Тарифні коефіцієнти на електроенергію для акумуляційних систем опалення, вентиляції та кондиціонування повітря
Bibliographic record
Abstract
Background. The most efficient use of available electricity capacity during the hours of consumption decline is very important problem in Ukraine. This article provides an analysis of the actual tariff policy and the use of electricity during the hours of the low tariff for heating, ventilation and air conditioning systems.Objective. The aim of the paper is to analyze the set validity periods of the reduced prices for electrical energy. Priority attention is paid to the tariff policy differences for the cost of electricity in Ukraine and abroad and how these differences affect possible storage system cost and, thus, payback period.Methods. The general feasibility of using electricity as the heat source is presented, different energy sources as a generator of heat are compared, the possibility of strengthening cooperation between producers and consumers of electricity in order to achieve optimal modes of generation and consumption of heat is stated, the tariff plans for electricity in Ukraine and abroad are provided.Results. As a result of the work it was made the comparison of tariff policy in Ukraine and three other countries: the UK, Canada and Spain. It is shown that overseas tariff rates are more flexible than in Ukraine, and promotes more effective relationships between the power generating companies and consumers in both economic and technological aspects. It was also shown that additional day charging can significantly reduce a necessary amount of heat storage material as well as the set power of the system.Conclusions. At the current level of technological development, the actual policy for determining electricity tariffs should be based on innovative technologies, for example, on the dynamic determination of the electricity cost. It becomes relevant with the growth of the share of renewable energy sources in general electricity generation.
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How this classification was reachedexpand
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".