WIT Press


Integrating End-use Metering, Building Modeling And Statistical Regressions In The Energy Analysis Of Buildings

Price

Free (open access)

Paper DOI

10.2495/BE050671

Volume

39

Pages

11

Published

2005

Size

272 kb

Author(s)

K. Tiedemann

Abstract

Demand-side management (DSM) programs have been significant components of electric utility integrated resource plans, which attempt to meet load growth requirements as cost efficiently as possible. Evaluation of DSM resources is required to ensure that projected demand and energy savings are credible and realistic. Three main methods have been proposed for the evaluation of commercial sector DSM programs: (a) engineering models, including simple one line algorithms and whole-building computer simulations; (b) statistical models, including quasi-experimental designs and regression modeling; (c) metering, including end-use metering and whole building metering. This paper demonstrates how on-site metering, building energy use simulations, and regression modeling can be combined to evaluate a commercial new construction DSM program. In particular, it develops and applies a statistical framework for the evaluation of new commercial construction DSM programs. Keywords: energy conservation, program evaluation, building simulations, regression analysis, green house gas emissions. 1 Introduction BC Hydro is the largest electricity electric utility in Western Canada and produces about eighty percent of the electricity generated in British Columbia. The commercial and institutional market accounts for about thirty percent of BC Hydro’s sales and the sector offers considerable opportunities for cost effective energy savings. Recent work suggests that about thirty percent of the electricity consumption in new commercial and institutional buildings could be saved if existing cost-effective technologies were utilized. If new buildings do not

Keywords

energy conservation, program evaluation, building simulations, regression analysis, green house gas emissions