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A software-based approach in designing a rooftop bifacial PV system for the North Hall of Residence, IUT

A software-based approach in designing a rooftop bifacial PV system for the North Hall of... ENERGY DEMAND 444,733.5 kWh CONSUMPTION Orientation-1 PV SYSTEM 352,224.88 kWh ENERGY Orientation-2 TAKEN 350,090.02 kWh FROM GRID Orientation-3 INVERTER 357,974.6 kWh GRID PV ENERGY PRODUCED Orientation-1 92,508.62 kWh Orientation-3 86,758.9 kWh Orientation-2 94,643.48 kWh Keywords: bifacial solar PV panel; PVSOL; PVsyst; SAM; annual energy yield; bifacial gain significant amount of grid consumption and saves a lot of Introduction electricity bills in the process. In this era of rapid technological advancement, the ever- Bangladesh is still heavily dependent on the traditional increasing demand for energy and diminishing fossil fuels fossil fuels for electricity generation and transmission have made it necessary to look for eco-friendly, sustainable but, due to limited reserves of fossil fuels, the country is renewable-energy schemes, keeping in mind the global en- advancing towards a power crisis [13] in the near future. ergy demand, climate change and already available tech- So, this country must make a shift to a renewable-energy nologies [1–3]. Extensive research and studies are going on system to tackle the impending problem. According to to find innovative methods to ensure clean energy tran- the Bangladesh Energy Situation, the power sector in these sitions and the effective harvesting and integration of re- parts has not quite reached the transition stage to renew- newables to the conventional energy mix [4–6]. According ables, with only 3.3% of the country’s electricity produc- to the Renewables 2020 [7] report by the International tion coming from renewables and also, in 2018, the total Energy Agency, net installed renewable capacity was ex- renewable-energy capacity in this country was 439 MW pected to grow by ~4% globally in the year 2020, reaching [14]. Having said this, Bangladesh has excellent potential nearly 200 GW. So, by the proper harnessing of these and scope for solar power, with the average daily solar ir - sources, the world has enormous potential to make a tran- radiance ranging from 215 W/m in the north-west to 235 sition to a sustainable, efficient and clean energy system W/m in the south-west [15]. Thus, solar energy can be ex- [8]. In this context, one of the most widely used forms of ploited using photovoltaic (PV) technology [16]. In recent renewable energy is solar energy, having a plethora of ad- times, solar PV markets have flourished a lot and, in 2020, vantages compared to other forms of energy. Solar energy global PV capacity additions were predicted to reach al- prevents the emission of carbon dioxide and other poi- most 107 GW [7]. Hence, the demand and use of PV tech- sonous gases and waste products. The utilization of solar nology have drastically increased worldwide. Solar energy energy also reduces the number of transmission lines from has enormous prospects, especially in irrigation, mini- grids. It is abundant and readily available in direct and in- grid, solar rooftop and several other fields [17]. Despite its direct forms, and is a free source of clean energy [9–12]. So, massive potential, some challenges need to be addressed, the Sun’s energy can efficiently be utilized in the peak load which mainly include lack of land area and proper tech- hours during the daytime, or it can also be stored in bat- nology, inadequate space and high installation costs [18]. teries for later use. Thus, solar energy helps us to reduce a Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 405 So, it is required to find a feasible solar energy scheme that bifacial panels have been conducted as well. Mahmud et al. will mitigate these barriers. It is also necessary to ensure conducted an analysis of bifacial PV set-ups in the high- the social acceptance of a solar energy infrastructure so ways of Bangladesh [31]. Nussbaumer et al. carried out an that the general public will also become ready for novel accuracy test on the simulation data for bifacial modules and innovative technology [19]. Such a feasible and accept- through the variation of tilt angles and share of diffuse ra- able application of PV energy can be the rooftop installa- diation [32]. Chudinzow et  al. performed simulation ana- tion of PV panels, which will help to mitigate the problem lysis of the energy yield of a bifacial PV plant, taking into of the limited land area and crowded cities of Bangladesh consideration several irradiance contributions and the im- by utilizing the empty, unused space of rooftops. pact of ground shadows [33]. Pisigan et  al. researched the Two categories of solar modules are in use, namely performance of bifacial modules in tropical urban settle- monofacial solar modules and bifacial solar modules ments [34]. Baumann et al. studied the use of vertically in- [20]. Monofacial solar modules are the conventional solar stalled bifacial PV panels with roof greening in Winterthur, modules that are commonly used. Most of the works on Switzerland [35]. solar installation and design are based on this type of In our previous work, a primary investigative analysis module. There are numerous works on monofacial-based was conducted on the rooftop of the residential hall of the PV plants and rooftop PV installations. Kazem et  al. p -re Islamic University of Technology (IUT) campus with the sented a case study on the techno-economic feasibility help of monofacial modules [36]. An energy-profile ana- of a 1-MW grid-connected PV system in Adam, Oman, by lysis was conducted with the help of PVSOL, PVsyst and doing a numerical investigation into the optimal config- SAM, with the monofacial modules placed at a tilt angle of uration of the plant, based on real-time data [21]. Shuvho 24°, and the monthly consumption coverage by PV and the et al. predicted the solar irradiation and evaluated the per - grid have been presented. Our research and investigation formance of an 80-kWp grid-connected PV power plant in showed that our proposed monofacial PV model can gen- Dhaka using fuzzy logic and demonstrated a solar irradi- erate ~81 838.5 kWh—almost 18.4% of the annual demand ation predicted model based on fuzzy logic and artificial of our selected site, which is ~444 733.5 kWh. In this work, neural networks [22]. Şenol et al. worked on an optimized bifacial modules have been utilized and a comprehensive design of a self-consumption-based large-scale solar plant analysis has been carried out. Physical implementation of in Cyprus International University and carried out simula- such a system requires a lot of careful calculations and tions using PVSOL for capacities ranging from 450 to 1250 there are several maintenance issues as well. A  detailed kWp [23]. Al-Addous et al. conducted an analysis on stand- software analysis prior to physical implementation can alone PV systems in the Jordan Valley where an analysis of help us find out these minute calculations and issues, the power production of PV modules, weather dependence and also provide a fair idea of the production capacity of and temperature-induced deteriorations has been con- our system. For this reason, we have shown rigorous soft- ducted [24]. Kumar et  al. also carried out software-based ware modelling and simulation in three different orienta- modelling of a 10-MW on-grid PV plant in India employing tions, analysed the feasibility of each and lastly presented PVsyst and PV-GIS software and observed an annual pro- a comparative analysis among the three set-ups and also duction of 15  798.192 mWh/annum [25]. Dondariya et  al. with the monofacial one. performed a simulation-based analysis of grid-connected rooftop PV panels for small households in Ujjain, India, with the help of PVSOL, PVGIS, Solargis and SISIFO, and 1 Methodology obtained an annual yield of ~1528.125 kWh/kWp [9]. 1.1 Site and meteorological information Bifacial PV panels hold noteworthy promise in harvesting energy from the Sun. Unlike monofacial modules, bifacial In order to design a solar PV system, the selection of the modules can utilize the sunlight entering the module from site and the identification of a suitable area are the first both the front and rear sides [26]. Hence, these modules and foremost concerns, as site information helps to im- can improve power density, reduce area costs and rear side prove system performance and efficiency. The proposed contributions to increase cell efficiency by up to ~35% [27]. site is the North Hall of Residence of the IUT campus, Moreover, bifacial modules also have 50% more power gain shown in Fig. 1, having ample rooftop space for a PV set-up. as compared to monofacial modules [28]. However, the bi- The hall is a south-facing building, with a combination of facial yield also depends on albedo factors and tilt-angle three blocks connected together, with each block having configurations [29]. The bifacial annual energy yield can be a mounting area of ~503 square metres. It has a height increased by 30% if the modules are placed 2 metres above of 17.126 metres and no external shading by trees or any the ground instead of close to the ground as in conven- other obstacle [37], as any obstacle can reduce the reli- tional installations [30]. There have been notable works on ability of solar modules. The 3D model of the hall building bifacial modules as well. These works mainly emphasized has been shown in Fig. 2, which is imported from PVSOL. the irradiation and other physical characteristics of bi- The whole rooftop is considered as a plain field for the facial modules and how they behave in the tropics [26] and convenience of system design without any arbitrary ob- in desert conditions. Rooftop and highway-based works on ject. The meteorological data have been collected from Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 406 | Clean Energy, 2021, Vol. 5, No. 3 Monthly Temperature Temperature ( °C ) Jan Feb Mar Apr May JunJul AugSep Oct NovDec Fig. 1: North Hall of Residence of the Islamic University of Technology Month Fig. 3: Monthly temperature data at IUT Source: Meteonorm7.2 data from PVsyst7.0. Direct Irradiance Diffuse Irradiance Fig. 2: Imported 3D model on PVSOL Table 1: Site and meteorological data Site name Islamic University of Technology, Board-Bazar, Dhaka Coordinates 23.9481° N, 90.3793° E 2 130 Annual global irradiance 1793 kWh/m Horizontal diffuse irradiance 864 kWh/m JanFeb Mar Apr MayJun Jul Aug Sep Oct Nov Dec Average temperature 24.9°C Month Wind velocity 0.8 m/s Humidity 81% Fig. 4: Monthly variation in direct and diffuse irradiation Source: Meteonorm 7.2 data from PVsyst 7.0. Source: Meteonorm7.2 data from PVsyst7.0. [40]. The monthly temperature data of the IUT is plotted several weather databases such as NREL, Meteonorm, and presented in Fig. 3 using PVSOL. Meteosyn, etc. The essential meteorological data that The module absorbs radiation in the form of global hori- are taken into account are direct and diffuse irradiance, zontal irradiance, which is made up of direct radiation that average temperature, wind velocity and humidity [38 39 , ]. travels in a straight line from the Sun to Earth and indirect The required data have been tabulated in Table 1, which diffuse radiation that is dispersed by clouds, dust in the air will be needed for the purpose of simulation. The most sig- and other objects and travels in a random direction before nificant meteorological parameters affecting the solar-cell reaching Earth. Direct radiation has a particular direction, performance are irradiance and temperature. Increasing while diffuse radiation may pass in any random direction. The irradiance increases both the open-circuit voltage and the proportion of diffuse light is higher when the radiance is low short-circuit current, thus causing variation in the max- due to cloud cover than when the radiance is high, and the imum power point (MPP). On the other hand, an increase gain relative to monofacial PV is also higher [41]. The monthly in temperature causes a significant decrease in cell voltage variation in direct and diffuse irradiation is presented in Fig. 4. Temperature ( °C ) Direct Irradiance (kWh/m ) Diffuse Irradiance (kWh/m ) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 407 orientation affects the annual yield. However, rear irradi- 1.2 Load-profile analysis ance has to be considered, which depends on the albedo The capacity of a PV module is selected based on the total of the reflecting surface [44]. Hence, the albedo was con- amount of electricity consumed as per the load profile. The sidered to be 0.65, which can be obtained through artifi- IUT has two residential halls. We have taken the same load cially added light-coloured aggregate to the roof [45]. Then profile as in our previous work, considering one (North again, vertical mounting (VM) of bifacial modules helps to Hall) of those two halls, as both halls are analogous (a avoid regular panel cleaning by alleviating soiling losses five-storey building having three blocks where each block [46]. Thus, a low soiling loss of 5% is taken into account for contains 10 rooms and 1 washroom). The load profile is the vertically mounted panel and, for an optimum-tilted provided in Table 2. The annual consumption for one hall panel, it was considered as 15%. Power loss due to mis- is ~444 733.5 kWh. match or reduced yield was considered to be 2%. A DC–AC ratio of 1.08 was chosen. Lastly, bifaciality and diode loss were taken as 0.7 and 0.5%, respectively. Using 174 mod- 1.3 System design ules rated at 340 W, an installed capacity of 59.16 kW was Monocrystalline silicon solar modules are used in the obtained. The overall parameters of the system are sum- system design because they are more effective than poly- marized in Table 3 [47]. Fig. 5 shows the I–V characteris- crystalline and amorphous ones [3942 , ]. This work, like tics of the solar panel. Inverter specifications are provided the previous work, uses modules made by LG Electronics, in Table 4 and an efficiency characteristic curve of the in- Inc. with a rated power of 340 W and a module efficiency verter is shown in Fig. 6. of 19.8%. The maximum power voltage is 34.4 V and the maximum power current is 9.89 A.  The open-circuit 1.3.1 Orientation-1 voltage is 40.8 V and the short-circuit current is 10.38 The first scheme uses a special design in which vertical A. Inverters, which serve as a current source [43], are at bifacial panels are mounted in a rectangular pattern at the heart of the system. They were selected from Huawei the edge of the roof, leaving an open area in the middle Technologies, with the model number SUN2000L-5KTL. that can be used for other purposes. All of the modules The inverter has a nominal AC power rating of 5000 kW were tilted at a 90° angle for this design. A total of 23 mod- and an efficiency rating of 98.58%. Aside from modules ules were aligned in a straight line east–west and another and inverters, PV systems need robust and dependable 23 modules were aligned in a parallel position with an mounting systems that can withstand environmental azimuth of 180°. Six modules were arranged in a north– adversities while supporting PV panels [23]. To achieve a south direction, with another six arranged in parallel. As high energy yield, all modules were installed at a height a result, each block has a total module count of 58, for a of 2 metres above the mounting surface. The mounting total of 174 modules across three blocks. The distance be- system has been tilted at various angles to meet the tween each panel was kept to a minimum and they were system-configuration requirements. To inspect the overall system, three different orienta- Table 3: System parameters tions were simulated by deploying the three software plat- Parameters Description forms mentioned before. Three bifacial PV models were designed and a comparative study was carried out. A total Module type Bifacial of 174 modules were utilized in all simulations to increase Number of panels 174 the reliability of the design and determine how each Module power 340W Model LG340N1T-v5 Module efficiency 19.8% Table 2: Monthly load profile Module maximum power 340W Module maximum power voltage 34.4 V Month Consumption (kWh) Module maximum power current 9.89 A January 24 797.52 Module open-circuit voltage 40.8 V February 30 173.52 Module short-circuit current 10.38 A March 47 799.1 Module NMOT (nominal module 42 ± 3°C April 47 799.1 operating temperature) May 23 983.9 Module bifaciality 0.7 June 47 799.1 Module mismatch loss 2% July 47 799.1 Module diode loss 0.5% August 23 881.9 Albedo for the system 0.65 September 47 799.1 Soiling loss for the system 5% for VM, October 48 100.2 15% for op- November 30 003.5 timum tilt December 24 797.5 DC–AC ratio for the system 1.08 Total 444 733.5 Installed capacity of the system 59.16 kW Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 408 | Clean Energy, 2021, Vol. 5, No. 3 05 10 15 20 25 30 35 40 Module Volts (V) Fig. 5: I–V curve of the LG bifacial solar module Source: System Advisory Model 2020. Table 4: Inverter specifications Fig. 8: South-east view of Orientation-1 Nominal AC power 5000 kW Minimum MPP voltage 90 V Maximum MPP voltage 500 V Input maximum voltage 600 V Frequency 60 Hz EURO efficiency 98.58% Maximum inverter input current 22 A  Source: PVsyst. 260 V, T°C = 45°C, CosPhi = 1.00 Fig. 9: 3D model of Orientation-2 Eff. for U = 480 V Eff. for U = 380 V Eff. for U = 260 V 1.3.2 Orientation-2 34 56 01 2 The second design had the panels facing east–west, with P in (DC) [KW] an azimuth of 90° and a tilt of 90°, while keeping the total Fig. 6: Efficiency curve of the SUN2000L-5KTL inverter number of panels the same. Five modules were arranged in a Source: PVsyst. row with a 3.5-metre gap between them to minimize row-to- row shading. There was, however, a 0.5-metre gap between each row of modules. Fig. 9 illustrates the 3D model. One of the benefits of this orientation is that panels are completely exposed to radiation all day due to the vertical set-up. As a result, this set-up is expected to have less variation in hourly yield during the day. However, due to the overcrowding of the space, some shading losses are to be expected. 1.3.3 Orientation-3 The total module number was kept constant at 174 in the third method. The bifacial modules were arranged to have an optimum tilt angle of 24°, which corresponded to the latitude of the site [48]. However, azimuth was taken into account at 180° to ensure that the panels were facing south to receive the most radiation. The distance between Fig. 7: Aerial view of Orientation-1 in which the bifacial modules are the modules was 0.1 metres and the row spacing was 3.5 mounted at the edge of the rooftop metres. Fig. 10 depicts the design and Table 5 lists all of the arranged in such a way that row-to-row shading was min- parameters for three different orientations. This design imized. Figs 7 and 8 show the aerial and south-east views was purposefully created to compare the benefits of a ver - of Orientation-1 created by PVSOL, respectively. tically mounted set-up to an optimally facing one. Efficiency [%] Module Current (Amps) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 409 After meticulous simulation, the obtained energy yields 1.4 Software details from different orientations are tabulated. With the help The three proposed prominent software packages are of the results, a detailed analysis has been performed to widely used for constructing design-based energy models evaluate the prospect of each orientation. In this context, by a lot of researchers. PVSOL premium was developed coverage of consumption and usages of PV has been dis- by Valentin Software, which is a PV simulation program played as part of the energy-profile analysis. After that, a with facilities for 3D visualization and detailed shading deviation and statistical analysis have been shown among analysis for the calculation of PV systems in combination the performances of the three software packages, followed with electrical equipment, battery systems and electric ve- by comparative analysis among the orientations proposed. hicles [49]. Using the 3D model, comprehensive and pre- In addition, a comparative study is also carried out with cise modelling of the proposed site is done to enhance the monofacial south-facing panel set-up, which was ac- the shading and yield calculation. On the other hand, complished previously [36]. Finally, an approximate finan- PVsyst, developed by PVsyst SA, Switzerland, is an energy- cial analysis has been presented in order to gain insights modelling tool that analyses how much solar energy can into the economic feasibility of the proposed software- be harvested and converted into electrical energy from based analysis. a particular site or location [50]. After choosing the loca- tion, the optimized orientation and configuration are set using the built-in algorithm that suggests the best possible 1.5 Performance parameters combination. Using this, a detailed PV system is prepared. 1.5.1 Annual PV energy The System Advisor Model (SAM), developed by NREL, is a The output energy obtained from the PV modules in kWh techno-economic software model that facilitates system- units in a year is the annual PV energy. It is given by the designing decision-making for people involved with re- formula: newables [51]. After selecting the preferred panel and inverter model, the system is configured using a versatile E = I × V × t(kWh) (1) a dc dc System and Sizing platform that offers easy configuration where E represents the annual PV energy (kWh), I repre- a dc of the PV system. The basic working methodology for all sents the DC current (A), V represents the DC voltage (V) dc three software packages is almost similar. At first, the lo- and t represents the time (h). cation and climate and relevant parameters are taken into account. Then, proposed orientations are configured and 1.5.2 Reference yield the necessary modules are chosen according to their ap- The reference yield, Y [25], is calculated by dividing the plicability and suitability. Lastly, the designed model is total in-plane solar radiation H by the PV’s reference ir - simulated to determine the required results. The overall radiance G. It represents the maximum energy that can be workflow diagram is illustrated in Fig. 11. obtained under ideal conditions. Y reflects the amount of peak Sun hours or solar radiation in kWh/m if G = 1 kW/ m and basically defines the solar-radiation resource for the PV system. It is determined by the location of the PV array, the alignment or orientation and the weather-profile variability from month to month and year to year. Its unit is h/d. kWh Y = 1kW (2) Y = where Y represents the reference yield (h/d), H represents r t the total horizontal irradiance on the array plane (Wh/m ) and G represents the global irradiance under the standard Fig. 10: Bifacial modules tilted at 24° 2 test conditions (STC) (W/m). Table 5: Orientation parameters Azimuth Height above Number of Power Tilt (degrees) Module gap Row gap Number of the mounting Design modules (kW) (degrees) (north is 0) (metres) (metres) inverters surface (metres) Orientation-1 174 59.16 90 180 and 90 0.001 N/A 11 2 Orientation-2 174 59.16 90 90 0.5 3.5 11 2 Orientation-3 174 59.16 24 180 0.1 3.5 11 2 Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 410 | Clean Energy, 2021, Vol. 5, No. 3 1.5.3 Final yield peak power of the installed PV array under an STC of 1000 The final yield, Y [25], is calculated by dividing the annual, W/m solar irradiance and 25°C cell temperature. Its unit monthly or daily net AC energy output of the system by the is kWh/d*kWp. Y = E , /P pv AC max G,STC (3) Site Selection where Y represents the final yield (kWh/d*kWp), E rep- f pv,AC Meterological Data resents the net AC energy output of the system (kWh/d) Collection and P represents the peak power of the PV array max G, STC under STC (kWp). Load Profile Analysis Orientation 1 1.5.4 Performance ratio Orientation 2 System Design The performance ratio (PR) is a globally accepted indicator of PVSOL the overall effect of losses on the rated output of a PV system Orientation 2 PVsyst Software Simulation due to array temperature, incomplete utilization of the ir - radiation and system component inefficiencies or failures. SAM The final yield divided by the reference yield is the PR. Output A  PR is a comparison of the output of the plant with the output that the plant could have reached if the irradiation, Energy Profile Deviation Comparative Financial panel temperature, grid availability, aperture area, nom- Analysis Analysis Analysis Analysis inal power output and temperature correction values were all taken into account [52, 53]. Fig. 11: Overall workflow diagram (4) PR = Monthly Energy Profile for Orientation 1 PVSOL where PR represents the performance ratio, r Y epresents PVsyst SAM the final yield (kWh/d*kWp) and Y represents the refer - Average ence yield (h/d). 1.5.5 Specific yield The specific yield, Y , is defined by the amount of energy (kWh) generated per unit of module capacity (kWp) over a period of 1 year [54]. Its unit is kWh/kWp. gen Y = (5) Cap module where Y represents the specific yield (kWh/kWp), E rep- s gen resents the amount of energy generated (kWh) and Cap module represents the module capacity (kWp). JanFeb Mar Apr MayJun JulAug Sep Oct NovDec 1.5.6 Shading loss Month Shading happens when a shadow partly or completely ob- Fig. 12: Monthly energy profile for Orientation-1 scures a solar panel, preventing sunlight from reaching the Table 6: Monthly energy profile for Orientation-1 Month PVSOL (kWh) PVsyst (kWh) SAM (kWh) Mean (kWh) January 9215 8597 7608.43 8473.477 February 8345 7764 7719.92 7942.973 March 8891.3 8341 8649.29 8627.197 April 8109.3 7666 7607.11 7794.137 May 7915.5 7450 7457 7607.5 June 6742.3 6399 6254.88 6465.393 July 7121.7 6663 6636.78 6807.16 August 6820.7 6604 6697.6 6707.433 September 7057.8 6783 6552.1 6797.633 October 8078.2 7413 7863.18 7784.793 November 9273 8691 8185.77 8716.59 December 9342.3 9060 7950.69 8784.33 Total 96 912.1 91 431 89 182.75 92 508.62 Energy (kWh) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 411 cells and decreasing the power output. Even a small amount that if only 1 out of 36 cells is shaded, the power loss can be of shading will result in substantial power loss. In the book ≤75%. PV plants are also affected by shadows cast between by Stanford University’s Gil Masters [55], it was demonstrated PV arrays, especially at sunrise and sunset [56]. 1.5.7 Capacity utilization factor Monthly Energy Profile for Orientation 2 The capacity utilization factor (CUF) is a metric that is often PVSOL used to describe the efficiency of a PV power plant [25]. It is PVsyst the ratio of the real production of a solar plant over a year SAM 10 000 Average to the maximum output over a year under optimal condi- tions. The CUF is usually calculated as a percentage: Actual energy from the plant(kWh) Capacity Utilisation factor(C.U.F)= Plant capacity(kWp) × 24 × 365 8000 (6) 1.5.8 Carbon balance The carbon-balance tool computes the estimated reduc- 6500 tion in CO emissions from a PV installation. This calcu- lation is based on life cycle emissions (LCE), which reflect the CO emissions associated with a specific component or amount of energy. These values include the total life cycle of a part or amount of material, which includes Jan Feb Mar Apr May Jun July AugSep Oct NovDec manufacturing, servicing, maintenance and removal, Month among other things [57]. Its unit is tonnes per year. Fig. 13: Monthly energy profile for Orientation-2 It is found by: Table 7: Monthly energy profile for Orientation-2 Month PVSOL (kWh) PVsyst (kWh) SAM (kWh) Mean (kWh) January 7580.8 7078 6335.12 6997.973 February 7600.8 7124 7065.51 7263.437 March 9380.8 8909 9105.95 9131.917 April 9558.4 9117 9028.58 9234.66 May 9606.9 8887 9393.16 9295.687 June 8001.1 7229 7343.31 7524.47 July 8457.9 7648 7925.39 8010.43 August 8002.3 7539 8025.28 7855.527 September 7855.1 7440 7428.72 7574.607 October 7622 7267 7659.45 7516.15 November 7739.6 7364 6923.73 7342.443 December 7314.5 7078 6296.03 6896.177 Total 98 720.2 92 680 92 530.23 94 643.48 Table 8: Monthly energy profile for Orientation-3 Month PVSOL (kWh) PVsyst (kWh) SAM (kWh) Mean (kWh) January 7777.4 7086 5879.96 6914.453 February 7393.5 7128 6892.47 7137.99 March 8353.5 8449 8787.01 8529.837 April 7906.4 8228 8452.46 8195.62 May 7554.3 7899 8499.72 7984.34 June 6089.8 6453 6626.66 6389.82 July 6395.7 6663 7070.09 6709.597 August 6329 6655 7083.91 6689.303 September 6569.7 6839 6794.75 6734.483 October 7183.5 6942 7355.43 7160.31 November 8038.6 7361 6658.14 7352.58 December 7800.3 7217 5864.53 6960.61 Total 87 391.7 86 920 85 965.13 86 758.94 Energy (kWh) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 412 | Clean Energy, 2021, Vol. 5, No. 3 (E × project life time × LCE ) − LCE (7) gCO /kWh according to IEA. LCE has been found to be grid grid system 2 system 79.8 tons of CO using the PVsyst carbon-balance tool; this where LCE represents the average amount of CO emis- grid 2 includes production related to solar modules, inverters, sions per energy unit for the electricity produced by the wiring and mounting systems [57]. LastlyE, represents grid grid given in gCO /kWh. In the case of Bangladesh, it is 584 the annual energy yield obtained. Here, the project life time is considered to be 20 years. Monthly Energy Profile for Orientation 3 PVSOL PVsyst 1.5.9 Bifacial gain SAM Average 9000 The bifacial gain (BG) is an important parameter in the characterization of bifacial modules and it will be used in our comparison of bifacial and monofacial mod- ules. The BG [58, 59] is defined as the relative increase in energy yield of the bifacial module over that of the monofacial module. We can calculate the BG mathemat- ically as follows E − E 6000 b m BG = (8) where BG represents the bifacial gain, E represents the en- ergy yield of the bifacial module and E represents the en- ergy yield of the monofacial module. JanFeb Mar Apr MayJun JulAug SepOct Nov Dec 1.5.10 Calculation of the payback period Month The payback period [60] is defined as the time required for Fig. 14: Monthly energy profile for Orientation-3 the amount invested in an asset to be repaid by the net ENERGY DEMAND 444,733.5 kWh CONSUMPTION Orientation-1 PV SYSTEM 352,224.88 kWh ENERGY TAKEN Orientation-2 FROM GRID 350,090.02 kWh INVERTER Orientation-3 GRID 357,974.6 kWh PV ENERGY PRODUCED Orientation-1 92,508.62 kWh Orientation-3 86,758.9 kWh Orientation-2 94,643.48 kWh Fig. 15: Schematic diagram of the proposed bifacial solar PV system with simulated values of different orientations Energy (kWh) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 413 Table 9: Monthly coverage of consumption by each orientation PV energy supplied PV energy supplied by PV energy supplied by PV energy supplied by by monofacial panels Month Orientation-1 (kWh) Orientation-2 (kWh) Orientation-3 (kWh) (kWh) January 8473.477 6997.973 6914.45 7006.16 February 7942.973 7263.437 7137.99 6922.98 March 8627.197 9131.917 8529.84 7992.367 April 7794.137 9234.66 8195.62 7463.46 May 7607.5 9295.687 7984.34 7116.3 June 6465.393 7524.47 6389.82 5678.6 July 6807.16 8010.43 6709.6 5978.527 August 6707.433 7855.527 6689.3 6035.56 September 6797.633 7574.607 6734.48 6224.2 October 7784.793 7516.15 7160.31 6820.53 November 8716.59 7342.443 7352.58 7387.98 December 8784.33 6896.177 6960.61 7211.813 Total 92 508.62 94 643.48 86 758.94 81 838.5 Deviation for Orientation-1 Deviation for Orientation-3 PVSOL and PVsyst PVSOL and PVsyst PVSOL and SAM PVSOL and SAM PVsyst and SAM PVsyst and SAM 2000 –500 –1000 –500 Jan Feb Mar Apr May JunJul AugSep Oct NovDec Jan Feb Mar Apr May Jun JulAug Sep Oct NovDec Month Month Fig. 18: Deviation for Orientation-3 Fig. 16: Deviation for Orientation-1 cash outflow generated by the asset. It is determined as Deviation for Orientation-2 follows: PVSOL and PVsyst Y = C /(E ∗ C ) payback pv annual u (9) PVSOL and SAM PVsyst and SAM where Y represents the payback period (years), C rep- payback pv resents the total cost of the rooftop solar system ($), rep C - resents the power price ($/kWh) and E represents the annual annual production (kWh/year). 1.6 Parameters for statistical analysis between software packages To facilitate the calculation of deviation between each –200 software package and to obtain a reliable comparison, –400 several comparison parameters have been used. Apart from annual deviation between each piece of software, –600 the RMSE (root mean square error) and MAD (mean abso- Jan Feb Mar Apr May JunJul AugSep Oct NovDec lute deviation) have been incorporated into the analysis Month as well. Fig. 17: Deviation for Orientation-2 Generally, the RMSE is given by: Energy (kWh) Energy (kWh) Energy (kWh) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 414 | Clean Energy, 2021, Vol. 5, No. 3 Table 10: RMSE analysis for Orientation-1 Month RMSE between PVSOL and PVsyst RMSE between PVSOL and SAM RMSE between PVsyst and SAM January 178.40 463.78 285.38 February 167.72 180.45 12.72 March 158.86 69.86 88.996 April 127.97 144.97 17.00007 May 134.38 132.36 2.02 June 99.102 140.71 41.603 July 132.42 139.98 7.57 August 62.56 35.54 27.02 September 79.33 145.98 66.66 October 192.03 62.07 129.96 November 168.009 313.86 145.85 December 81.49 401.72 320.23 Table 11: RMSE analysis for Orientation-2 Month RMSE between PVSOL and PVsyst RMSE between PVSOL and SAM RMSE between PVsyst and SAM January 145.15 359.597 214.45 February 137.64 154.52 16.88 March 136.197 79.34 56.85 April 127.42 152.95 25.52 May 207.82 61.701 146.12 June 222.89 189.89 32.998 July 233.798 153.72 80.08 August 133.74 6.63 140.38 September 119.83 123.09 3.26 October 102.48 10.81 113.29 November 108.43 235.52 127.095 December 68.27 294.007 225.74 Table 12: RMSE analysis for Orientation-3 Month RMSE between PVSOL and PVsyst RMSE between PVSOL and SAM RMSE between PVsyst and SAM January 199.59 547.74 348.15 February 76.64 144.63 67.99 March 27.57 125.14 97.58 April 92.84 157.63 64.796 May 99.51 272.92 173.41 June 104.85 154.98 50.13 July 77.16 194.68 117.52 August 94.11 217.92 123.82 September 77.74 64.97 12.77 October 69.72 49.63 119.35 November 195.61 398.504 202.898 December 168.38 558.81 390.42 MAD = |A − B | RMSE = (A − B ) t t (11) t t (10) t=1 t=1 Here, A and B are the monthly energy profiles obtained t t from the two pieces of software between which we want 2 Results and analysis to calculate the deviation and n is the number of time 2.1 Energy-profile analysis periods—in our case, months. The MAD, which is used to calculate statistical disper - 2.1.1 Orientation-1 sion, is the next statistical parameter considered in our The monthly energy profile was collected and mean analysis. The terms used in this equation are the same as values were determined using the three software plat- those in the RMSE equation. This parameter is calculated forms. In the case of Orientation-1, the overall mean an- using the formula: nual yield happens to be 92  508.62 kWh, with a specific Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 415 Orientation-1 Orientation-3 RMSE between PVSOL and PVsyst RMSE between PVSOL and PVsyst RMSE between PVSOL and SAM RMSE between PVSOL and SAM RMSE between PVsyst and SAM RMSE between PVsyst and SAM Jan Feb Mar Apr May JunJul AugSep Oct NovDec Month JanFeb Mar Apr MayJun JulAug Sep Oct NovDec Month Fig. 19: RMSE for Orientation-1 Fig. 21: RMSE for Orientation-3 Orientation-2 RMSE between PVSOL and PVsyst the solar panel to heat up and lose performance. In add- 400 RMSE between PVSOL and SAM ition, a gloomy sky reduces the amount of direct radi- RMSE between PVsyst and SAM ation that reaches the solar panels. This means that the location of the Sun over PV panels in different seasons is also essential for energy generation. The total annual energy consumption is estimated to be 444  733.5 kWh. The PV system supplies 92  508.62 kWh (20.8%), while the remaining 352  224.88 kWh is drawn from the grid. The annual shading loss is just 1.9%, since this orienta- tion leaves a wide-open area in the centre of the rooftop. 100 Furthermore, the PR is 71.0%. The monthly energy profile for Orientation-1 is seen graphically in Fig. 12 and is sum- marized in Table 6. 2.1.2 Orientation-2 Jan Feb Mar Apr May JunJul AugSep Oct NovDec By taking the mean of the three software platforms, the Month gross annual yield for Orientation-2 is 94 643.48 kWh and the specific production is 1599.7 kWh/kWp. The highest Fig. 20: RMSE for Orientation-2 yield (9295.7 kWh) is achieved in May due to the highest direct irradiation (180.3 kWh/m) received from solar panels. The lowest yield (6896.18 kWh) is in December, production of 1570 kWh/kWp. High yields are obtained when direct irradiation is minimal. The total annual en- from November to January, which is considered the ergy consumption is 444 733.5 kWh. As a result, 94 643.48 winter season in Bangladesh, with the maximum yield of kWh (21.2%) will be supplied by the PV system, with the re- 8784.33 kWh obtained in December. Since solar cells are maining 350 090.02 kWh supplied by the grid. Orientation-2 very sensitive to the operating temperature, the tempera- has a greater shading loss of 5.7% due to row-to-row ture is optimal for solar cells to operate at high efficiency shading; therefore, the PR is found to be 66.4%. This sug- during this period [61]. Furthermore, during the winter, gests that Orientation-2 wasted a large amount of energy bright skies and low rainfall make for extended exposure per year. The monthly energy profile for Orientation-2 is to sunshine, increasing the energy harvest in bifacial seen graphically in Fig. 13 and is summarized in Table 7. panels. On the other hand, a substantial yield of 8627.2 kWh is achieved in March, as there is a high direct irradi- ance of 173.6 kWh/m , which plays a significant role in 2.1.3 Orientation-3 the high yield. In June, the lowest yield is achieved, with a Orientation-3 has a total annual yield of 86 758.94 kWh and a value of 6465.4 kWh, since the atmospheric temperature specific production of 1466 kWh/kWp based on the mean of observed exceeds the maximum value of 28.3°C, causing the three software platforms. The highest yield (8529.8 kWh) RMSE RMSE RMSE Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 416 | Clean Energy, 2021, Vol. 5, No. 3 Table 13: MAD analysis for Orientation-1 Month MAD between PVSOL and PVsyst MAD between PVSOL and SAM MAD between PVsyst and SAM January 51.5 133.88 82.38 February 48.42 52.09 3.67 March 45.86 20.17 25.69 April 36.94 41.85 4.91 May 38.79 38.21 0.58 June 28.61 40.62 12.01 July 38.23 40.41 2.19 August 18.06 10.26 7.8 September 22.9 42.14 19.24 October 55.43 17.92 37.52 November 48.5 90.603 42.103 December 23.53 115.97 92.44 Table 14: MAD analysis for Orientation-2 Month MAD between PVSOL and PVsyst MAD between PVSOL and SAM MAD between PVsyst and SAM January 41.9 103.81 61.91 February 39.73 44.61 4.87 March 39.32 22.904 16.41 April 36.78 44.15 7.37 May 59.99 17.82 42.18 June 64.34 54.82 9.53 July 67.49 44.38 23.12 August 38.61 1.92 40.52 September 34.59 35.53 0.94 October 29.58 3.12 32.704 November 31.3 67.99 36.69 December 19.71 84.87 65.16 Table 15: MAD analysis for Orientation-3 Month MAD between PVSOL and PVsyst MAD between PVSOL and SAM MAD between PVsyst and SAM January 57.62 158.12 100.503 February 22.13 41.75 19.63 March 7.96 36.13 28.17 April 26.8 45.51 18.71 May 28.73 78.79 50.06 June 30.27 44.74 14.47 July 22.28 56.199 33.92 August 27.17 62.91 35.74 September 22.44 18.75 3.69 October 20.13 14.33 34.45 November 56.47 115.04 58.57 December 48.61 161.31 112.71 is obtained in March, when direct irradiation is high. During 2.2 Statistical analysis the month of June, the lowest value (6389.8 kWh) is received. A statistical analysis between the three PV software plat- Direct irradiance is poor due to the gloomy skies and rain. The forms will help in analysing the obtained findings and in PV system provides 86 758.94 kWh (19.5%) of overall electricity future estimation and planning [62]. There is a contrast demand, with the remaining 357 974.6 kWh provided by the between the three software systems in terms of system grid. Since the row-to-row distance is sufficiently managed, production. There is a significant difference between the shading loss is just 0.4%, and the PR is 72%. The monthly en- results of PVSOL vs. SAM and PVsyst vs. SAM. In general, ergy profile for Orientation-3 is given in Table 8 and is shown many additional losses are considered in SAM, resulting in graphically in Fig. 14F . ig. 15 depicts an outline of all the elec- various yields on different occasions. On the other hand, tricity provided by the PV system and grid, and Table 9 shows there is less variation in the obtained values between the monthly coverage of consumption in each orientation. Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 417 Orientation-1 MAD between PVSOL and PVsyst MAD between PVSOL and SAM MAD between PVsyst and SAM Fig. 25: Prospect of a green roof using different orientations Jan Feb Mar Apr MayJun JulAug Sep OctNov Dec Energy supplied by PV (%) Month 25 21.2 20.8 Fig. 22: MAD for Orientation-1 19.5 Orientation-2 MAD between PVSOL and PVsyst MAD between PVSOL and SAM MAD between PVsyst and SAM Orientation-1 Orientation-2 Orientation-3 Fig. 26: Percentage of energy supplied by each PV system the weather profiles used in the three software platforms vary where there are differences in irradiation and tem- perature. The deviations between each software platform for Orientation-1, Orientation-2 and Orientation-3 are seen JanFeb Mar Apr May Jun JulAug Sep Oct Nov Dec Month in Figs 16–18. The RMSE and MAD analyses both show that the de- Fig. 23: MAD for Orientation-2 viation between PVSOL and SAM is comparatively higher in the three orientations. The deviation between PVSOL– Orientation-3 PVsyst and PVsyst–SAM, on the other hand, is inconsistent MAD between PVSOL and PVsyst MAD between PVSOL and SAM among the three orientations in terms of both RMSE and MAD between PVsyst and SAM MAD. As our graphical representation shows, the deviation was higher in some months and lower in others. Hence, both the RMSE and MAD and the deviation analysis, in 120 the beginning, suggest that the difference in results is maximum between PVSOL and SAM. The RMSE between PVSOL and PVsyst, PVSOL and SAM, and PVsyst and SAM for Orientation-1, Orientation-2 and Orientation-3 are given in Tables 10–12, respectively, and graphically rep- resented in Figs 19–21, respectively. The MAD between PVSOL and PVsyst, PVSOL and SAM, and PVsyst and SAM for Orientation-1, Orientation-2 and Orientation-3 are pro- vided in Tables 13–15, respectively, and graphically illus- Jan FebMar Apr MayJun Jul Aug Sep Oct Nov Dec Month trated in Figs 22–24, respectively. Fig. 24: MAD for Orientation-3 2.3 Comparative analysis PVSOL and PVsyst, since they use almost identical variables during the simulation process. Furthermore, the statistical 2.3.1 Comparison among the three orientations model of each platform and the measurement processes Orientation-1 generates more electricity than the other of the irradiation value and yield differ slightly. Moreover, configurations during the months of November, December, MAD MAD MAD Energy supplied by PV (%) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 418 | Clean Energy, 2021, Vol. 5, No. 3 Table 16: Monthly bifacial gain Month Orientation-1 (%) Orientation-2 (%) Orientation-3 (%) January 20.94 -0.17 -1.31 February 14.73 4.92 3.11 March 7.94 14.26 6.73 April 4.43 23.73 9.81 May 6.90 30.62 12.19 June 13.85 32.51 12.52 July 13.86 33.99 12.23 August 11.13 30.15 10.83 September 9.21 21.7 8.20 October 14.14 10.20 4.98 November 17.98 –0.62 –0.48 December 21.80 –4.38 –3.48 is a significant shading loss of 5.7%, which decreases the Orientation-1 annual yield in the case of Orientation-2. As a result, the Orientation-2 difference between Orientation-1 and Orientation-2 is just Orientation-3 2134.86 kWh. Orientation-2 seems to have the upper hand in terms of meeting annual demand, as it can satisfy 21.2% of the energy requirements. We know that higher albedo increases energy production from bifacial panels, so the vertically positioned device may effectively use both the front and back sides of the panels to optimize the produc- tion yield. The optimal inclined panels, on the other hand, suffer significantly because there is too little space for dif- 5 fuse radiation to enter the ground and reflect onto the rear side. Furthermore, a small row-to-row distance makes it impossible for irradiance to penetrate the back line. –5 Coverage of the area should be addressed before installing a rooftop solar panel. There is a wide space in the centre of JanFeb Mar Apr MayJun JulAug Sep Oct Nov Dec each block for Orientation-1. Although the same number of Month modules were mounted in different orientations, they did Fig. 27: Percentage increase in energy due to bifacial panels as com- not have an equivalent amount of space. There were some pared to monofacial panels open spaces between the rows in Orientation-2, but they would be impossible to use for other purposes. Similarly, January and February. Orientation-2, on the other hand, Orientation-3 has left just the bare minimum of room for generates more energy than the other orientations during other uses. As a result, Orientation-1 offers an environmen- the months of May to September. Since Orientation-2 has tally friendly configuration that includes vacant gaps in the more modules facing east–west, it experiences more direct centre of the roof that can be used further by incorporating a irradiation during the year than Orientation-1, which green roof scheme. This would have an optimal effect while has just 36 modules facing east–west and the other 138 also lowering the ambient temperature, allowing the panels facing north–south. As a result, Orientation-1 is better to work more effectively. Fig. 25 depicts the green rooftop de- suited for winter and late autumn, while Orientation-2 is sign. The PV contribution to the total energy demand in each better suited for summer and the monsoon season. In the orientation is also presented in Fig. 26. case of Orientation-3, however, a higher yield is obtained in late spring and early summer (March, April, May). Following this, the yield declines until it approaches its 2.3.2 Comparison between bifacial and lowest point in June, when the atmosphere is gloomy and monofacial systems there is inadequate direct irradiation. Thus, Orientation-1 The percentage of energy gain for three different orien- and Orientation-2 have higher yield during the mon- tations is compared with respect to a monofacial config- soon season than Orientation-3 owing to the higher dif- uration. For each orientation, the monthly mean energy fuse irradiation captured on both sides of the bifacial value is taken into account. In the case of Orientation-1, panel as a result of a vertically positioned device. As a re- the energy gain is high during the winter season, sult, Orientation-2 has the highest production yield with reaching ~22% in December and January. After January, a value of 94  643.48 kWh, while Orientation-1 has the the energy gain steadily declines, reaching a low of 4.43% second-highest value of 92 508.62 kWh. Despite this, there in April. From late June to July, the energy gain increases Percentage Increase in Energy Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 419 Table 17: Summary of all of the performance parameters Output parameters Orientation-1 Orientation-2 Orientation-3 Monofacial PV system Annual PV energy (kWh) 92 508.62 94 643.48 86 758.94 81 838.48 Specific production (kWh/kWp) 1570 1599.7 1466 1378 Annual energy demand (kWh) 444 733.5 444 733.5 444 733.5 444 733.5 Total percentage supplied by PV (%) 20.8 21.2 19.5 18.4 Energy taken from grid (kWh) 352 224.88 350 090.02 357 974.6 362 895 Performance ratio (%) 71.0 66.4 72 73.3 Overall annual energy gain compared to monofacial set-up (%) 13 15.6 6 N/A Shading loss (%) 1.9 5.7 0.4 0.4 Capacity utilization factor 0.179 0.183 0.167 0.158 Carbon balance (tCO/year) 50.04 51.28 46.68 43.80 Table 18: Financial analysis Item Quantity Unit price ($) Total cost ($) Solar panel 174 261.57/panel 45 513.18 Inverter 11 1495.41/inverter 16 449.51 Mounting – 0.047/W 2780.52 Wiring and miscellaneous costs – 3537.66 Total installation/capital cost – 68 280.87 Operation and maintenance – 5% of capital cost 3414.0435 ATV – 5% of solar-panel cost 2275.659 Annual savings in total grid price – 0.071/kWh 6482.56 Table 19: Payback period for each orientation 2.4 Financial analysis An approximate financial analysis has been carried out Orientation Payback period (years) for our PV rooftop set-up. Mainly, the installation or cap- Orientation-1 10.4~10 ital cost, operation and maintenance cost, ATV (Advance Orientation-2 10.16~10 Trade Vat) and the annual saving in the total grid-power Orientation-3 11.08~11 price have been illustrated, where the cost of the solar panels, inverters, mounting systems and the wiring and again because the vertically installed device will capture miscellaneous costs have been taken for the installation diffuse irradiation to compensate for the low direct ir - cost of our system. The solar-panel model that we have radiation caused by cloudy conditions. This is because selected is the LG340N1T-v5 bifacial model, which costs cloudy weather increases the ratio of diffuse radiation ~$261.57 [63]. Hence, the total capital cost for 174 panels is compared to direct radiation, which, in fact, provides $45 513.18. The price of one SUN2000L-5KTL model inverter the upper hand to the bifacial panel system and hence is ~$1495.41 [64]. So, a total of $16 449.51 is estimated for more BG is observed during these times. The energy gain 11 inverters. Considering a rooftop mounting cost of $0.047 decreases again until September, when it begins to rise per watt [65] of electricity produced, for our total PV design again after that. For Orientation-2, the BG is low during with a capacity of 59.16 kW, the capital cost for mounting the winter season. It begins to rise in February and hits will be ~$2780.52. Finally, wiring and other miscellan- its peak in July, when it stands at 34%. Following that, the eous costs such as fuses, switchgear, relay and others will BG reduces and reaches its lowest point in December. In roughly require an installation cost of $3537.66. Hence, the Orientation-3, the energy gain continues to climb after total installation is ~$68 280.87. As for operation and main- January and hits a high of 12.5% in June. The energy tenance (O&M) costs, we have considered the expenses to gain then begins to decline until it reaches its lowest be 5% of the capital cost [66]. Thus, the O&M cost accounts point around December. In terms of annual yield, the for ~$3414.0435. The grid-power price was considered at average growth in the energy gain for Orientation-1, 0.071 $/kWh. The mean annual PV yield is 91 303.68 kWh. Orientation-2 and Orientation-3 is 13%, 15.6% and 6%, Hence, it will be possible to make savings of ≤$6482.56 an- respectively, which implies an advantage of vertically nually. According to the National Board of Revenue (NBR), mounted systems compared to optimum-tilted modules. 5% ATV tax is to be applied to imported solar panels and Table 16 and Fig. 27 show the monthly bifacial benefit in PV cells [67]. As the chosen model, LG340N1T-v5, has to percentage terms. be imported, these parts are subject to ATV. 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A software-based approach in designing a rooftop bifacial PV system for the North Hall of Residence, IUT

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Copyright © 2021 National Institute of Clean-and-Low-Carbon Energy
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10.1093/ce/zkab019
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Abstract

ENERGY DEMAND 444,733.5 kWh CONSUMPTION Orientation-1 PV SYSTEM 352,224.88 kWh ENERGY Orientation-2 TAKEN 350,090.02 kWh FROM GRID Orientation-3 INVERTER 357,974.6 kWh GRID PV ENERGY PRODUCED Orientation-1 92,508.62 kWh Orientation-3 86,758.9 kWh Orientation-2 94,643.48 kWh Keywords: bifacial solar PV panel; PVSOL; PVsyst; SAM; annual energy yield; bifacial gain significant amount of grid consumption and saves a lot of Introduction electricity bills in the process. In this era of rapid technological advancement, the ever- Bangladesh is still heavily dependent on the traditional increasing demand for energy and diminishing fossil fuels fossil fuels for electricity generation and transmission have made it necessary to look for eco-friendly, sustainable but, due to limited reserves of fossil fuels, the country is renewable-energy schemes, keeping in mind the global en- advancing towards a power crisis [13] in the near future. ergy demand, climate change and already available tech- So, this country must make a shift to a renewable-energy nologies [1–3]. Extensive research and studies are going on system to tackle the impending problem. According to to find innovative methods to ensure clean energy tran- the Bangladesh Energy Situation, the power sector in these sitions and the effective harvesting and integration of re- parts has not quite reached the transition stage to renew- newables to the conventional energy mix [4–6]. According ables, with only 3.3% of the country’s electricity produc- to the Renewables 2020 [7] report by the International tion coming from renewables and also, in 2018, the total Energy Agency, net installed renewable capacity was ex- renewable-energy capacity in this country was 439 MW pected to grow by ~4% globally in the year 2020, reaching [14]. Having said this, Bangladesh has excellent potential nearly 200 GW. So, by the proper harnessing of these and scope for solar power, with the average daily solar ir - sources, the world has enormous potential to make a tran- radiance ranging from 215 W/m in the north-west to 235 sition to a sustainable, efficient and clean energy system W/m in the south-west [15]. Thus, solar energy can be ex- [8]. In this context, one of the most widely used forms of ploited using photovoltaic (PV) technology [16]. In recent renewable energy is solar energy, having a plethora of ad- times, solar PV markets have flourished a lot and, in 2020, vantages compared to other forms of energy. Solar energy global PV capacity additions were predicted to reach al- prevents the emission of carbon dioxide and other poi- most 107 GW [7]. Hence, the demand and use of PV tech- sonous gases and waste products. The utilization of solar nology have drastically increased worldwide. Solar energy energy also reduces the number of transmission lines from has enormous prospects, especially in irrigation, mini- grids. It is abundant and readily available in direct and in- grid, solar rooftop and several other fields [17]. Despite its direct forms, and is a free source of clean energy [9–12]. So, massive potential, some challenges need to be addressed, the Sun’s energy can efficiently be utilized in the peak load which mainly include lack of land area and proper tech- hours during the daytime, or it can also be stored in bat- nology, inadequate space and high installation costs [18]. teries for later use. Thus, solar energy helps us to reduce a Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 405 So, it is required to find a feasible solar energy scheme that bifacial panels have been conducted as well. Mahmud et al. will mitigate these barriers. It is also necessary to ensure conducted an analysis of bifacial PV set-ups in the high- the social acceptance of a solar energy infrastructure so ways of Bangladesh [31]. Nussbaumer et al. carried out an that the general public will also become ready for novel accuracy test on the simulation data for bifacial modules and innovative technology [19]. Such a feasible and accept- through the variation of tilt angles and share of diffuse ra- able application of PV energy can be the rooftop installa- diation [32]. Chudinzow et  al. performed simulation ana- tion of PV panels, which will help to mitigate the problem lysis of the energy yield of a bifacial PV plant, taking into of the limited land area and crowded cities of Bangladesh consideration several irradiance contributions and the im- by utilizing the empty, unused space of rooftops. pact of ground shadows [33]. Pisigan et  al. researched the Two categories of solar modules are in use, namely performance of bifacial modules in tropical urban settle- monofacial solar modules and bifacial solar modules ments [34]. Baumann et al. studied the use of vertically in- [20]. Monofacial solar modules are the conventional solar stalled bifacial PV panels with roof greening in Winterthur, modules that are commonly used. Most of the works on Switzerland [35]. solar installation and design are based on this type of In our previous work, a primary investigative analysis module. There are numerous works on monofacial-based was conducted on the rooftop of the residential hall of the PV plants and rooftop PV installations. Kazem et  al. p -re Islamic University of Technology (IUT) campus with the sented a case study on the techno-economic feasibility help of monofacial modules [36]. An energy-profile ana- of a 1-MW grid-connected PV system in Adam, Oman, by lysis was conducted with the help of PVSOL, PVsyst and doing a numerical investigation into the optimal config- SAM, with the monofacial modules placed at a tilt angle of uration of the plant, based on real-time data [21]. Shuvho 24°, and the monthly consumption coverage by PV and the et al. predicted the solar irradiation and evaluated the per - grid have been presented. Our research and investigation formance of an 80-kWp grid-connected PV power plant in showed that our proposed monofacial PV model can gen- Dhaka using fuzzy logic and demonstrated a solar irradi- erate ~81 838.5 kWh—almost 18.4% of the annual demand ation predicted model based on fuzzy logic and artificial of our selected site, which is ~444 733.5 kWh. In this work, neural networks [22]. Şenol et al. worked on an optimized bifacial modules have been utilized and a comprehensive design of a self-consumption-based large-scale solar plant analysis has been carried out. Physical implementation of in Cyprus International University and carried out simula- such a system requires a lot of careful calculations and tions using PVSOL for capacities ranging from 450 to 1250 there are several maintenance issues as well. A  detailed kWp [23]. Al-Addous et al. conducted an analysis on stand- software analysis prior to physical implementation can alone PV systems in the Jordan Valley where an analysis of help us find out these minute calculations and issues, the power production of PV modules, weather dependence and also provide a fair idea of the production capacity of and temperature-induced deteriorations has been con- our system. For this reason, we have shown rigorous soft- ducted [24]. Kumar et  al. also carried out software-based ware modelling and simulation in three different orienta- modelling of a 10-MW on-grid PV plant in India employing tions, analysed the feasibility of each and lastly presented PVsyst and PV-GIS software and observed an annual pro- a comparative analysis among the three set-ups and also duction of 15  798.192 mWh/annum [25]. Dondariya et  al. with the monofacial one. performed a simulation-based analysis of grid-connected rooftop PV panels for small households in Ujjain, India, with the help of PVSOL, PVGIS, Solargis and SISIFO, and 1 Methodology obtained an annual yield of ~1528.125 kWh/kWp [9]. 1.1 Site and meteorological information Bifacial PV panels hold noteworthy promise in harvesting energy from the Sun. Unlike monofacial modules, bifacial In order to design a solar PV system, the selection of the modules can utilize the sunlight entering the module from site and the identification of a suitable area are the first both the front and rear sides [26]. Hence, these modules and foremost concerns, as site information helps to im- can improve power density, reduce area costs and rear side prove system performance and efficiency. The proposed contributions to increase cell efficiency by up to ~35% [27]. site is the North Hall of Residence of the IUT campus, Moreover, bifacial modules also have 50% more power gain shown in Fig. 1, having ample rooftop space for a PV set-up. as compared to monofacial modules [28]. However, the bi- The hall is a south-facing building, with a combination of facial yield also depends on albedo factors and tilt-angle three blocks connected together, with each block having configurations [29]. The bifacial annual energy yield can be a mounting area of ~503 square metres. It has a height increased by 30% if the modules are placed 2 metres above of 17.126 metres and no external shading by trees or any the ground instead of close to the ground as in conven- other obstacle [37], as any obstacle can reduce the reli- tional installations [30]. There have been notable works on ability of solar modules. The 3D model of the hall building bifacial modules as well. These works mainly emphasized has been shown in Fig. 2, which is imported from PVSOL. the irradiation and other physical characteristics of bi- The whole rooftop is considered as a plain field for the facial modules and how they behave in the tropics [26] and convenience of system design without any arbitrary ob- in desert conditions. Rooftop and highway-based works on ject. The meteorological data have been collected from Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 406 | Clean Energy, 2021, Vol. 5, No. 3 Monthly Temperature Temperature ( °C ) Jan Feb Mar Apr May JunJul AugSep Oct NovDec Fig. 1: North Hall of Residence of the Islamic University of Technology Month Fig. 3: Monthly temperature data at IUT Source: Meteonorm7.2 data from PVsyst7.0. Direct Irradiance Diffuse Irradiance Fig. 2: Imported 3D model on PVSOL Table 1: Site and meteorological data Site name Islamic University of Technology, Board-Bazar, Dhaka Coordinates 23.9481° N, 90.3793° E 2 130 Annual global irradiance 1793 kWh/m Horizontal diffuse irradiance 864 kWh/m JanFeb Mar Apr MayJun Jul Aug Sep Oct Nov Dec Average temperature 24.9°C Month Wind velocity 0.8 m/s Humidity 81% Fig. 4: Monthly variation in direct and diffuse irradiation Source: Meteonorm 7.2 data from PVsyst 7.0. Source: Meteonorm7.2 data from PVsyst7.0. [40]. The monthly temperature data of the IUT is plotted several weather databases such as NREL, Meteonorm, and presented in Fig. 3 using PVSOL. Meteosyn, etc. The essential meteorological data that The module absorbs radiation in the form of global hori- are taken into account are direct and diffuse irradiance, zontal irradiance, which is made up of direct radiation that average temperature, wind velocity and humidity [38 39 , ]. travels in a straight line from the Sun to Earth and indirect The required data have been tabulated in Table 1, which diffuse radiation that is dispersed by clouds, dust in the air will be needed for the purpose of simulation. The most sig- and other objects and travels in a random direction before nificant meteorological parameters affecting the solar-cell reaching Earth. Direct radiation has a particular direction, performance are irradiance and temperature. Increasing while diffuse radiation may pass in any random direction. The irradiance increases both the open-circuit voltage and the proportion of diffuse light is higher when the radiance is low short-circuit current, thus causing variation in the max- due to cloud cover than when the radiance is high, and the imum power point (MPP). On the other hand, an increase gain relative to monofacial PV is also higher [41]. The monthly in temperature causes a significant decrease in cell voltage variation in direct and diffuse irradiation is presented in Fig. 4. Temperature ( °C ) Direct Irradiance (kWh/m ) Diffuse Irradiance (kWh/m ) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 407 orientation affects the annual yield. However, rear irradi- 1.2 Load-profile analysis ance has to be considered, which depends on the albedo The capacity of a PV module is selected based on the total of the reflecting surface [44]. Hence, the albedo was con- amount of electricity consumed as per the load profile. The sidered to be 0.65, which can be obtained through artifi- IUT has two residential halls. We have taken the same load cially added light-coloured aggregate to the roof [45]. Then profile as in our previous work, considering one (North again, vertical mounting (VM) of bifacial modules helps to Hall) of those two halls, as both halls are analogous (a avoid regular panel cleaning by alleviating soiling losses five-storey building having three blocks where each block [46]. Thus, a low soiling loss of 5% is taken into account for contains 10 rooms and 1 washroom). The load profile is the vertically mounted panel and, for an optimum-tilted provided in Table 2. The annual consumption for one hall panel, it was considered as 15%. Power loss due to mis- is ~444 733.5 kWh. match or reduced yield was considered to be 2%. A DC–AC ratio of 1.08 was chosen. Lastly, bifaciality and diode loss were taken as 0.7 and 0.5%, respectively. Using 174 mod- 1.3 System design ules rated at 340 W, an installed capacity of 59.16 kW was Monocrystalline silicon solar modules are used in the obtained. The overall parameters of the system are sum- system design because they are more effective than poly- marized in Table 3 [47]. Fig. 5 shows the I–V characteris- crystalline and amorphous ones [3942 , ]. This work, like tics of the solar panel. Inverter specifications are provided the previous work, uses modules made by LG Electronics, in Table 4 and an efficiency characteristic curve of the in- Inc. with a rated power of 340 W and a module efficiency verter is shown in Fig. 6. of 19.8%. The maximum power voltage is 34.4 V and the maximum power current is 9.89 A.  The open-circuit 1.3.1 Orientation-1 voltage is 40.8 V and the short-circuit current is 10.38 The first scheme uses a special design in which vertical A. Inverters, which serve as a current source [43], are at bifacial panels are mounted in a rectangular pattern at the heart of the system. They were selected from Huawei the edge of the roof, leaving an open area in the middle Technologies, with the model number SUN2000L-5KTL. that can be used for other purposes. All of the modules The inverter has a nominal AC power rating of 5000 kW were tilted at a 90° angle for this design. A total of 23 mod- and an efficiency rating of 98.58%. Aside from modules ules were aligned in a straight line east–west and another and inverters, PV systems need robust and dependable 23 modules were aligned in a parallel position with an mounting systems that can withstand environmental azimuth of 180°. Six modules were arranged in a north– adversities while supporting PV panels [23]. To achieve a south direction, with another six arranged in parallel. As high energy yield, all modules were installed at a height a result, each block has a total module count of 58, for a of 2 metres above the mounting surface. The mounting total of 174 modules across three blocks. The distance be- system has been tilted at various angles to meet the tween each panel was kept to a minimum and they were system-configuration requirements. To inspect the overall system, three different orienta- Table 3: System parameters tions were simulated by deploying the three software plat- Parameters Description forms mentioned before. Three bifacial PV models were designed and a comparative study was carried out. A total Module type Bifacial of 174 modules were utilized in all simulations to increase Number of panels 174 the reliability of the design and determine how each Module power 340W Model LG340N1T-v5 Module efficiency 19.8% Table 2: Monthly load profile Module maximum power 340W Module maximum power voltage 34.4 V Month Consumption (kWh) Module maximum power current 9.89 A January 24 797.52 Module open-circuit voltage 40.8 V February 30 173.52 Module short-circuit current 10.38 A March 47 799.1 Module NMOT (nominal module 42 ± 3°C April 47 799.1 operating temperature) May 23 983.9 Module bifaciality 0.7 June 47 799.1 Module mismatch loss 2% July 47 799.1 Module diode loss 0.5% August 23 881.9 Albedo for the system 0.65 September 47 799.1 Soiling loss for the system 5% for VM, October 48 100.2 15% for op- November 30 003.5 timum tilt December 24 797.5 DC–AC ratio for the system 1.08 Total 444 733.5 Installed capacity of the system 59.16 kW Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 408 | Clean Energy, 2021, Vol. 5, No. 3 05 10 15 20 25 30 35 40 Module Volts (V) Fig. 5: I–V curve of the LG bifacial solar module Source: System Advisory Model 2020. Table 4: Inverter specifications Fig. 8: South-east view of Orientation-1 Nominal AC power 5000 kW Minimum MPP voltage 90 V Maximum MPP voltage 500 V Input maximum voltage 600 V Frequency 60 Hz EURO efficiency 98.58% Maximum inverter input current 22 A  Source: PVsyst. 260 V, T°C = 45°C, CosPhi = 1.00 Fig. 9: 3D model of Orientation-2 Eff. for U = 480 V Eff. for U = 380 V Eff. for U = 260 V 1.3.2 Orientation-2 34 56 01 2 The second design had the panels facing east–west, with P in (DC) [KW] an azimuth of 90° and a tilt of 90°, while keeping the total Fig. 6: Efficiency curve of the SUN2000L-5KTL inverter number of panels the same. Five modules were arranged in a Source: PVsyst. row with a 3.5-metre gap between them to minimize row-to- row shading. There was, however, a 0.5-metre gap between each row of modules. Fig. 9 illustrates the 3D model. One of the benefits of this orientation is that panels are completely exposed to radiation all day due to the vertical set-up. As a result, this set-up is expected to have less variation in hourly yield during the day. However, due to the overcrowding of the space, some shading losses are to be expected. 1.3.3 Orientation-3 The total module number was kept constant at 174 in the third method. The bifacial modules were arranged to have an optimum tilt angle of 24°, which corresponded to the latitude of the site [48]. However, azimuth was taken into account at 180° to ensure that the panels were facing south to receive the most radiation. The distance between Fig. 7: Aerial view of Orientation-1 in which the bifacial modules are the modules was 0.1 metres and the row spacing was 3.5 mounted at the edge of the rooftop metres. Fig. 10 depicts the design and Table 5 lists all of the arranged in such a way that row-to-row shading was min- parameters for three different orientations. This design imized. Figs 7 and 8 show the aerial and south-east views was purposefully created to compare the benefits of a ver - of Orientation-1 created by PVSOL, respectively. tically mounted set-up to an optimally facing one. Efficiency [%] Module Current (Amps) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 409 After meticulous simulation, the obtained energy yields 1.4 Software details from different orientations are tabulated. With the help The three proposed prominent software packages are of the results, a detailed analysis has been performed to widely used for constructing design-based energy models evaluate the prospect of each orientation. In this context, by a lot of researchers. PVSOL premium was developed coverage of consumption and usages of PV has been dis- by Valentin Software, which is a PV simulation program played as part of the energy-profile analysis. After that, a with facilities for 3D visualization and detailed shading deviation and statistical analysis have been shown among analysis for the calculation of PV systems in combination the performances of the three software packages, followed with electrical equipment, battery systems and electric ve- by comparative analysis among the orientations proposed. hicles [49]. Using the 3D model, comprehensive and pre- In addition, a comparative study is also carried out with cise modelling of the proposed site is done to enhance the monofacial south-facing panel set-up, which was ac- the shading and yield calculation. On the other hand, complished previously [36]. Finally, an approximate finan- PVsyst, developed by PVsyst SA, Switzerland, is an energy- cial analysis has been presented in order to gain insights modelling tool that analyses how much solar energy can into the economic feasibility of the proposed software- be harvested and converted into electrical energy from based analysis. a particular site or location [50]. After choosing the loca- tion, the optimized orientation and configuration are set using the built-in algorithm that suggests the best possible 1.5 Performance parameters combination. Using this, a detailed PV system is prepared. 1.5.1 Annual PV energy The System Advisor Model (SAM), developed by NREL, is a The output energy obtained from the PV modules in kWh techno-economic software model that facilitates system- units in a year is the annual PV energy. It is given by the designing decision-making for people involved with re- formula: newables [51]. After selecting the preferred panel and inverter model, the system is configured using a versatile E = I × V × t(kWh) (1) a dc dc System and Sizing platform that offers easy configuration where E represents the annual PV energy (kWh), I repre- a dc of the PV system. The basic working methodology for all sents the DC current (A), V represents the DC voltage (V) dc three software packages is almost similar. At first, the lo- and t represents the time (h). cation and climate and relevant parameters are taken into account. Then, proposed orientations are configured and 1.5.2 Reference yield the necessary modules are chosen according to their ap- The reference yield, Y [25], is calculated by dividing the plicability and suitability. Lastly, the designed model is total in-plane solar radiation H by the PV’s reference ir - simulated to determine the required results. The overall radiance G. It represents the maximum energy that can be workflow diagram is illustrated in Fig. 11. obtained under ideal conditions. Y reflects the amount of peak Sun hours or solar radiation in kWh/m if G = 1 kW/ m and basically defines the solar-radiation resource for the PV system. It is determined by the location of the PV array, the alignment or orientation and the weather-profile variability from month to month and year to year. Its unit is h/d. kWh Y = 1kW (2) Y = where Y represents the reference yield (h/d), H represents r t the total horizontal irradiance on the array plane (Wh/m ) and G represents the global irradiance under the standard Fig. 10: Bifacial modules tilted at 24° 2 test conditions (STC) (W/m). Table 5: Orientation parameters Azimuth Height above Number of Power Tilt (degrees) Module gap Row gap Number of the mounting Design modules (kW) (degrees) (north is 0) (metres) (metres) inverters surface (metres) Orientation-1 174 59.16 90 180 and 90 0.001 N/A 11 2 Orientation-2 174 59.16 90 90 0.5 3.5 11 2 Orientation-3 174 59.16 24 180 0.1 3.5 11 2 Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 410 | Clean Energy, 2021, Vol. 5, No. 3 1.5.3 Final yield peak power of the installed PV array under an STC of 1000 The final yield, Y [25], is calculated by dividing the annual, W/m solar irradiance and 25°C cell temperature. Its unit monthly or daily net AC energy output of the system by the is kWh/d*kWp. Y = E , /P pv AC max G,STC (3) Site Selection where Y represents the final yield (kWh/d*kWp), E rep- f pv,AC Meterological Data resents the net AC energy output of the system (kWh/d) Collection and P represents the peak power of the PV array max G, STC under STC (kWp). Load Profile Analysis Orientation 1 1.5.4 Performance ratio Orientation 2 System Design The performance ratio (PR) is a globally accepted indicator of PVSOL the overall effect of losses on the rated output of a PV system Orientation 2 PVsyst Software Simulation due to array temperature, incomplete utilization of the ir - radiation and system component inefficiencies or failures. SAM The final yield divided by the reference yield is the PR. Output A  PR is a comparison of the output of the plant with the output that the plant could have reached if the irradiation, Energy Profile Deviation Comparative Financial panel temperature, grid availability, aperture area, nom- Analysis Analysis Analysis Analysis inal power output and temperature correction values were all taken into account [52, 53]. Fig. 11: Overall workflow diagram (4) PR = Monthly Energy Profile for Orientation 1 PVSOL where PR represents the performance ratio, r Y epresents PVsyst SAM the final yield (kWh/d*kWp) and Y represents the refer - Average ence yield (h/d). 1.5.5 Specific yield The specific yield, Y , is defined by the amount of energy (kWh) generated per unit of module capacity (kWp) over a period of 1 year [54]. Its unit is kWh/kWp. gen Y = (5) Cap module where Y represents the specific yield (kWh/kWp), E rep- s gen resents the amount of energy generated (kWh) and Cap module represents the module capacity (kWp). JanFeb Mar Apr MayJun JulAug Sep Oct NovDec 1.5.6 Shading loss Month Shading happens when a shadow partly or completely ob- Fig. 12: Monthly energy profile for Orientation-1 scures a solar panel, preventing sunlight from reaching the Table 6: Monthly energy profile for Orientation-1 Month PVSOL (kWh) PVsyst (kWh) SAM (kWh) Mean (kWh) January 9215 8597 7608.43 8473.477 February 8345 7764 7719.92 7942.973 March 8891.3 8341 8649.29 8627.197 April 8109.3 7666 7607.11 7794.137 May 7915.5 7450 7457 7607.5 June 6742.3 6399 6254.88 6465.393 July 7121.7 6663 6636.78 6807.16 August 6820.7 6604 6697.6 6707.433 September 7057.8 6783 6552.1 6797.633 October 8078.2 7413 7863.18 7784.793 November 9273 8691 8185.77 8716.59 December 9342.3 9060 7950.69 8784.33 Total 96 912.1 91 431 89 182.75 92 508.62 Energy (kWh) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 411 cells and decreasing the power output. Even a small amount that if only 1 out of 36 cells is shaded, the power loss can be of shading will result in substantial power loss. In the book ≤75%. PV plants are also affected by shadows cast between by Stanford University’s Gil Masters [55], it was demonstrated PV arrays, especially at sunrise and sunset [56]. 1.5.7 Capacity utilization factor Monthly Energy Profile for Orientation 2 The capacity utilization factor (CUF) is a metric that is often PVSOL used to describe the efficiency of a PV power plant [25]. It is PVsyst the ratio of the real production of a solar plant over a year SAM 10 000 Average to the maximum output over a year under optimal condi- tions. The CUF is usually calculated as a percentage: Actual energy from the plant(kWh) Capacity Utilisation factor(C.U.F)= Plant capacity(kWp) × 24 × 365 8000 (6) 1.5.8 Carbon balance The carbon-balance tool computes the estimated reduc- 6500 tion in CO emissions from a PV installation. This calcu- lation is based on life cycle emissions (LCE), which reflect the CO emissions associated with a specific component or amount of energy. These values include the total life cycle of a part or amount of material, which includes Jan Feb Mar Apr May Jun July AugSep Oct NovDec manufacturing, servicing, maintenance and removal, Month among other things [57]. Its unit is tonnes per year. Fig. 13: Monthly energy profile for Orientation-2 It is found by: Table 7: Monthly energy profile for Orientation-2 Month PVSOL (kWh) PVsyst (kWh) SAM (kWh) Mean (kWh) January 7580.8 7078 6335.12 6997.973 February 7600.8 7124 7065.51 7263.437 March 9380.8 8909 9105.95 9131.917 April 9558.4 9117 9028.58 9234.66 May 9606.9 8887 9393.16 9295.687 June 8001.1 7229 7343.31 7524.47 July 8457.9 7648 7925.39 8010.43 August 8002.3 7539 8025.28 7855.527 September 7855.1 7440 7428.72 7574.607 October 7622 7267 7659.45 7516.15 November 7739.6 7364 6923.73 7342.443 December 7314.5 7078 6296.03 6896.177 Total 98 720.2 92 680 92 530.23 94 643.48 Table 8: Monthly energy profile for Orientation-3 Month PVSOL (kWh) PVsyst (kWh) SAM (kWh) Mean (kWh) January 7777.4 7086 5879.96 6914.453 February 7393.5 7128 6892.47 7137.99 March 8353.5 8449 8787.01 8529.837 April 7906.4 8228 8452.46 8195.62 May 7554.3 7899 8499.72 7984.34 June 6089.8 6453 6626.66 6389.82 July 6395.7 6663 7070.09 6709.597 August 6329 6655 7083.91 6689.303 September 6569.7 6839 6794.75 6734.483 October 7183.5 6942 7355.43 7160.31 November 8038.6 7361 6658.14 7352.58 December 7800.3 7217 5864.53 6960.61 Total 87 391.7 86 920 85 965.13 86 758.94 Energy (kWh) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 412 | Clean Energy, 2021, Vol. 5, No. 3 (E × project life time × LCE ) − LCE (7) gCO /kWh according to IEA. LCE has been found to be grid grid system 2 system 79.8 tons of CO using the PVsyst carbon-balance tool; this where LCE represents the average amount of CO emis- grid 2 includes production related to solar modules, inverters, sions per energy unit for the electricity produced by the wiring and mounting systems [57]. LastlyE, represents grid grid given in gCO /kWh. In the case of Bangladesh, it is 584 the annual energy yield obtained. Here, the project life time is considered to be 20 years. Monthly Energy Profile for Orientation 3 PVSOL PVsyst 1.5.9 Bifacial gain SAM Average 9000 The bifacial gain (BG) is an important parameter in the characterization of bifacial modules and it will be used in our comparison of bifacial and monofacial mod- ules. The BG [58, 59] is defined as the relative increase in energy yield of the bifacial module over that of the monofacial module. We can calculate the BG mathemat- ically as follows E − E 6000 b m BG = (8) where BG represents the bifacial gain, E represents the en- ergy yield of the bifacial module and E represents the en- ergy yield of the monofacial module. JanFeb Mar Apr MayJun JulAug SepOct Nov Dec 1.5.10 Calculation of the payback period Month The payback period [60] is defined as the time required for Fig. 14: Monthly energy profile for Orientation-3 the amount invested in an asset to be repaid by the net ENERGY DEMAND 444,733.5 kWh CONSUMPTION Orientation-1 PV SYSTEM 352,224.88 kWh ENERGY TAKEN Orientation-2 FROM GRID 350,090.02 kWh INVERTER Orientation-3 GRID 357,974.6 kWh PV ENERGY PRODUCED Orientation-1 92,508.62 kWh Orientation-3 86,758.9 kWh Orientation-2 94,643.48 kWh Fig. 15: Schematic diagram of the proposed bifacial solar PV system with simulated values of different orientations Energy (kWh) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 413 Table 9: Monthly coverage of consumption by each orientation PV energy supplied PV energy supplied by PV energy supplied by PV energy supplied by by monofacial panels Month Orientation-1 (kWh) Orientation-2 (kWh) Orientation-3 (kWh) (kWh) January 8473.477 6997.973 6914.45 7006.16 February 7942.973 7263.437 7137.99 6922.98 March 8627.197 9131.917 8529.84 7992.367 April 7794.137 9234.66 8195.62 7463.46 May 7607.5 9295.687 7984.34 7116.3 June 6465.393 7524.47 6389.82 5678.6 July 6807.16 8010.43 6709.6 5978.527 August 6707.433 7855.527 6689.3 6035.56 September 6797.633 7574.607 6734.48 6224.2 October 7784.793 7516.15 7160.31 6820.53 November 8716.59 7342.443 7352.58 7387.98 December 8784.33 6896.177 6960.61 7211.813 Total 92 508.62 94 643.48 86 758.94 81 838.5 Deviation for Orientation-1 Deviation for Orientation-3 PVSOL and PVsyst PVSOL and PVsyst PVSOL and SAM PVSOL and SAM PVsyst and SAM PVsyst and SAM 2000 –500 –1000 –500 Jan Feb Mar Apr May JunJul AugSep Oct NovDec Jan Feb Mar Apr May Jun JulAug Sep Oct NovDec Month Month Fig. 18: Deviation for Orientation-3 Fig. 16: Deviation for Orientation-1 cash outflow generated by the asset. It is determined as Deviation for Orientation-2 follows: PVSOL and PVsyst Y = C /(E ∗ C ) payback pv annual u (9) PVSOL and SAM PVsyst and SAM where Y represents the payback period (years), C rep- payback pv resents the total cost of the rooftop solar system ($), rep C - resents the power price ($/kWh) and E represents the annual annual production (kWh/year). 1.6 Parameters for statistical analysis between software packages To facilitate the calculation of deviation between each –200 software package and to obtain a reliable comparison, –400 several comparison parameters have been used. Apart from annual deviation between each piece of software, –600 the RMSE (root mean square error) and MAD (mean abso- Jan Feb Mar Apr May JunJul AugSep Oct NovDec lute deviation) have been incorporated into the analysis Month as well. Fig. 17: Deviation for Orientation-2 Generally, the RMSE is given by: Energy (kWh) Energy (kWh) Energy (kWh) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 414 | Clean Energy, 2021, Vol. 5, No. 3 Table 10: RMSE analysis for Orientation-1 Month RMSE between PVSOL and PVsyst RMSE between PVSOL and SAM RMSE between PVsyst and SAM January 178.40 463.78 285.38 February 167.72 180.45 12.72 March 158.86 69.86 88.996 April 127.97 144.97 17.00007 May 134.38 132.36 2.02 June 99.102 140.71 41.603 July 132.42 139.98 7.57 August 62.56 35.54 27.02 September 79.33 145.98 66.66 October 192.03 62.07 129.96 November 168.009 313.86 145.85 December 81.49 401.72 320.23 Table 11: RMSE analysis for Orientation-2 Month RMSE between PVSOL and PVsyst RMSE between PVSOL and SAM RMSE between PVsyst and SAM January 145.15 359.597 214.45 February 137.64 154.52 16.88 March 136.197 79.34 56.85 April 127.42 152.95 25.52 May 207.82 61.701 146.12 June 222.89 189.89 32.998 July 233.798 153.72 80.08 August 133.74 6.63 140.38 September 119.83 123.09 3.26 October 102.48 10.81 113.29 November 108.43 235.52 127.095 December 68.27 294.007 225.74 Table 12: RMSE analysis for Orientation-3 Month RMSE between PVSOL and PVsyst RMSE between PVSOL and SAM RMSE between PVsyst and SAM January 199.59 547.74 348.15 February 76.64 144.63 67.99 March 27.57 125.14 97.58 April 92.84 157.63 64.796 May 99.51 272.92 173.41 June 104.85 154.98 50.13 July 77.16 194.68 117.52 August 94.11 217.92 123.82 September 77.74 64.97 12.77 October 69.72 49.63 119.35 November 195.61 398.504 202.898 December 168.38 558.81 390.42 MAD = |A − B | RMSE = (A − B ) t t (11) t t (10) t=1 t=1 Here, A and B are the monthly energy profiles obtained t t from the two pieces of software between which we want 2 Results and analysis to calculate the deviation and n is the number of time 2.1 Energy-profile analysis periods—in our case, months. The MAD, which is used to calculate statistical disper - 2.1.1 Orientation-1 sion, is the next statistical parameter considered in our The monthly energy profile was collected and mean analysis. The terms used in this equation are the same as values were determined using the three software plat- those in the RMSE equation. This parameter is calculated forms. In the case of Orientation-1, the overall mean an- using the formula: nual yield happens to be 92  508.62 kWh, with a specific Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 415 Orientation-1 Orientation-3 RMSE between PVSOL and PVsyst RMSE between PVSOL and PVsyst RMSE between PVSOL and SAM RMSE between PVSOL and SAM RMSE between PVsyst and SAM RMSE between PVsyst and SAM Jan Feb Mar Apr May JunJul AugSep Oct NovDec Month JanFeb Mar Apr MayJun JulAug Sep Oct NovDec Month Fig. 19: RMSE for Orientation-1 Fig. 21: RMSE for Orientation-3 Orientation-2 RMSE between PVSOL and PVsyst the solar panel to heat up and lose performance. In add- 400 RMSE between PVSOL and SAM ition, a gloomy sky reduces the amount of direct radi- RMSE between PVsyst and SAM ation that reaches the solar panels. This means that the location of the Sun over PV panels in different seasons is also essential for energy generation. The total annual energy consumption is estimated to be 444  733.5 kWh. The PV system supplies 92  508.62 kWh (20.8%), while the remaining 352  224.88 kWh is drawn from the grid. The annual shading loss is just 1.9%, since this orienta- tion leaves a wide-open area in the centre of the rooftop. 100 Furthermore, the PR is 71.0%. The monthly energy profile for Orientation-1 is seen graphically in Fig. 12 and is sum- marized in Table 6. 2.1.2 Orientation-2 Jan Feb Mar Apr May JunJul AugSep Oct NovDec By taking the mean of the three software platforms, the Month gross annual yield for Orientation-2 is 94 643.48 kWh and the specific production is 1599.7 kWh/kWp. The highest Fig. 20: RMSE for Orientation-2 yield (9295.7 kWh) is achieved in May due to the highest direct irradiation (180.3 kWh/m) received from solar panels. The lowest yield (6896.18 kWh) is in December, production of 1570 kWh/kWp. High yields are obtained when direct irradiation is minimal. The total annual en- from November to January, which is considered the ergy consumption is 444 733.5 kWh. As a result, 94 643.48 winter season in Bangladesh, with the maximum yield of kWh (21.2%) will be supplied by the PV system, with the re- 8784.33 kWh obtained in December. Since solar cells are maining 350 090.02 kWh supplied by the grid. Orientation-2 very sensitive to the operating temperature, the tempera- has a greater shading loss of 5.7% due to row-to-row ture is optimal for solar cells to operate at high efficiency shading; therefore, the PR is found to be 66.4%. This sug- during this period [61]. Furthermore, during the winter, gests that Orientation-2 wasted a large amount of energy bright skies and low rainfall make for extended exposure per year. The monthly energy profile for Orientation-2 is to sunshine, increasing the energy harvest in bifacial seen graphically in Fig. 13 and is summarized in Table 7. panels. On the other hand, a substantial yield of 8627.2 kWh is achieved in March, as there is a high direct irradi- ance of 173.6 kWh/m , which plays a significant role in 2.1.3 Orientation-3 the high yield. In June, the lowest yield is achieved, with a Orientation-3 has a total annual yield of 86 758.94 kWh and a value of 6465.4 kWh, since the atmospheric temperature specific production of 1466 kWh/kWp based on the mean of observed exceeds the maximum value of 28.3°C, causing the three software platforms. The highest yield (8529.8 kWh) RMSE RMSE RMSE Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 416 | Clean Energy, 2021, Vol. 5, No. 3 Table 13: MAD analysis for Orientation-1 Month MAD between PVSOL and PVsyst MAD between PVSOL and SAM MAD between PVsyst and SAM January 51.5 133.88 82.38 February 48.42 52.09 3.67 March 45.86 20.17 25.69 April 36.94 41.85 4.91 May 38.79 38.21 0.58 June 28.61 40.62 12.01 July 38.23 40.41 2.19 August 18.06 10.26 7.8 September 22.9 42.14 19.24 October 55.43 17.92 37.52 November 48.5 90.603 42.103 December 23.53 115.97 92.44 Table 14: MAD analysis for Orientation-2 Month MAD between PVSOL and PVsyst MAD between PVSOL and SAM MAD between PVsyst and SAM January 41.9 103.81 61.91 February 39.73 44.61 4.87 March 39.32 22.904 16.41 April 36.78 44.15 7.37 May 59.99 17.82 42.18 June 64.34 54.82 9.53 July 67.49 44.38 23.12 August 38.61 1.92 40.52 September 34.59 35.53 0.94 October 29.58 3.12 32.704 November 31.3 67.99 36.69 December 19.71 84.87 65.16 Table 15: MAD analysis for Orientation-3 Month MAD between PVSOL and PVsyst MAD between PVSOL and SAM MAD between PVsyst and SAM January 57.62 158.12 100.503 February 22.13 41.75 19.63 March 7.96 36.13 28.17 April 26.8 45.51 18.71 May 28.73 78.79 50.06 June 30.27 44.74 14.47 July 22.28 56.199 33.92 August 27.17 62.91 35.74 September 22.44 18.75 3.69 October 20.13 14.33 34.45 November 56.47 115.04 58.57 December 48.61 161.31 112.71 is obtained in March, when direct irradiation is high. During 2.2 Statistical analysis the month of June, the lowest value (6389.8 kWh) is received. A statistical analysis between the three PV software plat- Direct irradiance is poor due to the gloomy skies and rain. The forms will help in analysing the obtained findings and in PV system provides 86 758.94 kWh (19.5%) of overall electricity future estimation and planning [62]. There is a contrast demand, with the remaining 357 974.6 kWh provided by the between the three software systems in terms of system grid. Since the row-to-row distance is sufficiently managed, production. There is a significant difference between the shading loss is just 0.4%, and the PR is 72%. The monthly en- results of PVSOL vs. SAM and PVsyst vs. SAM. In general, ergy profile for Orientation-3 is given in Table 8 and is shown many additional losses are considered in SAM, resulting in graphically in Fig. 14F . ig. 15 depicts an outline of all the elec- various yields on different occasions. On the other hand, tricity provided by the PV system and grid, and Table 9 shows there is less variation in the obtained values between the monthly coverage of consumption in each orientation. Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 417 Orientation-1 MAD between PVSOL and PVsyst MAD between PVSOL and SAM MAD between PVsyst and SAM Fig. 25: Prospect of a green roof using different orientations Jan Feb Mar Apr MayJun JulAug Sep OctNov Dec Energy supplied by PV (%) Month 25 21.2 20.8 Fig. 22: MAD for Orientation-1 19.5 Orientation-2 MAD between PVSOL and PVsyst MAD between PVSOL and SAM MAD between PVsyst and SAM Orientation-1 Orientation-2 Orientation-3 Fig. 26: Percentage of energy supplied by each PV system the weather profiles used in the three software platforms vary where there are differences in irradiation and tem- perature. The deviations between each software platform for Orientation-1, Orientation-2 and Orientation-3 are seen JanFeb Mar Apr May Jun JulAug Sep Oct Nov Dec Month in Figs 16–18. The RMSE and MAD analyses both show that the de- Fig. 23: MAD for Orientation-2 viation between PVSOL and SAM is comparatively higher in the three orientations. The deviation between PVSOL– Orientation-3 PVsyst and PVsyst–SAM, on the other hand, is inconsistent MAD between PVSOL and PVsyst MAD between PVSOL and SAM among the three orientations in terms of both RMSE and MAD between PVsyst and SAM MAD. As our graphical representation shows, the deviation was higher in some months and lower in others. Hence, both the RMSE and MAD and the deviation analysis, in 120 the beginning, suggest that the difference in results is maximum between PVSOL and SAM. The RMSE between PVSOL and PVsyst, PVSOL and SAM, and PVsyst and SAM for Orientation-1, Orientation-2 and Orientation-3 are given in Tables 10–12, respectively, and graphically rep- resented in Figs 19–21, respectively. The MAD between PVSOL and PVsyst, PVSOL and SAM, and PVsyst and SAM for Orientation-1, Orientation-2 and Orientation-3 are pro- vided in Tables 13–15, respectively, and graphically illus- Jan FebMar Apr MayJun Jul Aug Sep Oct Nov Dec Month trated in Figs 22–24, respectively. Fig. 24: MAD for Orientation-3 2.3 Comparative analysis PVSOL and PVsyst, since they use almost identical variables during the simulation process. Furthermore, the statistical 2.3.1 Comparison among the three orientations model of each platform and the measurement processes Orientation-1 generates more electricity than the other of the irradiation value and yield differ slightly. Moreover, configurations during the months of November, December, MAD MAD MAD Energy supplied by PV (%) Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 418 | Clean Energy, 2021, Vol. 5, No. 3 Table 16: Monthly bifacial gain Month Orientation-1 (%) Orientation-2 (%) Orientation-3 (%) January 20.94 -0.17 -1.31 February 14.73 4.92 3.11 March 7.94 14.26 6.73 April 4.43 23.73 9.81 May 6.90 30.62 12.19 June 13.85 32.51 12.52 July 13.86 33.99 12.23 August 11.13 30.15 10.83 September 9.21 21.7 8.20 October 14.14 10.20 4.98 November 17.98 –0.62 –0.48 December 21.80 –4.38 –3.48 is a significant shading loss of 5.7%, which decreases the Orientation-1 annual yield in the case of Orientation-2. As a result, the Orientation-2 difference between Orientation-1 and Orientation-2 is just Orientation-3 2134.86 kWh. Orientation-2 seems to have the upper hand in terms of meeting annual demand, as it can satisfy 21.2% of the energy requirements. We know that higher albedo increases energy production from bifacial panels, so the vertically positioned device may effectively use both the front and back sides of the panels to optimize the produc- tion yield. The optimal inclined panels, on the other hand, suffer significantly because there is too little space for dif- 5 fuse radiation to enter the ground and reflect onto the rear side. Furthermore, a small row-to-row distance makes it impossible for irradiance to penetrate the back line. –5 Coverage of the area should be addressed before installing a rooftop solar panel. There is a wide space in the centre of JanFeb Mar Apr MayJun JulAug Sep Oct Nov Dec each block for Orientation-1. Although the same number of Month modules were mounted in different orientations, they did Fig. 27: Percentage increase in energy due to bifacial panels as com- not have an equivalent amount of space. There were some pared to monofacial panels open spaces between the rows in Orientation-2, but they would be impossible to use for other purposes. Similarly, January and February. Orientation-2, on the other hand, Orientation-3 has left just the bare minimum of room for generates more energy than the other orientations during other uses. As a result, Orientation-1 offers an environmen- the months of May to September. Since Orientation-2 has tally friendly configuration that includes vacant gaps in the more modules facing east–west, it experiences more direct centre of the roof that can be used further by incorporating a irradiation during the year than Orientation-1, which green roof scheme. This would have an optimal effect while has just 36 modules facing east–west and the other 138 also lowering the ambient temperature, allowing the panels facing north–south. As a result, Orientation-1 is better to work more effectively. Fig. 25 depicts the green rooftop de- suited for winter and late autumn, while Orientation-2 is sign. The PV contribution to the total energy demand in each better suited for summer and the monsoon season. In the orientation is also presented in Fig. 26. case of Orientation-3, however, a higher yield is obtained in late spring and early summer (March, April, May). Following this, the yield declines until it approaches its 2.3.2 Comparison between bifacial and lowest point in June, when the atmosphere is gloomy and monofacial systems there is inadequate direct irradiation. Thus, Orientation-1 The percentage of energy gain for three different orien- and Orientation-2 have higher yield during the mon- tations is compared with respect to a monofacial config- soon season than Orientation-3 owing to the higher dif- uration. For each orientation, the monthly mean energy fuse irradiation captured on both sides of the bifacial value is taken into account. In the case of Orientation-1, panel as a result of a vertically positioned device. As a re- the energy gain is high during the winter season, sult, Orientation-2 has the highest production yield with reaching ~22% in December and January. After January, a value of 94  643.48 kWh, while Orientation-1 has the the energy gain steadily declines, reaching a low of 4.43% second-highest value of 92 508.62 kWh. Despite this, there in April. From late June to July, the energy gain increases Percentage Increase in Energy Downloaded from https://academic.oup.com/ce/article/5/3/403/6317703 by DeepDyve user on 13 July 2021 Al Mehadi et al. | 419 Table 17: Summary of all of the performance parameters Output parameters Orientation-1 Orientation-2 Orientation-3 Monofacial PV system Annual PV energy (kWh) 92 508.62 94 643.48 86 758.94 81 838.48 Specific production (kWh/kWp) 1570 1599.7 1466 1378 Annual energy demand (kWh) 444 733.5 444 733.5 444 733.5 444 733.5 Total percentage supplied by PV (%) 20.8 21.2 19.5 18.4 Energy taken from grid (kWh) 352 224.88 350 090.02 357 974.6 362 895 Performance ratio (%) 71.0 66.4 72 73.3 Overall annual energy gain compared to monofacial set-up (%) 13 15.6 6 N/A Shading loss (%) 1.9 5.7 0.4 0.4 Capacity utilization factor 0.179 0.183 0.167 0.158 Carbon balance (tCO/year) 50.04 51.28 46.68 43.80 Table 18: Financial analysis Item Quantity Unit price ($) Total cost ($) Solar panel 174 261.57/panel 45 513.18 Inverter 11 1495.41/inverter 16 449.51 Mounting – 0.047/W 2780.52 Wiring and miscellaneous costs – 3537.66 Total installation/capital cost – 68 280.87 Operation and maintenance – 5% of capital cost 3414.0435 ATV – 5% of solar-panel cost 2275.659 Annual savings in total grid price – 0.071/kWh 6482.56 Table 19: Payback period for each orientation 2.4 Financial analysis An approximate financial analysis has been carried out Orientation Payback period (years) for our PV rooftop set-up. Mainly, the installation or cap- Orientation-1 10.4~10 ital cost, operation and maintenance cost, ATV (Advance Orientation-2 10.16~10 Trade Vat) and the annual saving in the total grid-power Orientation-3 11.08~11 price have been illustrated, where the cost of the solar panels, inverters, mounting systems and the wiring and again because the vertically installed device will capture miscellaneous costs have been taken for the installation diffuse irradiation to compensate for the low direct ir - cost of our system. The solar-panel model that we have radiation caused by cloudy conditions. This is because selected is the LG340N1T-v5 bifacial model, which costs cloudy weather increases the ratio of diffuse radiation ~$261.57 [63]. Hence, the total capital cost for 174 panels is compared to direct radiation, which, in fact, provides $45 513.18. The price of one SUN2000L-5KTL model inverter the upper hand to the bifacial panel system and hence is ~$1495.41 [64]. So, a total of $16 449.51 is estimated for more BG is observed during these times. The energy gain 11 inverters. Considering a rooftop mounting cost of $0.047 decreases again until September, when it begins to rise per watt [65] of electricity produced, for our total PV design again after that. For Orientation-2, the BG is low during with a capacity of 59.16 kW, the capital cost for mounting the winter season. It begins to rise in February and hits will be ~$2780.52. Finally, wiring and other miscellan- its peak in July, when it stands at 34%. Following that, the eous costs such as fuses, switchgear, relay and others will BG reduces and reaches its lowest point in December. In roughly require an installation cost of $3537.66. Hence, the Orientation-3, the energy gain continues to climb after total installation is ~$68 280.87. As for operation and main- January and hits a high of 12.5% in June. The energy tenance (O&M) costs, we have considered the expenses to gain then begins to decline until it reaches its lowest be 5% of the capital cost [66]. Thus, the O&M cost accounts point around December. In terms of annual yield, the for ~$3414.0435. The grid-power price was considered at average growth in the energy gain for Orientation-1, 0.071 $/kWh. The mean annual PV yield is 91 303.68 kWh. Orientation-2 and Orientation-3 is 13%, 15.6% and 6%, Hence, it will be possible to make savings of ≤$6482.56 an- respectively, which implies an advantage of vertically nually. According to the National Board of Revenue (NBR), mounted systems compared to optimum-tilted modules. 5% ATV tax is to be applied to imported solar panels and Table 16 and Fig. 27 show the monthly bifacial benefit in PV cells [67]. As the chosen model, LG340N1T-v5, has to percentage terms. be imported, these parts are subject to ATV. 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Clean EnergyOxford University Press

Published: Sep 1, 2021

References