A Data-Driven Residential Transformer Overloading Risk Assessment Method

by   Ming Dong, et al.

Residential transformer population is a critical type of asset that many electric utility companies have been attempting to manage proactively and effectively to reduce unexpected failures and life losses that are often caused by transformer overloading. Within the typical power asset portfolio, the residential transformer asset is often large in population, having lowest reliability design, lacking transformer loading data and susceptible to customer loading behaviors such as adoption of distributed energy resources and electric vehicles. On the bright side, the availability of more residential operation data along with the advancement of data analytics techniques have provided a new path to further our understanding of local residential transformer overloading risks statistically. This research developed a new data-driven method to combine clustering analysis and the simulation of transformer temperature rise and insulation life loss to quantitatively and statistically assess the overloading risk of residential transformer population in one area and suggest proper risk management measures according to the assessment results. Case studies from an actual Canadian utility company have been presented and discussed in detail to demonstrate the applicability and usefulness of the proposed method.



There are no comments yet.



Residential Transformer Overloading Risk Assessment Using Clustering Analysis

Residential transformer population is a critical type of asset that many...

A Data-driven Dynamic Rating Forecast Method and Application for Power Transformer Long-term Planning

This paper presents a data-driven method for producing annual continuous...

Combining Modified Weibull Distribution Models for Power System Reliability Forecast

In recent years, under deregulated environment, electric utility compani...

Critical Risk Indicators (CRIs) for the electric power grid: A survey and discussion of interconnected effects

The electric power grid is a critical societal resource connecting multi...

Multi-Transformer: A New Neural Network-Based Architecture for Forecasting S P Volatility

Events such as the Financial Crisis of 2007-2008 or the COVID-19 pandemi...

Utility-driven Data Analytics on Uncertain Data

Modern Internet of Things (IoT) applications generate massive amounts of...

Exploiting Big Data in Logistics Risk Assessment via Bayesian Nonparametrics

In cargo logistics, a key performance measure is transport risk, defined...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.