Electric utility deregulation: failure or success
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.
Bibliographic record
Abstract
The electric utilities approach for restructuring the power market determines the failure or success of electric utility deregulation. It will cost billions of dollars, if restructuring is not done properly. Federal Energy Regulatory Commission (FERC) Order 2000 endorses competitive power markets, and price signals for the purpose of managing electricity grid congestion and achieving reliability. In a deregulated competitive electricity market, companies have to pay for the reactive power losses out of the revenues they earn. If the investors are reimbursed for reliability, there might be more investments. California deregulated in 1998 but the deregulated market was not structured efficiently and allowed some companies to manipulate the market by sending the power out of California and then reselling it back into the state. The utilities were not allowed long-term contracts and were required to sell many of their existing plants. California's experience is unique; in fact, when done well, the success stories in Pennsylvania, Ohio, Texas, England, and Japan show the benefit to both consumers and sellers from electric utility deregulation. Deregulation has been successful in New York, Virginia, and Ontario by protecting the customers from price volatility by price caps. By definition, price caps are not effective in a deregulated market, however, a price cap (i.e., a little regulation) to protect consumers in the transition period to deregulation is good. The price caps can be removed at a later date when the deregulated industry has matured like the power market in New Jersey. Circumstances like the August 14th, 2003 blackout in the northeast of the United States (not caused by deregulation) brought industry uncertainty to investors and consumers. Under deregulation, dispersed power generation (such as co-generation, biomass, microturbines, solar photovoltaic cells, wind turbines, fuel cells, geothermal, and diesel generators) is being promoted vigorously and more prominence is being put in the ancillary services and FACTS devices because of shortage of transmission lines in a deregulated power market. One of the results of economic deregulation of the electric power industry has been the development of a market for advanced nuclear power plants that will be cheaper to build and cheaper to run. In conclusion, by implementing a limited price control, the electric utility deregulation can be successful.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it