From simulation to monitoring: Evaluating the potential of mixed-mode ventilation (MMV) systems for integrating natural ventilation in office buildings through a comprehensive literature review

Salcido, Juan C.; Raheem, Adeeba A.; Issa, Raja R. A.

doi:10.1016/j.enbuild.2016.06.054

Cited by 70 publications

(39 citation statements)

References 61 publications

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“…Comprehensive reviews focus on behavioral change programs and behavioral impacts on energy savings [9][10][11][12]. Other reviews center their attention on simulation of building users' adaptive behaviors and control systems for the energy and comfort management of buildings [13][14][15][16][17][18]. Awareness about how all these topics are highly interconnected could significantly influence building energy use.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Building Occupant Behavior on Energy Efficiency and Methods to Influence It: A Review of the State of the Art

2018

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Buildings consume a significant amount of energy, estimated at about one-third of total primary energy resources. Building energy efficiency has turned out to be a major issue in limiting the increasing energy demands of the sector. Literature shows that building user behavior can increase the efficiency of the energy used in the building and different strategies have been tested to address and support this issue. These strategies often combine the quantification of energy savings and qualitative interpretation of occupant behavior in order to foster energy efficiency. Strategies that influence building occupant behaviors include eco-feedback, social interaction, and gamification. This review paper presents a study conducted on the state of the art related to the impact of building user behavior on energy efficiency, in order to provide the research community with a better understanding and up-to-date knowledge of energy, comfort-related practices, and potential research opportunities. Achieving and maintaining energy-efficient behavior without decreasing the comfort of building occupants still represents a challenge, despite emerging technologies and strategies as well as general research progress made over the last decade. Conclusions highlight eco-feedback as an effective way to influence behavior, and gamification as a new opportunity to trigger behavioral change. The impact of user behavior is difficult to quantify for methodological reasons. Factors influencing human behavior are numerous and varied. Multi-disciplinary approaches are needed to provide new insights into the inner dynamic nature of occupant's energy behavior.

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Section: Introductionmentioning

confidence: 99%

The Impact of Building Occupant Behavior on Energy Efficiency and Methods to Influence It: A Review of the State of the Art

2018

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“…However, most of the efforts are focused on the thermal dynamics of the modelled systems and subsystems [10]. Little effort has been made in the field of predicting indoor air CO 2 concentration levels, and there is a lack of simple simulation tools and low-order state space models for predicting room CO concentrations [19].…”

Section: Introductionmentioning

confidence: 99%

Modelling indoor air carbon dioxide concentration using grey-box models

Macarulla

Casals

Carnevali

et al. 2017

Building and Environment

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Predictive control is the strategy that has the greatest reported benefits when it is implemented in a building energy management system. Predictive control requires low-order models to assess different scenarios and determine which strategy should be implemented to achieve a good compromise between comfort, energy consumption and energy cost. Usually, a deterministic approach is used to create low-order models to estimate the indoor CO2 concentration using the differential equation of the tracer-gas mass balance. However, the use of stochastic differential equations based on the tracer-gas mass balance is not common. The objective of this paper is to assess the potential of creating predictive models for a specific room using for the first time a stochastic grey-box modelling approach to estimate future CO2 concentrations. First of all, a set of stochastic differential equations are defined. Then, the model parameters are estimated using a maximum likelihood method. Different models are defined, and tested using a set of statistical methods. The approach used combines physical knowledge and information embedded in the monitored data to identify a suitable parametrization for a simple model that is more accurate than commonly used deterministic approaches. As a consequence, predictive control can be easily implemented in energy management systems.Peer ReviewedPostprint (author's final draft

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“…Section 5.2.1 in this paper presents how to calculate ventilation rates during monitoring [110]. J. C. Salcido et al [111] specifies that the main limitation of simulation techniques is inconsistency between simulation performance and monitored (actual) performance. Concordantly, this research claims that energy savings in the actual case might not be as visible as savings in simulated conditions.…”

Section: Monitoring Techniquesmentioning

confidence: 99%

A Review of Performance Specifications and Studies of Trickle Vents

Biler

Tavil

et al. 2018

Buildings

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The air quality of indoor spaces is the most significant parameter in providing a healthy living environment. Low indoor air quality (IAQ) leads to Sick Building Syndrome—one of the major reasons for labor loss in office buildings. The fundamental measure to ensure indoor air quality is ventilation, which includes two basic types: mechanical ventilation and natural ventilation. Natural ventilation is an exchange of stale indoor air with fresh outdoor air by means of a pressure difference due to wind and/or stack effect. Trickle Vents, known also as background ventilators, are natural ventilation devices which can be integrated into façades or window systems as an alternative to operable vents, specifically in high-rise buildings. The major design criteria of Trickle Vents are ventilation capacity, controllability, actuation, thermal insulation, air permeability, water tightness, climatic adaptation, security, and acoustic attenuation. Other important parameters in Trickle Vents design are positioning, equivalent area, and control strategy. This paper aims to review all these aspects, particularly with reference to building regulations and commercial products. Furthermore, simulation, experimental, monitoring, and survey studies of Trickle Vents are also discussed. This literature review is presented from the perspective of performance parameters, control strategies, positioning, etc., with an aim to provide a comprehensive overview of such technology.

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From simulation to monitoring: Evaluating the potential of mixed-mode ventilation (MMV) systems for integrating natural ventilation in office buildings through a comprehensive literature review

Cited by 70 publications

References 61 publications

The Impact of Building Occupant Behavior on Energy Efficiency and Methods to Influence It: A Review of the State of the Art

The Impact of Building Occupant Behavior on Energy Efficiency and Methods to Influence It: A Review of the State of the Art

Modelling indoor air carbon dioxide concentration using grey-box models

A Review of Performance Specifications and Studies of Trickle Vents

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