HVAC system optimization for energy management by evolutionary programming

Fong, K.F.; Hanby, V. I.

doi:10.1016/j.enbuild.2005.05.008

Cited by 294 publications

(119 citation statements)

References 8 publications

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“…These different levels of display options are essential because users need to be able to recognize the energy consumption of their buildings and to analyze and improve their buildings' energy performance at different user interest levels. Some other researchers have examined the benefits of BEMS usage in companies in term of energy efficiency [11][12][13][14][18][19][20][21][22][23]. With those benefits in mind, this study sought to investigate the related factors that are useful to improve user responses from the perspectives of those in management.…”

Section: Introductionmentioning

confidence: 99%

A Behavioral Model of Managerial Perspectives Regarding Technology Acceptance in Building Energy Management Systems

Chin

Lin

2016

Sustainability

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Abstract:The Building Energy Management System (BEMS), a well-known system that has been implemented in some energy corporations, has become attractive to many companies seeking to better monitor their energy consumption efficiency. This study investigated the external factors that influence acceptance of the BEMS from managerial perspectives. An extended model based on the Technology Acceptance Model (TAM) was created to evaluate the implementation of the BEMS in the manufacturing industries. A structural equation modeling (SEM) approach was used to analyze the model by adopting compatibility, features, technology complexity, and perceived risk as the external variables, and integrating the five dimensions of perceived ease of use, perceived usefulness, attitude, user satisfaction, and behavioral intention. The analysis results indicated that the external factors positively influenced users' behavioral intention to use the BEMS through expected satisfaction, perceived ease of use, and perceived usefulness. Suggestions for BEMS developers are provided as well.

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Section: Introductionmentioning

confidence: 99%

A Behavioral Model of Managerial Perspectives Regarding Technology Acceptance in Building Energy Management Systems

Chin

Lin

2016

Sustainability

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“…Smart homes are equipped with sensors that not only feed into the building energy management system but also improve the safety of, e.g., elderly occupants. 174 There is an extensive literature on optimization algorithms and strategies, such as whole building simulations, 175 model predictive control, 176 evolutionary programming 177 and genetic algorithms, 178 artificial neural networks, 179 and particle swarm optimization. 180 Taking into account the weather prediction and its associated uncertainties further increases the comfort and lowers energy consumption.…”

Section: Electrical Energy Storagementioning

confidence: 99%

Energy in buildings—Policy, materials and solutions

Koebel

Wernery

Malfait

2017

MRS Energy & Sustainability

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Buildings account for ∼40% of global energy demands, and the increased adoption of innovative solutions for buildings represents an enormous potential to reduce energy demands and greenhouse gas emissions. Here, we critically review the current and future materials and solutions for the construction sector. We describe how policy affects innovative businesses and the adoption of new products and solutions. We investigate how the building envelope and user behavior determine building energy demands. Compared to conventional solutions, superinsulation materials (vacuum insulation panels, silica aerogel) can achieve the same thermal performance with drastically thinner insulation. With low-emissivity coatings and appropriate filler gasses, double and triple glazing reduces thermal losses by an order of magnitude. Vacuum and aerogel glazing reduce these even further. Switchable glazing solutions maximize solar gains during wintertime and minimize illumination demands whilst avoiding overheating in summer. Upon integration of renewable energy systems, buildings become both producers and consumers of energy. Combined with the dynamic user behavior, temporal variations in energy production require thermal and electrical storage and the integration of buildings into smart grids and energy district networks. The combination of these measures can reduce the energy consumption of the building's stock by a factor of three.

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“…There has been a corresponding increase in guidelines and regulations aimed at improving energy efficiency in the workplace. 1,2 In response, attempts to reduce workplace energy use have included building service management (Fong, Hanby, and Chow 2006), intelligent manufacturing (Dietmair and Verl 2009) and paperless office systems (Sellen and Harper 2003). However, the use of office equipment and lighting regularly accounts for more than half of overall consumption in commercial buildings (Murakami et al 2006) and so user behaviour can have an important impact (IPCC 2007).…”

Section: Introductionmentioning

confidence: 99%

Apportioning energy consumption in the workplace: a review of issues in using metering data to motivate staff to save energy

Bedwell

Leygue

Goulden

et al. 2014

Technology Analysis & Strategic Management

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The UK government has set ambitious targets to reduce carbon emissions, and lowering energy demand within workplaces is important to help meet these. With the rollout of smart metres and the availability of more fine-grained energy monitoring equipment for the workplace, it is increasingly possible to disaggregate collective energy consumption and apportion this among building users. This article presents an interdisciplinary perspective on the rationale and feasibility of different approaches to apportionment to motivate staff to reduce energy consumption. Our review indicates greatest potential for energy saving when consumption is apportioned to small to medium-sized groups, rather than individuals or entire buildings, particularly when they represent existing communities to which staff members strongly identify. We highlight the complexity of technical, psychological, social and organisational factors that not only inspire, but also often confound, efforts to innovate in this area.

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HVAC system optimization for energy management by evolutionary programming

Cited by 294 publications

References 8 publications

A Behavioral Model of Managerial Perspectives Regarding Technology Acceptance in Building Energy Management Systems

A Behavioral Model of Managerial Perspectives Regarding Technology Acceptance in Building Energy Management Systems

Energy in buildings—Policy, materials and solutions

Apportioning energy consumption in the workplace: a review of issues in using metering data to motivate staff to save energy

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