Understanding household energy consumption behavior: The contribution of energy big data analytics

Zhou, Kaile; Yang, Shanlin

doi:10.1016/j.rser.2015.12.001

Cited by 330 publications

(152 citation statements)

References 88 publications

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“…By understanding the sphere of those motivational factors, research and development in the industry sector are assuming the capability of developing models to explain, predict, and replicate the decisionmaking process that leads humans to interact with the indoor environment having comparable endogenous and exogenous characteristics [121,141]. A considerable amount of MPC, behavioral models, modeling approaches, and behavioral campaigns have been developed, tested, evaluated, and critically reviewed over the last 30 years [18,19,64,65].…”

Section: Supporting Research Advancementsmentioning

confidence: 99%

“…Integrating building operating patterns with demand response logics that seek to balance energy loads and reduce the peak power demand in buildings is a current matter of research for energy utilities and program developers [64,[155][156][157]. One of the key challenges is the spread and market adoption of demand-side energy management technologies, bridging the research know-how with the deployment of real-time optimization of DR intelligent building automation systems.…”

Section: The Human Dimensions Of Building Services: Energy Utilities mentioning

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

301

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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: Supporting Research Advancementsmentioning

confidence: 99%

Section: The Human Dimensions Of Building Services: Energy Utilities mentioning

confidence: 99%

The human dimensions of energy use in buildings: A review

D’Oca

Hong

Langevin

2018

Renewable and Sustainable Energy Reviews

301

View full text Add to dashboard Cite

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“…Supported by the vast amount of available energy consumption and human-related data, together with the advancements in big data analysis techniques, scholars [20] proposed an interdisciplinary research framework at the boundaries of energy and social sciences bounded with data information science. A conceptual framework for assessing energy use in the domestic sector was developed by Kowsari and Zerriffi [21].…”

Section: Energy Use Also Input From Environmental Scientists Can Bementioning

confidence: 99%

Synthesizing building physics with social psychology: An interdisciplinary framework for context and occupant behavior in office buildings

D’Oca

Chen

Hong

et al. 2017

Energy Research & Social Science

113

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This study introduces an interdisciplinary framework for investigating building-user interaction in office spaces. The framework is a synthesis of theories from building physics and social psychology including social cognitive theory, the theory of planned behavior, and the driversneeds-actions-systems ontology for energy-related behaviors. The goal of the research framework is to investigate the effects of various behavioral adaptations and building controls (i.e., adjusting thermostats, operating windows, blinds and shades, and switching on/off artificial lights) to determine impacts on occupant comfort and energy-related operational costs in the office environment. This study attempts to expand state-of-the-art understanding of: (1) the environmental, personal, and behavioral drivers motivating occupants to interact with building control systems across four seasons, (2) how occupants' intention to share controls is influenced by social-psychological variables such as attitudes, subjective norms, and perceived behavioral control in group negotiation dynamic, (3) the perceived ease of usage and knowledge of building technologies, and (4) perceived satisfaction and productivity. To ground the validation of the theoretical framework in diverse office settings and contexts at the international scale, an online survey was designed to collect cross-country responses from office occupants among 14 universities and research centers within the United States, Europe, China, and Australia.

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“…After long-term endeavors, the first method has maintained a good momentum on the single equipment with manufacturing process improvement, material savings, and waste reduction [7][8][9]. As for the second method, energy-saving through optimization the manufacturing system faces great challenges due to changeable market demand, diversified product structure, and flexible processing routes [10][11][12], as well as insufficient accurate data of energy consumption [13,14], so researchers still struggle to break down these technical and theoretical barriers.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Distribution Algorithm for Energy-Efficient Scheduling in Turning Processes

et al. 2016

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Abstract:With the increasing concern for the environment, energy-efficient scheduling of the manufacturing industry is becoming urgent and popular. In turning processes, both spindle speed and processing time affect the final energy consumption and thus the spindle speed and scheduling scheme need to be optimized simultaneously. Since the turning workshop can be regarded as the flexible flow shop, this paper formulates a mixed integer nonlinear programming model for the energy-efficient scheduling of the flexible flow shop. Accordingly, a new decoding method is developed for the optimization of both spindle speed and scheduling scheme simultaneously, and an estimation of the distribution algorithm adopting the new decoding method is proposed to solve large-size problems. The parameters of this algorithm are determined by statistics from a simplified practical case. Validation results of the proposed method show that the makespan is shortened to a large extent, and the consumed energy is significantly saved. These results demonstrate the effectiveness of the proposed mathematical model and algorithm.

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Understanding household energy consumption behavior: The contribution of energy big data analytics

Cited by 330 publications

References 88 publications

The human dimensions of energy use in buildings: A review

The human dimensions of energy use in buildings: A review

Synthesizing building physics with social psychology: An interdisciplinary framework for context and occupant behavior in office buildings

Estimation of Distribution Algorithm for Energy-Efficient Scheduling in Turning Processes

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