A Study on the Power Production Potential of Parking Space Solar Shelters in Kingston, Ontario
Notice bibliographique
Résumé
The implementation of solar shelters over top of parking spaces has the potential to make the production of renewable energy a secondary function of parking lots without impeding their ability to function as parking locations. This has the capacity to reduce the amount of natural space converted to solar farms as solar energy becomes more common. In addition, if these shelters are outfitted as charging stations for electric vehicles, they could serve as a driver for a cultural shift towards a more sustainable vehicle fleet. Implementation of this technology has begun on a small scale in San Diego, California and this project assessed the feasibility of implementation in Kingston, Ontario. This study set out to determine how much energy could be produced by a solar shelter over one parking space and how many parking spaces would be required to produce 1% of Kingston’s total electricity consumption. An insolation model was written in C, which used past climate data and mathematical models to incorporate the effects of latitude, cloud cover and snow. This model was compared to the current production in San Diego to check for validity. Since the insolation model was deemed to be valid, the results were used in conjunction with typical solar panel efficiencies in Kingston to calculate the potential energy production per structure. This was then used to determine the number of structures that would be required to provide 1% of Kingston’s electricity. Through literature review, it was determined that although snow on the panels would have a drastic effect on power production, it would not remain on the panels long enough to cause a significant effect. It was found that a single parking space in Kingston would be capable of generating 5500±_800^1000 kWh/year using the single-axis tracking model that is currently being implemented in San Diego, although a dual-axis tracking model would be capable of generating 11% more energy. Using the current prototype, Kingston would require implementation across about 2750 parking spaces in order to provide 1% of its electricity and it has ample locations which would be suitable. However, due to the current $40,000 price tag per structure, the current buy-back period is about 55 years which makes the current technology not economically feasible without lowering the cost or increasing the efficiency.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».