The Use of Battery Bank for Rationalization of Electricity in Broiler Poultry Farms
Bibliographic record
Abstract
Electricity is one of the main inputs used in poultry production. An aviary needs electricity to feed the various motors and electrical devices that compose the lighting systems, exhaustion, heating, food, among others. Aiming to give incentives to producers of broiler chickens, specifically in the state of Paraná, Brazil, in 2007, the Night Poultry Program was implemented, in which the government grants discounts in electricity tariff for poultry farmers at night. In this work it was proposed two energy storage systems through the use of lead-acid batteries and batteries of nickel chloride and sodium to feed the of charge of four brazillian aviaries over one year of poultry housing. For this purpose, it was evalueted the use of a bank of batteries in higher tariff, period comprising the time of 9:30 pm to 6 am of the next day, and charging the battery bank in reduced tariff period. The experiment was conducted using the electricity meters installed in the aviaries, weekly data of each aviary were collected and the active energy values, obtaining the data for six lots corresponding to a year of poultry accommodation. From the total consumption of active energy, it was calculated the average daily electricity consumption (kWh) for the set of aviaries. This value was used as input for the sizing of the battery banks. The two proposed storage systems demonstrate an alternative to energy supply for the rural areas, however the economical analysys indicates inviability, since the initial investment of the banks of batteries is high compared with the costs avoided with electricity by using these systems.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".