Energy and Economic Analysis for Greenhouse Envelope Design
Bibliographic record
Abstract
Abstract. The energy consumption of a building is significantly impacted by its envelope design, particularly for greenhouses where coverings typically provide high heat and daylight transmission. Energy and life cycle cost (LCC) analysis were used to identify the most cost-effective cladding design for a greenhouse located in Ottawa, Ontario, Canada (45.4° N) that employs supplemental lighting. The base case envelope design uses single glazing, whereas the two alternative designs consist of replacing the glass with twin-wall polycarbonate and adding foil-faced rigid insulation (permanent or movable) on the interior surface of the glass. All the alternative envelope designs increased electricity consumption for lighting and decreased heating energy use except when permanent or movable insulation was applied to the north wall and in the case of permanent insulation on the north wall plus polycarbonate on the east wall. This demonstrates how the use of reflective opaque insulation on the north wall can be beneficial for redirecting light onto the crops to achieve simultaneous reductions in electricity and heating energy costs. A maximum reduction in LCC of 5.5% (net savings of approximately $130,000) was achieved when permanent insulation was applied to the north and east walls plus polycarbonate on the west wall. This alternative envelope design increased electricity consumption for horticultural lighting by 4.3%, reduced heating energy use by 15.6%, and caused greenhouse gas emissions related to energy consumption to decrease by 14.7%. This analysis demonstrates how energy and economic analysis can be employed to determine the most suitable envelope design based on local climate and economic conditions. Keywords: Artificial lighting, Consistent daily light integral, Energy modeling, Envelope design, Greenhouse, Life cycle cost analysis, Light emitting diode, Local agriculture.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".