Energetic performances of an optimized passive Solar Heating Prototype used for Tunisian buildings air-heating application

Energy Conversion and Management 87 (2014) 285–296

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Energy Conversion and Management journal homepage: www.elsevier.com/locate/enconman

Energetic performances of an optimized passive Solar Heating Prototype used for Tunisian buildings air-heating application Farah Mehdaoui, Majdi Hazami ⇑, Nabiha Naili, Abdelhamid Farhat Laboratoire des Procédés Thermique, Centre de Recherches des Technologies de l’Energie, Hammam Lif, B.P. 95, 2050 Tunis, Tunisia

a r t i c l e

i n f o

Article history: Received 24 February 2014 Accepted 5 July 2014

Keywords: TRNSYS 16 Floor heating Auxiliary heating Solar fraction

a b s t r a c t This paper deals with the energetic performances of a Solar Heating Prototype (SHP) conceived in our laboratory to prevail the Tunisian households’ air-heating needs. The conceived SHP mainly consists of a flat-plate solar collector, solar hot water tank and an active layer integrated inside a single room. Firstly, a complete model is formulated taking into account various modes of heat transfer in the SHP by means of the TRNSYS simulation program. To validate the TRNSYS model, experimental tests under local weather conditions were performed for 2 days spread over 2 months (March and April 2013). Predicted results were compared to the measurements in order to determine the accuracy of the simulation program. A parametric study was then achieved by means of the TRNSYS program in order to optimize SHP design parameters (Collector area, collector mass flow rate, floor mass flow rate, storage tank volume and thickness of the active layer). The optimization of all design parameters shows that to achieve a maximum performances from the SHP it is essential to use a solar collector with an area equal to 6 m2 area, a collector mass flow rate equal to 100 kg h1 and a hot water storage tank with a capacity equal to 450 l. Concerning the floor heating, the optimal values of mass flow rate and the active layer thickness are 200 kg h1 and 0.06 m, respectively. The long-term SHP performances were afterward evaluated by means of the Typical Meteorological Year (TMY) data relative to Tunis, Tunisia. Results showed that for an annual total solar insolation of about 6493.37 MJ m2 the average solar fraction obtained is about 84%. The results show also that the request of auxiliary energy is limited to the cold months of the year chiefly from December to Mars. The results show also that the SHP reduce the relative humidity inside the monozone room of about 40%. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction 1.1. Literature review Tunisia does not much natural resources (only an average amount of Petroleum and gas in the south) and it depends mainly on what it imports of fuel for its industrial energy requirements. A major part of these demands, in fact are used for heating, cooling, ventilation and sanitary hot water used in households heating for taking showers and washing clothes in both urban and rural areas. In Tunisia, Surveys conducted by STEG [1] highlight the growing numbers of the electricity consumption in Tunisia, the rate of electricity consumption as a function of time follows a rising curve. Fig. 1 shows that in 1990 electricity consumption is equal to 4930 GW h and reaches 8960 GW h in 2000. In 2010, this value reaches 13,800 GW h. Henceforth, the use of solar energy through ⇑ Corresponding author. Tel.: +216 71430044/71430215; fax: +216 71430934. E-mail address: [email protected] (M. Hazami). http://dx.doi.org/10.1016/j.enconman.2014.07.024 0196-8904/Ó 2014 Elsevier Ltd. All rights reserved.

domestic solar water heating (DSWH) systems would likely present great chance for decreasing the amount of conventional energy needed .Besides, DSWH systems have a significant capability to diminish environmental pollution arising from the use of fossil fuels. Various studies and researches on domestic hot water (DHW) production were introduced and developed. The most popular of these studies aims to evaluate the energetic potential obtainable by the management and the vulgarization of DSWH systems all over the world [2–4]. The using of DSWH system in buildings air-heating application has also solicited a greater request from researchers from all over the world. Recently, solar floor heating systems has received more attention because of its advantages of the thermal regulation in the building, less pollution and easily integrated with solar system. It provides very comfortable, uniform heat, owing to the relatively low temperature and the large surface area from which the heat is radiated. It does not interfere with furnishings in a home as most other heat distribution systems do. It can be achieved with tubing embedded in a slab; hot water is pumped through the tubing. The

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Nomenclature Ac Ai Cp FR I Mi _ m md1 md2 _h m _L m N q QAux Qc QL Q0 Qi SF Sh SL Ta

total collector area (m2) surface area of the ith tank segment (m2) specific heat of the fluid (kJ kg1 k1) overall collector heat removal efficiency factor global (total) horizontal radiation (kJ h1 m2) mass of fluid in the ith section (kg h1) flow rate at use conditions (kg h1) collector mass flow rate (kg h1) floor mass flow rate (kg h1) fluid mass flow rate to tank from the heat source (kg h1) fluid mass flow rate to the load and/or of the makeup fluid (kg h1) number of fully mixed (uniform temperature) tank segments global heat transfer coefficient (W K1) auxiliary energy (MJ m2) useful energy gain (MJ m2) energy rate to load (MJ m2) heat output upwards from the floor (W) rate of energy input by the heating element to the ith segment (MJ m2) solar fraction (%) number of the tank segment to which the fluid from the heat source enters 1 6 Sh 6 N number of the tank segment to which the fluid replacing that extracted to supply the load enters 1 6 SL 6 N ambient (air) temperature (K)

slab warms up and slowly radiates heat into the room. Nematollahi et al. [5] investigate a purposed solar heating system used for domestic and buildings air-heating. The system consists of a flatplate solar collector that provides hot water connected to a vertical water storage tank and floor heating active layer integrated inside a tested room. The results indicate that the average efficiency of the purposed system is about 68%. In 2012, Will et al. [6] outlines the strengths of two modeling tools, TRNSYS and ESP-r, through a new co-simulator in order to evaluate the potential contributions of a seasonal solar thermal system at a single-house scal. This system uses a small shortterm tank for DHW loads and a second, larger seasonal tank for space heating. Zhao et al. [7] proposed a numerical study for a solar combi-system (DHW and space heating). This system was modeled through TRNSYS for a 3319 m2 building area in china. The TRNSYS model has been validated by data from the literature. Results showed that the designed solar system can meet 32.8% of the thermal energy demand in the

Fig. 1. Electricity consumption in Tunisia.

Tc Tenv Tf Th TL Ti T0 Tr U UL UL/T

inlet temperature of fluid to collector (K) temperature of the environment surrounding the tank (K) surface floor temperature (K) temperature of the fluid entering the storage tank from the heat source (K) temperature of the fluid replacing that extracted to supply the load (K) temperature of the ith tank segment (K) outlet temperature of fluid from collector (K) inside design room temperature (K) loss coefficient between the ith tank node and its environment (kJ h1 m2 k1) Overall thermal loss coefficient of the collector per unit area (kJ h1 m2 k1) Thermal loss coefficient dependency on T (kJ h1 m2 k1)

Greek symbols (sa) product of the cover transmittance and the absorber absorptance (sa)n (sa) at normal incidence ai a control function defined by ai ¼ 1 if i = Sh; 0 otherwise bi a control function defined by bi ¼ 1 if i = SL; 0 otherwise P _ h j¼i1 ci a control function defined by ci ¼ m j¼1 aj Pj¼N 1 _ L j¼iþ1 bj (kg h ) m

g

collector efficiency (%)

heating season and 84.6% of the energy consumption in non-heating season, with a yearly average solar fraction of 53.04% In 2011 Xi et al. [8] designed a solar-assisted ground-coupled heat pump (SAGCHP) system with heat storage for space heating and domestic hot water (DHW) supply. Simulation by TRNSYS aimed at achieving an advantage over a ground coupled heat pump (GCHP) system in climatic conditions in the region of Beijing. Optimization of the design shows that the heating efficiency is improved by 26.3%. In order to increase the fraction of solar energy used in supplying energy for the operation of a building, many studies are considered in literature: Li et al. [9] simulates a solar desiccant cooling and heating system. During this simulation, the seasonal total heating load is about 49.0% is handled by solar energy. Kemal et al. [10] studied the performance of the solar-powered floor heating system in a building designed in Shanghai. With respect to the whole heating period, the solar fraction was 56%. In 2012 Kacan et al. [11] has done an experimental study to improve the existing solar space heating systems in Turkey. The system includes two closed flow cycle. The results show that energy saving ratio is performed between 59% and 89% monthly. Also fractional solar consumption (FSC) change is investigated daily, monthly and annually. Annual FSC value of the established system is approximately 83%. A technical and an economic viability of a combined solar boiler integrated system that can run alternately, or simultaneously to reduce the yearly energy invoice was proposed by Al-Salaymeh et al., in 2010 [12]. He shows that the space and the water heating by using a DSWH system may reduce about 39% of home energy consumption. In this context Chargui et al. [13] developed a model for solar water heaters with a coupling of a thermosiphon collector and a single house. The results obtained by TRNSYS software show that the designed system could provide 40–70% of the hot water demands in winter by utilizing solar energy. In 2012, Mokhtari

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1.2. Context and endeavor of this paper By the virtue of its position Tunisia has an important potential of solar energy with a monthly average global radiation varies from 2 kW h m2 day1 for the month less sunny winter to 8 kW h m2 day1 for about the sunniest month of the summer [17]. The climate in Tunis, Tunisia is characterized by a relatively cold winters and relatively warm summers. In Fig. 2 is represented the annual external ambient temperature variation. The profile of the plot show that in cold months (October to Mars) the ambient temperature ranges between 7 and 18 °C. In Fig. 3 is represented the monthly average ambient temperature same as the average monthly insolation. We notice that August is the hottest month of the year with an average temperature of 26.8 °C and an insolation about 747 MJ m2 while January is the coldest month with an average temperature of 11.51 °C and an insolation about 280.16 MJ m2. The average annual temperature and insolation reached in the site are 18.35 °C and 541.11 MJ m2, respectively. Therefore, there is a necessity to uphold another type of heating systems based on solar energy. The most important advantage of solar energy compared to the usage of fossil fuels for DSWH production is that it does not pollute the environment. In this context we propose in this paper the study of the long-term performances of a prototype used for bulidings air-heating. The system is composed of a flat-plate solar collector, a storage hot water tank and an active layer integrated inside the heated room (Fig. 4). The endeavor of this paper is to achieve a long-term performances investigation of an air-heating solar prototype (SHP) used for Tunisian households by developing a simulation model by TRN-

900 800

28

I Tamb

26 24

700

22 600

20

500

18 16

400

temperature (°C)

insolation (MJ/m2,month)

et al. [14] presented the study of the thermal behavior of a house provided with a heating system per solar floor, it concludes that the control strategy taken, (the mode on/off of the pump), is a good strategy for radiant heat control since, it allowed the control of the floor temperature and makes it possible to keep the room air temperature in desired range. In 2011, Elmaleh et al. [15] has installed a solar system design floor heating. The surface temperature of the room and the temperature of the heating tube were measured. Experimental results were compared with the theoretical results given by TRNSYS. He noticed that the insulation has saved about 40% of the consumed fuel annually. Elmaleh et al. [16] presented a numerical study of a local thermal comportment integrating it under floor heating based on TRNSYS. The results showed that when the flow was reduced from 90 kg/h to 55 kg/h a slight changing happened on the room temperature between (20 °C and 22 °C) and can be overcome by reducing the step between the pipes.

14 300

12 10

200 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Months Fig. 3. Monthly weather data for borj-cedria.

SYS program. To accomplish this investigation the TRNSYS model need various inputs especially the SHP characteristics like the dimensions of all components (e.g. flat-plate solar collector (FPC) and hot water storage tank size), the FPC efficiency and storage tank energy losses. The methodology in this work consists in: – The determination of the experimental inputs of the TRNSYS simulation model of the FPC. – The carry out of an experimental tests during selected days of Mars and April 2013 by using TRNSYS model. The objective of these tests is the determination of the thermal behavior of the SHP during a short-term period. – The validation TRNSYS model presents suitable results by comparing the simulated and the experimental results during the selected days of Mars and April 2013, The evaluation of the long-term/annual performances of the SHP by introduction the meteorological year for Tunis, Tunisia. The long-term/ annual performances investigation includes: energy collected from the FPC, energy load, auxiliary energy and solar fraction (SF).

2. TRNSYS system simulation 2.1. Description of the TRNSYS program The SHP model was developed by using TRNSYS simulation program (Fig. 5) (Table 1). The description of the building components is assumed by Type 56. This Type permits the specification of the walls composition, orientation and types of glazing used. This Type defines also the initial conditions of the studied area (indoor temperature and relative humidity), the control parameters of heating and cooling as well as frees contributions. The different levels of the building are reconstituted through cutting the thermal homogeneous areas. The characteristics of the walls, windows, doors, floors and ceilings (dimensions, materials, orientation, etc.), in each area, were obtained from architectural drawings [18]. Thermo physical properties of each wall layer (thermal conductivity, density, specific heat, thickness, etc.) are either entered by the user or chosen from an existing library. The beginning of the work is to model home with a subroutine TRNBuild to define the structure and size of the buildings (Table 2).

2.2. Procedure followed

Fig. 2. Annual variation of the external temperature.

The studies of the thermal performances of the SHP were achieved conferring to the following approaches:

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Fig. 4. Schematic description of the experimental prototype.

Fig. 5. TRNSYS diagram relative to the SHP.

– The first approach consists in the achieving of an experimental investigation during the same selected days of March and April 2013 in view of determining the solar collector instantaneous efficiency and the storage tank heat loss coefficient. These parameters are used as TRNSYS program inputs. The experiments were also used to validate the TRNSYS simulation program.

– The second approach consists in performing a simulation of the SHP behavior by using TRNSYS program [18]. The simulation was accomplished during selected days of March and April 2013. – When the numerical results present an acceptable accuracy with the experimental results, we study the evaluation of the long-term/annual performances of the SHP according to Tunis, Tunisia weather data.

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F. Mehdaoui et al. / Energy Conversion and Management 87 (2014) 285–296 Table 1 The main components of the TRNSYS simulation program. Components

Symbol

Description

Type 1b (flat-plate solar collector)

Fluid(water) is usually circulated through tubing to transfer heat from the absorber to an insulated water tank

Type 56a (multizone building)

an active layer integrated inside the monozne room

Type 4c (storage tank)

A stratified storage tank having 2 inlets and 2 outlets. It includes an auxiliary electric heaters in order to have the desired hot water temperature

Type 3b (pump)

Computes a mass flow rate using a variable control function, which must have a value between 1 and 0, and a fixed maximum flow capacity

Type 2b (control function)

Generates a control function which can have a value of 1 or 0. The value of the control signal is chosen as a function of the difference between upper and lower temperatures

Type 65c (online plotter)

Display selected system variables while the simulation is progressing. The selected variables will be displayed in a separate plot window on the screen

Type 69b (Sky temperature)

Determines an effective sky temperature

Type 33e (psychrometric)

Calculate the corresponding moist air properties

Type 109 (TMY-2 weather data)

A Typical Meteorological Year (TMY) data bank (Type 109) is used to simulate Tunisian weather and Meteorological data changes

Type 57 (converter)

A unit conversion routine utilized to accustomed users to working with English units

Table 2 Structure and size of the buildings. Category

Area (m2)

Layer

Thickness (m)

Conductivity (kJ h1 m1 K1)

Density (kg m3)

Capacity (kJ kg1 K1)

External north

16

Brick Concrete Gypsum

0.15 0.05 0.05

3.2 7.56 0.75

1800 2400 1200

1 0.8 1

External south

12

Brick Concrete Gypsum

0.15 0.05 0.05

3.2 7.56 0.75

1800 2400 1200

1 0.8 1

External east

16

Brick Concrete Gypsum

0.15 0.05 0.05

3.2 7.56 0.75

1800 2400 1200

1 0.8 1

External west

12

Brick Concrete Gypsum

0.15 0.05 0.05

3.2 7.56 0.75

1800 2400 1200

1 0.8 1

Boundary

12

Concretes Active layer Concretes Insulation

0.06 0.06 0.05

4.068 4.068 0.144

1400 1400 40

1 1 0.8

Boundary

12

Concrete

0.240

7.56

2400

0.8

3. Mathematical description 3.1. Solar collector A general equation for solar thermal collector efficiency can be obtained from the Hottel-Whillier equation (Attar I [19]) as:

g¼

Qc T  Tc Tc  Ta _ p 0 ¼ mC ¼ F R ðsaÞn  F R U L I  Ac I  Ac I

ð1Þ

The loss coefficient UL is not exactly constant, so a better expression is obtained by taking into account a linear dependency of UL versus (Tc  Ta):

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4. Experimental study 4.1. Experimental apparatus

Fig. 6. Stratification hot water cylinder.

g¼

Qc Tc  Ta ðT c  T a Þ2 ¼ F R ðsaÞn  F R U L  F R U L=T I  Ac I I

ð2Þ

Eq. (2) can be rewritten as:

g¼

Qc Tc  Ta ðT c  T a Þ2 ¼ a0  a1  a2 I  Ac I I

ð3Þ

Which is the general solar collector thermal efficiency equation used in Type 1. The thermal efficiency is defined by 3 parameters: a0, a1 and a2 determined from the g plot by using the least square method. Those 3 parameters are available for collectors rated by Hazami et al. [20,21]. 3.2. Storage tank In this study, the cylindrical hot water storage tank is simulated by Type 4c. The thermal performance of a fluid-filled sensible energy storage tank, subject to thermal stratification, is modeled by assuming that the tank consists of N fully-mixed equal volume segments, as shown in Fig. 6. An assumption, employed in this model, is to assume that the fluid streams flowing up and down from each node are fully mixed before they enter each segment [18]. An energy balance written about the ith tank segment is expressed

Mi C p

dT i _ h C p ðT h  T i Þ þ bi m _ L C p ðT L  T i Þ þ UAi ðT env  T i Þ ¼ ai m dt þ ci ðT i1  T i ÞC p þ Q i

ð4Þ

The temperatures of each of the N tank segments are determined by the integration of their time derivatives expressed in the above equation. At the end of each time step, temperature inversions are eliminated by mixing appropriate adjacent nodes. 3.3. Heating loads The under floor heating model is based on one-dimensional heat transfer concepts for internal flow in pipes as well as heat transfer through a horizontal plate heated from its lower surface. The amount of energy heating the space per unit floor area is represented by Attar et al. [19]:

Q 0 ¼ qðT f  T r Þ

ð5Þ

An experimental device (Fig. 7) is mounted in CRTEn, Borj Cedria, Tunis (Located in the north of Tunisia) in order to test the reliability of the TRNSYS simulation program. The experimental device consist of a flat-plate solar collector, FPC, (1) with a total absorber surface of 2 m2, oriented N–S and tilted 45° towards the south. The FPC is connected to a stainless steel hot water tank (2) with 200 l storage capacity insulated with 5 cm thick of Armaflex. Inside the hot water tank is placed two immersion heaters of 3.0 kW. The electric heaters function of the heaters is controlled by a thermostat placed inside the hot water storage tank. The experimental device consists also of a monozone room (3  4  4 m) (3). The floor (4) consists of concrete slab traversed by a winding system composed of copper tubes. The floor is isolated from the ground by a layer of 50 mm of polystyrene. The heating flow is assured by a pump (5) a solenoid valve (6) and a flow-meter (7) integrated at the experimental loop. A data acquisition system was installed in the laboratory to track all experimental parameters changes during the tests. Thus, 2 Pt100 sensors (8) are used to measure the inlet and outlet temperature of the FPC vs local time variation. Another Pt100 sensor (9) was placed out of the solar collector to measure the ambient air temperature. The incident solar radiation was measured with a Kipp and Zonen pyranometre (11) installed such that its aperture is leveled with the aperture of the collector without casting shadow on the collector. The profile of temperature inside the tested room is measured by 4 Type K thermocouples (10) positioned vertically in the room (Fig. 7). All the measuring sensors were connected to a multi-channel data acquisition (12) system type HP Agilent, which were stocked in a PC station (13). 4.2. Experimental tests To validate the TRNSYS simulation program of the SHP thermal behavior a number of experiments are conducted in our laboratory – A primary outdoor experimental test was achieved in order to determine the characteristics parameters of the solar collector. The test begins at 9:00 h (Local solar time) and finished at 18:00 h (The end of the solar journey). During the tests, the following conditions have been taken into account in order to enhance the feasibility of results: (i) a total solar energy higher than 16 MJm2; (ii) the average wind speed should be lower than 1.5 ms1 without periods of more than 30 min with constant velocities higher than 3 ms1 (out of this range, the collectors performance is sensitive to air speed); (iii) the water inlet temperature in the system will be at 20 ± 2 °C and (iv) average ambient temperature between 20 °C and 30 °C. The test consists in varying the solar collector inlet water temperature by using a water/water heat pump and following the outside water temperature. The difference of water temperature between the inlet and the outlet of the solar collector permit the evaluation of the useful energy gain and then instantaneous efficiency g changes of the solar collector (Eq. (3)) (Hazami et al. [20,21]). – The second test is conducted in order to evaluate the heat loss coefficient (Uc) of the hot water storage cylinder is determined by an independent test (Hazami et al. [19,20]). It consists in: (i) heating the water inside the stainless steel storage tank to the value of 70 °C, then the immersion heaters were set to turnoff,(ii) measuring the temperature decrease of the hot water in the stainless steel storage tank while the hot water is left to cool down during Dt = 24 h. UC rate is calculated as:

F. Mehdaoui et al. / Energy Conversion and Management 87 (2014) 285–296

291

Fig. 7. Schematic description of the experimental prototype.

g¼

Cp T i  T ext ln V:Dt T f  T ext

ð6Þ

The characteristics parameters of the solar collector and the heat loss coefficient of the hot water storage cylinder presented in Table 3 are used as inputs parameters of the TRNSYS model. – Another experimental test is accomplished in order to track the SHP inlet and outlet temperature changes vs local time and the energy supplied from the SHP. These experiments were carried out for two selected days: (i) (07/03/2012), characterized by heavily overcast and intermittent cloud covered sky and (ii) (07/04/2012) characterized by a clear sky. The test begins at 0:00 h (Local solar time) when the data acquisition system is switched on. After 24 h the test is finished. 4.3. Uncertainty analysis In order to appraisal the accurateness of the experimental measurements, an uncertainty analysis is achieved. In this study, we evaluate the errors due to the sensitiveness of equipment and measurements explained in the section 4.2. Experimental errors came chiefly from measurement of temperature and the flow rate. The errors are evaluated as below: – Sensitiveness and measurement error of data acquisition system and Pt-100 sensor are respectively, about ±0.1 °C and ±0.2%.

Table 3 Trnsys input parameters. Parameters

Value

Unit

Tested flow rate Intercept efficiency, a0 First order efficiency coefficient, a1 First order efficiency coefficient, a2 Hot water cylinder loss coefficient

100 0.71 1.03 0.02 1.6

kg h1 m2 % W m2 K1 W m2 K2 W m2 K1

– Sensitiveness and errors measurement of the flow meter are respectively about ±0.1 °C and ±0.1%. In total, errors of measurement of the flow rate are about ±0.2%. 5. Results and discussions 5.1. Sensibility of TRNSYS simulation program In Fig. 8a and b is represented the variations of the inlet and the outlet temperature of the storage tank given by the experimental test and TRNSYS simulation program during 07/03/2013. We note that the TRNSYS model flows, with an acceptable inaccuracy, the measured values given by the experimental test. Indeed, the difference between the simulated and the measured values of the storage tank inlet temperature is about 2–4 °C whilst the difference between the modeled and the measured values of outlet temperature is about 1–5 °C. A comparison between the energy supplied from the SHP respectively given by the experimental test and TRNSYS simulation program during the same selected days (07/03/2013) and (07/04/ 2013). We note that, for the overcast cloud sky days (07/03/ 2013) (Fig. 9a) and for a clear sky day (07/04/2013) (Fig. 9b), the model slightly underestimates the measured values with accuracy that ranges between 5% and 7% points. However, the profile of the experimental and the TRNSYS simulation of the energy supplied from the SHP system vs local time represent a great similitude. The gap between the experimental and simulated results observed in Fig. 9 can be attributed to experimental errors that are a function of unstable weather conditions. Hence we conclude that the TRNSYS simulation program could reproduce with an acceptable accuracy the real behavior of the SHP. 5.2. Optimization of the SHP parameters The optimization of the SHP (the solar collector, the storage tank and flow among the prototype and the heating floor)

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Fig. 8. Measured and simulated temperature at: (a) inlet water storage tank and (b) outlet water storage tank.

performances was achieved by considering the TRNSYS simulation monthly/annual solar fraction, SF, changes. The SF is defined as [20,21]:

SF ¼

Q L  Q Aux Q ¼ 1  Aux QL QL

ð7Þ

where QAux is the total auxiliary energy supplied to the system to support the portion of the total load that is not provide by the solar energy. The first set of simulation is accomplished in order to evaluate the suitable solar collector area (Ac). It consists in the estimation of the monthly and annual SF value according to Ac changes. The set of simulations are achieved for; (i) one solar collector with an area of 2 m2, (ii) two coupled solar collectors with a total area of about 4 m2, (iii) three coupled solar collectors with a total area of about 6 m2 and (iv) four coupled solar collectors with a total area of about 8 m2. During the simulation, the modification of the collector areas is accomplished taking into account the initial value the hot water cylinder volume-to-collector area ratio (V/Ac) which is 75 l/m2 (Hazami et al. [21]). The monthly SF changes for each total collectors area is presented in Fig. 10. The results of the first simulation achieved for only one solar collector of 2 m2 of collected area shows that the SF ranges between 18% and 100%. The second rang of simulation is accomplished for a combination of 2, 3 and 4 coupled solar collectors with a total collector area equal to 4 m2, 6 m2 and 8 m2, respectively. The results of the simulation shows that, for 4 m2, 6 m2 and 8 m2 of total collectors area, the SF ranges between and 30–100%, 45–100% and 58–100%, respectively. Considering the cost, space requirements and reliability issues,

Fig. 9. Variation of simulated and measured energy supplied from the DSWH system during: (a) (07/03/2013) and (b) (07/04/2013).

6 m2 of area can be considered as the adequate size for the present application study. The second set of simulation is accomplished in order to determine the adequate the solar collector’s mass flow rate (md1) relatively to the optimal collector area of 6 m2. The annual SF was simulated for md1/Ac ranging from 5 to 60 kg h1 m2 (Fig. 11). The plot shows that SF rises rapidly as md1/Ac increases from 5 to 20 kg h1 m2. Indeed SF increases from 79% at 5 kg h1 m2 to a maximum value of approximately 84% in the range 16– 25 kg h1.m2. Then SF starts to decrease and becomes in the order of 82% once md1/Ac is of about 60 kg h1 m2. Hence, to promise a maximum value of SF, the flow rate md1 traversing the 6 m2 of solar collector should be equal to the optimal value of about 100 kg h1. Another set of simulation is accomplished in order to estimate the optimal value of storage tank volume (V) allowing for the optimal solar collector area (6 m2) and the adequate solar collector’s mass flow rate (100 kg h1). Various ratios of (V/Ac) (16– 200 l m2) are considered during the TRNSYS simulation. In Fig. 12 is resumed the outcome of the variation of the hot water tank volume on SF changes. We note that, for the SHP, the annual SF increases rapidly as V/Ac increases from 20 to 75 l m2 and beyond the value of 140 l m2 the SF decreases. It was found that for the values of 75 l m2 the annual SF reaches the maximum value of about 83.6%. Considering the optimal value of the solar collector area (6 m2), the optimal value of 75 l m2 corresponds to 450 l which represents the optimal capacity of the storage tank that permit the attempt of the maximum rate of SF. The effect of floor heating’s mass flow rate (md2) on the annual and monthly SF was also simulated for md2 ranging from 100 to 250 kg h1 (Fig. 13). The results indicate that the monthly SF

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1,2

1,2 2 m2 4 m2 6 m2 8 m2

1,0

1,0

0,8

0,8

SF (%)

SF (%)

150 kg.h-1 200 kg.h-1 250 kg.h-1

0,6 0,4

0,6 0,4

0,2

0,2

0,0 0,0

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Jan

Months

Feb Mar Apr May Jun

Jul

Aug Sep Oct Nov Dec

Months

Fig. 10. Variation of monthly SF for different collector area. Fig. 13. Variation of the annual SF for differents flow rate to floor heating.

1,1

0,84

1,0

e=0,06m e=0,1m e=0,2m

0,83 0,8

0,82

SF (%)

SF (%)

0,9

0,81

0,7 0,6 0,5

0,80

0,4 0,79 0

10

20

30

40

50

60

md1/A c (kg/hm2)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Months

Fig. 11. Variation of the annual SF versus the collector flow rate to area ratio (md1/ Ac).

Fig. 14. Variation of the annual SF for diffeerents thicknes.

Thus we conclude that 200 kg h1 can be considered as the optimal value of mass flow rate traversing the active layer. The effect of the thickness (e) between the active layer and surface of floor heating on the system performance was also studied over a range of e varying from 0.06 m to 0.2 m. The variation of the monthly SF for different thickness (e) is represented in Fig. 14. The results show that the thickness of 0.06 m represents the optimal value of distance between active layer and exchange of area. This is explained by the increase of the heat losses from the heating floor, when the thickness (e) becomes greater.

0,84 0,84 0,83 0,83

SF (%)

0,3

0,82 0,82 0,81 0,81

5.3. Long-term performances of the optimized SHP

0,80 0

50

100

150

200

V/A c (l/m2) Fig. 12. Variation of the annual SF of the value of the hot water tank volume to collector area ratio (V/Ac).

increase with mass flow rate (md2). Indeed by using mass flow rate of about 150 kg h1, the SF ranges between 26% and 100%. The results show also that whilst md2 is equal to 200 kg h1, the SF ranges between 45% and 100%. We note that once md2 is about 250 kg h1 there are no perceptible changes in the SF variation about 2% and 5% observed during the period of (January to May).

The optimization of all design parameters shows that to achieve a maximum performances from the SHP it is essential to use a solar collector with Ac equal to 6 m2 area, a collector mass flow rate md1 equal to 100 kg h1 and a hot water storage tank with a capacity (V) equal to 450 l. Concerning the floor heating, the optimal values of mass flow rate (md2) and the active layer thickness (e) are 200 kg h1 and 0.06 m, respectively. In this section we intend the appraisal of the long-term performance of the SHP by introduction the Typical Meteorological Year data relative to Tunis, Tunisia. In Fig. 15 is represented the monthly/yearly energy flows (The energy collected (QC), the auxiliary energy (QAux) and the heat delivered (QL)) and solar fraction, SF, variation through the SHP by considering the optimized parameters. Fig 15 shows clearly that the energy

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Fig. 15. SHP’s Monthly and yearly energy flows and solar fraction variation.

Table 4 Energetic analysis and monthly temperature. Time (month) January February March April May June July August September October November December Total Annual average

I (MJ m2 month1)

Tam (°C)

Qc (MJ m2 month1)

Tair (°C)

SF (%)

11.51 11.96 13.20 15.40 19.26 22.86 26.40 26.81 24.19 20.45 15.71 12.50

180.88 174.62 249.92 245.38 299.88 329.20 395.84 410.03 388.58 337.91 248.73 202.80

328.54 283.02 293.57 251.17 276.19 308.74 377.01 390.69 367.01 309.79 246.78 301.20

180.28 139.75 73.69 32.40 3.60 0.00 0.00 0.00 0.00 0.00 25.87 127.93

25.56 25.68 26.61 27.43 28.79 29.67 30.39 30.76 30.12 29.25 27.40 25.87

0.45 0.51 0.75 0.87 0.99 1.00 1.00 1.00 1.00 1.00 0.90 0.58

6493.37 541.11

– 18.35

3463.77 288.65

3733.71 311.14

583.52 48.63

– 28.13

– 0.84

30

Temperature (°C)

28 26 24 22 20 18

14 12

Qaux (MJ m2 month1)

280.16 320.93 502.48 589.54 748.63 810.20 848.59 747.81 594.52 459.10 322.03 269.38

32

16

QL (MJ m2 month1)

Tamb Tair (unheated room) Tair (without auxiliary energy) Tair (with auxiliary energy)

10 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Months

load. During the summer months (Jun, July and August) the heat requirements are fully met by solar, hence no auxiliary is needed. Indeed during the hot months (May, Jun, July, August September), about 100% with an annual average of SF about 84%. The comparaison between this value of annual solar fraction and those given by literature [22–25] shows that the proposed SHP presente many advantages shiftly in reducing the use of auxiliary energy in space heating. In fact, the SHP increase the solar fraction of about 20%. Also the SF achieved by the proposed SHP is slightly superior to the solar faction given by Kacan et al. [11], this is explained by the similar meteorological data of Tunisia and Turkey [26]. However, the SF is lower during the cold months (December, January and February), ranging from 45% to 50%. We perceive also that the heat delivered Q L is maximized in the month of August, about 390 MJ m2 (Fig. 15). Table 4 shows that the annual total value of the energy load (Q L) calculated by TRNSYS program is equal to 3733.71 MJ m2.

Fig. 16. Internal air temperature changes vs months.

5.4. Building temperature and relative humidity evolution collected (QC) during the summer season is more important compared to the cold season. The annual total and annual average of QC are respectively about 3436.77 MJ m2 and 288.65 MJ m2 (Table 4). On the other hand we noted that the monthly average quantity of auxiliary energy added varied respectively between 180 MJ m2 and 0 MJ m2 in January and July and with a yearly total estimated to 583.52 MJ m2 (Table 4). QAux represents about 17% of collected energy and about 15.6% of total annual energy

In order to study the influence of SHP on the thermal behavior of the simulated room, another series of simulations was accomplished. Fig. 16 illustrates the air temperature changes of the simulated room with and without auxiliary heating system applies. We notice that without making appeal to the auxiliary heating system the monthly average internal temperature during cold months (from December to Mars) ranges between 22 and 25 °C. When the auxiliary heating system is activated the temperature ranges

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100 outdoor humidity indoor humidity

Relative humudity (%)

90 80 70 60 50 40 30 20 10 0

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Months Fig. 17. Variation of the monthly relative humidity indoor and inside the room.

during the same period from 25 to 28 °C. This result confirms that the request of auxiliary energy is limited to the cold months of the year chiefly from December to Mars. We perceive that the auxiliary energy permit the gain of about 4 °C compared to the air temperature inside the room without using auxiliary heating system. The Fig. 16 shows also that from April to November there is no requisite of auxiliary heating system. Compared to the simulated inside air temperature variation whilst the room is not heated, we perceive that the SHP guaranteed the gain of about 6 to 10 °C respectively without and with auxiliary heating system. In Fig. 17 is represented the monthly indoor and outdoor relative humidity evolution vs months. Fig. 17 schows that the outdoor relative humidity ranges between 72% and 78% during cold months (From October to Mars). Fig. 17 shows that use of the SHP reduces obviously the relative humidity inside the tested room. Indeed the relative humidity inside the tested room ranges during cold months between 35% and 38%. The comparaison between these results and those given by literature ([5,13]) shows that the proposed SHP presente many advantages shiftly in reducing the excessive humidity in Tunisian houses. In fact, the SHP reduce the relative humidity inside the the monozone room of about 40%.

6. Conclusion In this study, the long-term thermal and energy performances of new passive SHP used for buldings air-heating during cold months. This SHP mainly consists of a flate plate collector, storage tank and an active layer integrated in a single house. A TRNSYS simulation program was proposed in order to optimize the SHP sizing design. In order to validate the TRNSYS simulation program an experimental test was achived. The results shows that, the profile of the experimental and the TRNSYS simulation of the energy supplied from the SHP system vs local time represent a great similitude. Therefore we conclude that TRNSYS simulation program could reproduce with an acceptable accuracy the real behavior of the SHP. Then the sizing and the optimization of the SHP (the solar collector, the storage tank and flow among the prototype and the heating floor) was achieved by considering the monthly/annual solar fraction, SF, changes. The results of simulation show that the optimal sizing of the SHP system that allows the supply of a maximum rate of the solar fraction consist on using a collector with Ac equal to 6 m2 area, a hot water storage cylinder with a capacity of V equal to 450 l and a collector mass flow rate md1 equal to 100 kg h1. Concerning the floor heating, the optimal values of mass flow rate (md2) and thickness (e) between active layer and exchange of area are 200 kg h1 and 0.06 m, respectively.

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The long-term performances of the optimized SHP show that the annual average SF is about 84%. The annual total and annual average of energy collected by the solar energy collector are respectively about 3436.77 MJ m2 and 288.65 MJ m2. We notice that without making appeal to the auxiliary heating system the monthly average internal temperature during cold months (from December to Mars) ranges between 22 and 25 °C. The long-term performances simulation of the SHP shows also that when the auxiliary heating system is activated the temperature ranges during the same period from 25 to 28 °C. This result confirms that the request of auxiliary energy is limited to the cold months of the year chiefly from December to Mars. We perceive that the auxiliary energy permit the gain of about 4 °C compared to the air temperature inside the room without using auxiliary heating system. From April to November there is no requisite of auxiliary heating system. Compared to the simulated inside air temperature variation whilst the room is not heated, we perceive that the SHP guaranteed the gain of about 6 to 10 °C respectively without and with auxiliary heating system. We found also that use of the SHP reduces obviously the relative humidity inside the tested room. Indeed the relative humidity inside the tested room ranges during cold months between 35% and 38%.

Acknowledgments The authors would like to thank the Laboratoire des Procédés Thermiques (LPT) and the Centre de Recherches et des Technologies de l’Energie (CRTEn), Tunis, Tunisia for financially supporting the project and for supplying some useful data.

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