A clustering-based climatic zoning method for office buildings in China

Deng, Xianmo; Tan, Zijing; Tan, Meijing; Chen, Wenjing

doi:10.1016/j.jobe.2021.102778

Cited by 11 publications

(3 citation statements)

References 29 publications

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“…Based on the above seasonal segmentation, we aim to model the thermal profiles of offices in layer 3 using unsupervised learning techniques. However, it is important for these algorithms to deal with scale invariance to prioritize the shape features of the thermal patterns over amplitude features, especially for time series clustering [33][34][35]. Therefore, z-normalization was used to normalize the thermal profiles:…”

Section: Indoor Thermal Information Managementmentioning

confidence: 99%

Smart Building Thermal Management: A Data-Driven Approach Based on Dynamic and Consensus Clustering

Chen,

Dai,

Meng

2023

Sustainability

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A customized and cost-effective building thermal control system is critical for accommodating thermal performance differences within the building, as well as satisfying the individual thermal comfort needs of occupants. Moreover, incorporating a building indoor thermal simulation procedure into the thermal control system can reduce the necessity of installing various expensive sensors (e.g., wearable sensors for personal thermal comfort management) in individual offices, as well as the requirement of extensive computing facilities without rendering the control performance, resulting into more sustainable building operations. An important step in achieving the above-mentioned goal is understanding how different offices/rooms behave differently given the same outdoor weather conditions. This study proposes a smart building indoor thermal profiling system to identify underlying physical factors that affect thermal performance in different seasons and to track dynamic cluster trajectories of considered offices to suggest indoor thermal optimization strategies. A consensus-based clustering approach is adopted to robustly cluster offices into different groups based on their hourly indoor temperature profiles for different seasons. Experimental results showed that our proposed approach could effectively discover more indoor thermal patterns in the buildings and is able to identify distinct dynamic cluster trajectories across four seasons (i.e., eight distinct dynamic trajectories in our case study). The data-driven analysis conducted in this study also indicated promising applications of the proposed smart building indoor thermal profiling system in effectively guiding the design of customized thermal control strategies for buildings. It also suggested that the proposed approach could be applied to a wide range of other applications, such as customized building energy management, energy pricing, as well as the economic benefit analysis of building retrofits and design.

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Section: Indoor Thermal Information Managementmentioning

confidence: 99%

Smart Building Thermal Management: A Data-Driven Approach Based on Dynamic and Consensus Clustering

Chen,

Dai,

Meng

2023

Sustainability

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“…Geographic units are relatively consistent units that are divided by the geographical environment and regional differences. The methods employed in the divided geographical units include remote sensing (RS) recognition [3][4][5][6][7], overlay analysis [8], land type clustering [9][10][11][12][13][14][15], etc. RS recognition is rich in data sources.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Comprehensive Land Consolidation in Cultivated Land Reserve Resource Areas Based on Two-Level Geographical Unit Division

Li,

Zhang,

Luo

et al. 2024

Land

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The scientific and reasonable division of geographical units of cultivated land reserve resource areas is an important foundation for comprehensive land consolidation (CLC). Saline–alkali land is an important cultivated land reserve resource, and is significant for ensuring food security. This paper constructs a two-level land consolidation index system for cultivated land reserve resource areas. The Kruskal graph theory clustering algorithm was used to divide the study area into four types of ecological zones. On the basis of ecological zones, the study area was further divided into three types of consolidation units. Finally, the spatial relationship between ecological zoning and land use types was clarified, and the classification distribution of land consolidation potential was determined through an analysis of the CLC of two-level geographical units. Da’an City, Jilin province, China, was selected as the study area. The results of this study show the following: (1) In Da’an City, the conservation priority areas are concentrated in the north, the development priority areas are concentrated in the central and southern areas, and the comprehensive upgrade areas and adjustment rebuilding areas are in the transition zones. (2) The CLC potential trend is low in the north but high in the south in Da’an City. This paper proposes a framework for a geographical unit delineation method for saline–alkali-enriched cultivated land reserve resource zones, and analyzes the spatial layout of ecological protection demands and land consolidation potential in Da’an City. The results and conclusions of this study will provide a reference for CLC in cultivated land reserve resource areas.

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“…Li et al 19 utilized the data cluster approach named the K-Nearest neighbours algorithm archiving the hourly electricity prediction. Deng et al 20 proved that the K-means algorithm has a good performance with respect to the climatic zone grouping. Deng et al 21 employed multiple linear regression to analyze the relationship between the building energy consumption group and residential layout.…”

Section: Introductionmentioning

confidence: 99%

The building plan automatic design optimization based on CFD numerical intelligent simulation

Chen

2022

Indoor and Built Environment

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To apply the thermal comfort to the optimization of building layout, a variable design method based on Kmeans clustering is proposed. The evaluation was based on numerical simulation, genetic algorithm and universal thermal climate index (UTCI) to implement the building layout optimization on Matlab. Finally, the building layouts with centralized type, decentralized type and edge flow type water configuration were optimized, respectively. The results show that after the optimization, a reduction of 0.1∼0.6°C of UTCI was observed. We concluded that under moderate heat stress, the increase in wind velocity is the key to thermal comfort improvement.

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A clustering-based climatic zoning method for office buildings in China

Cited by 11 publications

References 29 publications

Smart Building Thermal Management: A Data-Driven Approach Based on Dynamic and Consensus Clustering

Smart Building Thermal Management: A Data-Driven Approach Based on Dynamic and Consensus Clustering

Analysis of Comprehensive Land Consolidation in Cultivated Land Reserve Resource Areas Based on Two-Level Geographical Unit Division

The building plan automatic design optimization based on CFD numerical intelligent simulation

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