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Automation of I-V curve measurement for photovoltaic modules: a practical approach
Abstract
A photovoltaic (PV) module's efficiency is influenced by factors such as environmental conditions (Solar light intensity, temperature) and the load. These modules can encounter various problems that significantly impact their power output, leading to poor overall system performance. The Current-Voltage (I-V) curve is a graphical representation that illustrates the characteristics of a PV module (MPV). Measuring this curve in real-time is essential for diagnosing faults and analyzing PV installations. It offers a quick way to test modules and identify issues like shading, mismatching... This paper presents an experimental system designed to measure the I-V curve of a PV module under real operating conditions. The measurement process is automated and serves to assess the module’s health, degradation, and overall performance. An Arduino card is used to control the measurements, which are conducted in situ, in real time. The effectiveness of this method is validated through experimental data collected from a PV module. The developed system provides a visual display of the module's electrical characteristics and shows solar solar light intensity and temperature in real time on an LCD screen. All results are also displayed on PC. Experimental results are presented.
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Photovoltaics (PV) utilize sunlight to generate electricity, thus playing a crucial role in generating clean energy and decreasing carbon emissions. Simultaneously, these systems encourage self-sufficiency in energy production. Consequently, it becomes imperative to monitor the performance of photovoltaic systems as an essential method for assessing and confirming these advantages. Precise measurement and analysis of performance data offer researchers and industry experts valuable insights into system effectiveness, power generation trends, as well as their overall ecological influence. The significance of PV monitoring in ensuring and enhancing system performance is emphasized by the research conducted. The ability to collect and analyze real-time data enables operators to identify inefficient modules, as well as shading or other obstacles that could hinder energy production. Furthermore, monitoring systems enable early identification of potential malfunctions, which allows for timely maintenance and repair actions. Ultimately, these practices enhance overall energy generation while extending the longevity of PV installations. This paper presents the design and implementation of a portable electronic device to measure the I-V and P-V curves of photovoltaic panels. This instrument acquires solar radiation, ambient temperature, electric current, and voltage signals from a PV panel via a cellphone through a mobile application. The device, capable of real-time characterization of PV panels up to 20 A and 500 V, features a 240 MHz Tensilica LX6 dual-core processor and 4 MB of storage memory. Experimental tests were carried out in two different geographical locations in Colombia: the city of Puerto Carreño and the city of Bogotá. Among the main results, an efficiency of 13.29 % was obtained for solar radiation of 755.47 W/m 2 and a temperature of 29.60 • C for a monocrystalline PV panel of 405 W.
Due to the influence of meteorological conditions, shipboard photovoltaic (PV) systems have problems such as large fluctuation and inaccurate prediction of the output power. In this paper, a short-term PV power prediction method based on a novel digital twin (DT) model and BiLSTM is proposed. Firstly, a PV mechanism model and a data-driven model were established, in which the data-driven model was updated iteratively in real time using the sliding time window update method; then, these two models were converged to construct a PV DT model according to the DS evidence theory. Secondly, a BiLSTM model was built to make short-term predictions of the PV power using the augmented dataset of the DT model as an input. Finally, the method was tested and verified by experiments and further compared with main PV prediction methods. The research results indicate the following: firstly, the absolute error of the DT model was smaller than that of the mechanism model and the data-driven model, being as low as 5.62 W after the data update of the data-driven model; thus, the DT model realized data augmentation and high fidelity. Secondly, compared to several main PV prediction models, the PV DT model combined with BiLSTM had the lowest RMSE, MAE, and MAPE; the best followability; and the smallest absolute error under different weather conditions, which was especially obvious under cloudy weather conditions. In summary, the method can accurately predict the shipboard PV power, which has great theoretical significance and application value for improving the economy and reliability of solar ship operation.
Studying the operation of photovoltaic panels in the presence of varying meteorological parameters is a complex undertaking that requires the development of models to understand the physical phenomena associated with different meteorological factors. The main aim of this study is to examine the impact of meteorological factors, such as illuminance, temperature, and wind speed, on the performance of photovoltaic modules. Our goal is to develop precise models that illustrate how these factors affect the output of a photovoltaic system at a specific location. To achieve this, we utilized a rigorously validated mathematical model, previously tested with photovoltaic simulation software such as PVsyst, enabling accurate prediction of photovoltaic installation output. We compared the results of our simulations, conducted with the chosen mathematical model, with those obtained from PVsyst software. Subsequently, we validated the accuracy of our proposed model using real operating conditions simulated by PVsyst. Additionally, we incorporated additional curves, not available in the PVsyst database, accounting for wind speed as a meteorological parameter.
This paper details the design and implementation of a photovoltaic current – voltage (I-V) tracer. The I-V tracer employs a capacitive load controlled by a raspberry pi model 4B. The complete measurement system includes protections, capacitor charging/discharging power electronics and current, voltage, irradiance and temperature sensors. Results, which include maximum power point, open circuit voltage, short circuit current and module efficiency, are displayed on an LCD touch display. Detailed description of the required software and the graphical user interface is also presented. This measurement system is very useful for testing photovoltaic installations, allowing an immediate verification whether the panels fulfill with the specifications and detection of possible failures.
The computer is the greatest innovation of the 20th century. It has changed our lives. It executes tasks with precision. There is no limit with what we can do with software. Computers are seductive. Companies and students cannot work without them. They help students to perform mathematical computations. It is very important that mathematical ideas are expressed in computer programs in order to have theoretical results and to verify them practically. Nowadays, the development of new and non-polluting energy producing and energy-storage systems is a great challenge for scientists. An alternative to the nuclear and fossil fuel power is renewable energy technologies. Due to ever-increasing energy consumption, rising public awareness of environmental protection, and steady progress in power deregulation, alternative (i.e., renewable and fuel cell based) distributed generation systems have attracted increased interest. There is an accelerating world demand for environmentally friendly power. Among the renewable energy sources, the Photovoltaic (PV) energy is the most promising candidate for research and development for large scale users. Fuel cells have been receiving a lot of attention lately due to their potential of becoming a new energy source with a large range of applications. Fuel cells can be incorporated with other components to create high efficiency industrial power plants. Fuel cells permit clean and efficient energy production. The purpose of the work is to optimize the system’s operation. The main reason to build described system is to supply stand-alone systems using renewable energy sources. Therefore, the power plant has to produce energy independent of any weather fluctuations. Integrating photovoltaic energy sources with fuel cells, as a storage device replacing the conventional lead-acid batteries, leads to a non-polluting reliable energy source. In this chapter, an energy system comprising different energy sources, namely PV and fuel cells, is proposed. Photovoltaic cells coupled with electrolytic devices can be used to produce hydrogen and oxygen in a sustainable manner. With the produced hydrogen from the electrolysis process, it is possible to generate electricity through fuel cells. Photovoltaic panels in particular can provide a good source of producing green electricity. It is autonomous, its operation does not pollute the atmosphere, and it is an inexhaustible and renewable source with great reliability. The simulation program developed also allows the exportation of different configurations. The experimental system described has permitted the validation of the proposed method.
The I–V curve tracer is an instrument that captures the I–V characteristics of photovoltaic (PV) generators corresponding to variable environmental conditions. The device is widely used to evaluate power generation performance and detect the fault conditions of PV power generators. Various I–V tracer techniques have been developed and proposed to trace the IV characteristics and ensure high accuracy and fast speeds. A comprehensive classification and analysis was undertaken to identify the advantages and disadvantages of different technologies. This study proposes and uses five performance indices to evaluate the performance of I–V tracers. The quantitative fidelity of commercial I–V tracers were also reviewed and evaluated. This paper serves as a valuable reference tool that should be used to guide the direction of future research and lead future improvements in the field.
Photovoltaic energy is a natural form of energy and can replace conventional fuels. The photovoltaic performance depends mainly on the incident solar irradiation, temperature, photovoltaic generator material composition. This article proposes a method of photovoltaic arrays modeling. With data provided by the manufacturer, the method finds the electric equations (current versus voltage, power versus voltage) for photovoltaic array at standard conditions. Model also takes account of temperature and insolation variations to determine novel characteristics for specific conditions. This article also discusses the use of DC–DC converter realized as a means of maximum power point tracker (MPPT). The control card obtains informations from the PV array through microcontroller's ports. Combined methods: jump to maximum power point (MPP) and power's comparison method are used as an algorithm to track the maximum power point of the PV array. Analysis experimental results were carried in order to verify the proposed method. Another purpose of this article is to model the optimal power using the methodology of experimental design. An optimization of power delivered by photovoltaic generator takes into account the insolation and temperature factors. In general, in the methods in literature, only solar irradiation variations or load variations are considered. But, the results do not reflect the conditions that occur in the real conditions. The design of experiment (DoE) technique and the response surface methodology (RSM), are employed to analyze the results of tests obtained during different climatic conditions. Results are given and analyzed in this article. Results are used to fit and adjust response surfaces to experimental data. The obtained results made it possible to propose a mathematical model and, consequently to study interactions between temperature and insolation. The DOE simulation model can be implemented in future works. © 2016 American Institute of Chemical Engineers Environ Prog, 35: 1529–1536, 2016.
Photovoltaic energy has, nowadays, an increased importance in electrical power applications. However, the output power provided via the photovoltaic conversion process depends on solar irradiation and temperature. Tracking the Maximum Power Point (MPP) of photovoltaic (PV) systems is the most important part of the PV systems. In this paper, modeling and parameter extraction methods are proposed to describe the optimal current, voltage and power of the photovoltaic cells. The aim is to find a formula that considers these factors and to study the interactions between these various factors. The design of experiments is a powerful tool to understand systems and processes. Experiments are often run so that the effect of one factor is unknowingly confused with the effect of another factor. A brief comparison between classic modeling is presented. In order to model the optimal current, optimal tension and optimal power, a methodology of experimental design is presented. The obtained results show the merits of the proposed mathematical model, which makes the study of the interactions between various climatic factors possible.
In this work, we present a generic model based on universal of mathematical equations to model the operation of a solar cell. We analyze the output current and the electric power supplied by a solar cell according to the output voltage, temperature and power. The results obtained show that the model is very effective in treating the simulation model of a solar cell on the one hand and secondly the ability to model in an efficient manner a photovoltaic field with fewer errors. This allows operating the photovoltaic generators in optimal conditions, and consequently with a better exploitation of energy.
In terms of fuel cell steady-state performance modelling, many electrical models have been developed either from a theoretical point of view or from an empirical point of view. The model described in this article is from the empirical point of view approach. This model enables to simulate both fuel cells and electrolysers V-J curves (cell voltage versus current density) in typical conditions. This model is particularly adapted to regenerative fuel cell (RFC) simulation. It is a four degree-of-freedom model and it is convergent near zero current. It depends on the stack temperature and the oxygen partial pressure. The regions where mass transfer limitations occur have not been modelled, because they are usually avoided for efficiency or thermal reasons. The parameters have been fitted with a 4 kW(e) proton exchange membrane fuel cell (PEMFC) and a 3.6 kW(e) electrolyser. The electrical equations and the experimental data are well correlated.
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Mise en oeuvre d'une technique améliorant le fonctionnement d'un systéme vert
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Nouh Zegrar, Abdelkamel Habib Zahmani, Mise en oeuvre d'une technique
améliorant le fonctionnement d'un systéme vert, Master thesis, Electronics department,
USTOMB, 2024.
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Abelino, Photovoltaic Solar Energy Storage and Management System Applied to a
Functional Prototype / Sistema de Armazenamento e Gerenciamento de Energia Solar
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