MétaCan
Menu
Back to cohort
Record W236455485

Performance-Based Regulation of Utilities

2002· article· en· W236455485 on OpenAlexaboutno aff
Mark Newton Lowry, Lawrence Kaufmann

Bibliographic record

VenueEnergy law journal · 2002
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsCommissionIncentiveService (business)DeregulationEconomicsEnergy lawPublic economicsBusinessFinanceLawPolitical scienceEconomyMicroeconomics
DOInot available

Abstract

fetched live from OpenAlex

I. INTRODUCTION Performance-based regulation (PBR) is an alternative to traditional cost of service regulation of energy utilities. In North America, PBR plans have been approved in such diverse jurisdictions as Alberta, California, Florida, Illinois, Maine, and Ontario. The Federal Energy Regulatory Commission (FERC) and Canada's National Energy Board (NEB) use PBR to regulate oil pipelines and some gas lines. The FERC has recently encouraged the use of PBR to regulate electric power transmission. Outside North America, PBR is now the standard form of investor-owned energy utility regulation. PBR is also extensively used in other regulated industries, most notably in telecommunications. Despite the growing importance of PBR, the attention paid to it by economists is uneven. Several economists have addressed the incentive impacts of alternative regulatory systems using mathematical theory. Sophisticated cost research has been submitted as evidence in PBR proceedings. However, there has not to our knowledge been a scholarly and thorough non-technical review of PBR concepts and precedents serving as a reference for practitioners. This paper is intended to fill this gap. While not all-inclusive, we believe this PBR survey is the most authoritative and complete to date. Information is presented on approved plans for energy utilities in North America, Great Britain, and Australia. Analysis of plan design options is tendered reflecting the authors' practical experience. The paper is structured as follows. Section II discusses criteria economists use to select among alternative regulatory regimes. Section III examines cost of service regulation and introduces the PBR alternative. Sections IV through VI explore the main approaches to PBR in greater detail. The approaches examined are rate and revenue caps and benchmark regulation. In each of these sections, the regulatory mechanism is described, precedents are detailed, and the merits of the approach are evaluated. Sections VII and VIII explore two important sets of plan provisions that must be addressed under all of the general approaches. These are benefit sharing and plan termination provisions. Important details of IMAGE FORMULA10 energy PBR plans approved to date are summarized in the Appendix. Citations are provided for specific plans discussed in the text. II. CRITERIA FOR PLAN SELECTION In appraising alternative approaches to rate regulation, it is useful to have clear evaluation criteria. This chapter presents criteria widely used by economists in policy analysis. In later sections, we assess different regulatory systems primarily on the basis of these criteria. A. Efficiency In the view of economists, there are two fundamental criteria for evaluating regulatory systems. One is economic efficiency. A regulatory system is economically efficient to the extent that it generates the maximum possible net economic benefits for society. In appraising the efficiency of a regulatory regime, it is useful to recognize some major dimensions of efficiency. In this study, we separate efficiency into three components. These components are productive efficiency, allocative efficiency, and regulatory cost. 1. Productive Efficiency Utility regulation encourages productive efficiency to the extent that it induces the subject utility to meet the demand for its products at minimum cost. In the short run, some inputs are fixed in the sense that adjustments in the amounts used are quite expensive. Automated meter reading equipment is an example. Introduction of such equipment may save cost over time, but it would not be cost effective to transform the entire metering system in one year. In the short run, productive efficiency depends on meeting demand with a minimum-- cost mix of other, variable inputs. In the long run, all inputs are variable, and the cost-effective use of capital equipment is also a central efficiency concern. …

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.004
Scholarly communication0.0060.003
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0120.002

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 head0.008
GPT teacher head0.156
Teacher spread0.148 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueEnergy law journalSame topicElectric Power System OptimizationFrench-language works237,207