Smart City Gnosys
Smart city article details
| Title | Integrated System Concept For Energy Efficient Smart Buildings And Cities |
|---|---|
| ID_Doc | 31909 |
| Authors | Gökçe H.U.; Gökçe K.U. |
| Year | 2014 |
| Published | Progress in Sustainable Energy Technologies Vol II: Creating Sustainable Development |
| DOI | http://dx.doi.org/10.1007/978-3-319-07977-6_19 |
| Abstract | The quality of life in Europe’s cities states that although quality of life has improved in many areas, in other areas such as environmental issues and energy efficiency have deteriorated. In such places, people, companies and public authorities experience specific needs and demands regarding domains such as energy efficiency, environment and transportation services. These domains are increasingly enabled and facilitated by web-based applications, service oriented architectures, ubiquitous sensing infrastructure, advanced information management applications such as data warehousing and data mining technologies which generate actionable information for intelligent and predictive control for further optimised smart buildings and cities. The engineering and deployment of off-the-grid energy production systems for buildings addressing the renewable energy technologies (e.g. wind, solar, geothermal) and integration of these systems to the city level grid applications with the ICT-based sub-systems becomes a necessity. This paper addresses an integrated building concept that operates on energyefficient basis while capturing retrofit opportunities that scale from a single building to multiple buildings at cities level. The proposed concept is developed based on two research areas; (1) Building energy supply-side (microgrid) management and (2) Building energy demand-side management complementing with the integrated energy production from renewable energy sources, building energy diagnostics and predictive control, ubiquitous wireless sensing technologies, and microgrid power electronics and power control to exploit the potential for reduction of building energy consumption, thus addressing the deficit of insufficient tool support. The research findings will be demonstrated in an appropriately selected building in Hannover, Germany with EOS Sustainable Energy Solutions GmbH. This will be achieved by integrating different energy generation systems addressing the renewable energy technologies coupled with energy storage systems and building energy management systems comprising scalable and robust sensing network platforms, energy performance monitoring and data warehouse technologies. © Springer International Publishing Switzerland 2014. |
| Author Keywords | Artificial intelligence; Energy efficiency; Renewable energy; Smart buildings |
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