Photovoltaic (PV) module parameters act an important task in PV system design and simulation. Most popularly used single diode Rsh model has five unknown electrical parameters such as series resistance (Rse), shunt resistance (Rsh), diode quality factor (a), photo-generated current (Ipg) and dark saturation current (Is) in the mathematical model of PV module. The PV module output voltage and current relationship is represented by a transcendental equation and is not possible to solve analytically. This paper proposes nonlinear least square (NLS) technique to extract five unknown parameters. The proposed technique is compared with other two popular techniques available in the literature such as Villalva’s comprehensive technique and modified Newton-Raphson (N-R) technique. Only two parameters Rse and Rsh are estimated by Villalva’s technique, but all single diode unknown electrical parameters can be estimated by the NLS technique. The accuracy of different estimation techniques is compared in terms of absolute percentage errors at MPP and is found the minimum for the proposed technique. The elapsed time for parameter estimation for NLS technique is minimum and much less compared to other two techniques. Extracted parameters of polycrystalline ELDORA-40 PV panel by the proposed technique have been validated through simulation and experimental current-voltage (I-V) and power-voltage (P-V) characteristics.
Use of conventional sources of energy to generate electricity is
increasing rapidly due to growing energy demands. This is a
major cause of pollution as well and also is an environmental
concern for future. Considering this, there is lot of R&D going on in the field of alternate energy sources with recent advancements in technology. One of the most recent advancement is the perovskite solar technology in the photovoltaics industry. The power conversion efficiency of perovskite solar cells has been improved from 9.7 to 20.1% within 4 years which is the fastest advancement ever in the photovoltaic industry. Such a high photovoltaic performance can be attributed to optically high absorption characteristics of the hybrid lead perovskite materials. In this review, different perovskite materials are breifly discussed along with the fundamental details of the hybrid lead halide perovskite materials. The fabrication techniques, stability, device structure and the chemistry of the perovskite structure are also briefly described aiming for a better understanding of these materials and thus highly efficient perovskite solar cell devices. The main focus of this resarch is to understand possible methods to reduce toxicity due to lead and to improve Perovskite stability.
This presentation summarizes history and recent development of perovskite solar cells. If you have any questions or comments, you can reach me at agassifeng@gmail.com
Perovskites-based Solar Cells: The challenge of material choice for p-i-n per...Akinola Oyedele
Perovskite-based PV have triggered widespread interest in the scientific community because these materials offer the attractive combinations of low cost and theoretically high efficiency. However, several challenges must be overcome for these relatively new PV materials. Among the many important challenges, one is the choice of materials to be used in thin film PV devices..
Based on fundamental principles of solar photovoltaics, this problem focuses on two aspects of the perovskite system:
1) Based on a planar p-i-n device structure, a potential list of p- and n-type charge collecting layers as well as the conductive contacts that could be used with a promising perovskite absorber material was identified, and a proper justification for the selection of each material in the device was given.
2) Three theoretical p-i-n type solar cells were made with the chosen materials and appropriate conductive contacts.
Use of conventional sources of energy to generate electricity is
increasing rapidly due to growing energy demands. This is a
major cause of pollution as well and also is an environmental
concern for future. Considering this, there is lot of R&D going on in the field of alternate energy sources with recent advancements in technology. One of the most recent advancement is the perovskite solar technology in the photovoltaics industry. The power conversion efficiency of perovskite solar cells has been improved from 9.7 to 20.1% within 4 years which is the fastest advancement ever in the photovoltaic industry. Such a high photovoltaic performance can be attributed to optically high absorption characteristics of the hybrid lead perovskite materials. In this review, different perovskite materials are breifly discussed along with the fundamental details of the hybrid lead halide perovskite materials. The fabrication techniques, stability, device structure and the chemistry of the perovskite structure are also briefly described aiming for a better understanding of these materials and thus highly efficient perovskite solar cell devices. The main focus of this resarch is to understand possible methods to reduce toxicity due to lead and to improve Perovskite stability.
This presentation summarizes history and recent development of perovskite solar cells. If you have any questions or comments, you can reach me at agassifeng@gmail.com
Perovskites-based Solar Cells: The challenge of material choice for p-i-n per...Akinola Oyedele
Perovskite-based PV have triggered widespread interest in the scientific community because these materials offer the attractive combinations of low cost and theoretically high efficiency. However, several challenges must be overcome for these relatively new PV materials. Among the many important challenges, one is the choice of materials to be used in thin film PV devices..
Based on fundamental principles of solar photovoltaics, this problem focuses on two aspects of the perovskite system:
1) Based on a planar p-i-n device structure, a potential list of p- and n-type charge collecting layers as well as the conductive contacts that could be used with a promising perovskite absorber material was identified, and a proper justification for the selection of each material in the device was given.
2) Three theoretical p-i-n type solar cells were made with the chosen materials and appropriate conductive contacts.
Perovskite Solar Cells
a short general overview presentation
hadi maghsoudi
device structure
crystal structure
preparation synthesis method
review papers
A DFT & TDDFT Study of Hybrid Halide Perovskite Quantum DotsAthanasiosKoliogiorg
Perovskite quantum dots (QDs) constitute a novel and rapidly developing field of nanotechnology with promising potential for optoelectronic applications. However, few perovskite materials for QDs and other nanostructures have been theoretically explored. In this study, we present a wide spectrum of different hybrid halide perovskite cuboid-like QDs with the general formula of FABX3 (A = (NH2)CH(NH2), B = Pb, Sn, Ge, and X = Cl, Br, I) with varying sizes below and near the Bohr exciton radius. Density functional theory (DFT) and time-dependent DFT calculations were employed to determine their structural, electronic, and optical properties. Our calculations include both stoichiometric model, proved to be close to experimental results where available, and our results reveal several materials with high optical absorption and application-suitable electronic and optical gaps. Our study highlights the potential as well as the challenges and issues regarding nanostructured halide perovskite materials, laying the background for future theoretical and experimental work.
In times of fossil fuel shortage, increasing crude oil prices, as well as rejection of conventional energy sources (e.g. coal or nuclear power plants), sustainable energy forms become more and more the focus of attentions. Hydropower, wind power, geothermal power, or biomass processing are but a few of these sustainable resources.
Another important source for renewable energy is solar power. Photovoltaics and solar thermal collectors are most widely used.
Dye solar cells (DSCs) which are discussed in this application note are thin film cells. They are also called dye sensitized solar cells (DSSC) or Grätzel cells named after the Swiss chemist Michael Grätzel who was greatly involved in the development of new cell types.
Advantages and problems of perovskite solar cellalfachemistry
This article mainly introduces the advantages and problems of perovskite solar cell. Visit https://www.alfa-chemistry.com/products/perovskite-solar-cells-139.htm for more information.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
Different Generation Solar Cells
CIGS and CZTS Based Technology
Ink Based Technology
CIGS Device Structure
Making more efficient solar cells
Developing thin film technologies using alternative less costly materials and methods
Incorporate innovative cheaper deposition methods such as electrodeposition and printing technology
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This paper propose a new approach to determine a linear mathematical model of a PV moduel based on an accurate nonlinear model . In this study, electrical parameters at only one operating condition are calculated based on an accurate model. Then, first-order Taylor series approximations apply on the nonlinear model to estimate the proposed model at any operating conditionts. The proposed method determines the number of iteration times. This decreases calculation time and the speed of numerical convergence will be increased. And, it is observed that owing to this method, the system converged and the problem of failing to solve the system because of inappropriate initial values is eliminated. The proposed model is requested in order to allow photovoltaic plants simulations using low-cost computer platforms. The effectiveness of the proposed model is demonstrated for different temperature and irradiance values through conducting a comparison between result of the proposed model and experimental results obtained from the module data-sheet information.
Perovskite Solar Cells
a short general overview presentation
hadi maghsoudi
device structure
crystal structure
preparation synthesis method
review papers
A DFT & TDDFT Study of Hybrid Halide Perovskite Quantum DotsAthanasiosKoliogiorg
Perovskite quantum dots (QDs) constitute a novel and rapidly developing field of nanotechnology with promising potential for optoelectronic applications. However, few perovskite materials for QDs and other nanostructures have been theoretically explored. In this study, we present a wide spectrum of different hybrid halide perovskite cuboid-like QDs with the general formula of FABX3 (A = (NH2)CH(NH2), B = Pb, Sn, Ge, and X = Cl, Br, I) with varying sizes below and near the Bohr exciton radius. Density functional theory (DFT) and time-dependent DFT calculations were employed to determine their structural, electronic, and optical properties. Our calculations include both stoichiometric model, proved to be close to experimental results where available, and our results reveal several materials with high optical absorption and application-suitable electronic and optical gaps. Our study highlights the potential as well as the challenges and issues regarding nanostructured halide perovskite materials, laying the background for future theoretical and experimental work.
In times of fossil fuel shortage, increasing crude oil prices, as well as rejection of conventional energy sources (e.g. coal or nuclear power plants), sustainable energy forms become more and more the focus of attentions. Hydropower, wind power, geothermal power, or biomass processing are but a few of these sustainable resources.
Another important source for renewable energy is solar power. Photovoltaics and solar thermal collectors are most widely used.
Dye solar cells (DSCs) which are discussed in this application note are thin film cells. They are also called dye sensitized solar cells (DSSC) or Grätzel cells named after the Swiss chemist Michael Grätzel who was greatly involved in the development of new cell types.
Advantages and problems of perovskite solar cellalfachemistry
This article mainly introduces the advantages and problems of perovskite solar cell. Visit https://www.alfa-chemistry.com/products/perovskite-solar-cells-139.htm for more information.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
Different Generation Solar Cells
CIGS and CZTS Based Technology
Ink Based Technology
CIGS Device Structure
Making more efficient solar cells
Developing thin film technologies using alternative less costly materials and methods
Incorporate innovative cheaper deposition methods such as electrodeposition and printing technology
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This paper propose a new approach to determine a linear mathematical model of a PV moduel based on an accurate nonlinear model . In this study, electrical parameters at only one operating condition are calculated based on an accurate model. Then, first-order Taylor series approximations apply on the nonlinear model to estimate the proposed model at any operating conditionts. The proposed method determines the number of iteration times. This decreases calculation time and the speed of numerical convergence will be increased. And, it is observed that owing to this method, the system converged and the problem of failing to solve the system because of inappropriate initial values is eliminated. The proposed model is requested in order to allow photovoltaic plants simulations using low-cost computer platforms. The effectiveness of the proposed model is demonstrated for different temperature and irradiance values through conducting a comparison between result of the proposed model and experimental results obtained from the module data-sheet information.
Modeling and Simulation of Solar Photovoltaic module using Matlab/SimulinkIOSR Journals
Abstract: This paper presents the circuit model of photovoltaic (PV) module. Simulation and modeling is done
using MATLAB/ Simulink software package. The proposed model is user friendly and can be used as a common
platform for both applied physics scientist and power electronics engineers. A detailed modeling procedure is
presented. The designed model is verified by using STP255-20/Wd PV module. The IV and PV characteristics
are simulated at different temperature and irradiance conditions and the results are verified. The proposed
model is very simple fast and accurate. The designed model can be used for analysis of PV characteristics and
for simulation of maximum power point tracking algorithms
SINGLE-DIODE AND TWO-DIODE PV CELL MODELING USING MATLAB FOR STUDYING CHARACT...ecij
This paper presents a detailed eplaination about various characteristics of ideal single diode, practical single diode and two diode equivalent circuit models realized for modeling of solar photovoltaic cell. Then it presents non-linear mathematical equations necessary for producing I-V and P-V characteristics from a single diode model. A flowchart has been made for estimation of solar cell output current, for single diode and two diode model, using Newton-Raphson iterative technique which is then programmed in MATLAB script file accordingly. A typical 120W polycrystalline solar module specifications have been used for model accuracy evaluation. The characteristic curves were obtained with the use of manufacturer`s datasheet and it shows the precise correspondence to both the models.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Simulation Model for PV Array & Its CharacteristicsIJEEE
This paper presents the implementation of a photovoltaic model using Matlab software, which can be representative of PV cell module, and array for easy use on simulation. The proposed model is designed with a user-friendly icon and a dialog box like Simulink block libraries. This makes the PV model easily simulated and analyzed in conjunction with power electronics for a maximum power point tracker.
Modeling Simulation and Design of Photovoltaic Array with MPPT Control Techni...IJAPEJOURNAL
The Renewable energy is important part of power generation system due to diminution of fossils fuel. Energy production from photovoltaic (PV) is widely accepted as it is clean, available in abundance, & free of cost. This paper deals with modeling of PV array including the effects of temperature and irradiation. The DC-DC converter is used for boosting low voltage of the PV array to high DC voltage. Since the efficiency of a PV array is around 13% which is low, it is desirable to operate the module at the peak power point to improve the utilization of the PV array. A maximum power point tracker (MPPT) is used for extracting the maximum power from the solar PV array and transferring that power to the load. To track maximum power point (MPP) Perturb & Observe (P & O) algorithm is used which periodically perturbs the array voltage or current and compare PV output power with that of previous perturbation cycle which controls duty cycle of DC-DC converter. The entire system is simulated in MATLAB /SIMULINK and simulation results are presented.
This project proposes a simplified PV module simulator with MPPT. The PV model is designed in Matlab/Simulink based on various mathematical equations. This paper explains the use of MPPT technique in a photovoltaic system. The MPPT is implemented by incremental conductance or perturbation and observation methods. The overall system is designed, developed and validated by using MATLAB/SIMULINK
In this paper, modeling and simulation of the solar photo-voltaic (PV) power generator is observed using Matlab-Simulink environment. The study the fore-mentioned photovoltaic systems in an efficient manner the knowledge of I-V and P-V characteristics is a prerequisite. Effect of environmental parameters of temperature and irradiance variations could also be observed from simulated characteristics.
Modeling and Simulation of Fuzzy Logic based Maximum Power Point Tracking (MP...IJECEIAES
This paper presents modeling and simulation of maximum power point tracking (MPPT) used in solar PV power systems. The Fuzzy logic algorithm is used to minimize the error between the actual power and the estimated maximum power. The simulation model was developed and tested to investigate the effectiveness of the proposed MPPT controller. MATLAB Simulink was employed for simulation studies. The proposed system was simulated and tested successfully on a photovoltaic solar panel model. The Fuzzy logic algorithm succesfully tracking the MPPs and performs precise control under rapidly changing atmospheric conditions. Simulation results indicate the feasibility and improved functionality of the system.
Incremental Conductance MPPT Algorithm for PV System Implemented Using DC-DC ...IJERA Editor
The two basic topologies of switch mode DC-DC converters (Buck and Boost) are analyzed with a view of their use in PV (photovoltaic) systems, as the photovoltaic generator exhibits non-linear characteristics due to the change in environmental condition and load variation. As the efficiency of PV panels is low it becomes mandatory to extract maximum power from the PV panel at a given period of time. Several MPPT algorithms with different types of converters are being proposed for extracting maximum power from the PV panel. It is found that the nature of load plays an important role in the choice of topology. This paper investigates the implementation issues of Incremental Conductance method with Buck and Boost Converters. Mathematical analysis and desirable steady-state operating point of the converters are derived to give satisfactory maximum power point tracking operation.
Parametric estimation in photovoltaic modules using the crow search algorithmIJECEIAES
The problem of parametric estimation in photovoltaic (PV) modules considering man- ufacturer information is addressed in this research from the perspective of combinatorial optimization. With the data sheet provided by the PV manufacturer, a non-linear non-convex optimization problem is formulated that contains information regarding maximum power, open-circuit, and short-circuit points. To estimate the three parameters of the PV model (i.e., the ideality diode factor (a) and the parallel and series resistances (R p and R )), the crow search algorithm (CSA) is employed, which is a metaheuristic optimization technique inspired by the behavior of the crows searching food deposits. The CSA allows the exploration and exploitation of the solution space through a simple evolution rule derived from the classical PSO method. Numerical simulations reveal the effectiveness and robustness of the CSA to estimate these parameters with objective function values lower than 1 10 s 28 and processing times less than 2 s. All the numerical simulations were developed in MATLAB 2020a and compared with the sine-cosine and vortex search algorithms recently reported in the literature.
New Structure for Photovoltaic SystemApplications with Maximum Power Point Tr...IAES-IJPEDS
This paper recommendes a new structure for photovoltaicsystems with a new inverter topology. A quasi-Z-source DC-DC converter with capability of dividing its output voltage to the same voltages and tracking maximum power point is proposed. The proportional-integral incremental conductance method is used for maximum power point tracking. The new recommended inverter topology is linked to quasi-Z-source converter for transferring power. For triggering inverter switches, alternate phase opposition disposition switching technique is utilized. A comparison is drawn between suggested multilevel inverter topology and other conventional multilevel inverter topologies. Description of proposed structure along with detailed simulation results that verify its feasibility are given to demonstrate the availability of the proposed system by MATLAB/Simulink software.
Improving efficiency of Photovoltaic System with Neural Network Based MPPT Co...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
Similar to Parameter Extraction of PV Module using NLS Algorithm with Experimental Validation (20)
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
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Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
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Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Final project report on grocery store management system..pdfKamal Acharya
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Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
2. IJECE ISSN: 2088-8708
Parameter Extraction of PV Module using NLS Algorithm with Experimental Validation (Alivarani
Mohapatra)
2393
power system, both PV panels and converters exhibit nonlinear and time-varying characteristics, which
result in challenging control problem [9], [10].
The arithmetical model of a PV panel is vital to know which is coupled to a power converter in a
PV system [11]. Unluckily all model parameters are not on hand in the data sheet provided by the
manufacturer. Manufacturer datasheet only provide few parameters like open circuit voltage (Voc,n), Short
circuit current (Isc,n), voltage and current at maximum power point (Vmpp,n, Impp,n), temperature coefficients
for voltage (Kv), current (KI) and power (Kp) at standard test condition (STC). STC refers to irradiation of
1000 W/m2
and temperature of 25◦
C. Therefore it is essential to estimate unknown parameters to model a
PV system accurately [12]. Different models of the PV module are classified as an ideal model, single diode
four parameters model and single diode five parameters model [13]. The most commonly used model is the
single diode five parameters model as shown in Figure 1. It has five unknown parameters as photo-
generated current (Ipg), saturation current (Is), diode quality factor (a), series resistance (Rse) and shunt
resistance (Rsh). According to the semiconductor theory, diode D represents the p-n junction of the PV
module and current Id stands for the escaping current through the p-n junction due to the diffusion
mechanism. Series resistance (Rse) represents the losses due to contact resistance and shunt resistance (Rsh)
represents the leakage current at the p-n junction of the PV module. There are different parameter extraction
techniques are available in literature with their merits and demerits [14]–[20]. In this paper, unknown
parameters are estimated by nonlinear least square (NLS) technique and experimentally validated with a
laboratory set up. The NLS technique is also compared with two known techniques such as Villalva’s
comprehensive technique and modified Newton-Raphson (N-R) technique [3], [21], [22]. The superiority of
the proposed NLS technique is established by comparing the absolute error of maximum power.
2. MODELLING OF PV PANEL
The current voltage relationship of a PV panel is expressed as:[14]
pv se pv pv se pv
pv pg s
s t sh
V R I V R I
I I -I exp 1
N V a R
(1)
Rse
Ipg
Id
Rsh
+
-
Ipv
Vpv
D
Figure 1.Popular Rsh model of PV panel
Vpv and Ipv represent the module output voltage and current respectively, and Vt is the thermal
voltage of the p-n junction The electrical properties of the PV panel depend upon the environmental factor
like solar insolation and temperature [23]. The dependency of photo-generated current and open-circuit
voltage of the PV module is represented by equations:
pg pg,n I
n
G
I I K dt
G
(2)
oc oc,n vV V K dt (3)
Where, Ipg,n and Voc,n are measured at a nominal condition of the temperature of 25o
C and irradiation
of 1000 W/m2
. The temperature difference (dt=T-Tn) is a difference between nominal and actual
temperature. G is the insolation at operating condition, and Gn is insolation at nominal condition. The
saturation current of the PV module at a particular environmental condition is represented by equation (4)
[3].
sc,n I
s
oc,n v
s t
I K dt
I
V K dt
exp 1
N V a
(4)
3. ISSN: 2088-8708
IJECE Vol. 7, No. 5, October 2017 : 2392 – 2400
2394
Figure 2. I-V curve of ELDORA-40 PV panel and its three remarkable points
The simulated current-voltage (I-V) characteristic of the test module at STC is shown if Figure 2 with its
three remarkable points as Isc, Voc and Pmpp. Power extraction from the PV panel will be maximum when the
module is operated at its MPP.
3. EXTRACTION OF PV MODULE PARAMETERS
Construction of exact PV model is possible if all the electrical parameters of the module are to be
extracted accurately. Here an attempt has been taken to extract the model parameters accurately using only
the parameters of the manufacturer datasheet without any measurement. Three methods are discussed here
with their merits and demerits.
3.1. Starting of the methods
To estimate five unknown parameters, five equations whose dependencies upon the unknown
parameters is needed. Rewriting equation (1) at three remarkable points as short-circuit, open-circuit and
MPP gives three equations as (5), (6) and (7) respectively [22].
se sc se sc
sc pg s
s t sh
R I R I
I I -I exp 1
N V a R
(5)
oc oc
pg s
s t sh
V V
I =I exp 1
N V a R
(6)
mpp se m pp mpp se m pp
m pp pg s
s t sh
V R I V R I
I I I exp 1
N V a R
(7)
Two more equations are needed for solving five parameters model. Another two equations can be considered
knowing the fact that mpp
dP
V V 0
dV
and sc
sh
dI 1
I I
dV R
mpp se mpps
s t s t sh
mpp mpp
mpp se mppse s se
s t s t sh
V R II 1
exp
N V a N V a R
I V
V R IR I R
1 exp
N V a N V a R
(8)
s se sc
s t s t sh
sh se s se sc se
s t s t sh
I R I 1
exp
N V a N V a R1
R R I R I R
1 exp
N V a N V a R
(9)
0 5 10 15 20
0
0.5
1
1.5
2
2.5
Voltage (V)
Current(A)
Voltage
Source
region
Power region
Current Source region
MPPI
sc
V
oc
4. IJECE ISSN: 2088-8708
Parameter Extraction of PV Module using NLS Algorithm with Experimental Validation (Alivarani
Mohapatra)
2395
Some literature uses oc
se
dI 1
V V
dV R
as one equation but it has some disadvantages as discussed in
[24]. Now five equations are available to extract five unknown parameters using equations (5)-(9). Further
improving the model the photo generated current may be written as equation (10) by neglecting saturation
current sI in (5). Rsh,min as given in equation (11) represents the minimum value of Rsh taken as initial value
of parallel resistance [3].
sh se
pg,n sc,n
sh
R R
I I
R
(10)
mpp oc mpp
sh,min
sc mpp mpp
V V V
R
I I I
(11)
3.2. Review of Villalva’s iterative technique and mocified N-R technique
3.2.1. Villalva’s iterative technique
This method intends to adjust Rse and Rsh values such that with one pair of {Rse, Rsh}, the maximum
power as given in the datasheet (Pmpp,curve= Vmpp*Impp) must be equal to Pmpp, model. The iterative method
begins with Rse=0 and Rsh= Rsh,min. The adjustment of Rse and Rsh continues until Pmpp,curve= Pmpp,model.solving
(12). Figure 3 represents the flow diagram of Villalva’s technique. The main drawback of this technique is
that the diode quality factor ‘a’ chosen arbitrarily between1 a 2 before iteration starts. Only two
parameters Rse and Rsh are extracted by this method and Ipg and Is values are calculated as per equation (2),
(10) and (4). The extracted parameter values highly dependent on chosen tolerance and increment on Rse
value in the parameter extraction process.
mpp mpp se mpp
sh
mpp se mpp
mpp pg mpp s mpp s
s t
V V R I
R
V R I
V I V I exp V I Pmax,model
N V a
(12)
Inputs :datasheet parameters,
T,G,a=1.5,Rse=0,Rsh=Rsh,min,Eq(11)
Set, tol=e-5, ɛpmax>tol
ɛpmax>tol ?
Y
for 0 ≤V≤Voc,n
Solve Eq. (1),(2),(4),(10), (12)
Calculate P=V*I
Find Pmax,model
Calculate
Ɛpmax=║Pmax,model-Pmax,curve║
Increment Rse
Display Rse,
Rsh
N
Figure 3. Flow diagram for Villalva’s iterative method
3.2.2. Modified N-R technique
To mitigate slow convergence of N-R technique, the modified N-R technique has been developed to
solve nonlinear equations with multiple roots. This technique is utilized for estimation of unknown
5. ISSN: 2088-8708
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2396
parameters X=[Rse, Rsh, a. Ipg, Is] by considering five nonlinear equations (5)-(9) using fsolve command in
MATLAB. Chosen initial parameters play a vital role in accurate estimation of parameters.
4. PROPOSED NLS TECHNIQUE
4.1. Starting of the technique
To estimate unknown parameters of the polycrystalline Eldora-40 PV test module, equations (5)-(9) rewritten
as [21].
se sc se sc
1 pg s sc
s t sh
R I R I
0 I I 1 I
N V a R
f x exp
(13)
s
sh
oc oc
pg
s t
V V
0 I 1 I
N V a R
2f x exp
(14)
mpp se mpp mpp se mpp
pg mpp
s t
s
sh
V R I V R I
0 I I 1 I
N V a R
3f x exp
(15)
mpp mpp
s t s t
mpp mpp
mpp se mppse se
s t s
ses
sh
t
s
sh
V II 1
N aV N aV R
0 V I
V R IR I R
1
N aV N aV
R
R
4
exp
f x
exp
(16)
se sc
s t s t sh
se se sc se
s t s t s
s
sh
h
s
I R I 1
N aV N V a R 1
0
RR I R I R
1
N aV N V a R
5
exp
f x
exp
(17)
To reduce the computational complication and for reduction of iterations, NLS algorithm modifies
multi-objective function to a single objective function. The initial parameter values, lower and upper limit
constraints are chosen with its physical significance. The flow algorithm for NLS technique used for
estimation of unknown parameters is shown in Figure 4. To solve five nonlinear equations by this approach,
lsqnonlin command in MATLAB is used. The objective function f(x) is chosen as
2 2 2 2 2
x 1 2 3 4 5min f(x) f (x) f (x) f (x) f (x) f (x) considering upper and lower limit constraints.
4.2. Initialization
Since the accuracy of estimation depends very well upon the initial parameter values, an intelligent
estimate of initial condition is very much essential for the solution to converge to the solution. From the
available literature [3][25] the initial values of different parameters are as follows.
Ipg could be approximated by Isc.
Is is determined using equation (4).
Quality factor ‘a’ of the diode is chosen as1 a 2 .
Rsh is a large value approximated according to (11).
Rse is very small taken as 0, or in the range of milliohms.
In most cases, convergence occurs with the aforementioned initialization. If it fails, initialization
needs to be done randomly considering the range of each parameter values. The lower and upper bound of
search must be chosen carefully, keeping in mind the minimum and maximum values of the parameters.
5. RESULTS AND DISCUSSION
Unknown parameters are estimated by NLS technique and obtained results are compared with two
popular techniques like Villalva’s comprehensive technique and modified N-R technique. Module
6. IJECE ISSN: 2088-8708
Parameter Extraction of PV Module using NLS Algorithm with Experimental Validation (Alivarani
Mohapatra)
2397
characteristics are drawn at STC and compared as shown in Figure 5 and Figure 6. Extracted parameter
values are validated by conducting experiment on ELDORA-40 PV panel. Figure 5 (a) shows the I-V
characteristic of the ELDORA-40 PV panel and the result shows the characteristics match the datasheet
remarkable points such as, Isc, Voc, Vmpp, and Impp. Similarly Figure 5 (b) shows the P-V characteristics of the
ELDORA-40 PV panel and result shows the good agreement between the datasheet curve and simulated
curve using the extracted parameters. Table1 represents the datasheet of the test module at STC.
Start
Inputs: datasheet parameters
Initialize the unknown parameters,
Set lower and upper bounds of the
unknown parameters
Solve system of nonlinear equations:
Eqs.(13)-(17)
Function converge
to a solution?
Y
Output:
Rse,Rsh,a,Ipg,Is
N
End
Figure 4. Fowchart for nonlinear least square method of parameter extraction
Table 1. Datasheet of the test module ELDORA-40 at STC
Voc,n(V) Isc,n(A) Vmpp,n(V) Impp,n(A) Ns Kv(V/o
C) KI(A/o
C)
21.8 2.4 17.2 2.20 36 -0.32% 0.04%
Table 2. Comparison of extracted parameters of the test module at STC
Parameters Villalva’s technique
(Method-A)
Modified N-R technique
(Method-B)
NLS technique
(Method-C)
Rse ( Ω) 0.493 0.53 0.58
Rsh (Ω) 939.35 466.31 704.24
a 1.5 (fixed) 1.41 1.4
Ipg (A) 2.4 2.402 2.4
Is (A) 3.62e-7 1.1e-7 1.1e-7
Time of computation (S) 3.8 1.2 0.34
Absolute error of maximum power in % 0.43 0.24 0.07
The extracted parameter values are tabulated in Table 2 for ELDORA-40 PV module defined at
STC. The extracted parameter values are compared and it is seen that parameter values are in good agreement
with the datasheet characteristics. The absolute error of maximum power is calculated and seen that it is
minimum for NLS technique. The time of computation for parameter extraction is less in NLS technique as
compared to other two techniques.
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2398
(a)
(b)
Figure 5. (a) I-V (b) P-V characteristic of the test module at STC
5.1. Validation of the model
To validate the extracted parameter values, the characteristic curve of ELDORA-40 PV panel has
been drawn using the extracted parameter values. The test setup is placed inside the laboratory, and artificial
irradiation is used with the help of halogen light as shown in Figure 6. The current and voltage values are
measured from zero load to full load condition at 25◦
C of temperature and 220W/m2
of irradiation. Parameters
extracted by NLS method has been used for simulation of the P-V and I-V curves of the PV panel at the
above mentioned temperature and irradiation. Figure.7 (a) and Figure 7 (b) shows good agreement between
the simulated and experimental characteristics, using the parameters extracted by the proposed NLS method.
The absolute percentage error of maximum power is calculated and is found less than one percent. The I-V
characteristic shown in Figure 7 (a) shows the simulated and experimental curve matching at almost all
points including the three remarkable points. Similarly, P-V characteristics shown in Figure 7 (b) also show
good agreement between simulated and experimental results.
Figure 6. Test set-up of ELDORA-40 PV panel
8. IJECE ISSN: 2088-8708
Parameter Extraction of PV Module using NLS Algorithm with Experimental Validation (Alivarani
Mohapatra)
2399
(a)
(b)
Figure 7. (a) I-V (b) P-V characteristic of the test module using the parameters extracted by NLS technique
6. CONCLUSION
In this paper, NLS technique is proposed for parameter extraction of PV module and is compared
with other two well known techniques. All five unknown parameters of ELDORA-40 PV module extracted
using three different techniques and compared. The characteristics of the PV module show that proposed
NLS technique gives the best result with less computational complication compared to other two techniques.
It is seen that the proposed technique not only give good results at STC but also at other temperature and
irradiation. The absolute error of maximum power is compared with all the techniques and it is observed that
the value is very less for NLS technique. The absolute error of maximum power is also calculated taking the
experimental characteristics and simulated one at a temperature of 25o
C and irradiation of 220 W/m2
and it is
found less than one percent. From the experimental results, it is observed that the unknown parameter
extracted by the proposed NLS technique is correct and it validates the characteristic of the datasheet at all
the three remarkable points with less error.
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