scholarly journals A Density Peak-Based Clustering Approach for Fault Diagnosis of Photovoltaic Arrays

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Peijie Lin ◽  
Yaohai Lin ◽  
Zhicong Chen ◽  
Lijun Wu ◽  
Lingchen Chen ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Local Density ◽  
Operating Conditions ◽  
Cluster Center ◽  
Pv System ◽  
Density Peak ◽  
Pv Systems ◽  
Distribution Features ◽  
Clustering Approach ◽  
Distance Vector

Fault diagnosis of photovoltaic (PV) arrays plays a significant role in safe and reliable operation of PV systems. In this paper, the distribution of the PV systems’ daily operating data under different operating conditions is analyzed. The results show that the data distribution features significant nonspherical clustering, the cluster center has a relatively large distance from any points with a higher local density, and the cluster number cannot be predetermined. Based on these features, a density peak-based clustering approach is then proposed to automatically cluster the PV data. And then, a set of labeled data with various conditions are employed to compute the minimum distance vector between each cluster and the reference data. According to the distance vector, the clusters can be identified and categorized into various conditions and/or faults. Simulation results demonstrate the feasibility of the proposed method in the diagnosis of certain faults occurring in a PV array. Moreover, a 1.8 kW grid-connected PV system with6×3 PVarray is established and experimentally tested to investigate the performance of the developed method.

scholarly journals Fault diagnosis with states estimation in PV systems

2021 ◽  
Author(s):  
Ramiro Alejandro Plazas Rosas ◽  
Édinson Franco Mejia ◽  
Martha Lucía Orozco Gutiérrez
Keyword(s):  
Fault Diagnosis ◽  
Electricity Generation ◽  
Power Converter ◽  
Operating Conditions ◽  
Photovoltaic Systems ◽  
Pv System ◽  
Interconnected System ◽  
Pv Systems ◽  
A Cell ◽  
Mechanical Elements

The photovoltaic systems are electrical, electronic, and mechanical elements. These systems also face different environmental and operating conditions susceptible to failure. In addition, photovoltaic systems can be the only source of electricity generation, and an affectation on the energy supply can harm the community. In many places, photovoltaic systems are the only source of energy because they are not part of what is known in Colombia as the National Interconnected System (SIN). Which comprises the direct connection between large generators (hydroelectric and/or thermal plants) and consumers. In fact, PV system damage would affect food refrigeration or everyday things like charging a cell phone. Therefore, it is necessary to register, monitor the operation elements of PV systems, and develop strategies that allow the diagnosis to detect faults. In this work, we propose a fault-diagnosis using the PV systems measurements that is, power converter, photovoltaic panels with also mathematical models to determine the deviation between the estimated and measured signals as voltages and currents.

scholarly journals Different Techniques to Mitigate Partial Shading in Photovoltaic Panels

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3863
Author(s):  
Tiago Alves ◽  
João Paulo N. Torres ◽  
Ricardo A. Marques Lameirinhas ◽  
Carlos A. F. Fernandes
Keyword(s):  
Cell Model ◽  
Research Work ◽  
Experimental Tests ◽  
Operating Conditions ◽  
Pv System ◽  
Partial Shading ◽  
System Architectures ◽  
Pv Systems ◽  
Advantages And Disadvantages ◽  
Pv Panel

The effect of partial shading in photovoltaic (PV) panels is one of the biggest problems regarding power losses in PV systems. When the irradiance pattern throughout a PV panel is inequal, some cells with the possibility of higher power production will produce less and start to deteriorate. The objective of this research work is to present, test and discuss different techniques to help mitigate partial shading in PV panels, observing and commenting the advantages and disadvantages for different PV technologies under different operating conditions. The motivation is to contribute with research, simulation, and experimental work. Several state-of-the-artsolutions to the problem will be presented: different topologies in the interconnection of the panels; different PV system architectures, and also introducing new solution hypotheses, such as different cell interconnections topologies. Alongside, benefits and limitations will be discussed. To obtain actual results, the simulation work was conducted by creating MATLAB/Simulink models for each different technique tested, all centered around the 1M5P PV cell model. The several techniques tested will also take into account different patterns and sizes of partial shading, different PV panel technologies, different values of source irradiation, and different PV array sizes. The results will be discussed and validated by experimental tests.

scholarly journals Nonlinear Robust Backstepping Control for Three-Phase Grid-Connected PV Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Mohamed Habib Boujmil ◽  
Afef Badis ◽  
Mohamed Nejib Mansouri
Keyword(s):  
Control Strategy ◽  
Control Structure ◽  
Control Process ◽  
Backstepping Control ◽  
Operating Conditions ◽  
Cascade Control ◽  
Control Technique ◽  
Pv System ◽  
Pv Systems ◽  
Three Phase

This paper proposes a cascade control structure for three-phase grid-connected Photovoltaic (PV) systems. The PV system consists of a PV Generator, DC/DC converter, a DC link, a DC/AC fully controlled inverter, and the main grid. For the control process, a new control strategy using nonlinear Backstepping technique is developed. This strategy comprises three targets, namely, DC/DC converter control; tight control of the DC link voltage; and delivering the desired output power to the active grid with unity power factor (PF). Moreover, the control process relies mainly on the formulation of stability based on Lyapunov functions. Maximizing the energy reproduced from a solar power generation system is investigated as well by using the Perturb and Observe (P&O) algorithm. The Energetic Macroscopic Representation (EMR) and its reverse Maximum Control Structure (MCS) are used to provide, respectively, an instantaneous average model and a cascade control structure. The robust proposed control strategy adapts well to the cascade control technique. Simulations have been conducted using Matlab/Simulink software in order to illustrate the validity and robustness of the proposed technique under different operating conditions, namely, abrupt changing weather condition, sudden parametric variations, and voltage dips, and when facing measurement uncertainties. The problem of controlling the grid-connected PV system is addressed and dealt by using the nonlinear Backstepping control.

scholarly journals Comparison of Different MPPT Algorithms with a Proposed One Using a Power Estimator for Grid Connected PV Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Manel Hlaili ◽  
Hfaiedh Mechergui
Keyword(s):  
Operating Conditions ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Correct Operation ◽  
Pv Systems ◽  
Wide Range ◽  
Energy Conversion Systems ◽  
Simulation Results ◽  
Power Point

Photovoltaic (PV) energy is one of the most important energy sources since it is clean and inexhaustible. It is important to operate PV energy conversion systems in the maximum power point (MPP) to maximize the output energy of PV arrays. An MPPT control is necessary to extract maximum power from the PV arrays. In recent years, a large number of techniques have been proposed for tracking the maximum power point. This paper presents a comparison of different MPPT methods and proposes one which used a power estimator and also analyses their suitability for systems which experience a wide range of operating conditions. The classic analysed methods, the incremental conductance (IncCond), perturbation and observation (P&O), ripple correlation (RC) algorithms, are suitable and practical. Simulation results of a single phase NPC grid connected PV system operating with the aforementioned methods are presented to confirm effectiveness of the scheme and algorithms. Simulation results verify the correct operation of the different MPPT and the proposed algorithm.

scholarly journals PV Systems Control Using Fuzzy Logic Controller Employing Dynamic Safety Margin under Normal and Partial Shading Conditions

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 841 ◽  
Author(s):  
Mostafa Bakkar ◽  
Ahmed Aboelhassan ◽  
Mostafa Abdelgeliel ◽  
Michael Galea
Keyword(s):  
Fuzzy Logic ◽  
Performance Index ◽  
Safety Margin ◽  
Operating Conditions ◽  
Maximum Power ◽  
Practical Implementation ◽  
Pv System ◽  
Partial Shading ◽  
Pv Systems ◽  
A Performance

Because of the unpredictable activity of solar energy sources, photovoltaic (PV) maximum power point tracking (MPPT) is essential to guarantee the continuous operation of electrical energy generation at optimal power levels. Several works have extensively examined the generation of the maximum power from the PV systems under normal and shading conditions. The fuzzy logic control (FLC) method is one of the effective MPPT techniques, but it needs to be adapted to work in partial shading conditions. The current paper presents the FLC-based on dynamic safety margin (DSM) as an MPPT technique for a PV system to overcome the limitations of FLC in shading conditions. The DSM is a performance index that measures the system state deviation from the normal situation. As a performance index, DSM is used to adapt the FLC controller output to rapidly reach the global maxima of the PV system. The ability of the proposed algorithm and its performance are evaluated using simulation and practical implementation results for single phase grid-connected PV system under normal and partial shading operating conditions.

scholarly journals Intelligent PV Panels Fault Diagnosis Method Based on NARX Network and Linguistic Fuzzy Rule-Based Systems

2020 ◽  
Vol 12 (5) ◽  
pp. 2011 ◽  
Author(s):  
Sufyan Samara ◽  
Emad Natsheh
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Output Power ◽  
Fuzzy Inference ◽  
Maximum Power ◽  
Pv System ◽  
Artificial Intelligent ◽  
Pv Systems ◽  
System Output ◽  
Diagnosis Algorithm

The expanding use of photovoltaic (PV) systems as an alternative green source for electricity presents many challenges, one of which is the timely diagnosis of faults to maintain the quality and high productivity of such systems. In recent years, various studies have been conducted on the fault diagnosis of PV systems. However, very few instances of fault diagnostic techniques could be implemented on integrated circuits, and these techniques require costly and complex hardware. This work presents a novel and effective, yet small and implementable, fault diagnosis algorithm based on an artificial intelligent nonlinear autoregressive exogenous (NARX) neural network and Sugeno fuzzy inference. The algorithm uses Sugeno fuzzy inference to isolate and classify faults that may occur in a PV system. The fuzzy inference requires the actual sensed PV system output power, the predicted PV system output power, and the sensed surrounding conditions. An artificial intelligent NARX-based neural network is used to obtain the predicted PV system output power. The actual output power of the PV system and the surrounding conditions are obtained in real-time using sensors. The algorithm is proven to be implementable on a low-cost microcontroller. The obtained results indicate that the fault diagnosis algorithm can detect multiple faults such as open and short circuit degradation, faulty maximum power point tracking (MPPT), and conditions of partial shading (PS) that may affect the PV system. Moreover, radiation and temperature, among other non-linear associations of patterns between predictors, can be captured by the proposed algorithm to determine the accurate point of the maximum power for the PV system.

RBF-trained POD-accelerated CFD analysis of wind loads on PV systems

2017 ◽  
Vol 27 (3) ◽  
pp. 660-673 ◽  
Author(s):  
Victor Huayamave ◽  
Andres Ceballos ◽  
Carolina Barriento ◽  
Hubert Seigneur ◽  
Stephen Barkaszi ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Operating Conditions ◽  
Time Response ◽  
Cfd Analysis ◽  
Pv System ◽  
Data Set ◽  
Content Type ◽  
Pv Systems ◽  
Design Variables

Purpose Wind loading calculations are currently performed according to the ASCE 7 standard. Values in this standard were estimated from simplified models that do not necessarily take into account relevant flow characteristics. Thus, the standard does not have provisions to handle the majority of rooftop photovoltaic (PV) systems. Accurate solutions for this problem can be produced using a full-fledged three-dimensional computational fluid dynamics (CFD) analysis. Unfortunately, CFD requires enormous computation times, and its use would be unsuitable for this application which requires real-time solutions. To this end, a real-time response framework based on the proper orthogonal decomposition (POD) method is proposed. Design/methodology/approach A real-time response framework based on the POD method was used. This framework used beforehand and off-line CFD solutions from an extensive data set developed using a predefined design space. Solutions were organized to form the basis snapshots of a POD matrix. The interpolation network using a radial-basis function (RBF) was used to predict the solution from the POD method given a set of values of the design variables. The results presented assume varying design variables for wind speed and direction on typical PV roof installations. Findings The trained POD–RBF interpolation network was tested and validated by performing the fast-algebraic interpolation to obtain the pressure distribution on the PV system surface and they were compared to actual grid-converged fully turbulent 3D CFD solutions at the specified values of the design variables. The POD network was validated and proved that large-scale CFD problems can be parametrized and simplified by using this framework. Originality/value The solar power industry, engineering design firms and the society as a whole could realize significant savings with the availability of a real-time in situ wind-load calculator that can prove essential for plug-and-play installation of PV systems. Additionally, this technology allows for automated parametric design optimization to arrive at the best fit for a set of given operating conditions. All these tasks are currently prohibited because of the massive computational resources and time required to address large-scale CFD analysis problems, all made possible by a simple but robust technology that can yield massive savings for the solar industry.

Optimal Model-Free Approach Based on MDL and CHL for Active Brain Identification in fMRI Data Analysis

2020 ◽  
Vol 16 ◽  
Author(s):  
Hussain A. Jaber ◽  
Ilyas Çankaya ◽  
Hadeel K. Aljobouri ◽  
Orhan M. Koçak ◽  
Oktay Algin
Keyword(s):  
Data Analysis ◽  
Time Course ◽  
Extreme Values ◽  
Statistical Parametric Mapping ◽  
Fmri Data ◽  
Cluster Center ◽  
Jaccard Coefficient ◽  
Neural Gas ◽  
Model Free ◽  
Clustering Approach

Background: Cluster analysis is a robust tool for exploring the underlining structures in data and grouping them with similar objects. In the researches of Functional Magnetic Resonance Imaging (fMRI), clustering approaches attempt to classify voxels depending on their time-course signals into a similar hemodynamic response over time. Objective: In this work, a novel unsupervised learning approach is proposed that relies on using Enhanced Neural Gas (ENG) algorithm in fMRI data for comparison with Neural Gas (NG) method, which has yet to be utilized for that aim. The ENG algorithm depends on the network structure of the NG and concentrates on an efficacious prototype-based clustering approach. Methods: The comparison outcomes on real auditory fMRI data show that ENG outperforms the NG and statistical parametric mapping (SPM) methods due to its insensitivity to the ordering of input data sequence, various initializations for selecting a set of neurons, and the existence of extreme values (outliers). The findings also prove its capability to discover the exact and real values of a cluster number effectively. Results: Four validation indices are applied to evaluate the performance of the proposed ENG method with fMRI and compare it with a clustering approach (NG algorithm) and model-based data analysis (SPM). These validation indices include the Jaccard Coefficient (JC), Receiver Operating Characteristic (ROC), Minimum Description Length (MDL) value, and Minimum Square Error (MSE). Conclusion: The ENG technique can tackle all shortcomings of NG application with fMRI data, identify the active area of the human brain effectively, and determine the locations of the cluster center based on the MDL value during the process of network learning.

scholarly journals Reconfigurable Distributed Power Electronics Technique for Solar PV Systems

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1121
Author(s):  
Kamran Ali Khan Niazi ◽  
Yongheng Yang ◽  
Tamas Kerekes ◽  
Dezso Sera
Keyword(s):  
Energy Yield ◽  
Solar Pv ◽  
Charge Redistribution ◽  
Pv System ◽  
Partial Shading ◽  
Pv Systems ◽  
Simulation Based ◽  
In Series ◽  
A Cell ◽  
Power Balancing

A reconfiguration technique using a switched-capacitor (SC)-based voltage equalizer differential power processing (DPP) concept is proposed in this paper for photovoltaic (PV) systems at a cell/subpanel/panel-level. The proposed active diffusion charge redistribution (ADCR) architecture increases the energy yield during mismatch and adds a voltage boosting capability to the PV system under no mismatch by connected the available PV cells/panels in series. The technique performs a reconfiguration by measuring the PV cell/panel voltages and their irradiances. The power balancing is achieved by charge redistribution through SC under mismatch conditions, e.g., partial shading. Moreover, PV cells/panels remain in series under no mismatch. Overall, this paper analyzes, simulates, and evaluates the effectiveness of the proposed DPP architecture through a simulation-based model prepared in PSIM. Additionally, the effectiveness is also demonstrated by comparing it with existing conventional DPP and traditional bypass diode architecture.

scholarly journals State-Space Model of Quasi-Z-Source Inverter-PV Systems for Transient Dynamics Studies and Network Stability Assessment

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4150
Author(s):  
Lluís Monjo ◽  
Luis Sainz ◽  
Juan José Mesas ◽  
Joaquín Pedra
Keyword(s):  
Power Systems ◽  
State Space ◽  
State Space Model ◽  
Pv System ◽  
Pv Systems ◽  
Renewable Power ◽  
Ac Networks ◽  
Transient Interactions ◽  
The Stability ◽  
Averaged Model

Photovoltaic (PV) power systems are increasingly being used as renewable power generation sources. Quasi-Z-source inverters (qZSI) are a recent, high-potential technology that can be used to integrate PV power systems into AC networks. Simultaneously, concerns regarding the stability of PV power systems are increasing. Converters reduce the damping of grid-connected converter systems, leading to instability. Several studies have analyzed the stability and dynamics of qZSI, although the characterization of qZSI-PV system dynamics in order to study transient interactions and stability has not yet been properly completed. This paper contributes a small-signal, state-space-averaged model of qZSI-PV systems in order to study these issues. The model is also applied to investigate the stability of PV power systems by analyzing the influence of system parameters. Moreover, solutions to mitigate the instabilities are proposed and the stability is verified using PSCAD time domain simulations.

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