Fuzzy controller for a shaded daylighting system

Cziker, A.; Chindris, M.; Miron, Anca

doi:10.1109/optim.2008.4602522

Cited by 18 publications

(10 citation statements)

References 1 publication

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“…As reported by the Jordanian office of climate, the CO2 factor is about 88.2g/kWh. The overall annual emission is recognized to be one of the most significant indicators of the environmental measures and assessment [24], [25]. Figure 6 shows that using proposed control system, the yearly eliminated greenhouse gas emission is nearly 25.5 tons of CO2 by applying the most of fuzzy role sets.…”

Section: Payback Period Estimationmentioning

confidence: 99%

Energy, economic and environmental analysis of fuzzy logic controllers used in smart buildings

Baniyounes

Ghadi²,

Zahia

et al. 2021

IJPEDS

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This article is divided into three parts: the first presents a simulation study of the effect of occupancy level on energy usage pattern of Engineering building of Applied Science Private university, Amman, Jordan. The simulation was created on simulation mechanism by means of EnergyPlus software and improved by using the building’s data such as building’s as built plan, occupant’s density level based on data about who utilize the building throughout operational hours, energy usage level, Heating Ventilating and air conditioning (HVAC) system, lighting and its control systems and etc. Data regarding occupancy density level estimation is used to provide the proposed controller with random number of users grounded on report were arranged by the university’s facilities operational team. The other division of this paper shows the estimated saved energy by the means of suggested advanced add-on, FUZZY-PID controlling system. The energy savings were divided into summer savings and winter savings. The third division presents economic and environmental analysis of the proposed advanced fuzzy logic controllers of smart buildings in Subtropical Jordan. The economic parameters that were used to evaluate the system economy performance are life-cycle analysis, present worth factor and system payback period. The system economic analysis was done using MATLAB software

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Section: Payback Period Estimationmentioning

confidence: 99%

Energy, economic and environmental analysis of fuzzy logic controllers used in smart buildings

Baniyounes

Ghadi²,

Zahia

et al. 2021

IJPEDS

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show abstract

“…The handling level increases linked instruction and creates outcome for every single instruction, then the following of the merging the effects of this function. The output level changes the merged outcome to precise controlled command [19].…”

Section: Fuzzy Based-controllermentioning

confidence: 99%

“…The natural light FLC utilize uses as digital circuit of lightings' system adjustment and constant electronic reducing stabilities adjusted by using 110-220 volts analog signs as power controlling [19]. The stabilizer obtains a signal as of the controller and then variates the electric-current running through the light fixture, thus attaining a regular adjusted diminution in the light fixture amount produced.…”

Section: Natural Light Fuzzy Based-controllersmentioning

confidence: 99%

Exergy analysis of day light using fuzzy logic controllers of Jordanian commercial buildings

Baniyounes

Ghadi

Alnabulsi

2020

IJPEDS

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Saving energy and greenhouse gas emissions in commercial buildings become a very serious request of buildings’ designers and engineering crew. The goal behind the current research is to high light and demonstrate the outcome of utilizing advance and intelligent building management system (IBMS) based in utilizing a fuzzy logic controller that allows the usage and the control of natural light (day light). The fuzzy logic controller (FLC) was sat to control the buildings dimming system while utilizing natural light which normally allows to add outdoors illuminance into the inside ones. This control system is significant mean technique that can be used in intelligent buildings commercial buildings, hence energy savings and consequently, greenhouse gas emissions reduction. The proposed control system relies on enumerating the outdoor and the indoor illuminance and allowing some add-on controllers in order to put into effect a photometric computer that capable of comparing and tasking decisions to regulate rooms lighting fixtures. The article also demonstrates energy savings using this technique and then suggest proper markets for using this controlling system whether during the buildings’ design stage, existing commercial buildings.

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“…They are entirely deterministic methods that always assigns an action to mitigate threshold values of a controlling environmental parameter. Usually, rules are based on measuring the beam illuminance or beam solar radiation on the window [5,6], or illuminance levels on the work plane [7]. The reference active control strategy is to close the shades when the target environmental parameter exceeds a given upper threshold and to then reopen the shades once the parameter falls below the lower threshold [5,6].…”

Section: Introductionmentioning

confidence: 99%

Occupant-centered optimization framework to evaluate and design new dynamic shading typologies

et al. 2020

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Dynamic solar shading has the potential to dramatically reduce the energy consumption in buildings while at the same time improving the thermal and visual comfort of its occupants. Many new typologies of shading systems that have appeared recently, but it is difficult to compare those new systems to existing typologies due to control algorithm being rule-based as opposed to performance driven. Since solar shading is a design problem, there is no single right answer. What is the metric to determine if a system has reached its optimal kinematic design? Shading solutions should come from a thorough iterative and comparative process. This paper provides an original and flexible framework for the design and performance optimization of dynamic shading systems based on interpolation of simulations and global minimization. The methodology departs from existing rule-based strategies and applies to existing and to complex shading systems with multiple degree-of-freedom mobility. The strategy for control is centered on meeting comfort targets for work plane illuminance while minimizing the energy needed to operate space. The energy demand for thermal comfort and work plane daylight quantity (illuminance) are evaluated with Radiance and EnergyPlus based on local weather data. Applied to a case study of three typologies of dynamic shading, the results of the methodology inform the usefulness and quality of each degree-of-freedom of the kinematic systems. The case study exemplifies the iterative benefits of the methodology by providing detailed analytics on the behavior of the shades. Designers of shading systems can use this framework to evaluate their design and compare them to existing shading systems. This allows creativity to be guided so that eventually building occupants benefit from the innovation in the field.

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Fuzzy controller for a shaded daylighting system

Cited by 18 publications

References 1 publication

Energy, economic and environmental analysis of fuzzy logic controllers used in smart buildings

Energy, economic and environmental analysis of fuzzy logic controllers used in smart buildings

Exergy analysis of day light using fuzzy logic controllers of Jordanian commercial buildings

Occupant-centered optimization framework to evaluate and design new dynamic shading typologies

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