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Record W1481927063 · doi:10.2172/891031

Energy Efficiency in Western Utility Resource Plans: Impacts onRegional Resources Assessment and Support for WGA Policies

2006· report· en· W1481927063 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnergy
TopicEnergy Efficiency and Management
Canadian institutionsnot available
Fundersnot available
KeywordsElectricityEfficient energy useEnvironmental economicsResource (disambiguation)PortfolioBusinessElectricity generationEconomicsNatural resource economicsFinancePower (physics)EngineeringComputer science

Abstract

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In the aftermath of the consumer price shocks and short-term power shortages of the 2000-01 electricity crisis, policymakers and regulators in Western states are placing increased emphasis on integrated resource planning (IRP), resource adequacy and assessment and a diversified portfolio of resources to meet the needs of electricity consumers. In some states, this has led to a resurgence in state and utility commitments to energy efficiency. Increasing interest in acquiring energy efficiency as a power-system resource is also driven by the desire to dampen high growth rates in electricity demand in some Western states, rapid increases in natural gas prices, concerns about the environmental impacts of electricity generation (e.g. water consumption by power plants, air quality), and the potential of energy efficiency to provide utility bill savings for households and businesses (WGA CDEAC 2006). Recognizing the cost-competitiveness and environmental benefits of energy efficiency, the Western Governor's Association (WGA) has set a high priority for energy efficiency, establishing a goal of reducing projected electricity demand by 20% across the West by 2020 in a policy resolution on Clean and Diversified Energy for the West (WGA 2004). Nationally, the need for improved tracking of demand-side resources in load forecasting is formalized in the North American Electric Reliability Council (NERC)'s recently adopted reliability standards, which utilities and regional reliability organizations will need to comply with (NERC 2005a and 2005b). In this study, we examine the treatment of energy efficiency in recent resource plans issued by fourteen investor-owned utilities (IOUs) in the Western United States and Canada. The goals of this study are to: (1) summarize energy-efficiency resources as represented in a large sample of recent resource plans prepared by Western utilities and identify key issues; (2) evaluate the extent to which the information provided in current resource plans can be used to support region-wide resource assessment and tracking of state/utility progress in meeting the WGA's energy-efficiency goals (WGA 2004); and (3) offer recommendations on information and documentation of energy-efficiency resources that should be included in future resource plans to facilitate comparative review and regional coordination. The scope of this report covers projected electric end-use efficiency investments reported in all Western utility resource plans that were publicly available as of February 2006. While a few utilities included additional demand-side resources, such as demand response, in their plans, we do not report that information. However, many of the issues and recommendations in reference to energy efficiency in this report are relevant to other demand-side resources as well. This report is organized as follows. Section 2 outlines the data sources and approach used in this study and conceptualizes methods and metrics for tracking energy-efficiency resources over time. Section 3 presents results from the review of the utility resource plans. Important issues encountered in reviewing the resource plans are discussed in section 4. Finally, section 5 concludes with recommendations for improving the tracking and reporting of energy efficiency in forthcoming resource plans.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.760
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.318
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations13
Published2006
Admission routes1
Has abstractyes

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