Thermal-comfort degradation by a visual comfort fuzzy-reasoning machine under natural ventilation

Dounis, Anastasios I.; Santamouris, M.; Lefas, C.C.; Manolakis, D.E.

doi:10.1016/0306-2619(94)90018-3

Cited by 21 publications

(7 citation statements)

References 4 publications

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“…The theory of fuzzy logic and control is not discussed in this paper as there are many publications already detailing this 4,5,6,7 . Fuzzy logic has previously been used to control HVAC plant with claims of performance improvements over conventional control techniques 8,9,10,11,12,13,14,15,16,17,18,19,20,21 . The research project detailed here aimed to build on the supervisory abilities of fuzzy control using a computer model for assessment purposes.…”

Section: Fuzzy Logic As a Control Methodologymentioning

confidence: 99%

Fuzzy control strategies to provide cost and energy efficient high quality indoor environments in buildings with high occupant densities

Shepherd¹,

Batty²

2003

Building Services Engineering Research and Technology

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Since the oil crises of the 1970s building professionals have become increasingly aware of the effects of their design decisions on the energy consumption rates in buildings. Often this has led to strategies that have compromised aspects of human requirements such as thermal comfort or air quality. When this has been combined with an architectural approach that often takes little heed of local climate or custom the result has been uncomfortable buildings that are disliked by and have often affected the health of their occupants.The comfort of building occupants is dependant on many environmental parameters including those provided by the building envelope, building environmental services and control systems. Inadequate design and control can lead to reductions of occupant comfort, energy ef ciency and cost ef ciency. To achieve a high quality internal environment with good energy and cost ef ciencies, the interactions between the contributory factors must be taken into consideration. An examination of the notion of indoor environmental quality and the potential for control strategies and methodologies for this multivariate problem are considered within the contexts of energy ef ciency and running costs. The use of fuzzy logic control is examined as a technical response to this dilemma. A high level fuzzy supervisor was used to make control decisions on the best course of action to achieve high levels of indoor environmental quality while taking into account effects on energy and cost ef ciency. Simulation results indicated the potential for improvements in system operation. List of symbols BPbuilding performance CE cost ef ciency CO2 error zone CO 2 concentration error from set point (ppm) CO2 z zone air CO 2 concentration (ppm)

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Section: Fuzzy Logic As a Control Methodologymentioning

confidence: 99%

Fuzzy control strategies to provide cost and energy efficient high quality indoor environments in buildings with high occupant densities

Shepherd¹,

Batty²

2003

Building Services Engineering Research and Technology

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“…A fuzzy controller with adaptive profile, a GA optimized controller and a predictive controller were analysed using simulation analysis. • Dounis et al (1994) investigated the impact of natural ventilation on the thermal comfort index, assuming the implementation of fuzzy reasoning for visual comfort control. The analysis is based on mathematical models.…”

Section: Hybrid Applicationsmentioning

confidence: 99%

Artificial Intelligence in Buildings: A Review of the Application of Fuzzy Logic

Κολοκότσα¹

2007

Advances in Building Energy Research

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“…The mean radiant temperature has a significant influence on the body's rate of heat loss and thus its comfort state as defined by the Fanger PMV. 1,14 Calculation of the mean radiant temperature is complicated by the non-uniform 'view' that the body has of the various surfaces making up a room space. Thus an approximation has been used in the present work, and the mean radiant temperature has been calculated by the following equation based on an area-weighted mean in which the index nc refers to the number of instruction elements involved:…”

Section: Mean Radiant Temperaturementioning

confidence: 99%

Thermal comfort based fuzzy logic controller

Gouda¹,

Danaher

Underwood

2001

Building Services Engineering Research and Technology

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Most heating, ventilation and air conditioning (HVAC) control systems are considered as temperature control problems. In this work, the predicted mean vote (PMV) is used to control the indoor temperature of a space by setting it at a point where the PMV index becomes zero and the predicted percentage of persons dissatisfied (PPD) achieves a maximum threshold of 5%. This is achieved through the use of a fuzzy logic controller that takes into account a range of human comfort criteria in the formulation of the control action that should be applied to the heating system to bring the space to comfort conditions. The resulting controller is free of the set up and tuning problems that hinder conventional HVAC controllers. Simulation results show that the proposed control strategy makes it possible to maximize the indoor thermal comfort and, correspondingly, a reduction in energy use of 20% was obtained for a typical 7-day winter period when compared with conventional control.

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Thermal-comfort degradation by a visual comfort fuzzy-reasoning machine under natural ventilation

Cited by 21 publications

References 4 publications

Fuzzy control strategies to provide cost and energy efficient high quality indoor environments in buildings with high occupant densities

Fuzzy control strategies to provide cost and energy efficient high quality indoor environments in buildings with high occupant densities

Artificial Intelligence in Buildings: A Review of the Application of Fuzzy Logic

Thermal comfort based fuzzy logic controller

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