scholarly journals Application of Maximum Power Point Tracking Algorithm for Determination of the Solar Electric Potential in Gorkha Bazzar, Nepal

2021 ◽  
Author(s):  
Aamod Khatiwada ◽  
Rabin Dhakal ◽  
Sirapa Shrestha
Keyword(s):  
Solar Energy ◽  
East Asia ◽  
Surface Area ◽  
Maximum Power ◽  
Solar Irradiation ◽  
South East Asia ◽  
Maximum Power Point ◽  
Hilly Region ◽  
Geographical Regions ◽  
Power Point

It is inevitable fact that the use of excessive fossil fuel has establisheditself as a major concern for the existence of living kinds in the world. So thedevelopment of renewable energy source has been the must task to minimize theenergy crisis as well as the problems created by the use of fossil fuels. Nepal is acountry with geographical and climatic diversity in South East Asia with meansolar radiation of 4.7 kWh/m2 per day and a surface area of 1, 47,181 km2. It isthe region in South East Asia with a tremendous amount of solar energy potential.Among three major geographical regions namely Himalayan, Hilly and Terairegion, this study has been performed at Gorkha Municipality, located at centralNepal in Hilly region to determine the solar energy potential for grid-connectedphotovoltaic systems installed on rooftops. A methodology was developed, inwhich the characteristics of the buildings were categorized, followed by thecalculation of the roof surface area where photovoltaic panels could be installed.After that, the mean solar irradiation characteristics were defined as well as thetechnical parameters of the photovoltaic systems. With all these factors, theamount of electricity that could be potentially generated per year by solar panelsis estimated. Finally, the calculations were made to estimate the amount ofelectricity that could be generated with the implementation of incrementalconductance method for tracking the maximum Power Point and also, the systemwas developed using Arduino, PHP programming language, current and voltagesensors which aids for the maintenance of the installed photovoltaic cells.

scholarly journals A Kalman filter based MPPT algorithm

2020 ◽  
Author(s):  
Domingos T. S. Neto ◽  
Maurício B. C. Salles ◽  
Pablo D. P. Salazar ◽  
José R. Cardoso
Keyword(s):  
Renewable Energy ◽  
Kalman Filter ◽  
Solar Energy ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point ◽  
Relative Errors

The sun is a plenty and popular source of renewable energy. To transform solar energy into electricity it is necessary to use photovoltaic (PV) panels which in turn have flow efficiency and therefore do not provide maximum power. Maximum power depends on temperature and solar radiation. Changes in these  environmental factors require an algorithm to find the Maximum Power Point (MPP) where maximum power can be extracted. The algorithm is called the Maximum Power Point Tracking (MPPT). Through MatLab=Simulink the MPPT algorithm based on the Kalman Filter was implemented. The MPPT algorithm is essential for the maximum use of solar energy and therefore plays an important role for the feasibility and competitiveness of PVs in renewable energy. This article proposes a MPPT based on the kalman filter that has the advantage of efficiently estimating variables based on measurements with statistical noise, in this case measurements of solar irradiation and temperature. The results show efficiency because the relative errors are less than 1.13% compared to results obtained from simulink.

Comparison between Seven MPPT Techniques Implemented in a Buck Converter

2019 ◽  
Vol 12 (6) ◽  
pp. 476-486
Author(s):  
Lahcen El Mentaly ◽  
Abdellah Amghar ◽  
Hassan Sahsah
Keyword(s):  
Value Added ◽  
Buck Converter ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Solar Panels ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Pv Panel ◽  
Low Efficiency ◽  
Power Point

Background: The solar field on our planet is inexhaustible, which favors the use of photovoltaic electricity which generates no nuisance: no greenhouse gases, no waste. Methods: It is a high value-added energy that is produced directly at the place of consumption through photovoltaic (PV) solar panels. Notwithstanding these advantages, the maximum power depends strongly on solar irradiation and temperature, which means that a Maximum Power Point Tracking (MPPT) controller must be inserted between the PV panel and the load in order to follow the Maximum Power Point (MPP) continuously and in real time. In this work, MPP’s behavior was simulated at different temperatures and solar irradiations using seven techniques which identify the MPP by different methods. Results: The novelty of this work is that the seven MPPT methods were compared according to a very selective criterion which is the MPPT efficiency as well as a purely digital duty cycle control without using the PI controller. The simulation under the PSIM software shows that the FLC, TP, FSCC, TG, HC and IC methods have almost the same efficiency of 99%, whereas the FOCV method had a low efficiency of 96%. Conclusion: This makes it possible to conclude that the best methods are FLC, HC and IC because they use fewer sensors compared to the rest.

scholarly journals A Novel DSP-Based MPPT Control Design for Photovoltaic Systems Using Neural Network Compensator

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3260
Author(s):  
Ming-Fa Tsai ◽  
Chung-Shi Tseng ◽  
Kuo-Tung Hung ◽  
Shih-Hua Lin
Keyword(s):  
Neural Network ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Solar Irradiation ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Irradiation Cell ◽  
Power Point ◽  
Neural Network Compensator

In this study, based on the slope of power versus voltage, a novel maximum-power-point tracking algorithm using a neural network compensator was proposed and implemented on a TI TMS320F28335 digital signal processing chip, which can easily process the input signals conversion and the complex floating-point computation on the neural network of the proposed control scheme. Because the output power of the photovoltaic system is a function of the solar irradiation, cell temperature, and characteristics of the photovoltaic array, the analytic solution for obtaining the maximum power is difficult to obtain due to its complexity, nonlinearity, and uncertainties of parameters. The innovation of this work is to obtain the maximum power of the photovoltaic system using a neural network with the idea of transferring the maximum-power-point tracking problem into a proportional-integral current control problem despite the variation in solar irradiation, cell temperature, and the electrical load characteristics. The current controller parameters are determined via a genetic algorithm for finding the controller parameters by the minimization of a complicatedly nonlinear performance index function. The experimental result shows the output power of the photovoltaic system, which consists of the series connection of two 155-W TYN-155S5 modules, is 267.42 W at certain solar irradiation and ambient temperature. From the simulation and experimental results, the validity of the proposed controller was verified.

Maximum Power Point Tracking (MPPT) for a Solar Photovoltaic System: A Review

2015 ◽  
Vol 787 ◽  
pp. 227-232 ◽  
Author(s):  
L.A. Arun Shravan ◽  
D. Ebenezer
Keyword(s):  
Solar Energy ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Nonlinear Behaviour ◽  
Pv System ◽  
Maximum Power Point ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

In recent years there has been a growing attention towards use of solar energy. Advantages of photovoltaic (PV) systems employed for harnessing solar energy are reduction of greenhouse gas emission, low maintenance costs, fewer limitations with regard to site of installation and absence of mechanical noise arising from moving parts. However, PV systems suffer from relatively low conversion efficiency. Therefore, maximum power point tracking (MPPT) for the solar array is essential in a PV system. The nonlinear behaviour of PV systems as well as variations of the maximum power point with solar irradiance level and temperature complicates the tracking of the maximum power point. This paper reviews various MPPT methods based on three categories: offline, online and hybrid methods. Design of a PV system in a encoding environment has also been reviewed here. Furthermore, different MPPT methods are discussed in terms of the dynamic response of the PV system to variations in temperature and irradiance, attainable efficiency, and implementation considerations.

Design and Realization of Solar Energy Maximum Power Point Automatic Tracking System

2013 ◽  
Vol 339 ◽  
pp. 533-538
Author(s):  
Gang Wang
Keyword(s):  
Solar Energy ◽  
Wind Velocity ◽  
Tracking System ◽  
Maximum Power ◽  
Control Mode ◽  
Driving Mechanism ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Energy Maximum ◽  
Power Point

Aiming at the low generating efficiency of the current solar energy generating system, solar energy maximum power point tracking control system based on STC89C52 is designed and made. The photoelectric detection and tracking is adopted as the control mode in the system. By using stepping motor as driving mechanism, comprehensive trace of the sun is realized by controlling the movement of tracking mechanism in the horizontal and pitching directions. Based on this, real-time detection of wind velocity and change of wind direction is realized by wind velocity and direction transducer which is equipped on the tracking mechanism, which makes the system automatically avoid the typhoon above level 8 to weaken the damage to panel by the storm. The experiment results of model machine indicate that the system has reliable performance which can satisfy the need of auto-solar track, it can also make the panel orient towards east again after darkness to realize daily circular run and it is of relatively high practical value.

scholarly journals Multi-Objective Grasshopper Optimization Based MPPT and VSC Control of Grid-Tied PV-Battery System

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2770
Author(s):  
Mukul Chankaya ◽  
Ikhlaq Hussain ◽  
Aijaz Ahmad ◽  
Hasmat Malik ◽  
Fausto Pedro García Márquez
Keyword(s):  
Maximum Power ◽  
Solar Irradiation ◽  
Gaussian Kernel ◽  
Mean Square ◽  
Maximum Power Point ◽  
Dynamic Conditions ◽  
Multi Objective ◽  
Kernel Width ◽  
Dc Bus ◽  
Power Point

This article presents the control of a three-phase three-wire (3P-3W) dual-stage grid-tied PV-battery storage system using a multi-objective grass-hopper optimization (MOGHO) algorithm. The voltage source converter (VSC) control of the presented system is implemented with adaptive kernel width sixth-order maximum correntropy criteria (AKWSOMCC) and maximum power point tracking (MPPT) control is accomplished using the variable step-size incremental conductance (VSS-InC) technique. The proposed VSC control offers lower mean square error and better accuracy, convergence rate and speed as compared to peer adaptive algorithms, i.e., least mean square (LMS), least mean fourth (LMF), maximum correntropy criteria (MCC), etc. The adaptive Gaussian kernel width is a function of the error signal, which changes to accommodate and filter Gaussian and non-Gaussian noise signals in each iteration. The VSS-InC based MPPT is provided with a MOGHO based modulation factor for better and faster tracking of the maximum power point during changing solar irradiation. Similarly, an optimized gain conventional PI controller regulates the DC bus to improve the power quality, and DC link stability during dynamic conditions. The optimized DC-link generates an accurate loss component of current, which further improves the VSC capability of fundamental load current component extraction. The VSC is designed to perform multi-functional operations, i.e., harmonics elimination, reactive power compensation, load balancing and power balancing at point of common coupling during diverse dynamic conditions. The MOSHO based VSS-InC, and DC bus performance is compared to particle swarm optimization (PSO) and genetic algorithm (GA). The proposed system operates satisfactorily as per IEEE519 standards in the MATLAB simulation environment.

scholarly journals Modified Maximum Power Point Tracking Algorithm under Time-Varying Solar Irradiation

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6722
Author(s):  
Mehmet Ali Yildirim ◽  
Marzena Nowak-Ocłoń
Keyword(s):  
Renewable Energy Sources ◽  
Maximum Power Point Tracking ◽  
Average Power ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Time Varying ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Solar photovoltaic (PV) energy is one of the most viable renewable energy sources, considered less polluting than fossil energy. However, the average power conversion efficiency of PV systems is between 15% and 20%, and they must operate with high efficiency. Photovoltaic cells have non-linear voltage–current characteristics that are dependent on environmental factors such as solar irradiation and temperature, and have low efficiency. Therefore, it becomes crucial to harvest the maximum power from PV panels. This paper aims to study and analyze the most common and well-known maximum power point tracking (MPPT) algorithms, perturb and observe (P&O) and incremental conductance (IncCond). These algorithms were found to be easy to implement, low-cost techniques suitable for large- and medium-sized photovoltaic applications. The algorithms were tested and compared dynamically using MATLAB/Simulink software. In order to overcome the low performance of the P&O and IncCond methods under time-varying and fast-changing solar irradiation, several modifications are proposed. Results show an improvement in the tracking and overall system efficiencies and a shortened response time compared with original techniques. In addition, the proposed algorithms minimize the oscillations around the maximum power point (MPP), and the power converges faster.

A Highly Efficient and Adaptable Solar-Energy Harvesting Circuit for Batteryless IoT Devices

2018 ◽  
Author(s):  
Ching-Cheng Yang ◽  
Paul C.-P. Chao ◽  
Rajeev Kumar Pandey
Keyword(s):  
Energy Harvesting ◽  
Solar Energy ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Transfer Efficiency ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Solar Energy Harvesting ◽  
Power Point

In this paper a new on-chip 2nd generation solar energy harvesting DC-DC converter has been proposed for a battery-less Internet of Things (IoTs) Devices. The propose circuit is design to maximize the transfer efficiency and stability as well as enough high power supply to the back-end loads. Altogether the proposed circuit consists of a cross-coupled charge pump, a maximum power point tracking (MPPT) circuit, a timing control circuit and regulator. The range of input voltage is from 0.5V to 3V. Required boosted output voltage is in the range of 1V to 3.3V. The maximum transfer efficiency is more than 60% and the maximum throughout power is 200μW. A gated clock frequency modulation circuit has been designed and employed in the maximum power point tracking (MPPT) unit to lock the input resistance of the charge pump. In addition, to provide a stable voltage to the load a low dropout (LDO) regulator circuit is used. The experimental results show that the maximum power conversion efficiency (PCE) is 78% at 52μW input power condition.

Improvement of the Temperature Parametric (TP) Method for Fast Tracking of Maximum Power Point in Photovoltaic Modules

2019 ◽  
Vol 20 (5) ◽  
Author(s):  
Lahcen El Mentaly ◽  
Abdellah Amghar ◽  
Hassan Sahsah
Keyword(s):  
Maximum Power ◽  
Hill Climbing ◽  
Solar Irradiation ◽  
Operating Voltage ◽  
Maximum Power Point ◽  
New Approach ◽  
Fast Tracking ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Abstract In this work we have presented a generalization of the Temperature Parametric (TP) Method which is based on the detection of the maximum power point by the prediction of the corresponding optimal voltage. This operating voltage is determined by the continuous measurement of the ambient temperature and solar irradiation. This new approach is based on a 3D linear regression model linking these quantities and which allows to our method to realize the maximum power point tracking in real time. The simulation shows that this new technique has a better MPPT efficiency compared to Hill Climbing technique.

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