Fuzzy logic model to classify effectiveness of daylighting in an office with a movable blind system

Kazanasmaz, Tuğçe

doi:10.1016/j.buildenv.2013.07.011

Cited by 21 publications

(7 citation statements)

References 28 publications

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“…Approximately 50 methods were identified ranging from those which were solely manual to those requiring mainframe computers for implementation [24]. Various methods on daylighting predictions discussed in the past are scale building models with simulators [44,49,116,144], mathematical or analytical modelling [71,91,126,[145][146][147][148][149], full scale models or mock-ups for field measurement [19,35,37,49,67,71,91,92,111,115,141] and computer simulation software [18,19,23,26,33,35,37,46,49,59,67,68,91,92,111,115;116,118,132,141,149-156]. Table 6 shows the strengths and weaknesses of these methods as reported in literature.…”

Section: Methods Of Investigating Daylighting In Buildingsmentioning

confidence: 99%

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A review of daylighting design and implementation in buildings

Wong

2017

Renewable and Sustainable Energy Reviews

151

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Daylighting design has become prevalent in modern buildings in the effort to create a more sustainable living environment. Past and recent bodies of research emerged are mainly focused on the different methods of predicting and measuring daylight level and various range of daylighting technologies available. Despite a wide range of developed and commercially available daylighting systems have been reported, their applications have been limited by a lack of studies on their utilisations and high initial costs. Computer simulations have been frequently used in the past to investigate daylighting performance due to reliable and accurate predictions. However, additional simulation time and variable level of skills and knowledge required are major drawback of computer simulations. This paper includes and pools information on all major daylighting design topic in the built environment. The study critically reviews and compares daylighting design principles, strengths and weaknesses of different range of daylighting systems and calculation methods, such as, scale model with artificial sky, full scale model for field measurement, numerical modelling and manual calculation procedures with the aid of diagrams or tables. Such information could be of useful for engineers, researchers and designers to assess the suitability of applying these systems and technologies in different building types and examine the potential of energy and cost savings.

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Section: Methods Of Investigating Daylighting In Buildingsmentioning

confidence: 99%

“…These systems can be applied inside double glazed units and have been developed to deal with different incidence angles with minimum maintenance requirement. Adjustable or flexible systems that can be used to track the sunlight at different angles, such as, blinds with different slat angles [67,71,91,92],…”

Section: Light Guiding Systemsmentioning

confidence: 99%

A review of daylighting design and implementation in buildings

Wong

2017

Renewable and Sustainable Energy Reviews

151

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“…Zúñiga et al (2014) utilized fuzzy logic to model human behavior related to the activation of appliances and lighting at home and showed that the residential consumption sector contributes the most to the formation of the curve peaks and valleys. Further models built on this premise have examined the energy demand management strategy of the commercial buildings through the thermal storage system (Zhang et al, 2012) and estimation of the daylight luminance and its distribution in an office (Kazanasmaz, 2013). The energy consumption of urban buildings is also affected by the surrounding microclimate which can decrease sunlight and wind potentials for internal solar gains and passive cooling.…”

Section: Demand-side Modelsmentioning

confidence: 99%

An integrated supply-demand model for the optimization of energy flow in the urban system

Farzaneh

Doll

Oliveira

2016

Journal of Cleaner Production

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“…The daylight illuminance was successfully predicted (with 87% of accuracy) in a study of an office with a movable blind system. 15 Fuzzy logic modelling has an even wider application in the field of engineering. 14,16–18 In the view of recent knowledge and existing studies as mentioned above, the fuzzy model was used to develop the initial users’ behaviour model as proposed by Hunt 6,11 by relating them to interior design parameters such as desk layouts and the distance from desk to window in identical private offices.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy logic model for the categorization of manual lighting control behaviour patterns based on daylight illuminance and interior layout

Kunduracı

Kazanasmaz

2017

Indoor and Built Environment

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In considering total building energy consumption, lighting plays an important role in shaping energy consumption and use. Although key strategies (such as energy efficient lighting products, lighting control systems and energy simulation software) are developed so far, such attempts may be unsuccessful unless users are not taken into consideration. Users’ behaviours and their manual lighting control actions depend on various factors, though within the scope of this study manual lighting control behaviour was analysed only in terms of interior layout and daylight illuminance. Three private offices in Izmir Institute of Technology were monitored using illuminance metres and occupancy/light detectors under eight different interior layout conditions. In relation to change of interior layout and daylight penetrations, users’ manual lighting control behaviours were monitored. The obtained data were then used to construct a fuzzy logic model in MATLAB FIS editor. A fuzzy logic algorithm was applied to classify behaviour patterns about the tendency to turn on the lights. This kind of prediction of the light usage tendency regarding the occupancy is aimed to foresee the ‘possible’ manual lighting control behaviour within given conditions. The gathered classification can be used further in future studies of manual lighting control behaviour and energy-saving estimations/simulations.

show abstract

Fuzzy logic model to classify effectiveness of daylighting in an office with a movable blind system

Cited by 21 publications

References 28 publications

A review of daylighting design and implementation in buildings

A review of daylighting design and implementation in buildings

An integrated supply-demand model for the optimization of energy flow in the urban system

Fuzzy logic model for the categorization of manual lighting control behaviour patterns based on daylight illuminance and interior layout

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