Analysis of cooling load on commercial building in UAE climate using building integrated photovoltaic façade system

Solar Energy 199 (2020) 617–629

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Analysis of cooling load on commercial building in UAE climate using building integrated photovoltaic façade system

T

Tareq Salameha, Mamdouh El Haj Assada, Muhammad Tawalbeha, Chaouki Ghenaia, ⁎ Adel Merabetb, Hakan F. Öztopc, a

Department of Sustainable and Renewable Energy Engineering, College of Engineering, University of Sharjah, Sharjah, United Arab Emirates Division of Engineering, Saint Mary's University, Halifax, Canada c Department of Mechanical Engineering, Technology Faculty, Fırat University, Elazığ, Turkey b

A R T I C LE I N FO

A B S T R A C T

Keywords: Energy analysis HVAC system Cooling load Façade (BIPV) UAE climate

In this study the details of energy consumption and its cost were studied and analyzed for a commercial office building in United Arab Emirates (UAE) as hot, dry and humid region where the cooling load is very high. Two different cases were simulated namely (a) base case without photovoltaic (PV) with normal glass windows (b) building integrated photovoltaic (BIPV) façade system with transparent PV windows. The building size, space layout, dimensions, shape and orientation for both cases were exactly the same. The PVSYST software was used to determine the best orientation for BIPV façade system installation to minimize the cooling load and maximize the electrical energy production. The amorphous silicon thin film was used for case (b) along with the weather data for the building location in Sharjah, UAE. The cooling load inside the building and its cost were evaluated for both cases. The use of BIPV façade system case in hot, dry and humid region saved the annual electrical consumption for the air conditioning system by 27.69% while it reduced the yearly energy cost by US$ 2084. Such a study would offer data at critical climate conditions necessary for the design and future implementation of this system in the Emirate of Sharjah.

1. Introduction United Arab Emirate (UAE) is currently the world's 5th highest country in energy consumption per capita (Kazim, 2007; Salameh et al., 2020). Thus, it is necessary for the government to start taking some major steps to reduce energy consumption and to provide a more efficient environment. Residential and commercial buildings consume more than 40% of the total energy consumption globally (Sovetova et al., 2019), where a very high contribution of this energy is being consumed as electricity. In UAE, 36% of the electricity is used for cooling purposes (Demand-Side Management for Electricity and Water Use in Abu Dhabi- Final Report. EAA, RTI, 2009). Massive research and analysis were done on the properties of buildings components in order to reduce the heat losses through buildings' envelope. One of the methods to remedy this issue is employing photovoltaic (PV) glass into the building exterior. The PV glass will not only reduce the heat losses from the building but will also produce electricity for the building for other applications. Paridaa et al. (2011) and Chaar et al. (2011) provided a full description for the four major current types of PV existing photovoltaic: ⁎

crystalline, thin film, compound and nanotechnology. They also provide the power generation capability and the different existing light absorbing materials used with their environmental impacts coupled with a variety of their applications. In brief, the reason for the continuous development of PV technology is not only to improve the efficiency of the cells but also to reduce the production cost of the modules. Transparent solar photovoltaic (PV glass) modules offer very attractive building integrated photovoltaic (BIPV) solutions. These modules can be used to replace architectural elements that are commonly manufactured from glass. Crystalline and thin film solar cells technologies are used today for manufacturing PV transparent glass (Paridaa et al., 2011; El Chaar, 2011). The technology of thin film transparent amorphous glass (a-Si) is used in this study, which is the most used technology in manufacturing PV transparent glass. This is because a-Si offers a better transparency and lower cost when compared to the crystalline PV glass (c-Si) (Paridaa et al., 2011; El Chaar, 2011). Keeping in mind that, the efficiency of an amorphous silicon thin film PV glass typically ranges between 6% and 10% (Fortes et al., 2014). The higher the efficiency of the module the more expensive the model becomes. Hence, from an economical point of view, polycrystalline solar

Corresponding author. E-mail address: [email protected] (H.F. Öztop).

https://doi.org/10.1016/j.solener.2020.02.062 Received 1 March 2018; Received in revised form 13 January 2020; Accepted 16 February 2020 0038-092X/ © 2020 International Solar Energy Society. Published by Elsevier Ltd. All rights reserved.

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Nomenclature A a Cp di E G I k L m Ncs q Qc R T U V W

CFM CLF CLTD DB GBS HDD LHG MCWB SC SHG SHGC STC VLT WB

Area of the elements [m2] Diode quality factor Specific heat (J/kg.K) Intrinsic layer thickness [m] Energy [eV] Irradiance [W/m2] Current [A] Bolzman’s constant [J/K] Diffusion length [m] Mass low rate [kg/sec] Number of cell in series Charge of electrons [Coulomb] Cooling Load [J] Resistance[Ohm] Temperature [°C] Thermal transmittance [W/m2.K] Voltage [V] Electrical energy consumption [J]

Subscript bi c eff i mpp n o oc p ph ref rec s sc sh

Greek letters μ ρ σ ω

Temperature coefficient [%/°C] Density [kg/m3] Temperature coefficient [%/°C] Humidity ratio

Abbreviations ACH BIPV CDD

Air Change per Minute Cooling Load Factor Cooling Load Temperature Difference Dry Bulb Green Building Studio Heating Degree Days Latent Heat Gain Mean Coincidental Wet Bulb Shading Coefficient Sensible Heat Gain Solar Het Gain Coefficient Standard Test Condition Visible Light Transmission Wet Bulb

Air Change per Hour Building Integrated Photovoltaic Cooling Degree Days

Built in voltage (intrinsic layer) Cell Effective Input Maximum power point n type material Output Open circuit p type material Photo Reference Recombination Series Short circuit Shunt

and Garg, 2011). Previous studies on double skin facade systems (DSFS) in buildings (Shameri et al., 2011), found that DSFS has a significant impact on several aspects of the design phase of a building, mainly, the building safety, the fire propagation maintenance and glazing thermal break. The results showed that the amount of energy saved was mainly dependent on the climate and the design chosen (Shameri et al., 2011). Thus, the design of the DSFS involves decisions on geometric parameters, glass selection, ventilation strategy, shading, daylighting, aesthetics, wind loads, and maintenance and cleaning cost expectations (Shameri et al., 2011). Hamza (Hamza, 2008) also conducted a comparative analysis of cooling loads on a single skin base case and compared it to three possible changes to the physical properties of the external layer of the double skin façade. A dynamic thermal performance software APACHE-Sim was used (integrated environmental solutions IESVE, version 5.1) in the study of (Hamza, 2008). Simulation results indicated that a reflective double skin façade could achieve better energy savings than a single skin with reflective glazing as shown in the study of (Shameri et al., 2011). Furthermore, Fung and Yang (2008) proposed a one-dimensional transient heat transfer model to evaluate the annual total heat gain of semi-transparent photovoltaic modules for building-integrated applications. In their study, the Semi-transparent Photovoltaic Module Heat Gain model was used. The transmitted, absorbed and reflected energies in each element of the BIPV, such as solar cells and glass layers, were considered in detail in the model. It was found that the area of solar cell in the PV module had a significant effect on the total solar heat gain. On the other hand, the solar cell energy efficiency and the PV module’s thickness had inconsiderable influence on the total heat gain. The energy consumption in buildings is influenced by external and

panels could be a more feasible choice (Razykov et al., 2011). One of the best advantages of a-Si solar modules compared to modules of other materials is withstanding high temperatures and shading effects without a significant impact on their performance (El Chaar, 2011). Dubey et al. (2012) compared the performance of a-Si rooftop panel to that of a crystalline panel in summer. The temperature dependence coefficient for the a-Si solar cell was 0.2%/°C compared 0.5%/°C for crystalline module. Hence, less drop of efficiency for a-Si when the module temperature increases above the nominal operating cell temperature. Several studies showed that energy cost for office buildings can be reduced by up to 33.5% when transparent solar panels (PV glass) are utilized (Akinyele et al., 2016; Skoplaki and Palyvos, 2009). Ng and Mithraratne (2014) studied the life cycle performance of six commercially-available semi-transparent BIPV windows in commercial buildings in Singapore compared with conventional double-glazed windows in terms of environmental and economic performance. The main result indicated that the energy payback time for the PV glass was less than two years. The study also concluded the energy return on the investment which could be as high as 35 times. In another study done by Chae et al. (2014), a procedure for evaluating the energy performance of buildings incorporated with BIPV was suggested. Three types of semitransparent solar cells were fabricated and tested (Young Tae Chae, 2014), namely, flat solar cell with a 120-nm-thick intrinsic a-Si:H absorber, a flat solar cell with a 180-nm-thick a-Si:H absorber, and a textured solar cell with a 180-nm a-Si:H absorber. The main function for the glass is to let light in and to provide thermal, wind and rain protection. Glass is mainly used as windows, curtain walls and skylights (Façade system). Silica (silicon dioxide) covers 75% of the total composition of glass which makes it the main component of the glass (Singh 618

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lifecycle (Wu et al., 2017). Salameh et al. (Ghenai et al., 2018) performed simulation and optimization based on technico-economic analysis for off grid hybrid solar PV/Fuel Cell power system, the power system was designed to meet the desired electric load of a residential community located in a desert region. Other related studies can be found in Bayrak et al. (2017) and Bayrak et al. (2019). The cooling load consumes more than 50% and 36% of total electrical consumption in building and UAE respectively. The authors believe that the overall energy performance for BIPV façade system with transparent PV window is still require a substantial amount of research for such aforementioned climate regions. In this type of climate that occurs over the most months of the year, the air conditioning is running continuously for 24 h per day. In this study, the optimum energy saving of cooling load is evaluated using three different software’s, namely, Revit, GBS and PVsyst for office building consists of three storeys at the University City of Sharjah. Both Revit and GBS software’s from Autodesk were used to perform energy analysis and electrical energy consumption for HVAC system. Two different cases were simulated namely: (a) base case without photovoltaic (PV) with normal glass windows and, (b) building integrated photovoltaic (BIPV) façade system with transparent PV windows. The PVsyst software was used to determine the best orientation for façade solar PV installation in order to minimize the cooling load and maximize the electrical energy production.

internal factors such as the ambient weather conditions, the building structure and characteristics, the lighting and heating ventilation and the air conditioning (HVAC) systems, the occupancy and their behavior and activity. This, in turn, makes the prediction of the building energy consumption very difficult. The number of completed buildings whether commercial or residential is increasing with time and it will keep increasing since it's directly related to the growing population. Zhao and Magoules (2012) reviewed the developed models dealing with the energy analysis in buildings. These models included elaborated and simplified engineering methods, statistical methods and artificial intelligence methods. It is worth mentioning that, at the national level, energy use in buildings typically accounts for 20–40% of individual country total energy use, with the world average being around 30% (Vorsatz, 2012). Energy is used in buildings to provide a variety of services, including thermal comfort, refrigeration, illumination, communication and entertainment, sanitation, and nutrition, as well as food preparation. Afshari et al. (Salameh et al., 2020) presented the main energy applications in a typical building in UAE. Crawley et al. (2008) compared the features and capabilities of twenty major building energy simulation programs. The comparison was based on information provided by the program developers in the following categories: general modeling features, zone loads, building envelope and daylighting and solar, infiltration, ventilation and multizone airflow, renewable energy systems, electrical systems and equipment, HVAC systems and equipment, environmental emissions, economic evaluation, climate data availability, results reporting, validation, and user interface, links to other programs, and availability. Ghenai et al. (2017) used HOMER software to achieve sustainable, economically viable and environmentally friendly hybrid PV power system for residential application in UAE climate. Nariman et al. (Mostafavia et al., 2013) used three building analysis software programs, DOE-2 eQUEST, IESVE Revit Plug-in and Autodesk Green Building Studio (GBS) to predicte energy savings of a scheduled envelope retrofit on a university dormitory. Most of the energy in a typical office building in Arab countries is used mainly for cooling, lighting, computing, heating, and ventilation (B. Zeitoon (Primary Editor and Reviewer), Energy Efficiency Handbook: Environmental Housekeeping Handbook for Office Buildings in the Arab Countries, Arab Forum for Environment and Development (AFED), 2012). Since office buildings are responsible for one fifth of energy use in the commercial sector, it becomes important to follow certain systems or strategies for reducing the power draw of typical office equipment (Zhang et al., 2016). Economic benefits of BIPV facilities and equipment have been analyzed in terms of the net present values (NPV) and payback period of the BIPV façade of a shopping mall in Taiwan over its

2. Model and weather data 2.1. Building model description The model building that has been chosen for this study is a threestoreys building as shown in Fig. 1. The building type is a simple office building with a total (gross) floor area of 1900 m2. The total exterior wall area of the building is 1336 m2, with a wood frame wall, wood shingle with U-Value: 0.46 (W/m2 K) covering a 610 m2 area and a metal frame wall with a U-Value: 0.88 covering an area of 726 m2. While the exterior window ratio or window to wall ratio is 0.547. Before obtaining the cooling load and the electrical consumption, it is necessary to know the building in details in terms of number of floors, number of rooms in each floor, and type and area of each room. This will ease the process of calculating the cooling load, lighting consumption, as well as knowing the types of applications used in each room since every room has a specific or a standard amount of cooling, lighting, and equipment. Table 1 shows the details for each floor in the proposed model building. As mentioned earlier in this study, two alternative models were investigated. The first alternative is the base

Fig. 1. Three-storeys building model. 619

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Table 1 Description of the building rooms in terms of type, number and area. Room Type

Ground Floor

First Floor

Second Floor

Third Floor

Office (Area m2)

4 offices (18)

4 offices (18)

2 offices (16)

1 office (11)

6 offices (15)

6 offices (15)

4 offices (14)

5 offices (14) 2 offices (25)

5 offices (14) 2 offices (25)

2 offices (60)

___

___

___

1 office (35)

___

2 rooms (16)

2 rooms (16)

___

___

1 kitchen (14) 2 bathrooms (12)

1 kitchen (14) 2 bathrooms (12)

1 kitchen (12) 2 bathrooms (12)

1 kitchen (12)

290

290

213

(14) 137

642

642

432

184

Table 2 Cooling and heating annual design conditions.

1 office (10)

Manger Office (Area m2) Secretary Office (Area m2) Meeting Room (Area m2) Kitchen (Area m2) Bathroom (Area m2) Lobby (Area m2) Total (Area m2)

Annual Design Condition Threshold % Cooling DB (°C)

MCWB (°C)

Heating DB (°C)

MCWB (°C)

0.1 0.2 0.4 0.5 1 2 2.5 5

23 23 23.7 23.3 23.3 23.6 23.6 23.8

10 10.7 11.5 11.6 12.8 13.9 14.3 15.8

8.8 8.5 9.5 9.8 10.3 11.6 12.3 13.5

46.5 45.9 45.4 45.2 44.3 43.5 43.1 41.8

where air humidity is more likely to reach very high levels. Table 2 displays the annual dry and wet bulb (WB) temperatures for both cooling and heating conditions used in the analysis. It is important to mention here that GBS uses the worst case scenario in most of the cases. Hence, for the cooling conditions, GBS considers the high temperature such as 46.5 °C as the basis for the analysis. Likewise, for the heating conditions, GBS uses relatively low temperatures such as 10 °C to perform the calculations.

1 bathroom

2.2.2. Cooling and heating degree days (CDD and HDD) Cooling Degree Days (CDD) and Heating Degree Days (HDD) are the parameters used to decide if the building needs heating or cooling and to estimate the cost of the fuel for the HVAC systems. Table 3 presents the yearly average cooling and heating degree days for different outside design temperatures for the building in Sharjah. It can be seen the CDD values are always high and that is due to the hot weather conditions. Hence, for most days of the year, the average dry bulb temperature is higher than the comfort indoor temperature (20–25 °C), therefore, cooling air conditioning systems must be turned on. It can also be seen from Table 4 that the lower the design indoor temperature, the higher the value of the CDD, which means more energy and fuel consumptions. In general, in such cases, a design temperature of 21.1 °C or 23.9 °C would be considered, which are corresponding to 2829 and 2060 CDD values, respectively. On the other hand, HDD have very low values and that is due to the fact it is very rare to have the average dry bulb temperature lower than the design indoor temperature in this area of the world. Consequently, in most days of the year, the heating systems wouldn't be in use.

model where normal glass will be used for curtain walls, while in the second alternative the glass of the curtain walls will be replaced with PV glass. The building energy performance was also simulated under the conditions that are very close to the local conditions in terms of weather and climate data. The latitude and longitude for building location are 25.3° and 55.5° respectively. 2.2. Weather data base for Sharjah city 2.2.1. Dry and wet bulb temperatures Fig. 2 shows the mean dry bulb temperature for each month of the year along with the monthly average daily maximum and minimum. It also displays a 1% cooling dry bulb which is the temperature considered for computing the cooling loads. It means that only 1% of the total hours of the year, the outdoor temperature will be exceeded by the indoor temperature. In other words, 99% of the total hours of the year the outdoor temperature is actually higher than the indoor temperature, and that’s when the cooling is needed to keep the indoor temperature within the human comfort range. As mentioned earlier, this is the worst case scenario that GBS is taken in to consideration while performing the energy analysis calculations. Air humidity is an important parameter to be taken in consideration especially in the UAE

2.2.3. Radiation Radiation is a very important aspect to be considered when designing buildings. It plays a huge rule, not only in the amount of heat transferred in and out of the building, but also on the performance of the PV glass. Fig. 3 shows the direct solar, diffuse solar and daily

Fig. 2. Estimated average mean monthly temperatures in Sharjah (Revit and GBS). 620

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to the weather data for the location of the building as shown in Table 2. Cooling load is highly dependent on the climate conditions, the time of the day and the year. Accordingly, it should be analyzed for each month of the year and added to the electrical consumption in order to test the matching and mismatching between the electrical consumption of the building and the power generation of the PV system. The cooling load is basically composed of two types. The sensible cooling load and the latent cooling load. The former type is a function of many parameters such as: the construction components (the walls (exterior and interior), roof, ceiling, partitions, and floors), number of occupants and their type of activities, the amount of heat introduced to the building through the glazing of the exterior walls (curtain walls and windows), equipment used (especially those emitting heat such as ovens, microwaves, refrigerators etc., lights and finally the infiltration through the openings. The later type is related to the wet bulb temperature and humidity as well as to the moisture level. It depends basically on the occupants and their activities, infiltration through cracks and openings as well as equipment used and their types. The main purpose of calculating the thermal loads is to reach the human thermal comfort zone for the building. Heat can be transferred to the building from outside through many ways such as conduction, solar radiation through the glass, ventilation and infiltration. The heat gained through conduction was estimated using the following equation:

Table 3 Yearly average cooling and heating degree days. Cooling Degree Day (CDD) Threshold Value (°C) CDD Value

Heating Degree Day (HDD) Threshold Value (°C) HDD Value

18.3 21.1 23.9 26.7

18.3 15.6 12.8 10

3729 2829 2060 1400

10 0 0 0

Table 4 Properties of the glass used in different alternatives. Parameter

Base case with double glass

BIPV Façade case with PV transparent glass Triple low-E Actual

Standard value for Green Building in Dubai

U (W/m2.K) SHGC VLT

2.87 0.49 0.68

1.46 0.36 0.59

1.9 0.32 0.1

0.93 0.32 0.16

averages dry and wet bulb temperatures in Sharjah. It is clearly seen from the figure that the highest and the lowest values are 580–900 W/ m2 for December and May, respectively, while the value of diffuse horizontal solar radiation is around 100 W/m2. These radiation data were obtained using Rivet and GBS software.

Q = UA (CLTD)

(1)

where U is the heat or thermal transmittance of the element, A is the area of the element and CLTD is the cooling load temperature difference. The heat gained through solar radiation can be calculated using Eq. (2) as follows:

2.2.4. Wind and wind roses Wind could be used in passive design techniques to provide natural ventilation and cooling for the building and solar PV, hence, it should be studied in terms of direction and speed. Fig. 4(a) shows the annual wind rose (speed distribution). In the proposed location, most of the wind is coming from the west and the west-northwest directions. This could be useful information to be considered to disposition the windows of the building, in order to benefit from this wind in ventilation and cooling. On the other hand, Fig. 4(b) shows the annual wind rose (frequency distribution), i.e., the frequency of each speed in terms of number of hours per year in all the directions around the building location obtained using Rivet and GBS software from Autodesk.

Q = A × SHGC × SC × CLF

(2)

where A is the area of the glazing element, SHGC is solar heat gain coefficient, SC is the shading coefficient and CLF is cooling load factor. It worth mentioning that the calculation of heat gains through both conduction and solar radiation varied from case (a) to case (b). This variation is based on the values shown in Table 4. Both sensible and latent ventilation cooling loads were calculated after knowing the air change per minute (CFM) determined from American Society of Heating, Refrigerating and Air conditioning (ASHRAE) standards. Once the CFM is obtained, the mass flow rate can be calculated using:

2.3. Cooling load analysis

ṁ = CFM × ρair

The cooling load is always calculated based on the worst case scenario, i.e., the highest outdoor design temperature expected according

(3.a)

Another way to calculate the mass flow rate is by knowing the air

Fig. 3. Estimated average mean values for temperature and solar irradiance in Sharjah (Revit and GBS). 621

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Fig. 4. Estimated (a) annual wind speed (b) annual wind frequency (Speed Distribution) in Sharjah (Revit and GBS).

change per hour rate (ACH) for the room type, and the volume of the room as follows:

indoor design dry bulb temperatures, respectively. The latent ventilation load can be obtained using Eq. (5):

ṁ = V × ACH × ρair

Q = 4840 × CFM (ωo − ωi )

(3.b)

Once the mass flow rate is known, the sensible ventilation load is calculated using the following equation:

̇ p (To − To) Q = mC

(5)

where ωo and ωi are the outdoor and indoor absolute humidity ratios, respectively. Eq. (5) takes into consideration the humidity level within the living environment, especially in high humid locations such as Sharjah. Sensible and latent heat gain due to infiltration are calculated using

(4)

where Cp is the specific heat of the air, To and Ti are the outdoor and 622

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Fig. 5. (a) The methodology used for calculation of the thermal and electrical load for any location (b) Energy analysis model based on building element in Revit and Green Building Studio from AUTODESK. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Qlatent = N × LHG

equations similar to the equations used previously to calculate ventilation. However, the mass flow rate in the infiltration case is calculated after finding the velocity of air from temperature difference between the inside and outside. Internal thermal loads caused by people, lights and equipment can create more than half of the heat gain of the building making them important parameters to be studied and calculated in detail in order to be able to reduce them. The heat gain due to the occupants is of course dependent on the number of people present as well as their type of activity. The sensible heat, unlike the latent heat, is usually stored in thermal masses and not converted immediately into cooling load. Therefore, the Sensible Heat Gain (SHG) should be multiplied by the CLF in order to count this time lag as follows:

Qsensible = N × SHG × CLF

(7)

where N is the number of people, LHG is the latent heat gain per person (depends on activity). Noting that CLF depends on the number of hours of occupancy. The heat generated from the lights is usually function of many parameters such as the power rating of the lights, the type of fixture, the ventilation air flow rate, the HVAC system and the number of hours after the lights are turned on. Knowing the power of the lights used and the type of fixture as well as the number of hours of turned on lights, will enable us to specify some important parameters such as CLF, factor for fluorescent fixtures (FBF) as well as the ratio of wattage in use at design condition to the installation condition (FUT). These parameters will help in estimating an accurate heat gain values due to the used lights as given in Eq. (8).

(6)

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Fig. 6. Equivalent circuit or PV cell.

Fig. 7. The transposition factor for different orientations.

Qlight = FUT × Fb × CLFlight

makers, etc. are the main pieces of equipment running in offices and the amount of heat generated from such equipment is not that significant when it is added to the space. Tables providing the heat gain per hour of each type of equipment is usually provided online and can be found in ASHRAE hand book as well (American Society, 2009).

(8)

where Fb is ballast factor which equal 1.2 for fluorescent lamb, and CLF is function of FBF, air circulation rate and time. Since the proposed building is an office building model, so the analysis will exclude any machines or motors running within the building in the heat generation calculation. Computers, printers, coffee 624

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Fig. 8. Orientation of the curtain walls and the sun path.

be clearly seen from Table 4 that the PV glass perfectly complies with these regulations, since it has a U and SHGC values less than the maximum allowable values by Dubai’s green building regulations and VLT value greater than the minimum value (Green Building Regulations & Specifications, 2015).

2.4. Modeling and simulation The summery of scientific methodology used to study the performance of BIPV for any location is shown in Fig. 5. There are many parameters considered in this study. The effect of these parameters on the performance of BIPV is classified based on the simulation of thermal and electrical load. These parameters were optimized based on the location and weather conditions. Three types of software were used as shown in Fig. 5(a), two of these software (i.e. Revit and green building studio) used for calculating the cooling or thermal load, whereas PVSYST software used for calculating the power production by BIPV system in order to meet the electrical load. The building model was created in Revit, with all the details regarding the sections, rooms and objects used. The default settings were identified by Revit based on the building type and location. The energy consumption analysis for the building to find the cooling loads was then simulated using the building elements energy analysis tools using Revit and GBS software as shown in the Fig. 5(b). The same building, i.e. the three storeys office building model described earlier was used with two alternative scenarios. First scenario is the base case, where a double glazing glass is used for the curtain walls, whereas in the second scenario a PV glass is used. However, it was not possible to customize a new type of a glass using Revit to simulate the PV glass, thus, another built-in type of a glass which has close similar properties to the PV glass was used. The chosen glass is the triple Low-E glass. Table 4 shows the properties of the glass used in both scenarios. It can be clearly seen that the PV glass has significantly better thermal properties, i.e. lower U-value, SHGC and visible light transmission (VLT), than the chosen built-in glass used in the second scenario. Hence, it is expected to have a significantly better performance and higher efficiency than triple Low-E glass, when using PV glass for the curtain walls, see Eqs. (1) and (2). Table 4 shows the Green Building Regulations and Specifications in Dubai for curtain walls glass in case of 40% to 60% window to wall ratio. Since the building model in the case under study has a window to wall ratio of 54.7%, thus these specifications are applicable to it. It can

2.4.1. PV power generation model The PVSYST software was used to model the power generation from BIPV system. The I/V characteristic for PV module was computed by PVSYST software based on solving the five unknown parameters (Rs, Rsh, Iph, Ioref and a) in Eq. (9) as shown in Fig. 6, these parameters are represented by the electrical and thermal characteristic provided by manufactures and measured data such as Isc,Voc, Impp, Vmpp and σoc.

I = Iph − Irec − ID − (V + I × Rs )/ Rsh

(9)

where the photocurrent Iph proportional to the irradiance G with correction term for cell temperature Tc as shown in Eq. (10).

Iph = (G / Gref ) × Iphref + μsc × (Tc − Tref )

(10)

where the reference irradiance Gref is 1000 (W/m2), the reference cell's temperature Tref is 298 K and the temperature coefficient of the photocurrent (or short-circuit current) is μsc. The recombination current for p-n junction in Eq. (9) was calculated based on Eq. (11).

Irec = Iph × di 2/ μτeff × [Vbi − (V + I × Rs )]

(11)

where di is thickness of the intrinsic layer in order of 0.3 μm, Vbi is intrinsic voltage (built-in voltage) for an amorphous junction (0.9 V) and μτeff is diffusion length of the charge carriers p and n which represent by the following equation:

μτeff = 2 × μn τn × μp τp/(μn τn + μp τp)

(12)

PVsyst software used the value 1.4 V for di / μτeff for all amorphous modules, this value gives excellent results for the mean bias error (MBS) of open circuit voltage (Voc) and the model precision root mean square error (RMSE) of maximum power (Pmax) response for SHR-17 triple2

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Fig. 9. Monthly cooling load for the building location (a) base Case (b) BIPV case. Table 5 Monthly and Annual cooling load components for case (a) (values in GJ). Period

Lights

Equipment

Occupants

Window solar

Window conduction

Roof conduction

Wall conduction

Others

Total

April August November December Annual

18.6 19.7 18.2 17.8 222

27.8 29.4 27.2 26.7 331.4

6.3 6.8 6.1 6.1 75.3

83.9 86 77.5 56 966.8

28.5 67.5 17 −4.8 377.9

2.8 6.2 1.5 −0.7 35

7.8 15.3 5.5 0.8 100.7

7.5 18.7 8.8 3.2 126.2

183.2 249.6 161.8 105.1 2235.3

Table 6 Monthly and Annual cooling load components for case (b) (values in GJ). Period

Lights

Equipment

Occupants

Window solar

Window conduction

Roof conduction

Wall conduction

Others

Total

April August November December Annual

19.9 21.3 19.4 19.4 238.8

22.8 23.9 22.5 22.5 273.7

6.2 6.7 6 6.1 74.6

71.4 73 65.9 48.5 823.6

23.5 53.8 14.3 −3.9 305.9

2.8 6.2 1.5 −0.7 34.9

7.9 15.3 5.5 0.6 100.5

6.1 15.4 7.5 2.8 103.3

160.6 215.6 142.6 95.3 1955.3

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Table 7 Monthly and annual reduction in cooling load due to the use of the façade system with transparent PV window. Period

Reduction in Cooling Load (%)

April August November December Annual

12.34 13.62 11.87 9.33 12.53

3. Results and discussion In this section, the orientation of the building for solar BIPV façade system electrical energy production, the cooling load as well as the electrical consumption by the HVAC system (Chillers, Pumps, and Fans) inside the building for the two alternative cases will be discussed. All the results were obtained by Revit and GBS. The orientation of the building is one of the main aspects to be specified to evaluate the cooling load. It is more convenient to direct the curtain walls which are composed of the PV glass to the south in order to get the maximum radiation possible, since this building office is located in Sharjah city in the northern hemisphere. Results from PVSYST software. Showed that for a vertical surface (façade), the highest transposition factor (the ratio of the incident irradiation on the plane to the horizontal irradiation.) was obtained when the surface is directed towards eastern south (45° from south) with a value of 0.62 as can be seen from Fig. 7(a). However, due to the high temperatures in UAE which can have a huge impact on the power output and lifetime of the PV panels, thus, using the wind as a passive cooling source for the BIPV façade system especially in the summer could have an effective impact on their performance especially in the long run. As shown earlier in Fig. 4(a) the wind coming from the west has the highest speed across the year. Consequently, it is very convenient to direct the BIPV façade system towards the west. However, the results obtained using PVSYST software shown in Fig. 7(c) revealed that when the BIPV façade system was directed towards the west the transposition factor will be minimum with a value of 0.25. The best orientation of the BIPV façade system was obtained when using the wind for cooling is the west, hence, in order to use the wind for cooling without losing a lot of radiation, the BIPV façade system was directed toward the south as seen in Fig. 8. It can be also seen from Fig. 7(b) that the transposition factor due south is around 0.57, which is only 5% less than the optimum eastern south orientation. With, it is more convenient to direct the building towards south in order to get more radiation a significant wind cooling. Many studies showed that the output power of PV modules, at optimum conditions, i.e. optimum tilting angle and optimum maximum radiation orientation, were approximately linearly related to the incident irradiance. However, the weather conditions in the UAE are significantly different than the Standard Test Condition (STC). For instance, high temperatures can be serious concern for PV modules. Radhi (2010) analyzed the performance of single crystalline PV façade system for 3 storeys office building in Al Ain UAE with four orientations using Energy-10. Despite the fact that southern PV façade system received the highest amount of monthly radiation; the western PV façade system delivered the highest PV output power considering the PV modules are under the same operating conditions. In order to explain this, it is important to put the module temperature (which is a function of the weather local conditions) into consideration when estimating the power output of the PV system. Since PVSYST software does not take much into account the effect of the wind and its direction. BIPV façade system

junction. The diode current for Eq. (9) was calculated as follow:

ID = Io exp[q × (V + I × Rs )/(Ncs × a × k × Tc )] − 1

(13)

where the inverse saturation current Io is depending on the temperature as shown in Eq. (14).

Io = Ioref (Tc / Tcref )3 × [exp(EGap/ a × k )(1/ Tcref − 1/ Tc )]

(14)

The energy gap for amorphous silicon (EGap) is 1.7 eV. After considering the values of all currents Iph, Irec, ID and Ish in Eq. (8), the current I pass through the load can be represented as seen in Eq. (15).

I = Iph − Iph × di 2/ Leff × (Vbi − (V + I × Rs )) − (Io exp[q × (V + I × Rs )/(Ncs × a × k × Tc )] − 1) − (V + I × Rs )/ Rsh

(15)

Two cases for each equipment (Chillers, Pumps, and Fans) were used in this study, the base case and the PV glass case for HVAC system. In the base case, the normal, relatively inefficient equipment was used while for the PV glass case, the most efficient equipment was used to decrease the electrical consumption of the building. The efficient equipment can be used for both cases, but this efficient equipment is recommended for BIPV system which has small efficiency (12 to 18%) in order to help the operation of the BIVP façade system, increase the energy saving even the initial cost is very high compared with traditional appliances. This will make the comparison reasonable. Air-conditioning counts for more than 60% of the primary energy consumption in commercial buildings in UAE. This includes the energy used for chillers and to power the fans and pumps. The monthly electrical consumption for the chiller was calculated by dividing the monthly cooling load computed using GBS by the coefficient of performance (COP) of the chiller using Eq. (16):

COP =

Qc W

(16)

where W is the electrical consumption, and Qc is the cooling load. The annual electrical consumptions for both pumps and fans were computed using GBS by assuming constant daily electrical consumption. Hence, the monthly electrical consumption was calculated based on the daily consumption. The reduction percentage in cooling load (HVAC System) is calculated for these pieces of equipment using Eq. (17):

Reduction =

BaseCaseResult − PVglassCaseResults BaseCaseResults

(17)

Table 8 Monthly and annual electrical energy consumption and production for case (a) and case (b) in (MWh). Period

Chiller Electrical Consumption (MWh) Case a b

Pump Electrical Consumption (MWh) Case a b

Fan Electrical Consumption (MWh) Case a b

HVAC System Electrical Consumption (MWh) Case a b

BIPV Façade system Energy production (MWh) Case b

Reduction in HVAC System Electrical Consumption (%)

April August November December Annual

8.53 11.63 7.54 4.92 104.4

4.2 4.34 4.2 4.34 51.1

1.41 1.46 1.41 1.46 17.1

14.14 17.43 13.15 10.72 172.6

1.69 1.73 1.2 1.03 17.8

29.27 27.25 26.54 27.52 27.69

7.48 10.05 6.65 4.44 91.3

3.16 3.27 3.16 3.27 38.5

1.05 1.09 1.05 1.09 12.8

627

11.69 14.41 10.86 8.8 142.6

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Fig. 10. Monthly electrical energy production and consumption for BIPV façade and HVAC systems, respectively.

cooling load, however, it is much less than the external loads. This means that in local climate condition for Sharjah city, buildings engineers should pay more attention to the selection of the materials of the external walls as well as the building orientation in order to minimize the heat gain through them. Table 7 demonstrates the monthly reduction in the cooling load due to the use of the BIPV façade system case. It should be noticed that the thermal performance of the actual BIPV façade system should be better since it has better thermal properties for building construction than the ones used in the simulation see Table 4. The monthly reduction in cooling load varies between a maximum percentage of 13.62% in the month of August and a minimum value of percentage of 9.33% in the month of December. The yearly reduction in the cooling load is around 12.53%. It is important to mention that the cooling load values shown in Table 7 are not HVAC energy loads. This means that these values are used for sizing and design the HVAC system. In other words, these values represent the amount of heat that should be removed every month in order to reach thermal comfort. The months of August and December have the highest and lowest HVAC system electrical consumption, respectively, for both cases. On the other hand, the months of April and November have the highest and lowest reduction in electrical consumption for HVAC system, respectively. This is mainly due to the power production from the BIPV façade system as shown in Table 8. It is clearly seen that case (b) is significantly better than the case (a) since it reduces the HVAC electricity consumption. The monthly reduction in the electrical consumption of case (b) relative to case (a) is varied between 29.27% and 26.54% for months of April and November, respectively. The annual reduction in the cooling load was around 27.69%. The energy production and consumption change with the weather conditions. For instance, the highest and lowest power production were in May (~1.89 MWh) and December ((~1.03 MWh), respectively, while the highest and lowest cooling loads were in August (~14.41 MWh) and December (~8.8 MWh), respectively, evident from Fig. 10. Table 9 shows the cost of electricity consumption by HVAC system and the saving due to the integration of PV façade system with transparent PV window to the building. A total of US $ 2084 will be saved from HVAC electrical consumption. It is worth mentioning that the highest cost saving is in the month of August and the lowest cost saving is in the month of December. These savings depend directly on the amount of electrical consumption for each month. The cost was calculated using Sharjah Electricity and Water Authority electricity tariff for commercial buildings (Tariff, 2014). The tariff value depends on the consumption in kWh per month, it was found to be AED 0.16 /kWh ≈

Table 9 Monthly and annual electricity consumption cost for HVAC system in ($). Period

HVAC System Electrical consumption Cost ($) Case Base BIPV Façade

HVAC System Electrical Cost Saving ($)

April August November December Annual

617 760 573 467 7525

181 207 152 129 2084

436 553 421 339 5441

is directed towards the south in order to enhance the performance. Especially that the radiation will be weaker if the BIPV façade system is directed towards the west. This is due to the fact that it is vertically installed. The cooling load calculations are very much dependent upon the orientation as well as the weather data of the location. All the weather data for the project’s location in Sharjah are displayed and explained in details in previous section. These weather data as explained are obtained from GBS. Fig. 9 shows the monthly cooling load for each of the alternatives as well as its components. It is evident that the highest percentage of the cooling load for both cases is resulting from the window solar. This is due to the heat introduced to the building through the radiation heat transfer via the fenestration such as the curtain walls and the windows. This is logical since more than half of the external wall area is actually glass. Tables 5 and 6, show the contribution of each component for the highest and lowest month and annual cooling load for the two cases. It is clearly seen that for both cases there are negative values in both window conduction and roof conduction for the month of December. The contribution of each component of the cooling load indicates how much heat is gained through this component. Thus, negative values mean that these components are not resulting any heat gain, instead it is losing heat to the surroundings. This usually reduces the cooling load of the respective month, which explains why the least cooling load values were in December. In contrast, the highest cooling load values were in the hottest month of the year which is August. It can also be observed that most of the heat gain is coming from the external loads such as radiation and conduction through fenestration and walls as well as infiltration. Internal loads such as the occupants, lights and equipment, on the other hand, are responsible for a significant part of the 628

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US $ 0.0436 / kWh. This value was used for both cases.

Fung, T.Y.Y., Yang, H., 2008. Study on thermal performance of semi-transparent buildingintegrated photovoltaic glazings. Energy Build. 40, 341–350. Ghenai, C., Salameh, T., Merabet, A., Hamid, A.K., 2017. Modeling and optimization of hybrid solar-diesel-battery power system. In: 7th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO)pp. 1–5. Ghenai, C., Salameh, T., Merabet, A., 2018. Technico-economic analysis of off grid solar PV/Fuel cell energy system for residential community in desert region. Int. J. Hydrogen Energy 1–11. https://doi.org/10.1016/j.ijhydene.2018.05.110. Green Building Regulations & Specifications. Retrieved from World Wide Web on March 20th, 2015, https://www.dewa.gov.ae/en. Hamza, N., 2008. Double versus single skin facades in hot arid areas. Energy Build. 40, 240–248. Kazim, A.M., 2007. Assessments of primary energy consumption and its environmental consequences in the United Arab Emirates. Renew. Sustain. Energy Rev. 11, 426–446. Mostafavia, N., Farzinmoghadamb, M., Hoquea, S., 2013. Envelope retrofit analysis using eQUEST, IESVE Revit Plug-in and Green Building Studio: a university dormitory case study. Int. J. Sustain. Energ. https://doi.org/10.1080/14786451.2013.848207. Ng, P.K., Mithraratne, N., 2014. Lifetime performance of semi-transparent building-integrated photovoltaic (BIPV) glazing systems in the tropic. Renew. Sustain. Energy Rev. 31, 736–745. Paridaa, B., Iniyanb, S., Goicc, R., 2011. A review of solar photovoltaic technologies. Renew. Sustain. Energy Rev. 15, 1625–1636. Radhi, H., 2010. Energy analysis of facade-integrated photovoltaic systems applied to UAE commercial buildings. Sol. Energy 84, 2009–2021. Razykov, T.M., Ferekides, C.S., Morel, D., Stefanakos, E., Ullal, H.S., Upadhyaya, H.M., 2011. Solar photovoltaic electricity: Current status and future prospects. Sol. Energy 85 (8), 1580–1608. Salameh, T., Ghenai, C., Merabet, A., Alkasrawi, M., 2020. Techno-economical optimization of an integrated stand-alone hybrid solar PV tracking and diesel generator power system in Khorfakkan. United Arab Emirates, Energy 190, 116475. Singh, M.C., Garg, S.N., 2011. Suitable Glazing Selection for Glass-Curtain Walls in Tropical Climates of India. ISRN Renew. Energy 2011, 1–11. https://doi.org/10. 5402/2011/484893. Shameri, M.A., Alghoulb, M.A., Sopianb, K., Fauzi, M., Zaina, M., Elayeb, O., 2011. Perspectives of double skin facade systems in buildings and energy saving. Renew. Sustain. Energy Rev. 15, 1468–1475. Skoplaki, E., Palyvos, J.A., 2009. On the temperature dependence of photovoltaic module electrical performance: a review of efficiency/power correlations. Sol. Energy 83, 614–624. Sovetova, M., Memon, S.A., Kim, J., 2019. Thermal performance and energy efficiency of building integrated with PCMs in hot desert climate region. Sol. Energy 189, 357–371. Slab Tariff. Retrieved from World Wide Web on November 20th, 2014, https://www. dewa.gov.ae/tariff/tariffdetails.aspx. D.U. Vorsatz, Chap. 10 Energy End use: Buildings. In Global Energy Assessment Toward a Sustainable Future, (2012) ISBN: 9781107005198. Y.-W. Wu, M.-H. D. Wen, L.-M. Young, I-T. Hsu., LCA Based Economic Benefit Analysis for Building Integrated Photovoltaic (BIPV) Façades: A Case Study in Taiwan, Int. J. Green Energy 15 (2017) 8 – 12. Chae, Young Tae, Kim, Jeehwan, Park, Hongsik, Shin, Byungha, 2014. Building energy performance evaluation of building integrated photovoltaic (BIPV) window with semi-transparent solar cells. Appl. Energy 129, 217–227. Zhao, H.-X.., Magoules, F., 2012. Magoules, A review on the prediction of building energy consumption. Renew. Sustain. Energy Rev. 15, 3586–3592. B. Zeitoon (Primary Editor and Reviewer), Energy Efficiency Handbook: Environmental Housekeeping Handbook for Office Buildings in the Arab Countries, Arab Forum for Environment and Development (AFED) (2012) ISBN: 9789953437422. Zhang, T., Siebers, P.-O., Aickelin, U., 2016. Modelling Office Energy Consumption: An Agent Based Approach. SSRN Electronic Journal. https://doi.org/10.2139/ssrn. 2829316.

4. Conclusion For the first time, a mathematical simulation of office building in UAE was conducted to determine the energy savings. The cooling load capacity was studied for commercial office building in Sharjah city for two cases (a) base case without PV and with normal glass window (b) BIPV façade system with transparent PV window. The results showed that using BIPV façade system saved the energy consumption for HVAC system. Selecting the efficient HVAC components will help the BIPV façade system to save more energy. The maximum and minimum reduction in electrical consumption needed for HVAC system were obtained for April and November months, respectively. The annual electrical cost saving for HVAC system was US$ 2084 based on the thermal properties used for simulating the case (b). Used BIPV façade system for office building in hot, dry and humid region such as UAE increased the energy saving by 27.7% with considering efficient appliances used with BIPV façade system with transparent PV window. Such a study would offer data at critical climate conditions necessary for the design and future implementation of this system in the Emirate of Sharjah. Declaration of Competing Interest We confirm that there is no any conflict associated with this manuscript. References Akinyele, D.O., Rayudu, R.K., Tan, R.H.G., 2016. comparative study of photovoltaic technologies based on performance, cost and space requirement: strategy for selection and application. Int. J. Green Energy 13, 1352–1368. American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Handbook. (2009). Bayrak, F., Ertürk, G., Oztop, H.F., 2017. Effects of partial shading on energy and exergy efficiencies for photovoltaic panels. J. Clean. Prod. 164, 58–69. Bayrak, F., Oztop, H.F., Selimefendigil, F., 2019. Effects of different fin parameters on temperature and efficiency for cooling of photovoltaic panels under natural convection. Sol. Energy 188, 484–494. Crawley, D.B., Hand, J.W., Kummert, M., Griffith, B.T., 2008. Contrasting the capabilities of building energy performance simulation programs. Build. Environ. 43, 661–673. Demand-Side Management for Electricity and Water Use in Abu Dhabi- Final Report. EAA, RTI, 2009. Dubey, S., Sarvaiya, J.N., Seshadri, B., 2012. Temperature dependent photovoltaic (PV) efficiency and its effect on PV production in the world a review. Energy Procedia 33, 311–321. L. El Chaar, L.A. lamonta, N. El Zein, Review of photovoltaic technologies, Renew. Sustain. Energy Rev. 15 (2011) 2165 – 2175. Fortes, M., Comesaña, E., Rodriguez, J.A., Otero, P., Garcia-Loureiro, A.J., 2014. Impact of series and shunt resistances in amorphous silicon thin film solar cells. Sol. Energy 100, 114–123.

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