Building geometry-aware lifecycle optimization of hybrid renewable energy systems with solid gravity storage
Bibliographic record
Abstract
Urban buildings face challenges in integrating intermittent-supply renewable electricity sources while conforming to space and economic constraints. Solid gravity energy storage (GS) has not yet been explored in building applications despite its mechanical simplicity and long lifespan. The current literature lacks studies that link GS' optimal capacity to building geometry and energy intensity. This study introduces a novel hybrid energy system for buildings that combines façade-mounted PV panels, small rooftop wind turbines, Li-Ion batteries, and a rope-hoist-based GS. A multi-objective optimization framework is developed to minimize both the levelized cost of electricity (LCOE) and grid dependency (GD), considering realistic dispatch logic and annual operation. The system is optimized for 625 parametric building designs covering different energy use intensities (EUI) and geometric configurations, defined by façade area-to-volume, length-to-width, and height-to-footprint ratios. Tradeoff solutions achieved LCOE values between 0.051 and 0.111 USD/kWh, and GD between 0.195 and 0.888. GS was found to be the most impactful component on system autonomy, with the ratio between its capacity and the building's average daily demand ranging from 0.0 to 1.0 and strongly correlating with GD. Most optimal designs used PV extensively, wind turbines moderately, and batteries minimally. Payback periods ranged from 9 to 17 years, and carbon intensity values remained mostly below the Canadian average. Overall, the study highlights the synergy between the building design and the extent to which GS, as well as solar and wind systems, should be sized, hence offering a practical direction for low-carbon and resilient buildings. • A novel gravity storage system is proposed for urban building energy systems. • Renewable sources and storage units are optimized for different buildings. • Gravity storage size strongly impacts grid independence across building designs. • LCOE values range from 0.051 to 0.111 USD/kWh across 625 building designs. • Trade-off designs achieve low carbon intensity and competitive electricity costs.
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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 | 0.000 | 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".