Photovoltaic Systems In Order Research Articles

Improving Photovoltaic System Performance with Artificial Neural Network Control

Photovoltaic systems play a pivotal role in renewable energy initiatives. To enhance the efficiency of solar panels amid changing environmental conditions, effective Maximum Power Point Tracking (MPPT) is essential. This study introduces an innovative control approach based on an Artificial Neural Network (ANN) controller tailored for photovoltaic systems. The aim is to elevate the precision and adaptability of MPPT, thereby improving solar energy harvesting. This research integrated an ANN controller into a photovoltaic system in order dynamically optimize the operating point of solar panels in response to environmental changes. The performance of the ANN controller was compared with traditional MPPT approaches using simulation in Simulink/Matlab. The results of the simulation showed that the ANN controller performed better than the traditional MPPT techniques, highlighting the effectiveness of this method for dynamically changing solar panel performance. The ANN particularly demonstrates higher precision and adaptability when environmental conditions vary. The strategy consistently achieves and maintains the maximum power point, enhancing overall energy harvesting efficiency. The integration of an ANN controller marks a significant advance in solar energy control. The study highlights the superiority of the ANN controller through rigorous simulations, demonstrating increased accuracy and adaptability. This approach not only proves effective, but also has the potential to outperform other MPPT strategies in terms of stability and responsiveness.

A comprehensive comparative study on intelligence based optimization algorithms used for maximum power tracking in grid-PV systems

For maximum power point tracking (MPPT) in the solar Photovolatic (PV) system, the meta-heuristic optimization techniques have been widely applied in the last few decades. This is due to the fact that traditional MPPT methodologies are unable to monitor the global MPP in the face of shifting environmental factors. Hence, it is essential to use an intelligence based controlling algorithm for MPPT controlling. The main purpose of this study is to investigate and assess the effectiveness of three cutting-edge and distinctive optimization algorithms for MPPT controlling, including Mongoose Optimization (MO), Prairie Dog Optimization Algorithm (PDOA), and hybrid PDOA + MO. It also aims to select the most effective and sophisticated optimization algorithm to meet the grid systems' energy requirements. This research's original contribution is the implementation and performance evaluation of three alternative meta-heuristic models for MPPT controlling. The goal of this effort is to maximize the energy yield from photovoltaic systems in order to meet the energy demands of grid systems. Three different controlling strategies, including MO + MPPT, PDOA + MPPT, and MO + PDOA + MPPT, are used in this work to achieve this goal. To evaluate the effectiveness and improved performance outcomes, a number of parameters have been taken into account in this work, including time, error, power, THD, and others. Furthermore, using a comprehensive simulation and comparison study, the outcomes of the MO, PDOA, and hybrid PDOA + MO techniques have also been tested and confirmed in this work. Comparisons are also made between the peak, settling, and increasing times of the present and proposed regulatory models. The results and waveforms generated demonstrate that the hybrid PDOA + MO performs better than the other controlling models in terms of enhanced efficiency of 99.5 %, low rising time of 1.6 s, low peak time of 1.05 s, minimal settling time of 1.24 s, error rate of 0.48, response time of 0.005 s, and tracking time of 0.0019 s

Manufacture of solar wheelchairusing waste materials: applied in Bechar-Algeria

Mobility is a fundamental right for all and is essential to the social contacts and communication of every individual. The wheelchair is one of the most common technique use to improve mobility of person with reduced mobility, it helps them to become more productive members in their communities. These wheelchairs are usually recharged via the standard power grid where they require two rechargeable batteries of 12 volts.The main idea of this work is to create a wheelchair totally powered by solar energy using a photovoltaic system in order to charge the batteries and extends the autonomy of the wheelchair.

Enhancing the Performance of Photovoltaic Panels by Cooling: a Review

Recently the world moves toward high utilization of renewable energy application due to environmental and economic issues. Photovoltaic (PV) is one of the most common renewable technologies, which produces electricity from solar irradiance. Due to environmental friendliness, sustainability, and lack of fuel costs, the number of applications and studies relating to PV plants is rapidly growing. Apart from the numerous benefits provided by PV, it faces some issues. Dust and surface temperature are the most important issues which cause a detrimental impact on the conversion system's performance. The cell temperature also, reflects on the PV degradation rate and the system life time. PV surface Cooling is an important way to be considered while running solar photovoltaic systems in order to obtain improved efficiency. There are different cooling techniques are suggested in literatures including active cooling, passive cooling and hybrid cooling techniques up to the most recent researches. The common methods for PV cooling are reviewed, studied, and evaluated in this paper. Different features and capabilities of cooling technologies are presented, in addition to highlight the opportunities to enhance or upgrade the cooling techniques.

Automatic Irrigation System with Water Pumps and Sensor in the Junin Region Peru

This project presented the design and implementation of an automatic irrigation system with water pumps and sensors, powered by a photovoltaic system, in a simulation programme (Proteus). This project is designed for a harvesting site located in the district of Huancan-Junin. The project showed that it is feasible to improve the irrigation system for people who focus on agriculture. In addition, a control system was implemented based on programming, simulations, and mathematical models. Where we can perform the respective tests for the development of the project. The results of this project will be used to improve an autonomous irrigation system with pumps and sensors. Also, it will be powered by a photovoltaic system in order to reduce the physical effort of farmers and give them a better quality of life.

The Impact and the Need for the DC/DC Converter to Adapt the Energy Produced by the Photovoltaic Generator

Considering the environmental effects and the shortage of fossil fuels, research encourages us towards the development and use of more and more renewable energies such as the autonomous photovoltaic system which is very much used for rural applications such as solar lighting, battery charging, etc. The beginning of our study describes the photovoltaic effect and the current-voltage and power-voltage characteristics of a mathematical model of a cell with a single diode. This allows us to model a solar panel and get an idea of the behavior of the field and the photovoltaic generator. The model predicts the behavior and characteristics of the PV model using the Matlab/Simulink platform. Connected to a basic circuit, the constant DC source voltage step-up converter first and to the PV system last, allows us to conclude that the presence of power electronics is essential in the photovoltaic system in order to adapt and d Ensuring its proper functioning and satisfactory results suggest the effectiveness of this model.

EXPERIMENTAL MONITORING AND COMPARISON OF ENERGY PRODUCTION ON SOLAR TRACKING SYSTEMS AND FIXED SUPPORT

The major objectives of researchers and industrialists in the solar field are to improve the efficiency and reduce the costs of cells, modules, and photovoltaic systems in order to make them as competitive as possible. There are two ways to maximize the useful energy rate by optimizing the conversion and degree of absorption, and by increasing the incident radiation rate by using mechanical steering systems. These systems, also known as solar trackers, allow the modules to be oriented throughout the day.The solar tracker, also called solar tracker, is a motorized arm that allows photovoltaic panels to follow the sun. Throughout the day, the arm rotates to capture as much sunlight as possible.For this work, we compared the production of panels mounted on fixed supports and trackers.The measurements were obtained on a year to make it possible to estimate the energy gain due to the orientation which is around 25%, thus confirming the economic importance of this systemProduction on tracker supports ramps up in the morning while production on fixed support gradually increases to its maximum at solar noon. The difference measured greatly exceeds at the beginning and end of the day the average is 44.5% for this sunny day. The greater the sunshine in the place considered, the greater the difference in favor of the tracker. On an annual average, the optimum gain of a 1-axis solar tracker varies by approximately 25% and 40% for 2-axis trackers compared to a fixed photovoltaic plant.

Realization of a Dual Axis Solar Tracking System

The effective use of renewable energy sources is very important today. Energy resources are limited and it is necessary to make maximum use of renewable energy. In this study, a dual-axis solar tracking system was implemented in the photovoltaic system in order to obtain the maximum possible energy from solar energy. In the solar tracking system, chestnut material is used as the vertical holder in the mechanical arrangement, and iron is used as the solar panel holder. By using a total of 4 LDRs at 4 corners of the solar panel, Arduino-based solar tracking on vertical and horizontal axis was carried out. The solar panel power used in the system is 45W, a geared DC motor on the horizontal axis and a linear DC motor on the vertical axis. As a result of the implemented application, a system that performs sensitive sun tracking has been realized and higher efficiency has been obtained compared to a static PV system.

Passivity voltage based control of the boost power converter used in photovoltaic system

Introduction. This paper presents a robust nonlinear control of the DC-DC boost converter feeding by a photovoltaic system based on the passivity control. The control law design uses the passivity approach. Novelty. The novelty consists in designing a control law for a photovoltaic system using a passivity approach based on energy shaping and associated with damping injection. Purpose. The purpose consists to develop a tool for design and optimize a control law of the photovoltaic system in order to improve its efficiency under some conditions such as the variations of the temperature, the irradiation and the parameters. Also, the control law design should be simple with a lower overshoot and a shorter settling time. Methods. This work uses the port Hamiltonian mathematical approach with minimization of the energy dissipation in boost converter of the photovoltaic system to illustrate the modification of energy and generate a specify duty cycle applied to the converter. Results. The results with MATLAB/SimPowerToolbox® have proven the robustness against parameter variations and effectiveness of the proposed control. Practical value. The experimental results, carried out using a dSPACE DS1104 system, are presented to show the feasibility and the robustness of the proposed control strategy against parameter variations.

Design and Test of a High-Performance Wireless Sensor Network for Irradiance Monitoring.

Cloud-induced photovoltaic variability can affect grid stability and power quality, especially in electricity systems with high penetration levels. The availability of irradiance field forecasts in the scale of seconds and meters is fundamental for an adequate control of photovoltaic systems in order to minimize their impact on distribution networks. Irradiance sensor networks have proved to be efficient tools for supporting these forecasts, but the costs of monitoring systems with the required specifications are economically justified only for large plants and research purposes. This study deals with the design and test of a wireless irradiance sensor network as an adaptable operational solution for photovoltaic systems capable of meeting the measurement specifications necessary for capturing the clouds passage. The network was based on WiFi, comprised 16 pyranometers, and proved to be stable at sampling periods up to 25 ms, providing detailed spatial representations of the irradiance field and its evolution. As a result, the developed network was capable of achieving comparable specifications to research wired irradiance monitoring network with the advantages in costs and flexibility of the wireless technology, thus constituting a valuable tool for supporting nowcasting systems for photovoltaic management and control.

Charge-Controller Optimization on Lead-Acid Battery in Solar PV Systems: Temperature Effects and Efficiency Improvement

Long-term cell performance is very sensitive to the cell operating temperature, and cell storage capacity can degrade quickly, if the temperature is not maintained within a narrow range (25–50 °C) during charging and discharging of (solar) batteries [1]. Efforts are recently being dedicated to developing models that seek to provide insights into that issue. However, not all models consider the operation of the photovoltaic (PV) battery storage system with regard to battery optimization and temperature effects. The present work provides a controllable algorithm to help charge controllers provide exact amount of PV electricity (charge equalization) to batteries with temperature compensation included, and a proposed charging and discharging schedules of the battery storage. The temperature compensated duty cycle for charging is modelled and the pulse-width modulation (PWM) signal is programmed to change with temperature following this duty cycle model. This research work is based on the optimization of solar battery storage where the micro controller-based charge controller enhances battery life by monitoring the temperature and controlling charging voltages and float charging voltages for specific temperatures. A buck converter was simulated in Proteus, and then realized in the laboratory. The duty cycle of the buck converter was adjusted with temperature. Results collected from lab experiments were plotted on MatLab and it shows homogeneity with calculated results. Moreover, battery-charging currents, battery direct current (DC) disconnect and battery switching for charging and discharging were performed for the converter. Future work is to extend this study to large-scale solar photovoltaic systems in order to overcome the operation limits encountered.

Supertwisting Sliding Mode Algorithm Based Nonlinear MPPT Control for a Solar PV System with Artificial Neural Networks Based Reference Generation

The problem of extracting maximum power from a photovoltaic (PV) system with negligible power loss is concerned with the power generating capability of the PV array and nature of the output load. Changing weather conditions and nonlinear behavior of PV systems pose a challenge in tracking of varying maximum power point. A robust nonlinear controller is required to ensure maximum power point tracking (MPPT) by handling nonlinearities of a system and making it robust against changing environmental conditions. Sliding mode controller is robust against disturbances, model uncertainties and parametric variations. It depicts undesirable phenomenon like chattering, inherent in it causing power and heat losses. In this paper, a supertwisting sliding mode algorithm based nonlinear robust controller has been designed for MPPT of a PV system which not only removes the chattering but also enhances the overall system’s dynamic response. Moreover, supertwisting sliding mode controller is robust against changing environmental conditions like change in temperature and irradiance. Noninverting DC-DC Buck-Boost converter has been used as an interface between source and the load. The efficiency of MPPT of a PV system depends upon the accuracy of reference for peak power voltage, therefore an efficient mechanism for reference generation has also been proposed in this work. The reference for peak power voltage has been generated by using a trained artificial neural network, which is to be tracked by proposed nonlinear controllers. Sliding mode controller (SMC) and synergetic controllers have also been designed for MPPT of a PV system in order to compare them with supertwisting sliding mode controller (ST-SMC). Global asymptotic stability of the system has been ensured by using Lyapunov stability criterion. The performance of the proposed nonlinear controllers has been validated in MATLAB/Simulink ODE 45 environment. ST-SMC has also been compared with recently proposed integral backstepping controller and other conventional MPPT controllers given in the literature. The simulation results show the better performance of ST-SMC in terms of best dynamic response and robustness.

Design and Hardware Implementation Based on Hybrid Structure for MPPT of PV System Using an Interval Type-2 TSK Fuzzy Logic Controller

The major drawback of photovoltaic (PV) systems is their dependence on environmental conditions, such as solar radiation and temperature. Because of this dependency, maximum power point tracking (MPPT) control methods are used in PV systems in order to extract maximum power from the PV panels. This study proposes a controller with a hybrid structure based on angle of incremental conductance (AIC) method and Interval Type-2 Takagi Sugeno Kang fuzzy logic controller (IT2-TSK-FLC) for MPPT. MPPT performance of proposed hybrid controller is evaluated via detailed simulation studies and dSPACE-based experimental study. The results validate that the proposed hybrid controller offers fast-tracking speed, high stability, and robust performance against uncertainties arising from disturbance to inputs of the PV system.

Application of artificial neural network in sizing a stand-alone photovoltaic system: a review

<span>Artificial Neural Network (ANN) techniques are becoming useful in the current era due to the vast development of the current computer technologies. ANN has been used in various fields especially in the field of science and technology. One of the advantage that makes ANN so interesting is the ANN’s ability to learn the input and output relationship even though the relationship is non-linear. In addition, ANN is also useful for modelling, optimization, prediction, forecasting, and controlling systems. The main objective of this paper is to present a review of the ANN techniques for sizing a stand-alone photovoltaic (PV) system. The review in this paper shows the potential of ANN as a design tool for a stand-alone PV. In addition, ANN is very useful to improve the sizing process of the stand-alone PV system. The sizing process is of paramount importance to a stand-alone PV system in order to make sure the system can generate ample electrical energy to supply the load demand.</span>

Different Conventional and Soft Computing MPPT Techniques for Solar PV Systems with High Step-Up Boost Converters: A Comprehensive Analysis

Solar photovoltaic (PV) systems are attracting a huge focus in the current energy scenario. Various maximum power point tracking (MPPT) methods are used in solar PV systems in order to achieve maximum power. In this article, a clear analysis of conventional MPPT techniques such as variable step size perturb and observe (VSS-P&O), modified incremental conductance (MIC), fractional open circuit voltage (FOCV) has been carried out. In addition, the soft computing MPPT techniques such as fixed step size radial basis functional algorithm (FSS-RBFA), variable step size radial basis functional algorithm (VSS-RBFA), adaptive fuzzy logic controller (AFLC), particle swarm optimization (PSO), and cuckoo search (CS) MPPT techniques are presented along with their comparative analysis. The comparative analysis is done under static and dynamic irradiation conditions by considering algorithm complexity, tracking speed, oscillations at MPP, and sensing parameters. The single-diode model PV panel and double-diode model PV panel are also compared in terms of fill factor (FF) and maximum power extraction. Clear insight is presented supporting the suitability of MPPT techniques for different types of converter configurations.

Effects of External Magnetic Field and Air Mass on Space Charge Region Width Extension of a Bifacial Solar Cell Front Side Illumination

The environmental and economical merits of converting solar energy into electricity via photovoltaic cells have caused an ever increasing interest among developed and developing countries to allocate more budget on photovoltaic systems in order to boost up their efficiency in recent years. Besides the material and design parameters, there are several external factors such as magnetic field, air mass, intense light, external electric field, solar spectrum…. that can influence the PV cell’s performance. There have been a handful of studies conducted on the effect of various influential parameters on the efficiency and performance of photovoltaic cells; however none has taken these two parameters (magnetic field and air mass) into account simultaneously. In this 3D study the effects of magnetic field and the air mass illumination on space charge region width extension of a bifacial polycristalline solar cell front side illumination will be elaborated. Based on the columnar model of the grain and the quasi-neutral base, the continuity equation is established and the boundaries conditions are defined in order to use Green’s functions to solve this equation. New analytical expression of charge carriers’ density is found and the diffusion capacitance to the junction is calculated. The normalized carriers’ density plot versus base depth and magnetic field with various air mass illumination are presented and analyzed. The effects of magnetic field and air mass illumination on space charge region width extension are then deducted. The influences of magnetic field and air mass illumination on the junction capacitance and on the reverse of junction capacitance are also shown and analyzed.

Evaluación experimental del rendimiento de los controladores Fuzzy aplicados en un sistema fotovoltaico autónomo

En este artículo se pretende llevar a cabo una evaluación experimental de la utilización de técnicas de asignación de polos en el control Fuzzy aplicadas al flujo de CC en un sistema fotovoltaico autónomo, con el fin de garantizar una condición de estabilidad y un determinado rendimiento para la operación del sistema. Es presentado en la primera etapa del trabajo un modelo matemático que describe adecuadamente el comportamiento dinámico en cuestión fue linealizado el sistema en torno a un punto de operación haciendo uso de las series de Taylor, seguido por el análisis en un ambiente computacional del modelo linealizado del sistema fotovoltaico. Posteriormente, se evaluó de manera experimental el comportamiento dinámico en lazo abierto del sistema fotovoltaico autónomo, observando sus principales variables eléctricas (voltaje y corriente eléctrica). En la segunda etapa del trabajo, se investigó experimentalmente la aplicación de las técnicas de diseño de controladores PI clásico y controladores Fuzzy, con el objetivo de evaluar el comportamiento dinámico del sistema en lazo cerrado y garantizar la estabilidad de este, para pruebas en la variación del voltaje de referencia. Por fin, se presentaron los resultados de la evaluación experimental que demostró un mejor desempeño del controlador Fuzzy en comparación al controlador proyectado por la metodología clásica, cuando utilizada una planta fotovoltaica autónoma

Using fuzzy controller for improvement of power decoupling performance in PV systems

ABSTRACTIn photovoltaic systems in order to ensure the stable operation of the module, ripple value of the input voltage should be mitigated to a small value; for this purpose, the power decoupling circuit can be used. In this work, considering the four-switch-based power decoupling circuit developed, the conventional Proportional-Integral (PI) controller has been replaced with well-known fuzzy controller, which enjoys a wide range of control gain variation, both linear and nonlinear rules' capability, robustness and more flexibility. The operating modes of the circuit are addressed and accordingly the space state model is derived. Then, the proposed controller has been replaced and the performance of the system will be analysed. The power decoupling circuit along with the proposed controller is implemented by MATLAB/Simulink software. The simulation results show the ability of the proposed fuzzy controller to improve the performance of the system in comparison to the conventional PI controller. A deeper comparison of two controllers confirms that the system would experience more accuracy, faster response and lower total harmonic distortion (THD) in presence of the proposed fuzzy controller.

Developed and STM implementation of modified P&O MPPT technique for a PV system over sun

ABSTRACTThe non-linearity of photovoltaic systems and the change in maximum power point with a level of insolation and temperature complicates the tracking of the maximum power point. Several maximum power point tracker methods have been proposed and implemented in literature. The paper studies a modified perturb and observe (P&O) approach for a photovoltaic system in order to extract the maximum power point with more precision, fast speed and avoid the problems caused by the classic P&O method under the change of climatic conditions. This work is tested with a resistive load powered by a photovoltaic generator via a DC/DC converter. These methods are implemented with STM32F4 microcontroller running environment MATLAB/SIMULINK, using a computer incorporating a card DS1104 for visualization. The simulations and experimental results show that the proposed algorithm offers a fast response with smaller stationary oscillations compared to conventional methods.

Shading and Diode Fault Effects on PV Array Performances

The paper presents an experimental and theoretical study on the performance of a photovoltaic system in order to determine the impacts of various external and internal factors on the performance of photovoltaic modules. The proposed model of the photovoltaic module was developed using MATLAB/SIMULINK software. This accurate model shows solar illumination effect on electrical power generated by a PV module. Furthermore, the proposed model also illustrates the effect of partial shading and protection diodes faults on the current–voltage and power–voltage characteristics of a PV module, PV string and PV array. The obtained results and the theoretical basis confirm the reliability and performance of the proposed model.