Distribution System Load and Forecast Model

TL;DR

This paper provides experimental validation for assumptions on load distribution and forecast errors in distribution systems, showing normal distribution of load, uncorrelated errors, and an aggregation-error curve for day-ahead forecasts.

Contribution

It empirically confirms the normality of load distribution and uncorrelated errors in distribution system load forecasting, supporting prior assumptions.

Findings

Mean load is normally distributed with computed mean and variance.

Residuals are Gaussian beyond 500 customers.

Forecast errors are uncorrelated.

Abstract

This short document provides experimental evidence for the set of assumptions on the mean load and forecast errors made in \cite{Sevlian2014A_Outage} and \cite{Sevlian2014B_Outage}. We show that the mean load at any given node is distributed normally, where we compute the mean and variance. We then present an aggregation-error curve for a single day ahead forecaster. Residual analysis shows that beyond 500 customers, gaussian residuals is a reasonable model. We then show the forecaster has uncorrelated errors.