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Comparison between two calculation methods for designing a stand-alone PV system according to Mosul city basemap

  • Rasha A. Mohammed , Safwan A. Hamoodi and Ali N. Hamoodi EMAIL logo
Published/Copyright: June 8, 2021
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Abstract

Global heating, depletions, and high cost of fossil fuels ensued the exploitation of AC sources of energy such as solar stamina. The peculiarities of photovoltaic PV module are a condition for dimensioning and designing a PV system. The causation for developing PV modules beneficial for electrical applications, this manner permits the development of new hefty-performances stand-alone PV system. PV ingredients are permitting the computation of the demeanor of the total system in medley scenarios. In this work, a comparison between calculation solar program and manual mathematical method are made according to Mosul-Iraq site.

1 Introduction

PV is a manner of procreating electrical power by changing solar radiation to DC electricity using semiconductors that induct in PV technology. PV generation uses solar panel compounded of many solar cells. Because of the growing demand of clean energy sources, the fabrication of PV modules has developed considerably in recent years [1]. PV is one of the essential universal trends connected to gaining energy from renewable energy sources (RES) [2]. PV inability has important effect on the safety, accuracy, and energy balance of PV devices [3]. PV systems are growing rapidly, starting from low capacity to high capacity around 40,000 MW at the end of 2010. More than 100 countries use PV system [4]. PV is a technology that credibly converts sun light to DC electricity. Variable kinds of PV modules accredit on the rating scale of the power. Solar cell is a fabric cited by famous semiconductors like silicon [5]. Changeability in the temperature will affect the solar module efficiency, and because of these mutations this technology is facing big defiance in its power finesse rendition. Reintegrated of clean energy is considered a screed route [6]. Efficiency is a very significant signal for PV systems [7]. The requirement to decrease the environmental effect of conventional fossil fuels, as well as the depletion of these resources and the intense increase in fossil fuel prices, is the cause for the rising use of RES [8]. PV technology is very well suited to supply the stand-alone locations. It has good reliability [9].

Are obtained from calculation solar program by software package according to the longitudinal and latitude site in formation for a certain loads are given various premiums about the PV generation [10].

2 Literature review

Angga Romana, Eko Adhi Setiawan, and Kurnianto Joyonegoro (2018) studied the design of solar PV system according to two methods: Australia/New Zealand Standard and manual methods. The two methods take constant values for DC voltage bus (48 V) and oversupply coefficient (2). They concluded that Australian design method is better than the manual method [11].

Preeti Bhatt and Arunima Verma (2014) studied the design of solar PV system. They made a comparison between congenital and nano PV system they take (200 V) for bus voltage but did not include the dirt factor tilt angle, inverter efficiency, and oversupply coefficient in the calculations of solar PV system design for conventional and nano types. They concluded that nano PV system cannot be used for high power load on computation of its low conversion efficiency and the design for three phase load requirement of the whole building [12].

Ayaz A. Khamisani (2019) studied the design of off-grid solar PV system. He included the system losses in the calculations and he depended on the PWM charge controller instead of MPPT charge controller in the design of the charger. Solar PV system (off-grid) type systems more agreeable to areas where the consumer opts not to be supply back the energy that generated at this end and the electrisation is yet to be accomplished [13].

3 The uniqueness of this work

PV models have nonlinear characteristics of voltage–current relationship, and therefore, there is only unique point for stand-alone solar PV system as compared with the other previous design; in this work all practical environmental conditions are included in the design according to calculation solar program, and all main practical environmental conditions are taken from this program and compensated in the mathematical method. These practical conditions gave true sizing of PV modules, batteries, charge controller, and inverter as compared with previous works.

4 Stand-alone/off grid solar PV system

PV systems are considered a simple application for the customers to connect their loads to the grid [14]. Battery storage system is used in off-grid PV systems for providing the electricity during cloudy days and at night. The weather changes and the year round conditions must be considered at designing these systems [15]. When sun does not appear for many continuous days, back-up generators are required such as diesel, gasoline, and petroleum. The advantages of stand-alone PV systems are to give adequate energy to a house hold and powering the place which are distant from the grid [16]. Off-grid systems have further ingredients and these systems are considered expensive and comparatively costlier than grid direct system [17]. Table 1 illustrates the PV system components.

Table 1

PV system components

Particular Company
PV modules ATERSA
Batteries STECA TAROM
MPPT controller KHUN
Inverter VICIRO

Figure 1 represents the stand-alone PV system.

Figure 1 
               Stand-alone PV system.
Figure 1

Stand-alone PV system.

5 Materials and methods

Many materials and two calculation methods are suggested in this work.

5.1 Materials

Materials used in this work are given in Table 2.

Table 2

Materials of suggested PV system

Name/type Shapes Rating
Solar panel: ATERSA A-100M MONOCRISTALINO
Product warranty 10 years, P max (100 Wp), V max (18.95 V), I max (5.28 A), V oc (22.21 V), I sc (5.79 A), panel efficiency (15.07%)
Regulator: STECA TAROM 245 PWM.
System voltage 12 V/24 V, input I sc (45 A), maximum output current at load (45 A), maximum self-consumption (14 mA), charge voltage of the boost (14.4 V) and (28.8 V), floating case end of charge voltage (13.7 V) and (27.4 V), equalization charge (14.7 V) (29.4 V). Deep discharge protection (SOC/LVD) < 30% SOC/11.1 V (22.2 V/44.4 V)
Battery: KHUN 100 AH TUBULAR-PLATE.
Model type LPTT 12100H, warranty 5 years, rated capacity 100 A h, inverter support 10KYA-900 VA, nominal voltage 12 V, tall tubular technology, depth of discharge 80%
Inverters: VICTRON MULTIPLUS C 24/2000/50-30.
1,600 W constant output and 4,000 W peak current for 24 V battery voltage. Combination of inverter with transfer switch and 50 A battery charger. Provides pure sine wave at 50 Hz. VE.Bus communication port allows extensive possibilities in terms of connection, configuration, and controlling of victron multiplus devices. Supports three-phase operation (three units of the same model needed). Supports parallel operation – up to six units can be connected parallel to increase system power if needed. Inverter efficiency 94%
Appliances: Television, refrigerator, microwave oven, computer, and lighting

5.2 Methods

Calculation solar program is an implementation that determines the energy during 24 h, requested of a house hold and depending on the numerate that represented by batteries required and number of PV modules [18]. The implementations included the presumptive wattage of each appliance. Calculation solar program the appliances are collected to gather into four categories called entertainment, cleaning, air-conditioning, and lighting energy requested for each category is determined separately then displayed [19]. The forerunner version ditto numerates the rating of the inverter and the charge controller that required by the solar system [20]. These are necessary components for a solar system. In addition, the full clone takes within the account the system efficiency, depth of discharge, and offline verses online usage [21]. Solar are rate of the peak sunshine hours, there are three various estimation manners. The estimation manners annexing use of air mass formula, half-sine model and NASA solar insolation data [22]. The mechanism for calculating the area and panel tilt angle was included.

The proposed model is said to perform better at energy prediction than software tools such as PV watts, PV system, or ret screen. The approach was validated on two 5 MW PV plants in the same district of Mosul-Iraq [23]. Method to curriculum the demeanor of a PV apparatus as a prosthesis to the equivalent circuit model. In some implementation a very prompt and cushy approach to a solar panel demeanor is required [24]. Daytime temperature and global horizontal insolation (GHI) are the two core parameters affecting the PV plant output. According to these parameters, Mosul can be classified into 15 climatic zones [25]. From National Renewable Energy Laboratory (NREL) Mosul is classified into various climatic zones. Finally, the results show a decisive study to select the best PV technology for various climatic zones of Mosul [26].

6 Location and orientation

From basemap the installation is situated: unnamed road, Mosul, Iraq; the coordinates: 36.541461, 43.19386. PV array is bought according to the following peculiarity: inclination: 73° .

Disorientation belonging the south: 6°. AC with a voltage of 230 is used in this system [27].

6.1 Consumption

The energy consumption is determined from appliances and lighting per day. Tables 3 and 4 show the appliances and lighting consumption per day.

Table 3

Consume appliances per day

Consumer appliances (day)
Appliances Hours (h) Power (W) Energy (W h/day)
Computer 5 300 1,500
Television 3 70 210
Microwave oven 0.8 800 640
Refrigerator 8 195 1,560
Total 3,910
Table 4

Lighting consumption

Consumption by lighting (day)
Type Hours (h) Power (W) Energy (W h/day)
Fluorescent lamp 2 5 11 110
Fluorescent tube 2 5 30 300
Bulb 2 5 60 600
Total 1,010

6.2 Theoretical total daily energy 4,920 W h/day

Theoretical energy per day is 4,920 W h/day; the parameters given in Table 5 are used by the calculation of yield (performance ratio) [28,29,30,31,32,33].

Table 5

Performance ratios

Battery depth of discharge 80%
Battery losses coefficient 5%
Wiring loss coefficient 5%
Loss coefficient of DC/AC conversion 6%
Self-discharge coefficient of battery 0.5%
Autonomy system 3 days
Performance ratio 81.9%

Table 6 represents the calculation of PV modules number.

Table 6

PV calculation

ATERSA A-100M Monocristalino
Open circuit voltage (V oc) 22.21 V Voltage at max. power 18.95 V
Short circuit current (I sc) 5.79 A Current at max. power 5.28 A
Max. power 100 W Temperature coefficient of power (C) 0.44%
Real power 98.2928 W No. of serial model 2
Total Pico Power module 800 Wp No. of parallel modules 4
Optimization installation/needs most 0.7 Total modules 8
The degree of optimization election equipment/real n 70%

7 Regulator specifications

The specifications of the regulator are given in Table 7.

Table 7

Regulator specifications

STECA TAROM 245 PWM
Voltage (V) 48 Tension (V) 12–24
Consumption (mA) 14 Rated power (W) 0.3
Utilization ray 0.7 Capacity (A) 45
The degree of optimization election equipment/real n No. of regulator 1

8 Batteries calculations

Energy, depth of discharge, bus voltage, and days of autonomy are entered in the batteries calculations.

  • Nominal voltage of battery: 24 V.

  • Depth of discharge: 80%.

  • Days of autonomy: 3 days.

  • Daily real energy: 6,007 W h/day.

  • Battery capacity calculated helpful: 751 A h.

  • Actual capacity batteries calculated: 1,252 A h.

Battery specifications are given in Table 8.

Table 8

Battery specifications

KHUN 100 AH TUBULAR-PLATE
C10: 200 A h C20: 200 A h C40: 200 A h C100: 200 A h C120: 200 A h
Tension 12 V No. of series pcs element 2
Nominal capacity accumulate 200 A h No. of parallel pcs element 1
Nominal voltage of the battery 24 V Total element 2
The degree of optimization election equipment/real n 16%

9 Inverter charger

The choice of inverter charger is given in Table 9.

Table 9

Inverter specifications

VICTRON MULTIPLUS C 24/2000/50/30
Tension 24 V Rated power 2,000 W
Nominal capacity accumulate 1,600 W Instant power 4,000 W
Battery nominal voltage 11 W Efficiency 94%
Utilization ray 86% No. of inverter 1
The degree of optimization election equipment/real n 117%

The elements that obtained from the calculation solar program are summarized in Table 10.

Table 10

Stand-alone PV components (calculation solar program)

Units Elements
8 Module type – ATERSA A-100M MONOCRISTALINO
1 Regulator type – STECA TAROM 245 PWM
2 Battery type – KHUN 100 AH TUBULAR-PLATE
1 Type of inverter – VICTRON MULTIPLUS C 24/2000/50-30

10 Mathematical calculations

The mathematical calculations are obtained according to the theoretical total daily energy:

10.1 PV sizing

Total load (W h) = 3,910 + 1,010 = 4,920 W h.

Total power = Total load Sun Arc Rate = 4 , 920 W h 6.5 h = 756 W .

Power of PV module = 100 W.

Then,

No . of PV modules = Total power Power of PV module = 756 W 100 W = 7.56 8 pcs .

10.2 Battery sizing

Required battery capacity = Total energy DC voltage × Day of autonomy Depth  of discharge × Temperature correction factor = 4 , 920 24 × 3 0.6 × 0.95 = 615 0.57 = 1 , 078 A h .

Real performance = Battery capacity on cx ( Performance  ratio ) 16% = 200 A h 0.16 = 1 , 250 A h .

No. of series batteries is

( N s ) = Bus voltage Battery voltage = 24 12 = 2

No. of parallel batteries is

( N p ) = Required battery capacity Battery capacity on cx = 1 , 078 A h 1 , 250 A h = 0.862 1 .

N = N p × N s = 1 × 2 = 2 .

10.3 Inverter sizing

Inverter sizing = Total energy × f o = Energy ( W h) Sun Arc Rate ( h) × f o ,

where f o is the oversupply coefficient.

= 4 , 920 6 × 1.7 = 1 , 394 W .

The elements obtained from the mathematical calculations are summarized in Table 11.

Table 11

Stand-alone PV components (mathematical calculations)

Units Elements
8 Module type – ATERSA A-100M MONOCRISTALINO
2 Battery type – KHUN 100 AH TUBULAR-PLATE
1 Type of inverter – VICTRON MULTIPLUS C 24/2000/50-30 (MPPT built-in)

11 Discrepancy

The discrepancy between calculation solar program and mathematical method are made in this work: The solar PV components (PV sizing, battery sizing, charger sizing, and inverter sizing) are included in this study for two methods. Effective coefficients of the calculation solar program in the equations of the mathematical method in addition to the data of Mosul base map, like performance ratios, days of autonomy, nominal battery voltage, battery efficiency, inverter efficiency, and sun are rate.

The number of PV modules, batteries, chargers, and inverter capacity are appeared approximately equal. As compared with the literature review, all necessary parameters of calculation solar program are included in this work; therefore, the sizing of all solar PV system components obtained from this work is accurate and closed to the truth as compared with the previous works, and also this work can be applied on all types (conventional and nano) solar PV system.

12 Presumptions

The presumption effects of the practical conditions are:

  1. Dust particles are litters in the midair and are readily carried by the wind; these dust particles generated from industrial ambient cause 80% softening in the PV electrical output. Also the effect of dust and sighting will decrease the efficiency.

  2. The poor solar irradiant and inclination angle will lead to the fakir PV systems, also the wrong angles will cause a poor received of radiation.

  3. Day of autonomy can be expressed by the time that the load can be met with the batteries a lone unrested any solar inputs, embarking from full charged battery state, this may perform to sorely low average state of charge premium over broad periods of the year which is fully damaging for batteries bank.

13 Conclusion

The comparison results of two methods appear that the number of PV modules, batteries, and inverter are equally for same provenance and specifications of solar PV system components depending on the real cautions of calculation solar program and the theoretical mathematical calculations. Stand-alone PV system is more reliable than the on-grid PV system because of using battery storage system that gives more stability for this system. Days of autonomy have a large effect on the number of the batteries, which in turn will effect on the total cost of the system.

14 Future prospects and drawback

Stand-alone PV system is expected to grow very quickly from now to 2030. The drawbacks of these systems are very high initial cost, especially the storage back and the dust in the weather.


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Acknowledgements

We would like to express our special thanks to our affiliation (NTU).

  1. Conflict of interest: Authors state no conflict of interest.

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Received: 2021-02-19
Revised: 2021-04-13
Accepted: 2021-04-19
Published Online: 2021-06-08

© 2021 Rasha A. Mohammed et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  65. Study of the population in terms of knowledge about the distance between vehicles in motion
  66. UAVs in rail damage image diagnostics supported by deep-learning networks
  67. Exhaust emissions of buses LNG and Diesel in RDE tests
  68. Measurements of urban traffic parameters before and after road reconstruction
  69. The use of deep recurrent neural networks to predict performance of photovoltaic system for charging electric vehicles
  70. Analysis of dangers in the operation of city buses at the intersections
  71. Psychological factors of the transfer of control in an automated vehicle
  72. Testing and evaluation of cold-start emissions from a gasoline engine in RDE test at two different ambient temperatures
  73. Age and experience in driving a vehicle and psychomotor skills in the context of automation
  74. Consumption of gasoline in vehicles equipped with an LPG retrofit system in real driving conditions
  75. Laboratory studies of the influence of the working position of the passenger vehicle air suspension on the vibration comfort of children transported in the child restraint system
  76. Route optimization for city cleaning vehicle
  77. Efficiency of electric vehicle interior heating systems at low ambient temperatures
  78. Model-based imputation of sound level data at thoroughfare using computational intelligence
  79. Research on the combustion process in the Fiat 1.3 Multijet engine fueled with rapeseed methyl esters
  80. Overview of the method and state of hydrogenization of road transport in the world and the resulting development prospects in Poland
  81. Tribological characteristics of polymer materials used for slide bearings
  82. Car reliability analysis based on periodic technical tests
  83. Special Issue: Terotechnology 2019 - Part II
  84. DOE Application for Analysis of Tribological Properties of the Al2O3/IF-WS2 Surface Layers
  85. The effect of the impurities spaces on the quality of structural steel working at variable loads
  86. Prediction of the parameters and the hot open die elongation forging process on an 80 MN hydraulic press
  87. Special Issue: AEVEC 2020
  88. Vocational Student's Attitude and Response Towards Experiential Learning in Mechanical Engineering
  89. Virtual Laboratory to Support a Practical Learning of Micro Power Generation in Indonesian Vocational High Schools
  90. The impacts of mediating the work environment on the mode choice in work trips
  91. Utilization of K-nearest neighbor algorithm for classification of white blood cells in AML M4, M5, and M7
  92. Car braking effectiveness after adaptation for drivers with motor dysfunctions
  93. Case study: Vocational student’s knowledge and awareness level toward renewable energy in Indonesia
  94. Contribution of collaborative skill toward construction drawing skill for developing vocational course
  95. Special Issue: Annual Engineering and Vocational Education Conference - Part II
  96. Vocational teachers’ perspective toward Technological Pedagogical Vocational Knowledge
  97. Special Issue: ICIMECE 2020 - Part I
  98. Profile of system and product certification as quality infrastructure in Indonesia
  99. Prediction Model of Magnetorheological (MR) Fluid Damper Hysteresis Loop using Extreme Learning Machine Algorithm
  100. A review on the fused deposition modeling (FDM) 3D printing: Filament processing, materials, and printing parameters
  101. Facile rheological route method for LiFePO4/C cathode material production
  102. Mosque design strategy for energy and water saving
  103. Epoxy resins thermosetting for mechanical engineering
  104. Estimating the potential of wind energy resources using Weibull parameters: A case study of the coastline region of Dar es Salaam, Tanzania
  105. Special Issue: CIRMARE 2020
  106. New trends in visual inspection of buildings and structures: Study for the use of drones
  107. Special Issue: ISERT 2021
  108. Alleviate the contending issues in network operating system courses: Psychomotor and troubleshooting skill development with Raspberry Pi
  109. Special Issue: Actual Trends in Logistics and Industrial Engineering - Part II
  110. The Physical Internet: A means towards achieving global logistics sustainability
  111. Special Issue: Modern Scientific Problems in Civil Engineering - Part I
  112. Construction work cost and duration analysis with the use of agent-based modelling and simulation
  113. Corrosion rate measurement for steel sheets of a fuel tank shell being in service
  114. The influence of external environment on workers on scaffolding illustrated by UTCI
  115. Allocation of risk factors for geodetic tasks in construction schedules
  116. Pedestrian fatality risk as a function of tram impact speed
  117. Technological and organizational problems in the construction of the radiation shielding concrete and suggestions to solve: A case study
  118. Finite element analysis of train speed effect on dynamic response of steel bridge
  119. New approach to analysis of railway track dynamics – Rail head vibrations
  120. Special Issue: Trends in Logistics and Production for the 21st Century - Part I
  121. Design of production lines and logistic flows in production
  122. The planning process of transport tasks for autonomous vans
  123. Modeling of the two shuttle box system within the internal logistics system using simulation software
  124. Implementation of the logistics train in the intralogistics system: A case study
  125. Assessment of investment in electric buses: A case study of a public transport company
  126. Assessment of a robot base production using CAM programming for the FANUC control system
  127. Proposal for the flow of material and adjustments to the storage system of an external service provider
  128. The use of numerical analysis of the injection process to select the material for the injection molding
  129. Economic aspect of combined transport
  130. Solution of a production process with the application of simulation: A case study
  131. Speedometer reliability in regard to road traffic sustainability
  132. Design and construction of a scanning stand for the PU mini-acoustic sensor
  133. Utilization of intelligent vehicle units for train set dispatching
  134. Special Issue: ICRTEEC - 2021 - Part I
  135. LVRT enhancement of DFIG-driven wind system using feed-forward neuro-sliding mode control
  136. Special Issue: Automation in Finland 2021 - Part I
  137. Prediction of future paths of mobile objects using path library
  138. Model predictive control for a multiple injection combustion model
  139. Model-based on-board post-injection control development for marine diesel engine
  140. Intelligent temporal analysis of coronavirus statistical data
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