| Title | Analyzing Building Energy Consumption Patterns for Green Smart City Development Using a Data-driven Method |
|---|---|
| ID_Doc | 37057 |
| Authors | Zhang, J; Guo, X; Fu, H; Chen, TX; Zhang, Y |
| Title | Analyzing Building Energy Consumption Patterns for Green Smart City Development Using a Data-driven Method |
| Year | 2024 |
| Published | |
| Abstract | In the current era of dual-carbon construction, analyzing the energy consumption patterns of buildings is crucial for the development of green and low-carbon smart cities. This study analyzes the energy consumption of buildings with various functions, revealing the spatial and temporal patterns and their probability distributions. For the same type of buildings, the study further examines the correlations among main energy consumptions-water, electricity, and natural gas. The analysis is achieved by adopting the principal component analysis to reduce the dimensionality of high-dimensional building data, and employing the K-means clustering algorithm to categorize the energy consumption of buildings for various purposes. This study find that the energy consumption patterns of different functional buildings are different, and there is a positive correlation between all kinds of energy consumption, and the time variation is relatively strong. The conclusions can help to lay a solid foundation of building operations and maintenance in terms of the energy consumption and manage energy utilization for different regions and time periods for the development of green smart city. |
| https://www.atlantis-press.com/article/126001260.pdf |
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