An Approach Towards Development Of Pmv Based Thermal Comfort Smart Sensor

Kumar, Anuj; Singh, I. S.; Sud, S. K.

doi:10.21307/ijssis-2017-412

Cited by 21 publications

(15 citation statements)

References 23 publications

(32 reference statements)

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“…The PMV is then calculated by the followings relations :‐

italicPMV = ((),, 0.303 e^{- 0.036 M} + 0.028) * {((),, M - W) - 3.05 * 10^{- 3} ([],, 5733 - 6.99 ((),, M - W) P_{a}) - 0.42 ([],, ((),, M - W) - 58.15) - 1.7 * 10^{- 5} M ((),, 5867 - P_{a}) - 0.0014 M ((),, 34 - t_{a}) - 3.96 * 10^{- 8} F_{cl} true[{(t_{italiccl} + 273)}^{4} - ((],, t_{mr} + 273 true)^{4}) - F_{cl} h_{c} ((),, t_{cl} - t_{a}) true}

where

t_{cl} = 35.7 - 0.028 ((),, M - W) - I_{cl} {3.96 * 10^{- 8} F_{italiccl} [{(t_{italiccl} - 273)^{4} - (t_{italicmr} - 273)}^{4}] - F_{italiccl} h_{c} (t_{italiccl} - t_{a})}

h_{c} = ({,, \begin{array}{c} center & 2.38 {(t_{italiccl} - t_{a})}^{0.25} italicfor 2.38 {(t_{italiccl} - t_{a})}^{0.25} > 12.1 * V_{ar}^{0.5} \\ center & 12.1 * V... \end{array})

…”

Section: Predicted Mean Vote Indexmentioning

confidence: 99%

ClimaCon: An Autonomous Energy Efficient Climate Control Solution for Smart Buildings

Farag

2016

Asian Journal of Control

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In modern buildings, climate control is an essential aspect to ensure the utmost comfort for the occupants, even though, this very feature represents 40% ~ 70% of the energy consumption of these buildings. Therefore, using energy efficient climate control systems becomes a crucial requirement of modern smart buildings. In this paper, we propose an autonomous energy‐efficient climate control solution “ClimaCon”. ClimaCon is an external extension to any Heat Ventilation and Air Conditioning (HVAC) system. The main objective of this solution is to achieve the best thermal comfort for individuals in all building zones with the least possible energy consumption. The solution consists of several closed loops to control the HVAC actuators while getting measurements and feedback signals through wireless sensing nodes. These nodes are distributed across pre‐determined locations in the building zones. ClimaCon theory of operation is based on observing the thermal comfort of occupants based on predicted mean vote index, and maintaining it within pre‐specified limits; while allowing the execution of various energy saving profiles. The performance of ClimaCon is evaluated using many test cases and extensive simulation studies. These studies prove the ability of the proposed solution to maintain the thermal comfort of occupants in various zones while implementing different energy saving profiles.

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“…The PMV is then calculated by the followings relations :‐

italicPMV = ((),, 0.303 e^{- 0.036 M} + 0.028) * {((),, M - W) - 3.05 * 10^{- 3} ([],, 5733 - 6.99 ((),, M - W) P_{a}) - 0.42 ([],, ((),, M - W) - 58.15) - 1.7 * 10^{- 5} M ((),, 5867 - P_{a}) - 0.0014 M ((),, 34 - t_{a}) - 3.96 * 10^{- 8} F_{cl} true[{(t_{italiccl} + 273)}^{4} - ((],, t_{mr} + 273 true)^{4}) - F_{cl} h_{c} ((),, t_{cl} - t_{a}) true}

where

t_{cl} = 35.7 - 0.028 ((),, M - W) - I_{cl} {3.96 * 10^{- 8} F_{italiccl} [{(t_{italiccl} - 273)^{4} - (t_{italicmr} - 273)}^{4}] - F_{italiccl} h_{c} (t_{italiccl} - t_{a})}

h_{c} = ({,, \begin{array}{c} center & 2.38 {(t_{italiccl} - t_{a})}^{0.25} italicfor 2.38 {(t_{italiccl} - t_{a})}^{0.25} > 12.1 * V_{ar}^{0.5} \\ center & 12.1 * V... \end{array})

…”

Section: Predicted Mean Vote Indexmentioning

confidence: 99%

ClimaCon: An Autonomous Energy Efficient Climate Control Solution for Smart Buildings

Farag

2016

Asian Journal of Control

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“…An adaptive approach to thermal comfort estimation has been adopted in the ASHRAE55-2013 standard [10]. Some researchers have added the air quality factor (CO and CO 2 ) in the ISO-and ASHRAE-based PMV calculation procedures, and in accordance with this, we have chosen the adaptive PMV calculation technique with air quality aspect [25]- [31].…”

Section: A Graphical User Interface (Gui)mentioning

confidence: 99%

“…Kumar et al A. Kumar and G. P. Hancke, Senior Member, IEEE developed a ZigBee technology-based environment monitoring system for the measurement of indoor and outdoor environments. Based on the developed system, they proposed the procedure of measurement of thermal comfort analysis [25], [47]. Rawi et al proposed a distributed, fuzzy rule-based wireless sensor network system for calculation of comfort index.…”

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confidence: 99%

An Energy-Efficient Smart Comfort Sensing System Based on the IEEE 1451 Standard for Green Buildings

Kumar

Hancke

2014

IEEE Sensors J.

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Abstract-In building automation, comfort is an important aspect, and the real-time measurement of comfort is notoriously complicated. In this article, we have developed a wireless, smart comfort sensing system. The important parameters in designing the prevalent measurement of comfort systems such as portability, power consumption, reliability, and system cost were considered. To achieve the target design goals, the communication module, sensor node, and sink node were developed based on the IEEE1451 standard. Electrochemical and semiconductor sensors were considered for the development of the sensor array, and the results of both technologies were compared. The sensor and sink nodes were implemented using the ATMega88 microcontroller. Microsoft Visual Studio 2013 preview was used to create the graphical user interface (GUI) in C#. The sensors were calibrated after the signal processing circuit to ensure that the standard accuracy of the sensor was achieved. This article presents detailed design solutions to problems that existed in the literature.Index Terms-IEEE1451 standard, sensor node, thermal comfort, graphical user interface, smart sensor, green building.

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“…The PMV index can be determined when the metabolic rate and the clothing insulation are estimated and the environmental parameters of air temperature and relative humidity are measured. The PMV can be calculated by the following relations [17]: (7) Here, (8) Fig. (4).…”

Section: Pmv Model For Thermal Comfort Analysismentioning

confidence: 99%

A Modified PMV Model for Indoor Thermal Comfort Analysis: Case Study of a University Cafeteria

Ogedengbe¹

2013

TOREJ

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An energy demand load analysis of the 2001 Cafeteria complex, at the University of Lagos, with the budget of a feasible supply of biogas from a bio-degradable food waste using a downdraft bio-digester, is conducted. A walkthrough energy audit of all the appliances that are installed or operated within the complex and the thermophysical properties of the building envelope toward achieving the ASHRAE standard for thermal comfort and indoor air quality, is considered. The design and optimization process, involving collection, storage and management of the food waste from about twenty vendors operating inside the complex, is proposed. Using a standardized performance index for a conventional downdraft bio-digester, the level of dissatisfaction of occupants in each of the energy stocks within the 2001 Cafeteria is presented. The results are useful for the estimation of the economic and environmental impact assessment of a proposed development of a compact solar bio-reactor for independent generation and storage of hydrogen and the estimation of the thermal comfort of the occupants in the building, using an improved Predicted Mean Vote (PMV) model.

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An Approach Towards Development Of Pmv Based Thermal Comfort Smart Sensor

Cited by 21 publications

References 23 publications

ClimaCon: An Autonomous Energy Efficient Climate Control Solution for Smart Buildings

ClimaCon: An Autonomous Energy Efficient Climate Control Solution for Smart Buildings

An Energy-Efficient Smart Comfort Sensing System Based on the IEEE 1451 Standard for Green Buildings

A Modified PMV Model for Indoor Thermal Comfort Analysis: Case Study of a University Cafeteria

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