Estimation of distribution transformer kVA load using residential smart meter data

Abstract

A major challenge observed for smart meters installed at North American residential premises involves the absence of reactive power consumption measurement of residential customers, which limits the accurate assessment of kVA loading for a distribution transformer (DT), necessary to assess the loss of life and failure of a DT. This paper presents a hardware-free novel strategy for DT kVA load estimation that operates at the utility server level without requiring a fixed power factor assumption or reactive power load information across all residential customers. The proposed strategy provides a simple and effective fixed-point iteration-based formulation for a balanced secondary distribution network, that is extended for an unbalanced three-phase underground secondary distribution network. The efficacy and a detailed statistical analysis of the proposed scheme are studied on a balanced and an unbalanced secondary distribution systems against 1,000 random load profiles through Monte-Carlo simulations which represent uncertainty in smart meter data, with theoretical analysis on convergence and stability also provided. The results indicate that the proposed scheme provides better results in comparison to fixed power assumptions, with respect to the voltage magnitude estimation, and the results from this work may contribute to further smart-grid applications in DTs.