CC BY
29PERFORMANCE ANALYSIS OF SELF-CONTAINED PHOTOVOLTAIC SYSTEMS IN HARD-TO-REACH ENVIRONMENTS USING PVSYST SOFTWARE
MAKHSUMOV ILKHOM BURKHONOVICH
Candidate of Technical Sciences, Head of the Department of Relay Protection and Automation of the Tajik Power Engineering Institute, Kushoniyon district, Tajikistan
NOSIROV ISMOIL SAFAROVICH
Candidate of Technical Sciences, Senior Lecturer at the Department of Relay Protection and Automation of the Tajik Power Engineering Institute, Kushoniyon District, Tajikistan
ODINAEV NEKKADAM KHUSHKADAMOVICH
Candidate of Technical Sciences, Dean of the Faculty of Electromechanics and Innovative Technologies of the Tajik Power Engineering Institute, Kushoniyon district, Tajikistan
RASHIDOV AKRAM RAJABOVICH
Candidate of Technical Sciences, Head of the Department of Automated Electric Drive of the Tajik Power Engineering Institute, Kushoniyon district, Tajikistan
Annotation. The article presents the results of modeling of the autonomous photovoltaic system in the hard-to-reach area of the Punjikent district of the Republic of Tajikistan using the software package PVsyst. During the simulation the generation of electricity was analyzed, the stages and parameters of designing an autonomous photovoltaic system were determined. The average monthly global horizontal radiation for a given area, daily electricity consumption, principles of construction of 3D model of autonomous photoelectric system with shading are determined.
Keywords: autonomous photovoltaic system, solar insolation, shading, field losses.
Introduction
As electricity consumption grows, the demand for increased electricity generation, including from renewable energy sources, will constantly grow. Among the various types of renewable energy sources, solar photovoltaic systems have been developing rapidly in recent years. No other renewable energy source has as much potential as the sun. As a result of irradiation by the Sun, the earth's surface receives in one hour such an amount of energy that is sufficient to meet the energy needs of all mankind in one year. The use of such an energy source is quite effective in the southern regions, especially in places where there is no centralized power supply, for example, in hard-to-reach mountainous regions of the Republic of Tajikistan.
Small-scale grid-connected residential and commercial PV systems are gaining popularity due to new and flexible module designs that are also cost effective. Governments around the world and utilities are also encouraging the use of solar technology.
It is known that the system will work with the maximum possible efficiency only under the same operating conditions. The performance of photovoltaic systems is always characterized by various parameters such as geographic location, solar panel orientation, mounting structure, climatic conditions, etc. [1-3].
PV Module Performance Factors
Factors affecting PV performance have the following characteristics:
a) Temperature: The efficiency of a photovoltaic cell is increased by generating high currents at low temperatures. Also, the voltage across the photocell increases by 0.3-0.5% for every degree Celsius below 25°C. In temperature climates, a photovoltaic system will generate less power in winter
than in summer, but this is due to shorter daylight hours, lower solar declination angles, more cloud cover, and not cooler temperatures.
b) Seasonality: The city of Panjakent, where the APS is being analyzed, receives about 8 hours of sunshine per day and has favorable weather for the establishment of the APS.
c) Partial shading: The effect of shading on the power output of typical photovoltaic installations is non-linear. A small amount of shadow on part of the array can result in a significant reduction in power output.
e) Contamination: any material, most commonly in the form of dust and snow, deposited on the glass of a photovoltaic module interferes with the incoming radiation and adversely affects the generating potential of the module. The amount of pollution loss is highly dependent on the climate and location of the installation.
f) Aging: The power output of any PV module will gradually decrease over its lifetime after the initial break-in period is completed and this is primarily due to their operation at elevated temperatures.
Standalone PV system
A. Off-grid photovoltaic systems, sometimes referred to as off-grid systems, are designed to provide electricity to facilities without the use of an additional power grid. In off-grid photovoltaic systems, PV modules are often used to charge batteries, which, by storing the electrical energy produced by the modules, provide users with electrical energy on demand. In the case of off-grid photovoltaic systems installed in residential buildings, the need for electricity is mainly covered by this system. The excess is fed into the accumulator for storage. To supply electricity to stand-alone equipment, it is necessary to convert direct current to alternating current using an inverter. A backup generator is required in case of an emergency. On fig. 1. shows a diagram of such an autonomous photovoltaic system [4,6].
Bitter v
Photovoltaic Charge Invert* load*
Module Controller
Figure 1. Scheme of an autonomous photovoltaic system
B. PVsyst: Among various photovoltaic systems calculation software, PVsyst simulation software is the most popular. It gives detailed characteristics of photovoltaic installations under operating conditions, including heterogeneous ones. In addition to PVsyst, about twelve software tools are currently used for PV simulation, for example, PV FChart, SOLCEL-II PVSIM, PVFORM, TRNSYS, PVLab, PVSS, RETSCREEN, Renew, SimPhoSys, PVSOL Expert, HOMER, SolarPro, etc. [5].
C. Design: The procedure for designing an off-grid PV system is described below. The design of APS takes place in several stages.
1. Determining the load of the consumer per day.
In table.1. shows the average electrical load for residents of the Penjikent region.
Table 1 - The load of the consumer of electricity per day
Name of devices Quantity, pieces Power consumption, (W) Usage per day, (hour) Energy consumption per day, (W h/day)
LED lamp 8 10 5 400
TV TV/PC Mobile 2 20 5 200
Electric kettle 1 2200 1 2200
Fridge 1 33,3 24 799
Mobile air conditioner 1 785 6 4710
Washing machine 1 2200 1 1100
UPS 6 24 ч/день 144 (W h/day)
Total daily electricity consumption 9553 (W h/day)
2. Battery parameters:
- Required battery capacity - 21323 Ah,
- The current of the selected battery is 1247 Ah,
- Number of parallel batteries - 19,
- Total battery capacity - 23693 Ah,
- The voltage of the selected battery is 51 V.
3. Determination of solar radiation for the location.
Data on the monthly illumination of the area under consideration are reflected in Table. 2.
Table 1 - Monthly data on the illumination of the city of Penjikent
Months I II III IV V VI
Global horizontal 1,726 3,951 4,271 3,877 7,238 8,807
radiation, kW/m2/day
Months VII VIII IX X XI XII
Global horizontal 8,479 5,215 6,031 4,537 2,711 1,724
radiation, kW/m2/day
In a year 4,9 kW/m2/day
4. The dimensions of the photovoltaic array are determined on the basis that the system will be used all year round and the power consumption will be fairly constant.
As a photovoltaic module, the Poly 285 Wp model was chosen from 72 cells based on polycrystalline silicon in the amount of 48 pieces.
Project: For an off-grid photovoltaic system, the main parameters required for simulation are the following:
- PV components database including open circuit voltage, short circuit current, shunts as well as series resistances and a set of constants.
- The inverter database consists of required voltage and power.
- Ratings, geographic location information including latitude, longitude, altitude, etc., as well as monthly meteorological data for horizontal global illumination and temperature at a given point in time.
The meteorological data for the study was obtained from Meteonorm version 7.2, Sat = 100% of the global climatological database for solar energy applications [5].
1. Location: in the part of the project, the geographical location is determined - the city of Penjikent, with a latitude of 39.27° and a longitude of 67.68o
2. Orientation: in terms of orientation, the panels are usually facing south. The angle that the panels will form relative to the ground (tilt angle) is set.
The difference between energy consumption in winter and summer is large, but at the latitude of the Republic of Tajikistan, the gap in solar resources in winter and summer is small. This is the reason why the slope needs to be optimized for the summer months. The tilt of the solar panels for this area is about 45°, with an azimuth of 0°.
3. Horizon: The horizon line shows how much usable sun is actually available at a given time. The charts used indicate obstacles within the solar circle, mostly trees, and the corresponding automatic shading of the PV modules.
4. Near Shading: This piece of software simulates the shadow effect of nearby objects that are less than 50 meters long. For implementation, a 3D simulation is drawn with a house, a tree and photovoltaic panels.
Three-dimensional construction requires the plans of the architect, that is, the exact knowledge of the dimensions, position and height of the array and the surrounding obstacles. The graph to the right of the visualization shows the shading loss at that particular moment along with the linear ray loss.
5. System: Unlike a grid-mounted PV system, the size of an off-grid PV system will depend on the user's requirements, where the user must enter the desired power rating, or alternatively, the available area to install the PV modules.
In an off-grid PV system, the inverter module must be selected from the inverter database. All chains of connected photovoltaic modules must be homogeneous, which means that the modules must be the same, their number is also the same, in the same sequence, have the same orientation, etc.
Figure 2 shows a schematic diagram of an autonomous system. The diode shown here is a bypass diode used for protection purposes.
Figure 2. Diagram of an autonomous system
Simulation results of an autonomous photovoltaic system
A. PV Modules: To understand the basic characteristics of a PV module and array, we use the I-V characteristics commonly found in product data sheets. PV module manufacturers use different solar cells, therefore, PV module performance is expected to differ from one manufacturer to another. Different qualities of solar cells are used by the same manufacturer for modules in market segments.
There are many models for the operation of solar cells, but a five-parameter model is usually used, since it uses the ratio of current and voltage for a single solar cell and takes into account only cells or modules connected in series [7-8].
The power and current-voltage characteristics of various modules have different values when the insolation, air temperature, and the angle of inclination of the modules to the horizon change. This must be taken into account when designing an autonomous photovoltaic system.
B. Shading of photovoltaic modules: Shading an individual photovoltaic cell results in a reduction in insolation at the expense of the proportion of the cell that is shaded, and the current produced by the cell is reduced accordingly. When a cell is in a circuit with bypass diodes and other photocells in series and parallel combinations, the behavior of the entire circuit becomes complex [5,6].
Table 3 shows the annual balances and main results of the grid-connected photovoltaic system. The table shows that 27.310C is the ambient temperature during the year. The energy that can be delivered to the user is about 3.612 MW.
Table 3 - Main results of autonomous photovoltaic system modeling
GlobHor GlobEff E_Avail EUnused E_User E_Load SolFrac
kWh/m' kWh/m1 kWh kWh kWh kWh
January 62.4 95.9 1097 740 325.0 325.0 1.000
February 84.1 119.5 1365 1054 293.6 293.5 1.000
March 116.4 126.8 1455 1125 315.4 315.4 1.000
April 150.9 138.4 1586 1263 305.3 305.2 1.000
May 191.4 153.3 1761 1427 315.4 315.4 1.000
June 226.6 171.6 1950 1646 286.7 286.6 1.000
July 239.7 187.3 2120 1806 296.3 296.1 1.000
August 216.8 195.0 2200 1884 296.3 296.1 1.000
September 173.3 195.4 2213 1913 281.6 281.5 1.000
October 121.4 162.0 1855 1546 291.0 290.9 1.000
November 76.4 121.3 1392 1089 281.6 281.5 1.000
December 55.2 89,5 1025 688 325.0 325.0 1.000
Year 1715.1 1756.1 20019 16180 3613.1 3612.1 1.000
Conclusion
The performance of photovoltaic systems depends on the technology of materials, production and manufacturing process. The simulation takes into account losses that are caused by shading, the position of the module, the equipment used, the characteristics of solar modules, etc. A detailed analysis of all types of losses is provided by the PVsyst software. Using PVsyst allows you to optimally select suitable models for all parts of the photovoltaic system, including all identified sources of losses. However, the simulations retain the main uncertainties of PV data production: weather data (source and annual variability), PV module models, and validity of manufacturer specifications. The issues of taking into account and correcting such uncertainties are the subject of the following scientific research.
REFERENS:
1. Suresh P., Jaimol T. Performance Analysis of Stand-alone PV Systems Under Non-Uniform Operating Conditions Using PVsyst Jaimol Thoma // Advanced Research in Electrical and Electronic Engineering. 2014. vol. 1(4). P. 29-33.
2. MacAlpine, S.M., Erickson Robert W., Brandemuehl Michael J. Characterization of Power Optimizer Potential to Increase Energy Capture in Photovoltaic Systems Operating Under NonUniform Conditions // IEEE TRANSACTIONS ON POWER ELECTRONICS. 2013. vol. 28(6). P. 2936-2945.
3. Performance of Solar Power Plants in India (2011), Submitted by Dr. B D Sharma to Central Electricity Regulatory Commission, New Delhi, India.
4. National Renewable Energy Laboratory (NREL) [Electronic resource]. - access mode: https://www.nrel.gov/index.html (date of appeal: 23.03.2020).
5. Pragya Sharma and Tirumalachetty Harinarayana Enhancement of energy generation from two layer solar panels // International Journal of Energy and Environmental Engineering. 2012. vol. 3(12). P. 1-9.
6. PVsyst [Electronic resource]. - access mode: https://www.pvsyst.com/ (date of appeal: 23.01.2020).
7. Ramaprabha R., Mathur Badrilal L. Impact of Partial Shading on Solar PV Module Containing Series Connected Cells // International Journal of Recent Trends in Engineering. 2009. vol. 2(7). P. 56-60.
8. PVCDROM [Electronic resource]. - access mode: https://www.pveducation.org/pvcdrom (date of appeal: 23.01.2020).
