Estimating the Impact of Efficiency Standards on the Uncertainty of the Northwest Electric System
Andrew Ford
Additional contact information
Andrew Ford: University of Southern California, Los Angeles, California
Operations Research, 1990, vol. 38, issue 4, 580-597
Abstract:
The uncertainty of the Northwest electric system was the subject of a recent study for the Bonneville Power Administration. System uncertainty was described along two dimensions over a twenty year planning period. One dimension was uncertainty in the demand for electricity; the second dimension was uncertainty in the price of electricity. The study focused on the impact of efficiency standards that would reduce the electricity used in new buildings and appliances. Many planners expect that the standards would reduce the long-term uncertainty in electricity demand. Some planners have come to realize that the standards could also reduce the long-term uncertainty in the price of electricity. This paper explains the case study approach to estimating the magnitude of these reductions in uncertainty. I describe the analytical approach and the key findings of the study, and conclude with a discussion of the study's impact on decision making in the region.
Keywords: government; energy policy: the impact of efficiency standards; simulation; statistical analysis: estimating tolerance intervals; simulation; system dynamics: a model of the Northwest electric system (search for similar items in EconPapers)
Date: 1990
References: Add references at CitEc
Citations: View citations in EconPapers (13)
Downloads: (external link)
http://dx.doi.org/10.1287/opre.38.4.580 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:38:y:1990:i:4:p:580-597
Access Statistics for this article
More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().