Bibliographic record
Abstract
I. INTRODUCTION On August 14, 2003, the East Coast of the United States and parts of Canada experienced one of the largest blackouts in history. (1) The blackout originated in a small area in Ohio, yet ultimately affected over fifty million people in eight states and one Canadian province. (2) In the end, the total cost estimates were between four billion and ten billion dollars. (3) This recent example illustrates the level of national dependency and instability that our electricity system allows. This current state of our electricity grid has resulted from a combination of government regulatory actions and natural market forces. (4) Naturally, then, the solution must be likewise multi-faceted. (5) Distributed Generation (6) offers one micro solution to this macro problem by encouraging more localized generation through smaller, closed systems. This Comment will argue that the federal government, through policy incentives and law, should be promoting distributed generation to supplement and stabilize our current grid and to allow more widespread use of renewable resources. This Comment will discuss the feasibility of, and problems with, distributed generation as a solution to the energy problems currently faced by the United States, focusing on federal initiatives that should be undertaken. Part II briefly discusses the history of electricity generation in the United States, explaining the background on how the current landscape developed. Part III explores the Energy Policy Act of 2005, which is the federal statute that sets forth the federal government's energy policy. (7) Specifically, Part III discusses renewable energy and distributed generation policy on the federal level and how the slack left in federal policy falls on the states to make up. Part IV discusses the problems with our current system and suggests why it is not a sustainable long-term solution to meet future electricity needs. This part includes a discussion of externalities that are unaccounted for in traditional electricity generation, and the widely underestimated problem of grid unreliability. Part V introduces distributed generation as one potential solution to these current problems. Also discussed in this part is distributed generation as a vehicle for introducing renewable energy sources into the grid. Part VI offers some ideas for realistically integrating distributed generation into our grid on a large-scale basis including: load response programs or incentives, federal encouragement of local installed capacity markets, federal net metering standards, and federal municipality incentives and tax credits to offset costs. Lastly, Part VII looks at New York's approach to distributed generation and how it differs in scope and level of commitment from the federal approach. Overall, the federal response and action toward distributed power generation has been a failure, forcing the states to intervene independently. II. HISTORY OF ELECTRICITY MARKET DEREGULATION The late 1800s marked the electrification of the United States. With it, small privately owned generators began serving customer's electric power needs at cost-based prices. (8) However, many factors pushed the nation to restructure this localized system into a privately-owned, centralized system. (9) As a result, during the early 1900s, many of the small generation resources were purchased by larger privately-owned holding companies, (10) and by 1930, about sixteen companies owned seventy-five percent of the generators in the United States. (11) In response to the changing industry, Congress enacted the Public Utility Holding Company Act, (12) which initiated the regulation of such holding companies. (13) Furthermore, Congress created the Federal Power Commission in 1935, which eventually became the Federal Energy Regulatory Commission (FERC) in 1977.14 Also at this time, the federal government began to subsidize target development of power systems through legislation such as the Rural Electrification Act, (15) where loans and assistance were given to electricity providers in rural areas. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".