Exploring the sensitivity of residential energy consumption in China: Implications from a micro-demographic analysis

Fu, Chonghui; Wang, Wenjun; Jian, Tang

doi:10.1016/j.erss.2014.04.010

Cited by 27 publications

(17 citation statements)

References 20 publications

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“…Existing literature highlights residential building occupancy patterns as a key driver of building performance worldwide [30,36,42]. Similarly, simulation studies have shown that office workers who are proactive in saving energy (dimming lights, turning on HVAC systems only when needed, turning off plug loads and equipment when not needed) consume up to 50% less than occupants who do not [11].…”

Section: 22supporting Research Advancementsmentioning

confidence: 99%

“…The notion of HIL emerges from the cyber-physical area [39][40][41][42], as an application that integrates real-time human feedback with the management of complex systems for control optimization purposes. A variety of existing HIL applications in the energy sector can be classified based on the level of integration of human control over system functioning-as active, passive, or hybrid active-passive sensing and control systems.…”

Section: 32supporting Research Advancementsmentioning

confidence: 99%

“…Additionally, smart energy meters and pervasive environmental sensing technologies promote data-rich building environments that help to infer which occupant behaviors hold the greatest influence on energy performance outcomes [65][66][67]. Researchers have drawn from these available data sources in identifying correlations between observed system states (i.e., windows being opened/closed [31,38,48,[72][73][74][75][76][77][78][79][80][81][82], shades and blinds being drawn [79][80][81][82][83][84][85]); conditions or variables of the indoor and outdoor environment (i.e., indoor and outdoor air temperature, relative humidity); the attitudes, beliefs, satisfaction [86][87][88][89][90][91][92][93][94] and socio-demographic aspects of the occupant population [42,[99][100][101][102][103]; and actual building energy performance.…”

Section: 12supporting Research Advancementsmentioning

confidence: 99%

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The human dimensions of energy use in buildings: A review

D’Oca

Hong

Langevin

2018

Renewable and Sustainable Energy Reviews

291

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The "human dimensions" of energy use in buildings refer to the energy-related behaviors of key stakeholders that affect energy use over the building life cycle. Stakeholders include building designers, operators, managers, engineers, occupants, industry, vendors, and policymakers, who directly or indirectly influence the acts of designing, constructing, living, operating, managing, and regulating the built environments, from individual building up to the urban scale. Among factors driving high-performance buildings, human dimensions play a role that is as significant as that of technological advances. However, this factor is not well understood, and, as a result, human dimensions are often ignored or simplified by stakeholders. This paper presents a review of the literature on human dimensions of building energy use to assess the state-of-the-art in this topic area. The paper highlights research needs for fully integrating human dimensions into the building design and operation processes with the goal of reducing energy use in buildings while enhancing occupant comfort and productivity. This research focuses on identifying key needs for each stakeholder involved in a building's life cycle and takes an interdisciplinary focus that spans the fields of architecture and engineering design, sociology, data science, energy policy, codes, and standards to provide targeted insights.Greater understanding of the human dimensions of energy use has several potential benefits including reductions in operating cost for building owners; enhanced comfort conditions and productivity for building occupants; more effective building energy management and automation systems for building operators and energy managers; and the integration of more accurate control logic into the next generation of human-in-the-loop technologies. The review concludes by summarizing recommendations for policy makers and industry stakeholders for developing codes, standards, and technologies that can leverage the human dimensions of energy use to reliably predict and achieve energy use reductions in the residential and commercial buildings sectors.

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Section: 22supporting Research Advancementsmentioning

confidence: 99%

Section: 32supporting Research Advancementsmentioning

confidence: 99%

Section: 12supporting Research Advancementsmentioning

confidence: 99%

See 1 more Smart Citation

The human dimensions of energy use in buildings: A review

D’Oca

Hong

Langevin

2018

Renewable and Sustainable Energy Reviews

291

View full text Add to dashboard Cite

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“…Research has focused on developing interdisciplinary observation methods regarding individual, collective, and social motivations, as they are crucial in influencing behavioral patterns, and have various consequences for building energy consumption and indoor environmental comfort. Subjective measurements have been employed extensively to identify individuals' responses to indoor environments, to identify the dominant factors influencing occupant interaction with building control systems, and to record information about human-building interaction [34][35][36][37][38][39][40][41][42][43][44][45]. Subjective occupant data are typically gathered using self-reporting methods, such as mail-or web-based surveys or interview techniques.…”

Section: B Subjective Measurementsmentioning

confidence: 99%

Ten questions concerning occupant behavior in buildings: The big picture

Hong

Yan

D’Oca

et al. 2017

Building and Environment

417

196

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Occupant behavior has significant impacts on building energy performance and occupant comfort. However, occupant behavior is not well understood and is often oversimplified in the building life cycle, due to its stochastic, diverse, complex, and interdisciplinary nature. The use of simplified methods or tools to quantify the impacts of occupant behavior in building performance simulations significantly contributes to performance gaps between simulated models and actual building energy consumption. Therefore, it is crucial to understand occupant behavior in a comprehensive way, integrating qualitative approaches and data-and model-driven quantitative approaches, and employing appropriate tools to guide the design and operation of low-energy residential and commercial buildings that integrate technological and human dimensions. This paper presents ten questions, highlighting some of the most important issues regarding concepts, applications, and methodologies in occupant behavior research. The proposed questions and answers aim to provide insights into occupant behavior for current and future researchers, designers, and policy makers, and most importantly, to inspire innovative research and applications to increase energy efficiency and reduce energy use in buildings.

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“…Chen et al [18] analyzed the data of residential energy consumption in Hangzhou and find that the resident age structure has more influence than income. Fu et al [19] conducted a micro-demographic analysis on residential energy consumption in China and indicated that population change, urbanization and aging are sensitive, while population age is not, except for the 60+ age group. Golley [20] extended the notion of household energy consumption by including indirect energy requirements, then examined the extent of variation in total energy requirements and emissions across households with different income levels in China and, finally, identified that, while richer households do indeed emit more per capita, poorer households tend to be more emissions-intensive.…”

Section: Introductionmentioning

confidence: 99%

Factor Analysis of Residential Energy Consumption at the Provincial Level in China

et al. 2014

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This paper analyzes the differences in the amount and the structure of residential energy consumption at the provincial level in China and identifies the hidden factors behind such differences. The econometrical analysis reveals that population, economic development level, energy resource endowment and climatic conditions are the main factors driving residential energy consumption; while the regional differences in energy consumption per capita and the consumption structure can be mainly illustrated by various economic development levels, energy resource endowments and climatic conditions. Economic development level has a significant positive impact on the proportion of gasoline consumption, whereas its impact on the proportion of electricity consumption is not notable; energy resource endowment and climatic condition indirectly affect both the proportion of electricity consumption and that of gasoline consumption, primarily through their impacts on the proportions of coal consumption and heat consumption.

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Exploring the sensitivity of residential energy consumption in China: Implications from a micro-demographic analysis

Cited by 27 publications

References 20 publications

The human dimensions of energy use in buildings: A review

The human dimensions of energy use in buildings: A review

Ten questions concerning occupant behavior in buildings: The big picture

Factor Analysis of Residential Energy Consumption at the Provincial Level in China

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