Synergy of green hydrogen and Li-ion battery with electrification in hourly power supply and demand projection to 2050: A case study
Bibliographic record
Abstract
Long-term projections of electricity supply and demand on a national scale, especially with hourly frequency, are significantly rare but essential for determining the appropriate sizes of both long-term and short-term energy storage. This is particularly important during the transitional phase of energy systems. This study uses Denmark as a case study to project electricity supply and demand from 2025 to 2050 with hourly frequency in countries with high wind energy potential but low solar energy potential. Various macro and micro scenarios were examined to determine the necessary sizes for long-term and short-term energy storage from 2025 to 2050. In addition to determining the size of energy storage from 2025 to 2050, the findings highlighted two significant points. First, for countries to achieve energy independence and reduce reliance on energy imports, the ratio of annual electricity supply to demand should exceed 1.3, particularly when the share of renewables is significant (considering losses in Power-to-Hydrogen and Hydrogen-to-Power processes). Second, installing residential photovoltaic (PV) panels without batteries has a return on investment (ROI) of 50.15 %. In contrast, the ROI for installing both PV panels and batteries is −5.91 %. Thus, it is more cost-effective for households to install residential PV panels without batteries. • Electrification in heating and mobility considered in an hourly frequency for a year. • The adoption of installing residential solar panels considered. • Dynamic pricing is conducted based on generation cost in different years. • Demand of hydrogen calculated for two conditions (high and moderate supply) • Installing PV panels without battery is more profitable than PV panels with batteries for households.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".