers. The algorithm was tested on multiple datasets and predicted service transformer capacity with >98% accuracy, regardless of existing PV installations. This algorithm has various applications from model-free thermal impact analysis for hosting capacity studies to error detection and calibration of existing grid models.

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Research Organization:: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office; USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: NA0003525; 38426

OSTI ID:: 2228378

Alternate ID(s):: OSTI ID: 2251539; OSTI ID: 2311402

Report Number(s):: SAND-2024-00267J

Journal Information:: IEEE Journal of Photovoltaics, Vol. 14, Issue 1; ISSN 2156-3381

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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14 SOLAR ENERGY
Data-driven analysis
distribution system planning
parameter estimation
photovoltaic (PV) integration
smart meters

Title: A Model-free Approach for Estimating Service Transformer Capacity Using Residential Smart Meter Data

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