scholarly journals Chaos Induced Coyote Algorithm (CICA) for Extracting the Parameters in a Single, Double, and Three Diode Model of a Mono-Crystalline, Polycrystalline, and a Thin-Film Solar PV Cell

Electronics ◽  
2021 ◽  
Vol 10 (17) ◽  
pp. 2094
Author(s):  
Shoeb Ahmad Khan ◽  
Shafiq Ahmad ◽  
Adil Sarwar ◽  
Mohd Tariq ◽  
Javed Ahmad ◽  
...  
Keyword(s):  
Thin Film ◽  
Photovoltaic Cell ◽  
Search Space ◽  
Parameter Extraction ◽  
Mass Scale ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Pv System ◽  
Parameter Evaluation ◽  
Pv Cell

The design of a solar PV system and its performance evaluation is an important aspect before going for a mass-scale installation and integration with the grid. The parameter evaluation of a solar PV model helps in accurate modeling and consequently efficient designing of the system. The parameters appear in the mathematical equations of the solar PV cell. A Chaos Induced Coyote Algorithm (CICA) to obtain the parameters in a single, double, and three diode model of a mono-crystalline, polycrystalline, and a thin-film solar PV cell has been proposed in this work. The Chaos Induced Coyote Algorithm for extracting the parameters incorporates the advantages of the conventional Coyote Algorithm by employing only two control parameters, making it easier to include the unique strategy that balances the exploration and exploitation in the search space. A comparison of the Chaos Induced Coyote Algorithm with some recently proposed solar photovoltaic cell parameter extraction algorithms has been presented. Analysis shows superior curve fitting and lesser Root Mean Square Error with the Chaos Induced Coyote Algorithm compared to other algorithms in a practical solar photovoltaic cell.

scholarly journals Efficiency Improvement of on-Grid Solar PV System Using Hybrid MPPT

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2136-2138
Keyword(s):  
Photovoltaic Cell ◽  
Solar Photovoltaic ◽  
The Sun ◽  
Solar Pv ◽  
Pv System ◽  
Maximum Power Point ◽  
Pv Cell ◽  
Solar Pv System ◽  
Power Point ◽  
Sun Light

Solar photovoltaic systems are most commonly used renewable resources nowadays. These pv cells are eco-friendly, pollution free, easy in construction and are compact in size. The solar pv cell generates electricity by simply tracking the sun rays. The main advantage of solar pv cell is that it is dependent on sun light and the sun is available everywhere. The power generated by photovoltaic cell has less efficiency. Thus, this paper proposes the hybrid maximum power point tracker for improving the efficiency of generated energy of grid connected solar pv system.\

scholarly journals Investigations on grid connected PV system under variable irradiation conditions

2018 ◽  
Vol 7 (3.29) ◽  
pp. 253
Author(s):  
G Sreenivasa Reddy ◽  
T Bramhananda Reddy ◽  
M Vijaya Kumar
Keyword(s):  
Photovoltaic Cell ◽  
Photovoltaic System ◽  
Solar Irradiation ◽  
Electrical Performance ◽  
Photovoltaic Module ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Pv System ◽  
Photovoltaic Panel ◽  
Solar Photovoltaic System

A solar photovoltaic panel or a solar PV module is a device, which is to be considered universality the basic constituent of a solar photovoltaic system and is a combination of series and parallel assembly of solar cells. The electrical performance of this solar photovoltaic module be contingent on different environmental situations like PV cells/module solar spectral (air mass), ambient temperature, solar irradiance, angle-of-incidence.With these dependent conditions, there will be a petite chance to operate at its maximum power point (MPP) Hence, a Perturb and Observe (P&O) MPP algorithm is employed which draws considerable power with the desired time response. In present work, the interfacing of Solar PV system with the utility grid system which is having 15kW based on the Voltage Oriented Control (VOC). The temperature of the individual photovoltaic cell and solar irradiation are to be considered as inputs for the simulation process, whereas the duty cycle of the DC-DC boost converter is an output of the P&O controller. Performance of this grid-connected PV system with VOC method is analyzed with the simulation results and %THD values of the voltage and current at coupling point is verified. The results show the superiority of VOC method and its high dynamic behavior under variable irradiation conditions.  

Grid Parity of Residential Building Rooftop Solar PV in India

2021 ◽  
pp. 19-40
Author(s):  
Rakesh Dalal ◽  
Kamal Bansal ◽  
Sapan Thapar
Keyword(s):  
Residential Building ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Indian Government ◽  
Pv System ◽  
Pv Systems ◽  
Grid Parity ◽  
Solar Pv System ◽  
Utility Grid ◽  
Rooftop Solar

Rooftop solar photovoltaic(PV) installation in India have increased in last decade because of the flat 40 percent subsidy extended for rooftop solar PV systems (3 kWp and below) by the Indian government under the solar rooftop scheme. From the residential building owner's perspective, solar PV is competitive when it can produce electricity at a cost less than or equal grid electricity price, a condition referred as “grid parity”. For assessing grid parity of 3 kWp and 2 kWp residential solar PV system, 15 states capital and 19 major cities were considered  for the RET screen simulation by using solar isolation, utility grid tariff, system cost and other economic parameters. 3 kWp and 2 kWp rooftop solar PV with and without subsidy scenarios were considered for simulation using RETscreen software. We estimate that without subsidy no state could achieve grid parity for 2kWp rooftop solar PV plant. However with 3 kWp rooftop solar PV plant only 5 states could achieve grid parity without subsidy and with government subsidy number of states increased to 7, yet wide spread parity for residential rooftop solar PV is still not achieved. We find that high installation costs, subsidized utility grid supply to low energy consumer and financing rates are major barriers to grid parity.

scholarly journals An Effective Method for Parameter Estimation of Solar PV Cell Using Grey-Wolf Optimization Technique

2021 ◽  
Vol 6 (3) ◽  
pp. 911-931
Author(s):  
Abhishek Sharma ◽  
Abhinav Sharma ◽  
Averbukh Moshe ◽  
Nikhil Raj ◽  
Rupendra Kumar Pachauri
Keyword(s):  
Search Algorithm ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Parameter Extraction ◽  
Solar Pv ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Swarm Optimization ◽  
Pv Cell ◽  
Gravitational Search

In the field of renewable energy, the extraction of parameters for solar photovoltaic (PV) cells is a widely studied area of research. Parameter extraction of solar PV cell is a highly non-linear complex optimization problem. In this research work, the authors have explored grey wolf optimization (GWO) algorithm to estimate the optimized value of the unknown parameters of a PV cell. The simulation results have been compared with five different pre-existing optimization algorithms: gravitational search algorithm (GSA), a hybrid of particle swarm optimization and gravitational search algorithm (PSOGSA), sine cosine (SCA), chicken swarm optimization (CSO) and cultural algorithm (CA). Furthermore, a comparison with the algorithms existing in the literature is also carried out. The comparative results comprehensively demonstrate that GWO outperforms the existing optimization algorithms in terms of root mean square error (RMSE) and the rate of convergence. Furthermore, the statistical results validate and indicate that GWO algorithm is better than other algorithms in terms of average accuracy and robustness. An extensive comparison of electrical performance parameters: maximum current, voltage, power, and fill factor (FF) has been carried out for both PV model.

Global assessment for reduction of solar photovoltaic potential due to meteorological and geomorphological limiting factors

2021 ◽  
Author(s):  
Mustajab Ali ◽  
Hyungjun Kim
Keyword(s):  
Northern Hemisphere ◽  
Clean Energy ◽  
Global Scale ◽  
Limiting Factors ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Temperature Changes ◽  
Cell Efficiency ◽  
Maximum Reduction ◽  
Pv Cell

<p>Solar Photovoltaic (PV) has the potential to fulfill a considerable amount of growing electricity demands worldwide.  In addition, being neat and clean, it can help to keep the greenhouse gases emission within safe limits. This resource needs a substantial amount of area for its sitting to supply the required amount of electricity. Such an area mainly depends on the available solar resource which is mainly the function of the local environment where PV is installed. Although some previous studies exist at the global scale, however, they have not comprehensively considered environmental (e.g., temperature, dust deposition, and snow) limiting factors that affect the actual solar PV yield. This study addresses such shortcomings and deals with all limiting factors simultaneously to provide a reliable assessment of potential PV performance at a global scale. PV cell efficiency is reduced due to an increase in resistance between cells at a temperature above a certain limit. Meanwhile, the accumulation of soil (dust) and snow on PV modules are also proven to limit the solar PV resources as it tends to block the incoming solar radiation. Lastly, the geomorphological parameter, which is an arrangement of a PV module to face the sun, is also shown to change its power output.</p><p>PV cell efficiency corrections for temperature changes, soil, and snow covers are applied using the biased corrected data from Global Soil Wetness Project 3 (GWSP3), CanSISE Observation-Based Ensemble of Northern Hemisphere Terrestrial Snow Water Equivalent, Version 2 from National Snow and Ice Data Center (nsidc), and TERRA/MODIS Aerosol Optical Thickness data available from NASA Earth Observations (NEO). The daily mean solar climatological values near the Earth’s surface for the last 14 years (2001–2014) with global coverage of 0.5º x0.5º are used in the analysis. The results have demonstrated that PV performance is affected by temperature increase, soil, snow, and varying tilt-angles. An annual maximum reduction of 5.7% in the total solar PV resource is seen in the Middle East due to the temperature changes. Likewise, a maximum loss of 6.45% in the total solar PV resource is witnessed for soil deposition for Sub-Saharan Africa. A higher reduction (~20%) is shown by snow covers for Russia and Canada in the upper Northern Hemisphere. In addition, a decline of 5–7% is observed for variation in the solar PV tilt-angles in comparison to optimum ones. As a whole, a maximum reduction of 19.45% in the total solar PV resource is found, which leads to a higher coefficient of determination (R<sup>2</sup>= 0.78) than uncorrected estimation (R<sup>2</sup>=0.67). This study will be helpful for household as well as large scale solar schemes and may contribute particularly to achieving the UN SDG No. 07 — Affordable and Clean Energy — and No. 13 — Climate Action — quantitatively.</p>

scholarly journals Reliability, Availability and Maintainability Analysis for Grid-Connected Solar Photovoltaic Systems

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1213 ◽  
Author(s):  
A. Sayed ◽  
M. El-Shimy ◽  
M. El-Metwally ◽  
M. Elshahed
Keyword(s):  
Block Diagram ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Pv System ◽  
Safety Issues ◽  
Pv Systems ◽  
Area Of Interest ◽  
Novel Approach ◽  
Maintainability Analysis ◽  
Ram Analysis

Recently, solar power generation is significantly contributed to growing renewable sources of electricity all over the world. The reliability and availability improvement of solar photovoltaic (PV) systems has become a critical area of interest for researchers. Reliability, availability, and maintainability (RAM) is an engineering tool used to address operational and safety issues of systems. It aims to identify the weakest areas of a system which will improve the overall system reliability. In this paper, RAM analysis of grid-connected solar-PV system is presented. Elaborate RAM analysis of these systems is presented starting from the sub-assembly level to the subsystem level, then the overall system. Further, an improved Reliability Block Diagram is presented to estimate the RAM performance of seven practical grid-connected solar-PV systems. The required input data are obtained from worldwide databases of failures, and repair of various subassemblies comprising various meteorological conditions. A novel approach is also presented in order to estimate the best probability density function for each sub-assembly. The monitoring of the critical subassemblies of a PV system will increase the possibility not only for improving the availability of the system, but also to optimize the maintenance costs. Additionally, it will inform the operators about the status of the various subsystems of the system.

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