Thermal Comfort, Energy and Cost Impacts of PMV Control ... - MDPI

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12 hours ago - Keywords: metabolic rates; predicted mean vote (PMV); EnergyPlus; energy consumption; life cycle cost (LCC); thermal comfort. 1. Introduction.
energies Article

Thermal Comfort, Energy and Cost Impacts of PMV Control Considering Individual Metabolic Rate Variations in Residential Building Sung Hyup Hong 1 , Jong Man Lee 1 , Jin Woo Moon 2 and Kwang Ho Lee 3, * 1 2 3

*

Graduate School, Hanbat National University, San 16-1, Dukmyung-Dong, Yuseong-Gu, Daejeon 34158, Korea; [email protected] (S.H.H.); [email protected] (J.M.L.) School of Architecture and Building Science, Chung-ang University, 84, Heukseok-ro, Dongjak-gu, Seoul 06974, Korea; [email protected] Department of Architectural Engineering, Hanbat National University, San 16-1, Dukmyung-Dong, Yuseong-Gu, Daejeon 34158, Korea Correspondence: [email protected]; Tel.: +82-42-821-1126

Received: 30 May 2018; Accepted: 3 July 2018; Published: 5 July 2018

 

Abstract: To date, most of the indoor environment control is based on the dry-bulb air temperature, which is one of the simplified control methods having the limitation to truly represent the thermal comfort of individual occupants. A variety of factors affect the thermal comfort such as dry-bulb air temperature, humidity, air movement, radiation, clothing insulation, and metabolic activity level. In this circumstance, this study investigated the effects of considering hourly metabolic rate variations for predicted mean vote (PMV) control on the actual thermal load, energy usage, and life cycle cost (LCC). The case adopting PMV control taking the hourly metabolic rate into account was comparatively analyzed against the conventional dry-bulb air temperature control, using a detailed simulation technique after the validation process. As a result, when the activity state of the occupant is house cleaning in the summer, the indoor temperature decreases rapidly due to the high amount of activity. It requires a temperature that is 11.7 ◦ C and 9.7 ◦ C lower than the conventional dry-bulb air temperature control method, respectively, and generally forms a higher indoor air temperature than the conventional control method after 7 p.m. This means the difference in temperature to satisfy the comfort of the occupant according to the amount of activity, and during winter as opposed to summer, was found to form a lower indoor air temperature than the conventional temperature control. In case of annual boiler gas consumption, PMV control showed 7.3% less energy consumption than the dry-bulb air temperature control and showed 28.8% less energy consumption than the dry-bulb air temperature control for annual cooling electricity consumption. Considering the cooling and heating energy reduction rate and the initial installation cost of measuring equipment for real-time metabolic rate and PMV measurement, a payback period of approximately 4.15 years was required. Keywords: metabolic rates; predicted mean vote (PMV); EnergyPlus; energy consumption; life cycle cost (LCC); thermal comfort

1. Introduction 1.1. Background Today, one of the most important factors in the field of building science around the world is to minimize energy consumption while maintaining a pleasant indoor environment for the occupants. The importance of reducing energy consumption has been an important aspect for a long time, and studies and programs related to energy consumption optimization algorithms and programs have Energies 2018, 11, 1767; doi:10.3390/en11071767

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been actively performed [1]. In terms of the Korea Institute of S&T Evaluation and Planning (2015, 29) based on OECD (Organization for Economic Cooperation and Development) data, the energy intensity of OECD countries has been consistently declining as a result of technical and policy efforts in various countries over the past 40 years [2]. In addition, many countries regulate indoor space based on dry-bulb air temperature or recommend proper room temperature compliance to reduce energy consumption in buildings. Although these national policies may have a positive effect on reducing heating and cooling energy consumption, they are fragmentary policies and regulations that do not consider the thermal comfort experienced by the occupants [3]. Modern people today spend most of their day in indoor spaces such as houses and offices, and the demand for a pleasant indoor environment is growing as the quality of life improves along with social change [4]. PMV is a comfort index of the occupant that is influenced by air temperature, mean radiant temperature, air velocity, air humidity, clothing, and activity level, and the PMV calculation equation is implemented by software for the convenience of the user [5,6]. In conditioned spaces, the thermal comfort conditions of the human body as a whole can be evaluated by means of the PMV index [5,7] which integrates the influence of the thermal comfort factors (air temperature, air velocity, mean radiant temperature, humidity, clothing insulation, and activity) into a value on the well-known ASHRAE (American Society of Heating, Refrigerating, and Air-Conditioning Engineers) 7-points scale with a range of −3 to +3 (Table 1). Formulated by Fanger in 70’s [8], the PMV-index is an objective method based on an analysis of the heat balance equation for the human body together with the influence of the physical environment and expressed as a subjective sensation [7]. The typical comfort range is between −0.5 and 0.5 [9], and related studies are actively underway in many areas such as the metabolic rate, PMV, and high-efficiency air conditioners [10]. Table 1. The seven-point thermal sensation scale. +3 +2 +1 0 −1 −2 −3

Hot Warm Slightly warm Neutral Slightly cool Cool Cold

1.2. Literature Review In terms of existing studies related to this, there are two main categories. In the studies related to metabolic rate, ISO 8996:2004 defines a different method for determining the metabolic rate in the ergonomic context of a climatic work environment [11]. ISO 9920:2007 specifies a method for estimating the steady-state thermal characteristics of a garment ensemble based on known clothing, ensemble, and textile values. Other effects of clothing such as moisture absorption, cushioning, and touch feeling are not considered. Taking into consideration the influence of rain and snow on the temperature characteristics, we deal with the asymmetry of special protective clothing, discomfort due to the separated insulation of different parts of the body and clothing ensemble [12]. Malchaire J et al.’s study emphasizes that accurate evaluation of metabolic rate is necessary for evaluating severe working conditions. This paper revised the foundation described in the ISO 8996 standard concerning the evaluation of the metabolic rate at the workstation from the record of the worker’s heart rate during the representative period. From the review of the literature, an expression different from the formula given in the standard is proposed to estimate the maximum work capacity at rest, maximum heart rate, heart rate, metabolic rate, and baseline relationship. The Monte Carlo simulation is used to determine the inaccuracy of the estimated equivalent metabolic rate from these parameters and formal approximations. The result shows that the standard deviation of this estimate varies from 10 to 15% [13]. Next, in terms of existing studies related to PMV, d’Ambrosio Alfano et al. focuses on important

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parameters influencing the quality of the indoor environment and affects researchers of human comfort and indoor air quality. The analysis of every single topic in his research and its impact on past and present research requires more space than available in review articles. The authors are convinced that the research described in this document will serve as a beacon for researchers working on current and future thermal comfort [14]. The evaluation of PMV is a very hard matter as stressed by d’Ambrosio Alfano et al. especially when the metabolic rate is unknown. In particular, we compared all existing smartphones and web applications for computing PMV indexes running on different platforms for mobile devices with reference software compliant with the ISO 7730 standard. Unfortunately, there were only four applications that take into account all six variables that cause warmth and data entry seems very difficult. In addition, only one app considered the basic clothing insulation value correction by pumping effect. Based on the results of this preliminary test, web apps and smartphone tools for the evaluation of hot comfort by PMV currently on the market must be used with special care [15]. Leger J et al.’s study performed an experimental investigation of the electric heating system showing that the heat distribution influences the effectiveness of the device to actually maintain the thermal comfort. Baseboard heaters, convectors, and radiant heaters are compared in equal thermal comfort conditions within two climatic chambers at different cold room temperatures. To demonstrate the reproducibility of the results, a statistical analysis is presented. The results show that despite achieving similar thermal comfort, the convector consumes less energy than the baseboard and radiant heater. Therefore, there is an opportunity to improve the heating efficiency by improving the heat distribution of the device [16]. The existing studies above showed that PMV control can improve the thermal comfort and reduce the load, but they did not investigate the comprehensive impacts of considering metabolic rate during PMV control on thermal comfort and energy consumption in detail. In order to solve the limitations of such prior studies, the purpose of this study is to evaluate the thermal comfort of the occupant and the cooling and heating energy saving effect through PMV control considering the actual metabolic rate of the occupant and to enhance the applicability of measuring the metabolic rate for PMV control in Korea through economic analysis (Lifecycle cost). 1.3. Metabolic Rate Metabolic rate is a physiological measure of metabolism during physical activity. The metabolic rate can be expressed as (O2 mL/kg/min)*3.5, which indicates the amount of oxygen an adult consumes sitting down relaxing [17]. The Activity Level (unit: W) is an element that determines the amount of heat generated by an individual, and the Activity Level varies widely from 72 W up to 900 W [18]. The following Table 2 [19] shows various behavioral conditions according to the metabolic rate used in this study. The minimum value is 72 W/Person which indicates the sleeping state of the occupant, and the maximum value is 360 W/Person which indicates the house cleaning state. Table 2. The metabolic rates for various activities. Activity

Activity Level (W/Person)

Metabolic Rate Per Person (Met)

Sleeping Reclining Seated, quiet Standing, relaxed Reading, seated Writing Typing Filling, seated Filling, standing Cooking House cleaning

72 81 108 126 99 108 117 126 144 171 to 207 207 to 360

0.7 0.8 1 1.2 1 1 1.1 1.2 1.4 1.6 to 2.0 2.0 to 3.4

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2. Method 2.1. Simulation Software EnergyPlus v6.0 developed by the U.S Department of Energy was used as a theoretical analysis tool to conduct this study. EnergyPlus is the program combining the advantage of DOE-2 in the system analysis and the advantage of BLAST in the load analysis [17]. In addition, the building cooling and heating load analysis was based on the heat balance method recommended by the American Society of Heating Refrigerating and Air-conditioning Engineer (ASHRAE). The credibility of this program was verified by developing simulation tools as per the ASHRAE 140 guidelines which were the representative dynamic simulation protocol. In addition, the computations are based on the fully integrated solution of zone, air, and surface balances, systems, and plants [20]. Finally, detailed information on the assumptions, detailed algorithm, and validation of EnergyPlus models related to boiler calculations can also be found in Reference [20]. 2.2. Predicted Mean Vote (PMV) Assessment During Simulation PMV is one of the representative thermal indicators, developed as a comfort index by P.O. Fanger [8]. It is based on the heat balance of the human body and is divided into a 7-point scale as shown in Table 1. PMV is not only influenced by metabolic rate and clothing, but also by physical environmental factors such as air temperature, mean radiant temperature, airspeed, and humidity. The general comfort range of the occupant is −0.5 to +0.5 [10]. It is essential to accurately evaluate PMV in each time-step during the simulation and thus the following descriptions are provided in this section related to the variables such as clothing insulation, air velocity, relative humidity, and mean radiant temperature, which directly affect the PMV value. To begin with, clothing insulation is assumed to be equal to a constant value of 0.5 clo from 1 December through 28 February, 0.5 from 1 March through 30 April and from 1 November through 30 November, 0.65 during May and October, and 0.5 from 1 June through 30 September. Air velocities and relative humidities are automatically computed by the EnergyPlus software in each time-step since they are not the input variables but the variables that are the variables affected by a variety of operating conditions such as heating/cooling load and supply airflow provided to each zone, and so forth. Finally, MRT (Mean Radiant Temperature), which has a significant effect on PMV, is also computed by the EnergyPlus software in each time-step due to the fact that surface temperatures are determined by the heating operation conditions such as the supply hot water temperature and supply water flow into the radiant heating system, which, in turn, are determined by the heating load of each time-step in each zone. 2.3. Schedule The hourly variations of metabolic rate were based on ISO 18523-2 Residential Buildings Annex A [20]. Of the schedule for a family of four presented by the ISO 18523-2 Residential Buildings Annex A [20], a 44-year-old housewife who spends the most time in the residential building was applied. Tables 3 and 4 represent the Weekday and Holiday Schedules of the corresponding woman, respectively, and the values are averaged by the hour of the 15-min schedule presented by the ISO. Table 3. The weekday system ON/OFF and activity level.

Time

Metabolic Rate

System (ON/OFF)

1:00 2:00 3:00 4:00

0.7 0.7 0.7 0.7

OFF OFF OFF OFF

Activity Level (W/Person) 72 72 72 72

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Table 3. Cont.

Time

Metabolic Rate

System (ON/OFF)

5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00

0.7 0.7 1.4 1.05 2.7 1 0 0 1.35 1 0 0 1.3 1 1.6 1.225 1.3 1 1.25 0.775

OFF OFF ON ON ON ON OFF OFF ON ON OFF OFF ON ON ON ON ON ON ON ON

Activity Level (W/Person) 72 72 144 113 284 108 0 0 140 108 0 0 135 108 171 129 135 108 130 79

Table 4. The holiday system ON/OFF and activity level.

Time

Metabolic Rate

System (ON/OFF)

1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00

0.7 0.7 0.7 0.7 0.7 0.7 0.7 1.325 1.5 3.4 0 0 1.35 0 0 0 2 1.7 1.225 1.125 1 1 1.25 0.7

OFF OFF OFF OFF OFF OFF OFF ON ON ON OFF OFF ON OFF OFF OFF ON ON ON ON ON ON ON OFF

Activity Level (W/Person) 72 72 72 72 72 72 72 138 153 360 0 0 140 0 0 0 207 180 129 120 108 108 132 72

2.4. Description of the Simulated Apartment Building The EnergyPlus simulation model selected a residential apartment located in Paju, Gyeonggi Province, Korea. The floor plan of each floor is shown in Figure 1 and and exterior view is presented

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in Figure 2.11, Zones 1 and 2 are facing Zone and Zone 4 is facing northeast. Energies 2018, x 1 and 6 of 22 addition, Zone Zone 2 are 10.4 south, m wide, 14.43mfacing long,northwest, with a window area ratio of 34.3%, while The modeling is a 15-story general residential apartment with the same floor height of 2.7 m. In addition, Zone 3 and Zone 4 are 12.1 m wide, 12.1 m long, with a window area ratio of 21.3%. addition, Zone 1 and 2 are 10.414.4 m wide, 14.4 m long, with area a window ratio of 34.3%, Zone 1 and Zone 2 areZone 10.4 m wide, m long, with a window ratio ofarea 34.3%, while Zone while 3 and Zone 34 and Zone are 12.1 witharea a window ratio of 21.3%. are 12.1 m4wide, 12.1mmwide, long,12.1 withmalong, window ratio ofarea 21.3%.

Figure 1. Floor plan. Figure Figure 1. 1. Floor Floor plan. plan.

Figure 2. The exterior view of the simulation model.

Figure 2. The exterior view of the simulation model.

2.5. Simulation Condition 2.5. Simulation Condition Figure 2. The exterior view of the simulation model. In this study, the radiant floor heating system was applied for the heating and the cooling system In this study, the radiant floor window heating system was applied forbuilding the heating andinthe cooling was achieved through an indoor air conditioner. The used this studysystem was a 2.5. Simulation Condition was achieved through anon indoor windowbuilding air conditioner. The building usedProvince, in this study was a simulation model based a residential located in Paju, Gyeonggi Korea, but In this study, the radiant floor heating system was applied for the heating and the cooling system simulation model based on a residential building did located Paju, Gyeonggi Korea, but since the weather data provided by EnergyPlus not in exist, the weatherProvince, data of Incheon areasince was was achieved an indoor window airheat conditioner. The building used in this study a the weather provided by EnergyPlus did not exist, the weather data Incheon area waswas used, used, whichdata isthrough located nearby. The internal gain conditions for theof simulation modeling are simulation model based on a residential building located in Paju, Gyeonggi Province, Korea, but since which nearby. The internalperiod heat gain conditions for set the for simulation shown in shownisinlocated Table 5, and the analysis of the model was a wholemodeling year. Theare heating and the weather data provided by EnergyPlus did not exist, the weather data of Incheon area was used, Table 5, system and the was analysis period ofduring the model set for a whole year.when The heating and cooling system cooling not operated the was unoccupied hours and the occupant was sleeping which located internal heat gain conditions foroccupant the simulation modeling arecontrol shown in was notisoperated during The the unoccupied hours and when the was sleeping according to the according to the nearby. Occupancy Schedule and the Hours of Operation Schedule. In order to Table 5, andaccurately, the analysis period of the model was set into for a5whole The heating andthe cooling Occupancy Schedule and the Hours of Operation Schedule. In order to control PMVasystem more PMV more each household was divided zonesyear. with 3 rooms, a kitchen, and living was not operated during the unoccupied hours and when the occupant was sleeping according to accurately, each the household into 5 assumption zones with 3was rooms, a kitchen, and a living room, excluding verandawas and divided bathroom. The to measure the metabolic rate room, of the the Occupancythe Schedule the Hours ofThe Operation Schedule. order tothe control the PMV more excluding verandaand bathroom. assumption was toInmeasure metabolic rate sensor of the occupant in real-time byand installing a temperature and humidity sensor (KRW 2000), airflow accurately,ineach household was divided into 5 zones with 3 rooms, a kitchen,2000), and aairflow living sensor room, occupant real-time by installing a temperature and humidity sensor (KRW 70,000), MRT sensor (KRW 45,000), camera (KRW 6000), and board(KRW (KRW 90,000), respectively. excluding the veranda and bathroom. The assumption was to measure the metabolic rate of the (KRW 70,000), MRT sensor (KRW 45,000), camera (KRW 6000), and board (KRW 90,000), respectively. occupant in real-time by installing a temperature and humidity sensor (KRW 2000), airflow sensor The total sum of the five devices is about KRW 213,000, which will be considered later in the economic (KRW 70,000), MRT sensor (KRW 45,000), camera (KRW 6000), and board (KRW 90,000), respectively. The total sum of the five devices is about KRW 213,000, which will be considered later in the economic

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The total sum of the five devices is about KRW 213,000, which will be considered later in the economic analysis. In addition, the thermal properties of building constructions were configured as shown in Table 6 based on the drawing of the building, and the floor construction in which hot water pipes were laid for floor radiant heating consists of the material in the reverse order of the interior ceiling. Table 5. The internal load level. People Number of People Calculation Method Zone Floor Area per Person Fraction Radiant

Area/Person 32 m2 /Person 0.3

Light Design Level Calculation Method Watts per Zone Floor Area Return Air Fraction Fraction Radiant Fraction Visible

Watts/Area 3.88 W/m2 0 0.2 0.2

Equipment Design Level Calculation Method Watts per Zone Floor Area

Watts/Area 5.38 W/m2

Table 6. The construction properties. Construction Exterior Floor

I02 50 mm insulation board M15 200 mm heavyweight concrete

Exterior Wall

M01 100 mm brick M15 200 mm heavyweight concrete I02 50 mm insulation board F04 Wall airspace resistance G01a 19 mm gypsum board

Interior Wall

G01a 19 mm gypsum board F04 Wall airspace resistance G01a 19 mm gypsum board

Exterior Roof

M11 100 mm lightweight concrete F05 Ceiling airspace resistance F16 Acoustic tile

Interior Ceiling

Finish flooring INS-Expanded EXT polystyrene R12 2 In Concrete-dried sand and gravel 4

Exterior Window

Clear 3 mm Air 13 mm Clear 3 mm

Interior Window

Clear 3 mm

Exterior Door

F08 Metal surface I01 25 mm insulation board

Interior Door

G05 25 mm wood

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2.6. Simulation Case In order to analyze the annual cooling and heating load and energy reduction effect through PMV control considering the real-time activity of the occupant in the residential building in this study, it was compared with the conventional dry-bulb temperature control method. In other words, the cooling and heating loads of the conventional indoor dry-bulb temperature control and PMV control were compared, and the representative days of summer and winter were designated as Weekday and Holiday for a more precise comparison analysis. In the conventional dry-bulb temperature control method, the cooling and heating temperatures were set at 25 ◦ C and 21 ◦ C, respectively, and in PMV control, the cooling and heating were configured at PMV 0.5 and −0.5, respectively. The representative days were selected as 6–7 August in the summer and 25–26 December in the winter, and these days represented the Weekday and Holiday, respectively. The representative days were selected by analyzing the upper 1% and lower 1% temperature by compiling weather data from 3 March 2009 to 31 March 2018 of the Incheon area. 2.7. Weekday, Holiday Schedule In this study, the system operation time for Weekday and Holiday was determined according to the schedule of the occupant, and Tables 3 and 4 show the results. When PMV control is performed through EnergyPlus, values below 1.0 are out of range of ASHRAE 55-2017, and thus accurate PMV evaluation is impossible. Therefore, all systems are set to OFF during the sleeping and unoccupied states in consideration of the schedule of the occupant. 3. Result and Discussion 3.1. PMV This study predicted the level of thermal sensation expressed in terms of PMV on the representative days of summer and winter. As mentioned above, the system operating time is the time excluding sleeping time and unoccupied time. The sleeping time and unoccupied time are scheduled based on the ISO 18523-2 Residential buildings Annex A [20]. As a result, Figures 3 and 4 show dry-bulb temperature control and PMV control for the summer representative days (6–7 August). The analysis was performed except for sleeping time, and the cooling and heating system was not operated when the occupant was outside or during the unoccupied time period. In case of PMV control, PMVs of the time period in which the occupant is active in the corresponding zone are all located within the comfort zone. On the other hand, dry-bulb temperature control did not satisfy the comfort of the occupant most of the time, and PMV varied from −0.6 to 1.6. This indicates that it is difficult to satisfy the comfort of the occupant through dry-bulb temperature control when the activity level of the occupant is high. The change of the activity level over time is shown in Tables 3 and 4. During sleeping time and unoccupied time, the cooling and heating system do not operate, and the metabolic rate 1.0 and lower values including sleeping time and unoccupied time are outside the metabolic rate range of ASHRAE 55-2017, which makes accurate PMV evaluation impossible. As a result, even in the case of PMV control, PMV shows values from −0.5 to −0.8 which is below the heating setting value. On the other hand, Figures 3 and 4 show that the indoor PMV is maintained at PMV +0.5, which is the cooling setting value when the activity of the occupant is high, and PMV values temporarily decreased as the activity level decreased.

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Figure Figure 3. 3. The The predicted predicted mean mean vote vote (PMV) (PMV) variations variations in in the the summer summer holiday holiday (6 (6 August). August). Figure 3. The predicted mean vote (PMV) variations in the summer holiday (6 August).

Figure 4. The PMV variations in the summer weekday (7 August). Figure Figure 4. 4. The The PMV PMV variations variations in in the the summer summer weekday weekday (7 (7 August). August).

Figures 5 and 6 show PMV values for the representative days of winter (25–26 December), Figures 5 and 6 show PMV values for the representative days of winter (25–26 December), respectively. the case of PMV values when the occupant is active in theDecember), zone exist Figures In 5 and 6 show PMVcontrol, values PMV for the representative days of winter (25–26 respectively. In the case of PMV control, PMV values when the occupant is active in the zone exist within the comfort zone, where the PMV is +0.5 during the period of increased activity and the PMV respectively. In the case of PMV control, PMV values when the occupant is active in the zone exist within the comfort zone, where the PMV is +0.5 during the period of increased activity and the PMV is slightly lower than during theisperiod of decreased Because theand sleeping and within the comfort zone, +0.5 where the PMV +0.5 during the periodactivity. of increased activity the PMV is is slightly lower than +0.5 during the period of decreased activity. Because the sleeping and unoccupied time of the occupant are outside the metabolic rate range of ASHRAE 55-2017, PMV slightly lower than +0.5 during the period of decreased activity. Because the sleeping and unoccupied unoccupied time of the occupant are outside the metabolic rate range of ASHRAE 55-2017, PMV values correctly and, therefore, notrange located within the55-2017, comfortPMV zone.values The dry-bulb time ofare thenot occupant areestimated outside the metabolic rate of ASHRAE are not values are not correctly estimated and, therefore, not located within the comfort zone. The dry-bulb temperature control and, did not satisfy the many time periods, and the temperature comfortable correctly estimated therefore, notcomfort located condition within theincomfort zone. The dry-bulb temperature control did not satisfy the comfort condition in many time periods, and the comfortable sensation thesatisfy occupant was “slightly warm” fromtime 9 a.m. to 10and a.m., the activity of the control didofnot the comfort condition in many periods, thewhen comfortable sensation of sensation of the occupant was “slightly warm” from 9 a.m. to 10 a.m., when the activity of the occupant was high. the occupant was “slightly warm” from 9 a.m. to 10 a.m., when the activity of the occupant was high. occupant was high.

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Figure Figure 5. The The PMV PMV variations variations in in the winter holiday (25 December).

Figure Figure 6. The The PMV PMV variations variations in in the the winter weekday (26 December).

Comparing Comparing the the representative representative days days of of summer summer and and winter, winter, in in the the case case of of PMV PMV control, control, the the PMV PMV was within the comfort zone at all time periods when the occupant was indoors. On the other hand, was within the comfort zone at all time periods when the occupant was indoors. On the other hand, in in case of dry-bulb temperature control, the comfort of the occupant was not during satisfied during a case of dry-bulb temperature control, the comfort of the occupant was not satisfied a significant significant of time periods, and PMV dissatisfaction higher in the summerto compared number of number time periods, and PMV dissatisfaction was higherwas in the summer compared winter. to winter. 3.2. Indoor Temperature 3.2. Indoor Temperature The indoor temperature during summer and winter is analyzed in this chapter. The operating The indoor temperature summer andtime winter analyzed intime. this chapter. Theinoperating time of the system is the time during excluding sleeping andisunoccupied As a result, terms of time of the system is the timethe excluding sleeping time andrepresentative unoccupied time. a result, in of Figures 7 and 8 which show indoor temperature of the daysAs of summer, theterms system Figures 7 and 8 which show the indoor temperature of the representative days of summer, the system of the conventional control and PMV control does not operate when the activity state of the occupant of the conventional control PMVa control nottemperature operate when state of the occupant is sleep or unoccupied andand shows similar does indoor atthe theactivity corresponding time period. is sleep or unoccupied and shows a similar indoor temperature at the corresponding On On the other hand, a large temperature difference occurs depending on the activity time of theperiod. occupant the other hand, a large temperature difference occurs depending on the activity of the occupant when the system state is ON. On 6 August, the highest activity is observed at 10 a.m. and the activity level

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Energies 2018, 11, x reaches 360 W. Accordingly, the temperature difference at 10 a.m. between the11 of 22 of the occupant PMV control and the conventional temperature control method is 11.7 °C. In addition, the activity is highest when the systemreaches state is360 ON. 6 August, the activity is observed at 10 a.m. and the activity of occupant W.On Accordingly, thehighest temperature at 10 a.m. between the PMV at 9the a.m. on 7 August (Weekday), and the activity level reachesdifference 284 W. Accordingly, the temperature level of the occupant reaches 360 W. Accordingly, the temperature difference at 10 a.m. between the control and the conventional temperature control method is 11.7 °C. In addition, the activity is highest difference at 9 a.m. between PMV control and the conventional temperature control method is 7.6 °C. ◦ PMV control and the(Weekday), conventional temperature control method 11.7 C. In addition, the activity at 9 a.m. 7 August and the activity level reaches 284is W. Accordingly, the temperature Figures 3on and 4 show that indoor temperature difference between dry-bulb temperature control and is highest at 9 a.m. on 7 August (Weekday), and the activity level reaches 284 W. Accordingly, difference at 9isa.m. between PMV and the conventional temperature control is 7.6 °C. PMV control closely related tocontrol the activity level schedule when the comfort ofmethod the occupant is the temperature difference at 9 temperature a.m. between PMV control and the conventional temperature Figures 3 and 4 show that indoor difference between dry-bulb temperature control and considered. control method 7.6 ◦ C.related Figuresto3the andactivity 4 show level that indoor temperature dry-bulb PMV control is is closely schedule when thedifference comfort ofbetween the occupant is temperature control and PMV control is closely related to the activity level schedule when the comfort considered. of the occupant is considered. Dry blub temperature control PMV control

temperature[℃] IndoorIndoor temperature[℃]

35

Dry blub temperature control

PMV control

30 35 25 30 20 25 15 20 10 15 5 10 0 5 0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Time[h] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Time[h] Figure 7. The indoor temperature holiday (6 August). Figure 7. The indoor temperature holiday (6 August). Figure 7. The indoor temperature holiday (6 August). Dry blub temperature control PMV control

Temperature[℃] IndoorIndoor Temperature[℃]

33

Dry blub temperature control

PMV control

30 33 27 30 24 27 21 24 18 21 15 18 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 15

Time[h] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Figure 8. The indoor temperature Time[h]weekday (7 August). Figure 8. The indoor temperature weekday (7 August).

Figures 9 and 10 show the indoor temperature change of the representative days of winter, Figure 8. Theofindoor temperature weekday August). 9 and 10 show the days indoor temperature of the(7representative days of winter, and Figures unlike the representative summer, thechange indoor temperature is higher in the case ofand the unlike the representative of than summer, indoor temperature is higher in the of the conventional temperature days control in thethe case of PMV control. This indicates thatcase the indoor Figures 9generally and 10 show indoor change ofcontrol. thetemperature. representative ofofwinter, and conventional temperature than in thethan case the of PMV This indicates that the temperature set control inthe winter is temperature higher required In days terms the indoor indoor unlike the representative days of summer, the indoor temperature is higher in the case of the temperature in winter is higher than there the required In terms of thebetween indoor temperature generally and PMV set on 25 December (Holiday), is almosttemperature. no temperature difference conventional temperature in the case of PMV control. This indicates thatON thebetween temperature and PMV 25control December is almost no temperature difference the temperature until on 7 a.m. whenthan the(Holiday), system is there OFF and when the system is turned atindoor 8 a.m. temperature generally set in winter is higher than the required temperature. In terms of the indoor the until 7 a.m. when the system OFF and is turned at due 8 a.m. Thistemperature is because it takes a considerable amountis of time towhen reach the thesystem required comfortON zone to temperature and PMV on 25 December (Holiday), there is almost no temperature difference between the temperature until 7 a.m. when the system is OFF and when the system is turned ON at 8 a.m.

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12 of 21 12of of22 22 12

Thisisisbecause becauseitittakes takesaaconsiderable considerableamount amountof oftime timeto toreach reachthe therequired requiredcomfort comfortzone zonedue dueto tothe the This

the thermal effect evenafter afterthe thefloor floor radiant heating is operated. Figure 5 shows that thermal storage storage effect effect even even after the floor radiant heating operated. Figure shows that PMV PMVPMV thermal storage radiant heating isis operated. Figure 55 shows that experienced by the occupant does not have a significant temperature difference due to the increased experienced by the occupant does not have a significant temperature difference due to the increased experienced by the occupant does not have a significant temperature difference due to the increased activity from 8 a.m. to 10 a.m. and is located within the comfort zone. The indoor temperature shows activity fromfrom 8 a.m. to to 1010 a.m. withinthe thecomfort comfort zone. indoor temperature activity 8 a.m. a.m.and andisislocated located within zone. TheThe indoor temperature showsshows sudden increase ata.m. a.m. on 26 December(Weekday), (Weekday),and and this because thethe activity ofthe the occupant aasudden increase 88a.m. December isisis because the activity of a sudden increase at 8at onon 2626 December (Weekday), andthis this because activity ofoccupant the occupant declines at88a.m. a.m. and the system controlledto tosatisfy satisfythe the comfort ofthe thethe occupant byincreasing increasing the the declines and system controlled of occupant by the declines at 8 at a.m. and thethe system isisiscontrolled to satisfy thecomfort comfort of occupant by increasing indoortemperature. temperature. indoor indoor temperature. Dryblub blubtemperature temperaturecontrol control Dry

PMVcontrol control PMV

Indoor IndoorTemperature[℃] Temperature[℃]

25 25 20 20 15 15 10 10 55 00 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 11 22 33 44 55 66 77 88 99 10

Time[h] Time[h] Figure 9. The indoor temperature holiday (25 December). Figure 9. The indoor temperature holiday (25 December). Figure 9. The indoor temperature holiday (25 December). Dryblub blubtemperature temperaturecontrol control Dry

PMVcontrol control PMV

Indoor IndoorTemperature[℃] Temperature[℃]

25 25 20 20 15 15 10 10 55 00 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 11 22 33 44 55 66 77 88 99 10

Time[h] Time[h] Figure 10. The indoor temperature weekday (26 December).

Figure Theindoor indoor temperature temperature weekday (26(26 December). Figure 10.10.The weekday December).

3.3.Hourly HourlyCooling Coolingand andHeating HeatingRate Rate 3.3.

3.3. Hourly Cooling and Heating Rate

Thehourly hourlyzone zoneheating heatingand andcooling coolingare areanalyzed analyzedin inthis thischapter. chapter.As Asshown shownin inFigure Figure11, 11,PMV PMV The

The hourly zoneaaheating and cooling areat analyzed in this chapter. As shownisin Figure 11, PMV control generates rapidlyhigh high cooling coolingrate rate at10 10a.m. a.m. This This because the occupant is in in thehouse house control generates rapidly isis because the occupant the cleaning state which requires a high activity level at the corresponding time period. Due to the high control generates a rapidly high cooling rate at 10 a.m. This is because the occupant is in the cleaning state which requires a high activity level at the corresponding time period. Due to the highhouse activity ofwhich the occupant, occupant, the maximum loadlevel difference on the representative representative day of the the August cleaning state requires a maximum high activity at theon corresponding timeday period. Due to the high activity of the the load difference the of 66 August (Holiday) between PMV control and dry-bulb temperature control was 14,045.2 W. In addition, the (Holiday) PMV control and dry-bulb temperature was 14,045.2 W.day In addition, activity of thebetween occupant, the maximum load difference oncontrol the representative of the 6the August cooling rate was lower than that of the conventional control method for the rest of the day except for the cooling rate was lower than that of the conventional control method for the rest of the day except for (Holiday) between PMV control and dry-bulb temperature control was 14,045.2 W. In addition, 10 a.m. and 5 p.m. when the activity was high, but the daily total load of PMV control on the 10 a.m. p.m. when the activity was high, but control the dailymethod total load PMV cooling rate and was5lower than that of the conventional forofthe restcontrol of the on daytheexcept for 10 a.m. and 5 p.m. when the activity was high, but the daily total load of PMV control on the representative day of the 6 August (Holiday) was 12% higher than that of the dry-bul28b temperature control due to the high cooling rate at 10 a.m. As for Figure 12 for the weekday, the cooling rate

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representative day of the 6 August (Holiday) was 12% higher than that of the dry-bul28b temperature

rapidly increases at 9 a.m. Like the holiday, this is because the occupant is in the house cleaning state control due to the high cooling rate at 10 a.m. As for Figure 12 for the weekday, the cooling rate which requires a high activity level at the corresponding time period. Due to the high activity of the rapidly increases at 9 a.m. Like the holiday, this is because the occupant is in the house cleaning state occupant, maximum load difference the representative day Due of 7 to August (Weekday) which the requires a high activity level at theon corresponding time period. the high activity of between the PMVoccupant, control the andmaximum dry-bulbload temperature control was 6862.2 W. Like the holiday, the weekday difference on the representative day of 7 August (Weekday) between also shows a lower cooling rate than that of thecontrol conventional control method except for housealso cleaning PMV control and dry-bulb temperature was 6862.2 W. Like the holiday, the the weekday cooling than that of the conventional control except for the house cleaningto the timeshows whicha lower requires highrate activity, and load increases andmethod decreases irregularly according time of which requires highthan activity, and the decreasing load increases decreases irregularly according to the Even amount activity rather constantly asand in the conventional control method. amount of activity rather than constantly decreasing as in the conventional control method. Even though a high cooling rate occurred at 9 a.m, in case of the weekday, the daily total load of PMV though a high cooling rate occurred at 9 a.m, in case of the weekday, the daily total load of PMV control on the representative day of 7 August (Weekday) was 21% lower than that of the dry-bulb control on the representative day of 7 August (Weekday) was 21% lower than that of the dry-bulb temperature control. Figures 11 and 12 both show unusually high cooling rates at 10 a.m. and 9 a.m. temperature control. Figures 11 and 12 both show unusually high cooling rates at 10 a.m. and 9 a.m. due due to the activity when in the thehouse housecleaning cleaning state. PMV control shows to high the high activity whenthe theoccupant occupant is is in state. PMV control shows a higha high loadload for the holiday, while the dry-bulb temperature control shows a high load for the weekday. for the holiday, while the dry-bulb temperature control shows a high load for the weekday. This This is because the the high activity in the thehouse housecleaning cleaning state shows a high cooling is because high activityofofthe theoccupant occupant in state shows a high cooling rate inrate in bothboth holiday andand weekday, but holidayactivity activity level of the occupant is higher holiday weekday, butthe thedaily dailyaverage average holiday level of the occupant is higher than than the weekday activity level duetotothe thehigher higher activity activity level on on thethe holiday. the weekday activity level due levelafter after5 p.m. 5 p.m. holiday. Dry bulb temperature control

PMV control

20 18

Cooling rate[kW]

16 14 12 10 8 6 4 2 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Time[h]

Figure 11.The Thehourly hourly zone holiday (6 August). Figure 11. zonecooling coolingrate rate holiday (6 August).

Energies 2018, 11, x

Dry bulb temperature control

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PMV control

14

Cooling rate[kW]

12 10 8 6 4 2 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Time[h]

Figure Thehourly hourly zone zone cooling (7 August). Figure 12.12.The coolingrate rateweekday weekday (7 August).

However, controlling the PMV for every household considering the high activity when the occupant is cleaning seems to be unrealistic. In fact, the cooling system is not over-operated as shown in Figures 11 and 12, and most of the windows are open during cleaning time. Therefore, this study reflects this part and assumes to conduct the same dry bulb temperature control as the conventional control method at 10 a.m. (Holiday) and 9 a.m. (Weekday) when the occupant is cleaning for further analysis. As a result, the house cleaning time periods in Figures 13 and 14 show a sharp decrease of

2 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

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Figure 12. The hourly zone cooling rate weekday (7 August).

However, householdconsidering considering high activity when However,controlling controllingthe the PMV PMV for for every every household thethe high activity when the the occupant is cleaning seems to be unrealistic. In fact, the cooling system is not over-operated as shown occupant is cleaning seems to be unrealistic. In fact, the cooling system is not over-operated as shown in Figures 1111 and 12, areopen openduring duringcleaning cleaning time. Therefore, study in Figures and 12,and andmost mostof ofthe the windows windows are time. Therefore, this this study reflects this part and samedry drybulb bulbtemperature temperature control as the conventional reflects this part andassumes assumesto toconduct conduct the same control as the conventional control method atat 1010a.m. a.m.(Weekday) (Weekday)when whenthe the occupant is cleaning for further control method a.m.(Holiday) (Holiday) and and 9 a.m. occupant is cleaning for further analysis. result,the the house house cleaning in Figures 13 and 14 show a sharp decrease of analysis. AsAsa aresult, cleaningtime timeperiods periods in Figures 13 and 14 show a sharp decrease cooling load show thethe same results as the previous graph for for of cooling load compared comparedtotoFigures Figures1111and and1212and and show same results as the previous graph other time periods. Accordingly, PMV control shows a 29.3% coolingload loadreduction reductioneffect effectofof19.9 19.9kWh other time periods. Accordingly, PMV control shows a 29.3% cooling kWh on the holiday and a 39.7% reduction of 11.3 kWh on the weekday compared to the conventional on the holiday and a 39.7% reduction of 11.3 kWh on the weekday compared to the conventional control method. control method. Dry bulb temperature control

PMV control

9

Cooling rate[kW]

8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Time[h]

Figure13. 13.The Thehourly hourly zone (6 (6 August). Figure zone cooling coolingrate ratefor forthe theholiday holiday August).

Energies 2018, 11, x

Dry bulb temperature control

15 of 22

PMV control

7

Cooling rate[kW]

6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Time[h]

Figure14. 14.The Thehourly hourly zone zone cooling (7 (7 August). Figure coolingrate ratefor forthe theweekday weekday August).

On the representative days of 25–26 December in the winter, the graph forms of holiday and On the representative days of 25–26 December in the winter, the graph forms of holiday and weekday were significantly different from the previous representative days of summer. Figure 15 weekday were significantly different from the previous representative days of summer. Figure 15 shows that no load is generated even though the system is in the ON state when the activity is high, shows that no loadrate is generated even though the system is in when the ON when and the heating was generated from 7 p.m. to 11 p.m. thestate activity is the low.activity In caseisofhigh, andmaximum the heating raterate, waseven generated p.m. was to 11958.2 p.m.Wwhen activity is low. In case of heating thoughfrom PMV 7control higherthe than dry-bulb temperature control, the daily total heating rate of PMV control was 52.5% less than that of dry-bulb temperature control. In addition, the heating rate of PMV control occurred intensively from 8 p.m. to 10 p.m. when the activity level of the occupant was low. Figure 16 shows a high heating rate at 8 a.m. when the activity level is the lowest, and shows a higher heating load than that of the conventional control method due to low activity at 10 p.m.

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maximum heating rate, even though PMV control was 958.2 W higher than dry-bulb temperature control, the daily total heating rate of PMV control was 52.5% less than that of dry-bulb temperature control. In addition, the heating rate of PMV control occurred intensively from 8 p.m. to 10 p.m. when the activity level of the occupant was low. Figure 16 shows a high heating rate at 8 a.m. when the activity level is the lowest, and shows a higher heating load than that of the conventional control method due to low activity at 10 p.m. Examining the conventional control method and PMV control method separately, the amount of activity from 7 a.m. to 10 a.m. on the weekday is higher than that of the holiday, which results in the difference of heating load between the two cases. Although the maximum heating rate of PMV control was 1923.8 W higher than that of dry-bulb temperature control, the daily total heating rate of PMV control was 5.58% less than that of dry-bulb temperature control. Dry-bulb temperature control showed the highest heating rate when the system starts to operate for both holiday and weekday and PMV control showed the highest heating rate when the activity level of the occupant was the lowest. Energies 2018, x control, this confirms that the activity level and heating rate are closely 16 of 22 In the case of 11, PMV related.

Hydronic Low Temp Radiant Heating Rate[kW]

Dry bulb temperature control

PMV control

3 2.5 2 1.5 1 0.5 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Time[h]

Figure heating supplied byradiant the radiant floor heating the holiday (25 Figure 15.15. TheThe heating raterate supplied by the floor heating systemsystem duringduring the holiday (25 December). December).

Hydronic Low Temp Radiant Heating Rate[kW]

Dry bulb temperature control

PMV control

6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Time[h]

Figure 16.16. TheThe heating raterate supplied by the floor heating systemsystem duringduring the weekday (25 December). Figure heating supplied byradiant the radiant floor heating the weekday (25 December).

3.4. Daily Energy Consumption The daily energy consumption was analyzed in this chapter. Figure 17 shows the electric consumption in August. The maximum and minimum energy consumption occurred on 11 August

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3.4. Daily Energy Consumption The daily energy consumption was analyzed in this chapter. Figure 17 shows the electric consumption in August. The maximum and minimum energy consumption occurred on 11 August and 28 August, respectively. In addition, as a result of comparing the energy consumption of the conventional control and PMV control in August, PMV control consumes 176.9 kWh less energy than the conventional control, which corresponds to a 28.8% reduction rate. Figure 18 shows the gas consumption in December. The maximum and minimum energy consumption occurred on 16 December and 8 December, respectively. In addition, as a result of comparing the energy consumption of the conventional control and PMV control in December, PMV control consumes Energies 2018, 11, 17 Energies 2018, 11, xxenergy than the conventional control, which corresponds to a 24.8% reduction rate. 17 of of 22 22 249 kWh less

WindowAC ACeletric eletricpower[kWh] power[kWh] Window

Dry Dry bulb bulb temperature temperature control control

PMV PMV control control

35 35 30 30 25 25 20 20 15 15 10 10 55 00

11

44

77

10 10

13 13

16 16

19 19

22 22

25 25

28 28

31 31

28 28

31 31

Aug. Aug. day day

Figure Figure17. 17.The TheAugust Augustelectric electricconsumption. consumption. Figure 17. The August electric consumption.

Dry Dry bulb bulb temperature temperature control control

PMV PMV control control

Boilergas gasconsumption[kWh] consumption[kWh] Boiler

70 70 60 60 50 50 40 40 30 30 20 20 10 10 00

11

44

77

10 10

13 13

16 16

19 19

22 22

25 25

Dec. Dec. day day Figure18. 18.The TheDecember Decembergas gasconsumption. consumption. Figure Figure 18. The December gas consumption.

Figures Figures 17 17 and and 18 18 show show the the site site energy energy consumption. consumption. In In order order to to calculate calculate the the primary primary energy, energy, as stipulated under operating regulations of the Building Energy Efficiency Certification Program as stipulated under operating regulations of the Building Energy Efficiency Certification Program (2016.03.03, (2016.03.03, 6th), 6th), electricity electricity is is calculated calculated by by multiplying multiplying the the site site energy energy in in Figure Figure 17 17 by by 1.1, 1.1, and and the the gas gas is is calculated calculated by by multiplying multiplying the the site site energy energy heating heating rate rate in in Figure Figure 18 18 by by 2.75. 2.75. Table Table 77 [21] [21] shows shows the the primary primary energy energy conversion conversion factors factors of of the the operating operating regulations regulations of of the the Building Building Energy Energy Efficiency Efficiency Certification Program. Certification Program.

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Figures 17 and 18 show the site energy consumption. In order to calculate the primary energy, as stipulated under operating regulations of the Building Energy Efficiency Certification Program (2016.03.03, 6th), electricity is calculated by multiplying the site energy in Figure 17 by 1.1, and the gas is calculated by multiplying the site energy heating rate in Figure 18 by 2.75. Table 7 [21] shows the primary energy conversion factors of the operating regulations of the Building Energy Efficiency Certification Program. Table 7. The primary energy conversion factors.

Energies 2018, 11, x Energies 2018, 11, x

Category

Primary Energy Conversion Factor

Gas(fuel) Electricity District heating District cooling

1.1 2.75 0.728 0.937

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Heating energy[kWh] Heating energy[kWh]

3.5. Monthly and Annual Heating and Cooling Energy Consumption 3.5. Monthlyand andAnnual AnnualHeating Heatingand and Cooling Cooling Energy Energy Consumption 3.5. Monthly Consumption In this chapter, the annual heating and cooling energy consumption analysis is performed, and In thischapter, chapter, theannual heating and cooling energy consumption analysis is is performed, theInresults are shown inannual Figures 19 and 20.cooling The heating consumption was the highestand inand this the heating and energyenergy consumption analysis performed, the results are shown in Figures 19 and 20. The heating energy consumption was the highest in the lowest in April. In May, dry-bulb control did not heating theJanuary results and are shown in Figures 19 and 20. The heatingtemperature energy consumption was thegenerate highest in January January andPMV the lowest April. Inheating May,temperature dry-bulb temperature control did not generate heating energy, but control generated energy, and PMV control showed a higher heating ratebut and the lowest in April. Inin May, dry-bulb control did not generate heating energy, energy, but PMV control generated heating energy, and PMV control showed a higher heating rate consumption in March, April, and May. In the case of annual gas consumption, PMV control showed PMV control generated heating energy, and PMV control showed a higher heating rate consumption in consumption in March, andthan May.dry-bulb In the case of annual gas consumption, PMV control showed 7.3% April, less energy consumption control. Cooling energy showed the March, and May. InApril, the case of annual gas temperature consumption, PMV control showed 7.3% less energy 7.3% less energy consumption than dry-bulb temperature control. Cooling energy showed the highest consumption in August, and the consumption of dry-bulb temperature control was higher consumption than dry-bulb temperature control. Cooling energy showed the highest consumption highest consumption in August, the on consumption of dry-bulb was energy higher than PMV control in every month.and Based annual cooling energy, temperature PMV controlcontrol can reduce in August, and the consumption of dry-bulb temperature control was higher than PMV control in than PMV control in every month.toBased on annual coolingcontrol. energy, PMV control can reduce energy consumption by 28.8% compared dry-bulb temperature every month. Based on annual cooling energy, PMV control can reduce energy consumption by 28.8% consumption by 28.8% compared to dry-bulb temperature control. compared to dry-bulb temperature control. 1400 1400 1200 1200 1000

Dry bulb temperature control Dry bulb temperature control

PMV control PMV control

1 1

8 8

1000 800 800 600 600 400 400 200 2000 0

2 2

3 3

4 4

5 5

6 7 6 7 Month

9 9

10 11 12 10 11 12

Month

Cooling energy[kWh] Cooling energy[kWh]

Figure19. 19. The The annual annual heating Figure heatingenergy energyconsumption. consumption. Figure 19. The annual heating energy consumption.

800 800 600 600 400

Dry bulb temperature control Dry bulb temperature control

PMV control PMV control

400 200 2000 0

1 1

2 2

3 3

4 4

5 6 7 8 5 Month 6 7 8

9 9

10 11 12 10 11 12

Month

Figure 20. The annual cooling energy consumption. Figure 20. The annual cooling energy consumption. Figure 20. The annual cooling energy consumption.

In other words, boiler gas consumption mainly occurred in January, February, March, April, In otherand words, boiler while gas consumption occurred in January, February, March,inApril, November, December, window air mainly conditioner electricity consumption occurred May, November, and December, while electricitythe consumption occurred May, June, July, August, September, andwindow October.air Inconditioner the case of applying conventional control in method June, July,cleaning August, time September, October. In activity the caselevel of applying theoccupant conventional method for house which and requires a high from the on thecontrol weekday and

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In other words, boiler gas consumption mainly occurred in January, February, March, April, November, and December, while window air conditioner electricity consumption occurred in May, June, July, August, September, and October. In the case of applying the conventional control method for house cleaning time which requires a high activity level from the occupant on the weekday and holiday, the window air conditioner electricity consumption through PMV control reduces the electricity consumption by 28.8%, gas consumption by 7.3%, and annual energy consumption by 15.7% resulting in an excellent energy reduction effect. 3.6. Economic Analysis In this chapter, the economic efficiency was comparatively analyzed when the indoor space was controlled by the conventional dry-bulb temperature control and PMV control. In order to perform the economic efficiency evaluation, the life-cycle cost (LCC) analysis was performed based on the present value analysis method using the average discount rate of 3.24% of the 10-year base rate of the Bank of Korea, and the analysis period was for 11 years. The equipment required for PMV control and dry-bulb temperature control are listed in the following Table 8, and the initial investment cost was calculated by reviewing the quotations from many specialized companies. The annual maintenance cost of each system is assumed to be the same because the purpose is to analyze the payback period according to the annual energy cost reduction. Table 8. The initial investment cost. Dry Bulb Temperature Control Type

Temperature controller

PMV Control

Price (KRW)

Type

Price (KRW)

55,000 ($50.95)

Temperature & humidity sensor Airflow sensor MRT Camera Board Temperature controller

2000 ($1.85) 70,000 ($64.84) 45,000 ($41.69) 6000 ($5.56) 90,000 ($83.37) 55,000 ($50.95)

In case of the simulation model, each household was divided into 5 zones with 3 rooms, a kitchen, and a living room, excluding the veranda and bathroom. The total installation cost for the 5 zones of dry bulb temperature control was KRW 275,000 ($254.75), while the total installation cost for the 5 zones of PMV control was KRW 1,340,000 ($1241.32), so the initial installation cost difference between the two control methods was KRW 1,065,000 ($986.57). As a result of the monthly energy consumption analysis of dry-bulb temperature control and PMV control, PMV control showed a 7.2% and 28.8% reduction rate of annual gas and electricity energy consumption compared to dry-bulb temperature control, respectively, and an annual average energy reduction rate of 15.7%. In terms of calculating the operating cost of each system, the site energy consumption was calculated by considering the cooling and heating load and the COP of each system, and the daily and monthly power consumption was converted into the electric rate for calculation. In terms of the electric rate according to the electric base consumption, the residential service (high-voltage) rate table provided by KEPCO [22] was used, which is summarized in Table 9. The electric rates according to electricity consumption are shown in Table 10. In case of using 200 kWh or less, the guaranteed deduction for required consumption was applied through a limit reduction of KRW 2500 ($2.32) per month, and for summer (July to August) and winter (December to February), the electric rate was calculated based on the super-user rate of KRW 574.6 ($0.53)/kWh when using more than 1000 kWh. In addition, the gas rate according to gas consumption was based on the rate table provided by KOGAS [21], and the amount of adding a 10% premium to KRW 13.5353 ($0.01) per MJ was converted into kWh for calculation. As a result, the total annual savings amounted to KRW 158,845 ($147.15).

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Table 9. The rate table according to power consumption [22]. Base Rate (KRW) 1–200 kWh 201–400 kWh 400 kWh~

Energy Charge (KRW/kWh)

730 ($0.68) 1260 ($1.17) 6060 ($5.61)

1–200 kWh 201–400 kWh 400 kWh~

78.3 ($0.07) 147.3 ($0.14) 215.6 ($0.2)

Table 10. The analysis period present value. Year

Dry Bulb Temperature Control Present Value (KRW 1000)

PMV Control Present Value (KRW 1000)

1 2 3 4 5 6 7 8 9 10 11

825.68 ($767.30) 1325.07 ($1231.48) 1825.52 ($1696.74) 2310.27 ($2147.29) 2779.80 ($2583.46) 3234.60 ($3006.13) 3675.12 ($3415.54) 4101.82 ($3812.1) 4515.13 ($4196.22) 4915.46 ($4568.28) 5303.24 ($4928.66)

1731.84 ($1609.52) 2087.18 ($1939.76) 2443.27 ($2270.71) 2788.19 ($2591.26) 3122.29 ($2901.76) 3445.90 ($3202.52) 3759.36 ($3493.83) 4062.98 ($3776.01) 4357.07 ($4049.32) 4641.93 ($4313.66) 4917.85 ($4570.07)

The present value of future cash and the capitalization factor of annuity were considered in order to analyze the initial investment cost payback period according to the reduction of annual energy consumption through comparison between dry-bulb temperature control and PMV control. As a result, the calculation equations are shown in Equations (1)–(3), and the payback period analysis results considering the rate calculations and corresponding equations mentioned above are shown in Figure 21 1 PF = F (1) (1 + i ) n PA = A

(1 + i ) n − 1 i (1 + i ) n

P = PF + PA

(2) (3)

PF : The present value of future cash PA : Capitalization factor of annuity A: Annual cost F: Cost incurred after n years P: Present value I: Discount value n: Analysis period The present value of future cash for dry-bulb temperature control is KRW 275,000 ($254.75), and the capitalization factor of annuity for PMV control is KRW 1,340,000 ($1241.32). The annual cost was KRW 158,845 ($147.15), and the analysis period was for 11 years. The Table 10 shows the present value by year. As a result of payback period analysis, a payback period of about 8.4 years was required as can be seen in Figure 21. Since the schedule and activity level of the simulation model was based on a 44-year old woman from a family of four as presented in the ISO 18523-2 Residential Buildings Annex A [20], there will be some difference depending on the type of building, family members, and climate by region.

KRW 158,845 ($147.15), and the analysis period was for 11 years. The Table 10 shows the present value by year. As a result of payback period analysis, a payback period of about 8.4 years was required as can be seen in Figure 21. Since the schedule and activity level of the simulation model was based on a 44-year old woman from a family of four as presented in the ISO 18523-2 Residential Buildings Annex A [20], there will be some difference depending on the type of building, family Energiesmembers, 2018, 11, 1767 20 of 21 and climate by region. Dry bulb temperature control

PMV control

6,000

Charge($0.89)

5,000 4,000 3,000 2,000 1,000 0 0

1

2

3

4

5

6

7

8

9

10

11

Year

Figure 21. The lifecycle cost (LCC) analysis.

4. Conclusions In this study, the annual cooling and heating energy saving effect of PMV control taking hourly metabolic rate variations into account was evaluated in comparison with dry-bulb temperature control for the indoor environment of a 15-story residential apartment equipped with a radiant floor heating system and window air conditioner, and the LCC analysis was performed through the capitalization factor of annuity considering the annual cost, present value of future cash, and discount value. In case of PMV control, the indoor air was controlled to maintain a value between PMV −0.5 and +0.5 which corresponds to the comfort zone, and the conclusions of this study are as follow. In case of PMV control, when the system is ON, hourly PMVs are all located within the comfort zone. The system is turned OFF when the activity state of the occupant is sleep or unoccupied, in which PMV varies from −0.5 to −0.8, which is almost near the comfort region but not exactly within the PMV set-point of between −0.5 and +0.5. In addition, PMV values were observed to vary over time as the activity of the occupant increased or decreased. When the activity state of the occupant is house cleaning in the summer, the indoor temperature decreases rapidly due to the high amount of activity. It requires a temperature that is 11.7 ◦ C and 9.7 ◦ C lower than the conventional dry-bulb air temperature control method, respectively, and generally forms a higher indoor air temperature than the conventional control method after 7 p.m. This means the difference in temperature to satisfy the comfort of the occupant according to the amount of activity, and during winter as opposed to summer, it was found to form a lower indoor air temperature than the conventional temperature control. In case of annual boiler gas consumption, PMV control showed 7.3% less energy consumption than dry-bulb air temperature control, and PMV control showed 28.8% less energy consumption than dry-bulb air temperature control for annual cooling electricity consumption. Considering the cooling and heating energy reduction rate and the initial installation cost of measuring equipment for real-time metabolic rate and PMV measurement, a payback period of about 4.15 years is required, and in case of mass production, the payback period is expected to be further reduced due to the reduction of production costs. However, the corresponding schedule is based on a 44-year old woman described in ISO Standard 18523-2, and there will be some differences depending on the climatic condition by region and the type of building. Author Contributions: All authors contributed equally to this work. All authors designed the simulations, discussed the results and implications and commented on the manuscript at all stages. S.H.H. performed the energy simulations and J.M.L. led the development of the paper. J.W.M. and K.H.L. performed the result analysis and discussion. Acknowledgments: This research was supported by a grant (code 18CTAP-C130966-02) from Infrastructure and Transportation Technology Promotion Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

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Conflicts of Interest: The authors declare no conflict of interest.

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