Study of Photovoltaic Systems’ Performances with Different Module Types

2016 ◽  
Vol 856 ◽  
pp. 279-284 ◽  
Author(s):  
Zahari Zarkov ◽  
Ludmil Stoyanov ◽  
Hristiyan Kanchev ◽  
Valentin Milenov ◽  
Vladimir Lazarov
Keyword(s):  
Theoretical Study ◽  
Weather Conditions ◽  
Operating Conditions ◽  
Experimental Results ◽  
Photovoltaic Systems ◽  
Experimental Site ◽  
Pv Systems ◽  
Research Platform ◽  
Pv Modules ◽  
Different Types

The purpose of the work is to study and compare the performance of photovoltaic (PV) generators built with different types of panels and operating in real weather conditions. The paper reports the results from an experimental and theoretical study of systems with PV modules manufactured according to different technologies and using different materials. The experiment was carried out at a research platform for PV systems developed by the authors, built and located at an experimental site near the Technical University of Sofia. Based on the obtained results, comparisons are made between the different PV generators for the same operating conditions. The comparison between the theoretical and the experimental results demonstrates a good level of overlap.

Dependence of Snow Gauge Collection Efficiency on Snowflake Characteristics

2012 ◽  
Vol 51 (4) ◽  
pp. 745-762 ◽  
Author(s):  
Julie M. Thériault ◽  
Roy Rasmussen ◽  
Kyoko Ikeda ◽  
Scott Landolt
Keyword(s):  
Wind Speed ◽  
Theoretical Study ◽  
Collection Efficiency ◽  
Weather Conditions ◽  
Systematic Errors ◽  
Lagrangian Model ◽  
Field Observations ◽  
Research Fields ◽  
Different Types ◽  
Precipitation Gauge

AbstractAccurate snowfall measurements are critical for a wide variety of research fields, including snowpack monitoring, climate variability, and hydrological applications. It has been recognized that systematic errors in snowfall measurements are often observed as a result of the gauge geometry and the weather conditions. The goal of this study is to understand better the scatter in the snowfall precipitation rate measured by a gauge. To address this issue, field observations and numerical simulations were carried out. First, a theoretical study using finite-element modeling was used to simulate the flow around the gauge. The snowflake trajectories were investigated using a Lagrangian model, and the derived flow field was used to compute a theoretical collection efficiency for different types of snowflakes. Second, field observations were undertaken to determine how different types, shapes, and sizes of snowflakes are collected inside a Geonor, Inc., precipitation gauge. The results show that the collection efficiency is influenced by the type of snowflakes as well as by their size distribution. Different types of snowflakes, which fall at different terminal velocities, interact differently with the airflow around the gauge. Fast-falling snowflakes are more efficiently collected by the gauge than slow-falling ones. The correction factor used to correct the data for the wind speed is improved by adding a parameter for each type of snowflake. The results show that accurate measure of snow depends on the wind speed as well as the type of snowflake observed during a snowstorm.

scholarly journals On the Link between the Operating Point and the Temperature Distribution in PV Arrays Working under Mismatching Conditions

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Luigi Costanzo ◽  
Massimo Vitelli
Keyword(s):  
Temperature Distribution ◽  
Hot Spots ◽  
Thermal Stresses ◽  
Operating Conditions ◽  
Experimental Results ◽  
Operating Point ◽  
Accelerated Ageing ◽  
Global Maximum ◽  
Pv Systems ◽  
Power Point

Mismatching operating conditions negatively affect the extracted energy in photovoltaic (PV) systems. They may also lead to dangerous localized heating phenomena (hot spots) that can cause, in turn, accelerated ageing and reduced reliability. Since the adoption of bypass diodes or smart active switches does not prevent the occurrence of hotspots, it is necessary to investigate alternative strategies. A promising solution is represented by the proper regulation of the operating point of the PV cells in the current vs. voltage (I-V) or power vs. voltage (P-V) planes when mismatching conditions occur. In particular, in this paper, the existence of operating points allowing a suitable compromise between maximization of the extracted power and minimization of thermal stresses, due to hot spots, is experimentally evidenced. Experimental results highlighting the link existing between the operating point in the I-V plane and the PV cell temperature distribution under uniform and mismatching operating conditions are presented and discussed. On the basis of the obtained experimental results, it is possible to state that, when mismatching conditions occur, it is mandatory to properly choose the operating point: the global maximum power point may not be the best operating point. Hence, it is crucial to gain information about the eventual occurrence of mismatching conditions in order to be able to properly choose the best operating point. Therefore, another crucial aspect that is evidenced in this paper is represented by the fact that the detection of the occurrence of mismatching conditions, based on the analysis of the shape of the I-V and/or P-V characteristics, is effective only if the analysis is carried out for both positive and negative voltages.

Performance of Bi-Facial PV Modules in Urban Settlements in Tropical Regions

2013 ◽  
Vol 853 ◽  
pp. 312-316
Author(s):  
Carlo Pisigan ◽  
Fan Jiang
Keyword(s):  
Urban Areas ◽  
Weather Conditions ◽  
Energy Output ◽  
Rear Side ◽  
Energy Yield ◽  
Tropical Regions ◽  
Pv Systems ◽  
Irradiation Energy ◽  
Pv Modules ◽  
Urban Settlements

This paper studies the performance of bifacial Heterojunction with Intrinsic Thin-layer (HIT) PV modules through a one-year experiment in Singapore. Two 1.2kWp (front side)/0.84kWp (rear side) PV systems were installed vertically, facing the N-S and E-W directions respectively. The operational data of two systems were monitored and collected to analyze their performance under different weather conditions. This paper will presentthe change of irradiation, energy yield and the AC energy output of the bifacial PV systems. The results help to understand the impacts of system installation on the energy yield of vertically-installedbifacial HIT PV systems, to find out its advantages in applications over monofacial PV modules and to explore the potential of bifacial PV modules in tropical regions, especially in urban areas like Singapore.

A Dynamic Electrical Scheme for the Optimal Reconfiguration of PV Modules under Non-Homogeneous Solar Irradiation

2012 ◽  
Vol 197 ◽  
pp. 768-777 ◽  
Author(s):  
Roberto Candela ◽  
Eleonora Riva Sanseverino ◽  
Pietro Romano ◽  
Marzia Cardinale ◽  
Domenico Musso
Keyword(s):  
Dynamic System ◽  
Real Time ◽  
Output Power ◽  
System Simulation ◽  
Weather Conditions ◽  
Solar Irradiation ◽  
Pv Systems ◽  
Pv Modules ◽  
Optimal Reconfiguration ◽  
Pv Generator

This paper presents a strategy for the maximization of the output power of photovoltaic (PV) systems under non homogeneous solar irradiation by means of automatic reconfiguration of the PV arrays layout. The innovation of the proposed approach is the employment of a simple Dynamic Electrical Scheme (DES), allowing a large number of possible modules interconnection, to be installed between the PV generator and the inverter. The models of the PV generator and of the DES have been realized and simulated with Simulink (Dynamic System Simulation for MATLAB). The attained experimental results appear to be quite interesting in terms of the attainable benefit in power and thus energy terms. The limited calculation times of the reconfiguration algorithm allows the application of the DES for the real time adaptation of the configuration to the changing weather conditions or other causes of non-uniform solar irradiation. Moreover, the results confirm that, in case of non uniform solar irradiation, this approach allows to attain considerably much better results than those attainable with a static configuration.

scholarly journals Machine Learning-Based Condition Monitoring for PV Systems: State of the Art and Future Prospects

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6316
Author(s):  
Tarek Berghout ◽  
Mohamed Benbouzid ◽  
Toufik Bentrcia ◽  
Xiandong Ma ◽  
Siniša Djurović ◽  
...  
Keyword(s):  
Machine Learning ◽  
Electric Power ◽  
Condition Monitoring ◽  
Failure Modes ◽  
Generative Models ◽  
Operating Conditions ◽  
Detection Methods ◽  
Photovoltaic Systems ◽  
Pv Systems ◽  
Maintenance Program

To ensure the continuity of electric power generation for photovoltaic systems, condition monitoring frameworks are subject to major enhancements. The continuous uniform delivery of electric power depends entirely on a well-designed condition maintenance program. A just-in-time task to deal with several naturally occurring faults can be correctly undertaken via the cooperation of effective detection, diagnosis, and prognostic analyses. Therefore, the present review first outlines different failure modes to which all photovoltaic systems are subjected, in addition to the essential integrated detection methods and technologies. Then, data-driven paradigms, and their contribution to solving this prediction problem, are also explored. Accordingly, this review primarily investigates the different learning architectures used (i.e., ordinary, hybrid, and ensemble) in relation to their learning frameworks (i.e., traditional and deep learning). It also discusses the extension of machine learning to knowledge-driven approaches, including generative models such as adversarial networks and transfer learning. Finally, this review provides insights into different works to highlight various operating conditions and different numbers and types of failures, and provides links to some publicly available datasets in the field. The clear organization of the abundant information on this subject may result in rigorous guidelines for the trends adopted in the future.

scholarly journals Comparative study on different types of photovoltaic modules under outdoor operating conditions in Minna, Nigeria

2018 ◽  
Vol 6 (1) ◽  
pp. 35
Author(s):  
Joel A. Ezenwora ◽  
David O. Oyedum ◽  
Paulinus E. Ugwuoke
Keyword(s):  
Measured Data ◽  
Operating Conditions ◽  
Performance Variables ◽  
Photovoltaic Modules ◽  
Pv Module ◽  
Pv Modules ◽  
Different Types ◽  
Metal Support ◽  
One Year ◽  
Module Performance

There is need to always obtain the realistic outdoor performance variables of Photovoltaic (PV) module in a location for efficient PV power system sizing and design. Outdoor performance evaluation was carried out on three types of commercially available silicon PV modules rated 10 W each, using CR1000 software-based Data Acquisition System (DAS). The PV modules under test and meteorological sensors were installed on a metal support structure at the same test plane.The data monitoring was from 08.00 to 18.00 hours each day continuously for a period of one year, from December 2014 to November 2015. Maximum values of module efficiencies of 5.86% and 10.91% for the monocrystalline and polycrystalline modules were respectively recorded at irradiance of 375 W/m2, while the amorphous efficiency peaked at 3.61 % with irradiance of 536.5 W/m2. At 1000 W/m2 the efficiencies reduced to 3.30 %, 6.20 % and 2.25 % as against manufacturer’s specifications of 46 %, 48 % and 33 % for the monocrystalline, polycrystalline and amorphous modules respectively. The maximum power output achieved for the modules at irradiance of 1000 W/m2 were 0.711 W, 1.323 W and 0.652 W for the monocrystalline, polycrystalline and amorphous PV modules, respectively. Accordingly, Module Performance Ratios for the PV modules investigated were 0.07, 0.13 and 0.07, respectively. The rate of variation of module response variables with irradiance and temperature was determined using a linear statistical model given as Y= a + bHg+ c Tmod. The approach performed creditably when compared with measured data.

scholarly journals Experimental Evaluation of Distortion Effect for Grid-Connected PV Systems with Reference to Different Types of Electric Power Quantities

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 416
Author(s):  
Marko Ikić ◽  
Jovan Mikulović
Keyword(s):  
Electric Power ◽  
Solar Irradiance ◽  
Experimental Evaluation ◽  
Weather Conditions ◽  
Pv System ◽  
Pv Systems ◽  
Distortion Effect ◽  
Different Types ◽  
Huge Impact ◽  
The Impact

Aware of the fact that the installed PV capacity and its power production rapidly increased in the last decade, with the huge impact that has been done to the power system, the distortion effects for grid-connected PV systems with reference to different types of electric power quantities will be presented in this article. The impact of the frequent fluctuation of solar irradiance on the behavior of the grid-connected PV system, due to cloud movements and resulting shadows and in terms of power quality and the evaluation of power components, is the topic of analysis in this research. Besides the simulation results of certain study cases, an experimental evaluation of electric power quantities on an actual PV system in real weather conditions was also performed. The experimental setup, formed through the combination of a PC and multifunctional I/O board with an appropriate software solution, was established and used for obtaining the target results. The methodology used for the evaluation of electric power quantities relied on the current physical components (CPC) theory for power definition. The experimental results were obtained for three different cases, namely, the low, medium, and high solar irradiance cases. On the basis of these results, the conclusions about distortion effects are given.

scholarly journals Convolutional Neural Network for Dust and Hotspot Classification in PV Modules

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6357
Author(s):  
Giovanni Cipriani ◽  
Antonino D’Amico ◽  
Stefania Guarino ◽  
Donatella Manno ◽  
Marzia Traverso ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Operating Conditions ◽  
Electricity Production ◽  
Pv Systems ◽  
Pv Modules ◽  
Execution Speed ◽  
Abnormal Operating Conditions ◽  
The Impact ◽  
Non Destructive

This paper proposes an innovative approach to classify the losses related to photovoltaic (PV) systems, through the use of thermographic non-destructive tests (TNDTs) supported by artificial intelligence techniques. Low electricity production in PV systems can be caused by an efficiency decrease in PV modules due to abnormal operating conditions such as failures or malfunctions. The most common performance decreases are due to the presence of dirt on the surface of the module, the impact of which depends on many parameters and conditions, and can be identified through the use of the TNDTs. The proposed approach allows one to automatically classify the thermographic images from the convolutional neural network (CNN) of the system, achieving an accuracy of 98% in tests that last a couple of minutes. This approach, compared to approaches in literature, offers numerous advantages, including speed of execution, speed of diagnosis, reduced costs, reduction in electricity production losses.

scholarly journals Recent Meta-heuristic Algorithms with a Novel Premature Covergence Method for Determining the Parameters of PV Cells and Modules

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1846
Author(s):  
Mohamed Abdel-Basset ◽  
Reda Mohamed ◽  
Mohamed Abouhawwash ◽  
Yunyoung Nam ◽  
Attia El-Fergany
Keyword(s):  
Heuristic Algorithms ◽  
Operating Conditions ◽  
Solar Panels ◽  
Current Position ◽  
Unknown Parameters ◽  
Trade Off ◽  
Si Solar Cell ◽  
Pv Modules ◽  
Different Types ◽  
Convergence Method

Currently, the incorporation of solar panels in many applications is a booming trend, which necessitates accurate simulations and analysis of their performance under different operating conditions for further decision making. In this paper, various optimization algorithms are addressed comprehensively through a comparative study and further discussions for extracting the unknown parameters. Efficient use of the iterations within the optimization process may help meta-heuristic algorithms in accelerating convergence plus attaining better accuracy for the final outcome. In this paper, a method, namely, the premature convergence method (PCM), is proposed to boost the convergence of meta-heuristic algorithms with significant improvement in their accuracies. PCM is based on updating the current position around the best-so-far solution with two-step sizes: the first is based on the distance between two individuals selected randomly from the population to encourage the exploration capability, and the second is based on the distance between the current position and the best-so-far solution to promote exploitation. In addition, PCM uses a weight variable, known also as a controlling factor, as a trade-off between the two-step sizes. The proposed method is integrated with three well-known meta-heuristic algorithms to observe its efficacy for estimating efficiently and effectively the unknown parameters of the single diode model (SDM). In addition, an RTC France Si solar cell, and three PV modules, namely, Photowatt-PWP201, Ultra 85-P, and STM6-40/36, are investigated with the improved algorithms and selected standard approaches to compare their performances in estimating the unknown parameters for those different types of PV cells and modules. The experimental results point out the efficacy of the PCM in accelerating the convergence speed with improved final outcomes.

scholarly journals A Novel MPPT Technique Based on Mutual Coordination between Two PV Modules/Arrays

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 6996
Author(s):  
Ali Faisal Murtaza ◽  
Hadeed Ahmed Sher ◽  
Filippo Spertino ◽  
Alessandro Ciocia ◽  
Abdullah M. Noman ◽  
...  
Keyword(s):  
Weather Conditions ◽  
Fast Response ◽  
Graphical Analysis ◽  
Superior Performance ◽  
Pv Systems ◽  
Point Tracking ◽  
Perturb And Observe ◽  
Pv Modules ◽  
Power Point ◽  
Stage 1

A novel maximum power point tracking (MPPT) technique based on mutual coordination of two photovoltaic (PV) modules/arrays has been proposed for distributed PV (DPV) systems. The proposed technique works in two stages. Under non-mismatch conditions between PV modules/arrays, superior performance stage 1 is active, which rectifies the issues inherited by the perturb and observe (P&O) MPPT. In this stage, the technique revolves around the perturb and observe (P&O) algorithm containing an intelligent mechanism of leader and follower between two arrays. In shading conditions, stage 2 is on, and it works like conventional P&O. Graphical analysis of the proposed technique has been presented under different weather conditions. Simulations of different algorithms have been performed in Matlab/Simulink. Simulation results of the proposed technique compliment the graphical analysis and show a superior performance and a fast response as compared to others, thus increasing the efficiency of distributed PV systems.

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