Coupling of Wind Power Heating with High Energy-Consuming Industries to Increase Wind Power Consumption in Xinjiang, China
Bibliographic record
Abstract
Numerous problems have emerged with the rapid development of wind power in Xinjiang. The predominant problem is the inhibition of the healthy development of the wind power industry by wind power curtailment in Xinjiang. In this study, wind power heating and high energy-consuming industries were coupled to increase wind power consumption in Xinjiang on the load side. The feasibility analysis of wind power heating in Dabancheng showed that the heating load characteristics coincide with the wind characteristics and the electric heating technology can fulfill the requirements for wind power heating. A business model innovation achieved a win–win situation. Furthermore, a wind power heating system was designed in Dabancheng, the boiler capacity and the heat storage capacity were calculated, and a heating system model with heat storage technology was established. Wind power heating with heat storage can improve the consumption of wind power and increase the local electric load and system adjustability. Furthermore, heating with curtailed wind power can save 2942 tons of standard coal as well as reduce 5172 tons of CO2, 2.9 tons of SO2, 22 tons of NOX, and 2 tons of soot emissions. Non-grid-connected distributed wind power was applied to the high energy-consuming coal chemical industry to reduce wind power curtailment, expand the consumption market, and reduce pollution. A multifunctional wind-photovoltaic complementary system with hydrogen energy storage coupled with traditional high energy-consuming coal chemical industry was established. The implementation plan using wind and solar energy to produce, store, and apply hydrogen energy was proven beneficial. Wind power consumption was improved on the load side. The wind power curtailment problem was reduced by increasing local load using the curtailed wind power to provide clean heat in Dabancheng and constructing the multifunctional wind–photovoltaic complementary system. This study will contribute to the healthy and sustainable development of the wind power industry in Xinjiang.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".