Comparative analysis of window operating behavior in three different open-plan offices in Nanjing

Ren, Jiawen; Zhou, Xia; An, Jingjing; Yan, Da; Shi, Xing; Jin, Xing; Zheng, Shaoyan

doi:10.1016/j.enbenv.2020.07.007

Cited by 15 publications

(4 citation statements)

References 26 publications

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“…However, one of the greatest common occupant behaviors in buildings is the window operating behavior [22]. Based on the observation and analysis of 35 buildings, it was found that a strong correlation lies between temperatures (outdoor weather temperature and indoor air temperature) and window operation [104].…”

Section: Impact Of Windowmentioning

confidence: 99%

“…Despite the impact of window glazing, only a few studies explicitly considered and emphasized the essentiality, and potential benefits or drawbacks [6,23,54,104]. Ghosh and Neogi (2018) stipulated that, although glazed facades are progressively being utilized in contemporary buildings to ease interior daylight accessibility and also to beautify the building architecturally, the increased application of glazed facades is engendering a greater solar gain on the internal part of the building, which is gradually becoming a major problem in hot climate regions.…”

Section: Impact Of Windowmentioning

confidence: 99%

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Comprehensive Analysis of Influencing Factors on Building Energy Performance and Strategic Insights for Sustainable Development: A Systematic Literature Review

Olu-Ajayi,

Alaka,

Egwim

et al. 2024

Sustainability

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A prerequisite for decreasing the intensification of energy in buildings is to evaluate and understand the influencing factors of building energy performance (BEP). These factors include building envelope features and outdoor climactic conditions, among others. Based on the importance of the influencing factors in the development of the building energy prediction model, various researchers are continuously employing different types of factors based on their popularity in academic literature, without a proper investigation of the most relevant factors, which, in some cases, potentially leads to poor model performance. However, this can be due to the absence of an adequate comprehensive analysis or review of all factors influencing BEP ubiquitously. Therefore, this paper conducts a holistic and comprehensive review of studies that have explored the various factors influencing energy use in residential and commercial buildings. In total, 74 research articles were systematically selected from the Scopus, ScienceDirect, and Institute of Electrical Electronics Engineers (IEEE) databases. Subsequently, by means of a systematic and bibliometric analysis, this paper comprehensively analyzed several important factors influencing BEP. The results reveals the important factors (such as windows and roofs) and engendered or shed light on the application of some energy-efficient strategies such as the utilization of a green roof and photovoltaic (PV) window, among others.

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Section: Impact Of Windowmentioning

confidence: 99%

Section: Impact Of Windowmentioning

confidence: 99%

Comprehensive Analysis of Influencing Factors on Building Energy Performance and Strategic Insights for Sustainable Development: A Systematic Literature Review

Olu-Ajayi,

Alaka,

Egwim

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…The low proportion of studies that utilized occupancy features could be due to the inability to easily obtain these data [22,105]. However, observation and examination of 35 buildings elicited that there is a high correlation between outdoor weather (i.e., temperature, wind speed) and building properties (window, wall) [106]. It is also concluded that the lower the U-values of windows ultimately results in better energy performance of the building [107].…”

Section: Data Properties-types Of Featuresmentioning

confidence: 99%

Data-Driven Tools for Building Energy Consumption Prediction: A Review

et al. 2023

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The development of data-driven building energy consumption prediction models has gained more attention in research due to its relevance for energy planning and conservation. However, many studies have conducted the inappropriate application of data-driven tools for energy consumption prediction in the wrong conditions. For example, employing a data-driven tool to develop a model using a small sample size, despite the recognition of the tool for producing good results in large data conditions. This study delivers a review of 63 studies with a precise focus on evaluating the performance of data-driven tools based on certain conditions; i.e., data properties, the type of energy considered, and the type of building explored. This review identifies gaps in research and proposes future directions in the field of data-driven building energy consumption prediction. Based on the studies reviewed, the outcome of the evaluation of the data-driven tools performance shows that Support Vector Machine (SVM) produced better performance than other data-driven tools in the majority of the review studies. SVM, Artificial Neural Network (ANN), and Random Forest (RF) produced better performances in more studies than statistical tools such as Linear Regression (LR) and Autoregressive Integrated Moving Average (ARIMA). However, it is deduced that none of the reviewed tools are predominantly better than the other tools in all conditions. It is clear that data-driven tools have their strengths and weaknesses, and tend to elicit distinctive results in different conditions. Hence, this study provides a proposed guideline for the selection tool based on strengths and weaknesses in different conditions.

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“…In China, it has been suggested in the literature that studies divorced from user behavior cannot fundamentally achieve the energy efficiency goal in buildings [61]. The use of windows and doors [62], air conditioners [63][64][65], and lighting [66,67] by occupants has a substantial impact on building energy consumption. The importance of occupants' behavior has been overlooked for a long time in building energy efficiency, while the emphasis has been on the optimization and innovation of various technologies and equipment [68].…”

mentioning

confidence: 99%

Demand-Oriented Review of a Dynamic Energy-Loss Monitoring System for Primary School Buildings through Micro-Environmental Data Monitoring and Occupant Behavior Analysis

Peng,

Yu,

Guan

2023

Buildings

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The utilization of primary school buildings is multifaceted, primarily due to the high occupancy density, varying thermal preferences among occupants, diverse indoor activities (such as walking, sports, and conversation), and a constant flow of individuals entering and exiting the building. This results in the frequent opening and closing of external windows and doors and fluctuations in internal heat gain. Consequently, frequent interactions between the indoor and outdoor microenvironments lead to energy losses. This study conducts a comprehensive literature review on building energy loss stemming from occupant behavior and the interactions between indoor and outdoor microenvironments. Furthermore, it proposes a dynamic real-time monitoring system based on a foundation of computer data capture and a visualization platform for building energy loss. The research methods include data crawling, data association rule mining, and data association analysis. The research findings yield a universally applicable and informative building energy-saving design system based on extensive data analysis. Additionally, the system presents information on occupants’ behavior and the microclimate data of indoor and outdoor environments on a computer screen, facilitating human–machine communication and enabling timely adjustments to be made, thus facilitating the construction of design strategies for new buildings and operation and maintenance strategies for existing buildings.

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Comparative analysis of window operating behavior in three different open-plan offices in Nanjing

Cited by 15 publications

References 26 publications

Comprehensive Analysis of Influencing Factors on Building Energy Performance and Strategic Insights for Sustainable Development: A Systematic Literature Review

Comprehensive Analysis of Influencing Factors on Building Energy Performance and Strategic Insights for Sustainable Development: A Systematic Literature Review

Data-Driven Tools for Building Energy Consumption Prediction: A Review

Demand-Oriented Review of a Dynamic Energy-Loss Monitoring System for Primary School Buildings through Micro-Environmental Data Monitoring and Occupant Behavior Analysis

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