Project Report


Estimating Peak Reduction From Submetered
Residential Air Conditioner Data

Presented at The Sixth International Energy Program Evaluation Conference
Chicago, Illinois
Report Dated: July 2, 1993
By: John Proctor, P.E.

Abstract

In 1991 Pacific Gas and Electric Company ran a pre-production test of the Appliance Doctor Project in Fresno, California. This test consisted of quality assured distribution duct sealing of residential central air conditioning systems (and AC repairs to a few units). This project showed a cooling savings of 21.6% for high use customers and 9.2% for random customers.

The test included pre-treatment/post-treatment submetering of the air conditioners. Units were submetered from June 7 through July 10 (pre-treatment), Appliance Doctor repairs were made (treatment), and submetering continued from August 21 through September 25 (post-treatment). With this submetered data, the peak reduction due to these repairs was estimated. Proctor Engineering Group investigated the assumptions and results of six different analytical models applied to the Appliance Doctor data set.

This paper reports on the investigation of:

  1. Day matching
  2. A constrained regression model
  3. A temperature bin statistical model
  4. Hottest days statistical aggregation
  5. An hourly curve fitting model
  6. A simplified regression model

The paper also discusses the strengths and weaknesses of the models in estimating peak reduction from submeter data.

Also see Impact/Process Evaluations

Bound copies of the entire paper are available for $25 each.
For details about obtaining a copy see How To Order Project Reports

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