Our system is currently under heavy load due to increased usage. We're actively working on upgrades to improve performance. Thank you for your patience.
2004
DOI: 10.2172/840045
|View full text |Cite
|
Sign up to set email alerts
|

A new approach for modeling the peak utility impacts from a proposed CUAC standard

Abstract: This report describes a new Berkeley Lab approach for modeling the likely peak electricity load reductions from proposed energy efficiency programs in the National Energy Modeling System (NEMS). This method is presented in the context of the commercial unitary air conditioning (CUAC) energy efficiency standards. A previous report investigating the residential central air conditioning (RCAC) load shapes in NEMS revealed that the peak reduction results were lower than expected. This effect was believed to be due… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2013
2013
2013
2013

Publication Types

Select...
1

Relationship

1
0

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 3 publications
0
1
0
Order By: Relevance
“…Previous work at LBNL investigated in some detail the way that NEMS-BT responds to demand reductions for end-uses that are strongly coincident with the system peak, specifically residential and commercial air conditioning (Hamachi LaCommare et al 2002;LaCommare et al 2004). NEMS-BT runs have also been used to estimate the broader economic impacts of reduced natural gas demand (Carnall, Dale, and Lekov 2011).…”
Section: Introductionmentioning
confidence: 99%
“…Previous work at LBNL investigated in some detail the way that NEMS-BT responds to demand reductions for end-uses that are strongly coincident with the system peak, specifically residential and commercial air conditioning (Hamachi LaCommare et al 2002;LaCommare et al 2004). NEMS-BT runs have also been used to estimate the broader economic impacts of reduced natural gas demand (Carnall, Dale, and Lekov 2011).…”
Section: Introductionmentioning
confidence: 99%