scholarly journals Necessity to Design a Controller for PV Module

2020 ◽  
Vol 9 (5) ◽  
pp. 1932-1937
Keyword(s):  
Solar Cell ◽  
Power Output ◽  
Maximum Power ◽  
Atmospheric Conditions ◽  
Solar Cell Performance ◽  
Maximum Power Output ◽  
Point Tracking ◽  
Pv Module ◽  
Input Parameters ◽  
Power Point

Solar power is future of our planet due to the depletion of non-renewable sources of energy. We all are directly dependent on non-renewable source which will only last for 1 or 2 decades. The PV cell exhibit non linear I-V and P-V characteristics. In this paper it is discussed about the factors which will affect the PV module performance. Some factors will decrease the solar cell performance while some factors will improve the efficiency and increase its output power. The performance characteristics of PV module are modeled mathematically and simulated under different atmospheric conditions. The simulation model is obtained using MATLAB software and stimulated under different values of input parameters of PV module that include irradiance and temperature. The variations of these parameters were recorded under different atmospheric conditions. The input parameters of solar cell like solar irradiance and ambient temperature was evaluated. It observed that the maximum power produced fluctuates with both irradiance and temperature. Since the conversion efficiency of PV array is exceptionally low, it requires maximum power point tracking (MPPT) control techniques. The MPPT is the programmed controlled method used to guide the solar cell to achieve the maximum power output, during minute to minute variations of atmospheric changes like irradiance and temperature. The MPPT controller is used to provide maximum power output from PV module against changes in temperature and irradiance. Results obtain by simulation are presented and discussed.

scholarly journals Partial Shading Condition on PV Array: Causes, Effects and Shading Mitigation using DSMPPT

2020 ◽  
Vol 9 (3) ◽  
pp. 1134-1139
Keyword(s):  
Duty Cycle ◽  
Power Output ◽  
Solar Panel ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Pv Module ◽  
Power Point

Solar photovoltaic (PV) systems are gaining importance increasingly as it directly converts solar radiation into electrical energy which is renewable and environment friendly. Where it has a numerous advantage, some disadvantages are also there like its dependency on environmental conditions. The power developed by solar panel decreases if it does not get uniform radiation. Sometimes due to nearby buildings, passing clouds etc. PV module might be partially shaded because of which power output of solar panel may get decrease this is called partial shading conditions. It causes significant reduction in the system power output. To overcome this, maximum power point-tracking under partial shading condition by continuous duty cycle variation schemes have been proposed, in which dc–dc boost converters are connected to PV module to enable maximum power extraction. In this paper a new method of Duty Sweep Maximum Power Point Tracking (DSMPPT) has been implanted, which is capable of tracking the Global Maximum Power Point (GMPP) in the presence of other local maxima. The proposed scheme tracks Maximum Power Point (MPP) by continuous variation of converter’s duty cycle without the use of costly components such as signal converters and microprocessors thereby increasing the compactness of the system.

ANN-based Maximum Power Point Tracking for a Large Photovoltaic Farm Through Wireless Sensor Networks

2019 ◽  
Vol 14 (1) ◽  
pp. 38-48
Author(s):  
K. Annaraja ◽  
S. S. Sundaram ◽  
S. Selvaperumal ◽  
G. Prabhakar
Keyword(s):  
Power Output ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Matlab Simulink ◽  
Maximum Power Output ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Terminal Voltage ◽  
Power Point

Background: A novel system for the usage of Maximum Power Point Tracking of an expansive Solar Photo Voltaic (SPV) farm subjected to conceivable incomplete shading is displayed in this paper. The SPV farm being spread over an expansive territory a remote sensor organize is utilized for checking the sun based protection in the region of each board. The motivation behind the remote sensor organize is to screen the sunlight based protection at various areas near each of the PV board from the tremendous region of the photograph voltaic homestead comprising of countless voltaic boards. The observed protection information is utilized by a prepared. Artificial Neural Network to locate the ideal DC terminal voltage to be kept up over the general DC terminals of the photograph voltaic ranch. All the PV boards are associated in arrangement association with the fundamental bye pass diodes. The DC control accessible at the yield terminals of the SPV cultivate is first DC to DC changed over with a Positive Output Luo Converter (POLC) and bolstered to a heap. A MATLAB Simulink based reproduction was created to approve the proposed system. Methods: Maximum Power Point Tracking based on Artificial Neural Network through wireless sensor networks. Results: As the result of the proposed idea and its implementation in MATLAB we have two sets of results. In either case the input is a vector of 40 elements and the output of the first segment of the work is the estimation of the threshold PV terminal voltage that will guarantees maximum power point operation. In the first case we have the MATLAB SIMULINK implementation of the basic configuration of the forty PV panels arranged in series connection and we have provided a facility to edit the solar insulation levels pertaining to the individual PV panels. In this first configuration we have set a continuously variable PV current for all the panels and the PV current for all the panel are the same. Using this setup, for any combination of solar insulation pattern of the forty panels the overall PV curve and the overall VI curve can be drawn in MATLAB. As the simulation runs the PV current is changed from 0 to the maximum or the short circuit current level in a slowly rising manner implemented using a ramp signal. </P><P> During this period the total power output and the terminal voltage of the PV farm are sent to the work space and the data is thus collected in the workspace of MATLAB. Using basic MATLAB commands the maximum power output and the PV terminal voltage corresponding to the maximum power output are obtained. The PV current at maximum power output condition, the corresponding PV farm terminal voltage, the maximum power output recorded at this condition all correspond to the present insulation vector condition. This way, by changing the elements of the insulation for all the forty panels in a random manner we obtain for each case the Ipmax[i], Pmax[i], Vpmax[i] and this corresponds to insulation[n,i]. Where n is the number of panels, in this case 40 and i the ith experiment. In each experiment the solar insulation level of all the forty panels can be changed and the parameters Vpmax[i], Ipmax[i] and Pmax[i] can be obtained. The value of the harvested power as found from the characteristics for any given set of insulation is denoted as the estimated power. The value of power as obtained from the proposed ANN SMC POLC combination is denoted as the Actual Power. Conclusion: A wireless network based insulation monitoring has been done. An ANN based MPPT algorithm has been developed that gives the reference MPP voltage. The sliding mode control scheme uses the reference voltage and produces the switching pulses for the POLC. The ANN had been trained with a number of combinations of different insulation values falling on each of the forty panels and the ANN gives the correct reference voltage for any combination of insulation levels that were not used while training. The sliding mode controller uses this reference voltage and gives the switching pulses to the POLC that harvests the maximum power output to the RL load. The proposed system has been implemented in the MATLAB SIMULINK environment and has thus been validated. The obtained results have been compared against the maximum power output values that could be derived from the characteristic curves obtained for the given combination of insulation levels. The proposed system gives results very close to the values obtained from the characteristics. As a future work the proposed idea can be validated using hardware based experimental setup.

scholarly journals Modeling and simulation of solar PV module for comparison of two MPPT algorithms (P&O & INC) in MATLAB/Simulink

2020 ◽  
Vol 18 (2) ◽  
pp. 666
Author(s):  
Hayder Moayad Abd Alhussain ◽  
Naseer Yasin
Keyword(s):  
Maximum Output Power ◽  
Maximum Power ◽  
Maximum Output ◽  
Atmospheric Conditions ◽  
Solar Pv ◽  
Maximum Power Point ◽  
Matlab Simulink ◽  
Point Tracking ◽  
Pv Module ◽  
Power Point

<p>This paper introduces a procedure for the modelling of a Photo<em>ــ</em>Voltaic (PV) cell and the application of maximum power point tracking (MPPT) in step-by-step with MATLAB/Simulink. The model of one diode is used to explore the characteristics of I<em>ــ</em>V and P<em>ــ</em>V curves of 60W PV module. Due to the non-linear and time varying of PV characteristics, the generated power of the PV is continually varying with atmospheric conditions like temperature and irradiation, the MPPT technology is very important to chase maximum power point (MPP) on the P<em>ــ</em>V curve to obtain maximum output power from PV array. This study focuses on two common types algorithms of MPPT, namely perturb and observe (P&amp;O) and incremental conductance (INC). A DC--DC boost converter is implemented to regulate the voltage output from the PV array's and for the application of MPPT algorithm.</p>

Achieving high-performance planar perovskite solar cell with Nb-doped TiO2 compact layer by enhanced electron injection and efficient charge extraction

2016 ◽  
Vol 4 (15) ◽  
pp. 5647-5653 ◽  
Author(s):  
Bai-Xue Chen ◽  
Hua-Shang Rao ◽  
Wen-Guang Li ◽  
Yang-Fan Xu ◽  
Hong-Yan Chen ◽  
...  
Keyword(s):  
Solar Cell ◽  
Power Output ◽  
High Performance ◽  
Electron Injection ◽  
Perovskite Solar Cell ◽  
Maximum Power ◽  
Compact Layer ◽  
Doped Tio2 ◽  
Maximum Power Output ◽  
Efficient Charge

A PSC based on 2% Nb-doped TiO2 achieved a PCE of up to 16.3%, which is consistent with a stabilized maximum power output of 15.8%.

scholarly journals PV Maximum Power-Point Tracking by Using Artificial Neural Network

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Farzad Sedaghati ◽  
Ali Nahavandi ◽  
Mohammad Ali Badamchizadeh ◽  
Sehraneh Ghaemi ◽  
Mehdi Abedinpour Fallah
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Back Propagation ◽  
Maximum Power ◽  
Atmospheric Conditions ◽  
Maximum Power Point ◽  
Error Back Propagation ◽  
Point Tracking ◽  
Artificial Neural ◽  
Power Point

In this paper, using artificial neural network (ANN) for tracking of maximum power point is discussed. Error back propagation method is used in order to train neural network. Neural network has advantages of fast and precisely tracking of maximum power point. In this method neural network is used to specify the reference voltage of maximum power point under different atmospheric conditions. By properly controling of dc-dc boost converter, tracking of maximum power point is feasible. To verify theory analysis, simulation result is obtained by using MATLAB/SIMULINK.

scholarly journals Multi-Input Converter with MPPT Feature for Wind-PV Power Generation System

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Chih-Lung Shen ◽  
Shih-Hsueh Yang
Keyword(s):  
Maximum Power ◽  
Atmospheric Conditions ◽  
Leakage Inductance ◽  
Point Tracking ◽  
Pv Panel ◽  
Grid Connection ◽  
Power Point Tracking ◽  
Perturb And Observe ◽  
Power Point ◽  
Hybrid Renewable Energy

A multi-input converter (MIC) to process wind-PV power is proposed, designed, analyzed, simulated, and implemented. The MIC cannot only process solar energy but deal with wind power, of which structure is derived from forward-type DC/DC converter to step-down/up voltage for charger systems, DC distribution applications, or grid connection. The MIC comprises an upper modified double-ended forward, a lower modified double-ended forward, a common output inductor, and a DSP-based system controller. The two modified double-ended forwards can operate individually or simultaneously so as to accommodate the variation of the hybrid renewable energy under different atmospheric conditions. While the MIC operates at interleaving mode, better performance can be achieved and volume also is reduced. The proposed MIC is capable of recycling the energy stored in the leakage inductance and obtaining high step-up output voltage. In order to draw maximum power from wind turbine and PV panel, perturb-and-observe method is adopted to achieve maximum power point tracking (MPPT) feature. The MIC is constructed, analyzed, simulated, and tested. Simulations and hardware measurements have demonstrated the feasibility and functionality of the proposed multi-input converter.

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