Abstract
Wind power generation is playing an increasingly important role in delivering clean, smart, and sustainable energy. Onshore as well as in offshore wind energy Plants capture the power of the wind and produce a renewable energy. In the case of non-cohesive soil, onshore wind turbines are often founded on a shallow foundation with a circular or octagonal shape. The shallow foundation costs represent a considerable portion of the total construction costs and produces a huge amount of Carbon dioxide. Therefore, an economic optimization of the type of foundation is highly required. An innovative foundation type would be a pier foundation, which combines the load transfer over the foundation area at the pier base with the transfer of horizontal loads over the shaft surface area of the pier. Also, the excavated soil will be used to fill the pier construction. This system is called Patrick and Henderson system. This paper aims to compare the behavior of a pier foundation with traditional shallow foundation using Finite Element Method. A systematic analysis of the results at different load levels shows that the application of the typical pier foundation for small onshore wind turbines leads to a high saving of concrete mass, Carbon dioxide Emission (Carbon Footprint) and finally the total cost.
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2nd International Conference on Smart Cities 4.0 |
| Seiten | 318-323 |
| Seitenumfang | 6 |
| ISBN (elektronisch) | 978-1-6654-7430-6 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 2023 |
UN-Ziele für nachhaltige Entwicklung (SDGs)
2015 einigten sich die UN-Mitgliedstaaten auf 17 globale Ziele für nachhaltige Entwicklung (Sustainable Development Goals, SDGs) zur Beendigung von Armut, zum Schutz des Planeten und zur Förderung des allgemeinen Wohlstands. Hiermit leisten wir einen Beitrag zu folgendem/n Ziel(en) für nachhaltige Entwicklung (SDGs):
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SDG 7 Erschwingliche und saubere Energie
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SDG 11 Nachhaltige Städte und Gemeinschaften
ASJC Scopus Sachgebiete
- Informationssysteme und -management
- Artificial intelligence
- Energieanlagenbau und Kraftwerkstechnik
- Computernetzwerke und -kommunikation
- Verkehr
- Urban studies
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