Occupancy measurement in commercial office buildings for demand-driven control applications—A survey and detection system evaluation

Labeodan, TM Timilehin; Zeiler, W Wim; Boxem, G.; Zhao, Yang

doi:10.1016/j.enbuild.2015.02.028

Cited by 277 publications

(146 citation statements)

References 30 publications

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“…In Cluster 8, such possibilities are examined in some cases such as building operations (Labeodan et al, 2015), demand-response programs (Lopez-Rodriguez and Hernandez-Tejera, 2015), and distribution grid congestion management with electric vehicles (Hu et al, 2015). The uncertainty in the behaviors of agents involved in a smart energy system can be estimated or examined by agent-based simulation.…”

Section: Resultsmentioning

confidence: 99%

Simulation-Based Approaches for Design of Smart Energy System: A Review Applying Bibliometric Analysis

Kikuchi

2017

J. Chem. Eng. Japan / JCEJ

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The design of energy systems has become an issue of worldwide interest. A single optimal energy system cannot be suggested because the availability of infrastructure and resources, and the acceptability of the system should be discussed locally with the involvement of all related stakeholders. A simulation-based approach is strongly needed for such a purpose. In this paper, the current major trends are reviewed on research activities related to smart energy systems. First, a bibliometric analysis of academic papers was conducted with the aim of visualizing clusters that indicate the hot topics attributable to smart energy systems. Considering the extracted research topics and representative references that are the core of each cluster, possible simulation-based approaches for the design of smart energy system are schematically structured on the basis of social, economic, and technological aspects. Through this study, the framework needed for the design of smart energy systems is characterized with simulation-based socioeconomic and technological analyses.

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Section: Resultsmentioning

confidence: 99%

Simulation-Based Approaches for Design of Smart Energy System: A Review Applying Bibliometric Analysis

Kikuchi

2017

J. Chem. Eng. Japan / JCEJ

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“…Usually, space efficiency is preliminary fixed in the design phase and the operating times of the buildings are fixed based on the purpose of the building. The occupancy levels, however, have to be monitored, which is currently not easy to do in a reliable and cheap way (for most advanced existing methods, see for example [27]). …”

Section: Meaning Of Building Occupancymentioning

confidence: 99%

Effects of Building Occupancy on Indicators of Energy Efficiency

2017

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Abstract:The potential to reduce energy consumption in buildings is high. The design phase of the building is very important. In addition, it is vital to understand how to measure the energy efficiency in the building operation phase in order to encourage the right efficiency efforts. In understanding the building energy efficiency, it is important to comprehend the interplay of building occupancy, space efficiency, and energy efficiency. Recent studies found in the literature concerning energy efficiency in office buildings have concentrated heavily on the technical characteristics of the buildings or technical systems. The most commonly used engineering indicator for building energy efficiency is the specific energy consumption (SEC), commonly measured in kWh/m 2 per annum. While the SEC is a sound way to measure the technical properties of a building and to guide its design, it obviously omits the issues of building occupancy and space efficiency. This paper studies existing energy efficiency indicators and introduces a new indicator for building energy efficiency which takes into account both space and occupancy efficiency.

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“…Data are acquired by measurement the conditions in the room for is used for calculating the amount of energy actually required and for control the distribution routes for efficient air distribution. As stated in [2,3], there are besides CO2 other measuring technologies which are experimentally tested, according [4,5] were tested even their combinations for their complementing, however, each technology has its own restrictions. Today´s most used CO2 sensors occupancy estimation is relatively exact but may interfere with long responsive time and air circulation patterns must be known.…”

Section: Next Steps In Research and Validation Of The Models And Discmentioning

confidence: 99%

Development the tool for demand control ventilation systems elements design and their impact to building life-cycle assessment: a review

Pinka

2018

MATEC Web Conf.

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Abstract. The paper describes possible methodology for DCV -demand control ventilation design process which will lead to solving the most important problems of more accurate ventilation system design, the efficiency: time and costs of design while improving its effectivity (level of design confidence, degree of uncertainty, financial parameters). For this purpose it has been started developing the tool implementing the methodology. Furthermore, it describes steps of testing and validation design process by implementation state-of-the-art algorithms for measuring the occupancy or CO2 detection for DCV system control testing sites and their comparison with computation design results. It describes also the reasons and necessity of decomposition of whole ventilation system to specific elements for the design and assessment procedure.

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Occupancy measurement in commercial office buildings for demand-driven control applications—A survey and detection system evaluation

Cited by 277 publications

References 30 publications

Simulation-Based Approaches for Design of Smart Energy System: A Review Applying Bibliometric Analysis

Simulation-Based Approaches for Design of Smart Energy System: A Review Applying Bibliometric Analysis

Effects of Building Occupancy on Indicators of Energy Efficiency

Development the tool for demand control ventilation systems elements design and their impact to building life-cycle assessment: a review

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