Photovoltaic Converters Research Articles

Adaptive Frequency-Based Power Management for Off-Grid Hybrid Photovoltaic Converters

The intermittency in photovoltaic systems (PV) can lead to power quality issues, especially in off-grid applications. In these cases, adding an energy storage element helps to cope with the intermittency to provide adequate power to the local load. In this scenario, combining Li-Ion batteries and supercapacitors as a hybrid energy storage system (HESS) is powerful due to the battery's high energy density and the supercapacitor's high power density. The HESS demands adequate power management to operate adequately. This paper proposes an adaptive frequency-based power management for a Li-Ion battery and supercapacitor HESS applied to an off-grid PV converter. The main idea of this strategy is to guarantee a smoother current in the battery and reduce the power dissipation in the HESS. The smoother battery current transition helps avoid excessive battery stress and improves lifespan. The proposed strategy is compared with two other strategies. The results show that the proposed approach is more efficient in reducing the HESS' power dissipation and providing smooth current variations to the battery.

Research on a coordinated control strategy of three-phase photovoltaic converters based on a buck–boost DC link

Research on a coordinated control strategy of three-phase photovoltaic converters based on a buck–boost DC link

Photovoltaic laser power converters producing 21 W/cm2 at a conversion efficiency of 66.5%

Photovoltaic laser power converters producing 21 W/cm2 at a conversion efficiency of 66.5%

Computational survey of optoelectronic properties and half-metallicity in ZnFeMnS: insight from first principles calculations

The electronic structure, optic and magnetic properties of the ZnFeMnS quaternary compound are studied on the basis of band-structure calculations, using full-potential linearized augmented plane wave (FPLAPW) method. The calculations are performed within the generalized gradient approximation (GGA). The calculated results indicate that ternary ZnMnS has an insulating character for the two directions of spin so, in its current form, it is inappropriate for spintronics devices. In contrary, Fe/Mn codoped ZnS is a half-metallic (HM) ferromagnet with a magnetic moment of 9 μB per formula unit. The integer magnetic moment of this compound indicates the stability of its half-metallic behavior. Consequently ZnFeMnS could be a promising dilute magnetic semiconductor for application in spintronic devices. Moreover, we have computed optical properties (absorption coefficient and reflectivity) of the two compounds, and have found a pronounced peak occurring at low energies for ZnFeMnS in all the optical curves due to transition metal (TM) impurity. The improvement of optical properties allows this compound to be used in manufacturing photovoltaic static converter or in display devices.

Structural features and electrical properties of si(al) thermal migration channels for high-voltage photovoltaic converters

The results of a study of the structural features and electrical properties of Si(Al) through thermomigration p-channels in a silicon wafer are presented. Structural studies were performed using X-ray methods of projection topography, diffraction reflection curves and scanning electron microscopy. It is shown that the channel-matrix interface is coherent without the formation of mismatch dislocations. The possibility of using an array of thermomigration p-channels of 15 elements to form a monolithic photovoltaic solar module in a Si(111) silicon wafer based on p-channels with a width of 100 microns with walls in the plane is shown. The monolithic solar module has a conversion efficiency of 13.1%, an idle voltage of 8.5 V and a short-circuit current density of 33 mA/cm².

Results from Cryo-PoF: Power over fiber for fundamental and applied physics at cryogenic temperature

The Power over Fiber (PoF) technology delivers electrical power by sending laser light through an optical fiber to a photovoltaic power converter, in order to power sensors or electrical devices. This solution offers several advantages: removal of noise induced by power lines, robustness in a hostile environment, spark free operation when electric fields are present and no interference with electromagnetic fields.This technology is at the basis of the Cryo-PoF project: an R&D funded by the Italian Institute for Nuclear Research (INFN) in Milano-Bicocca (Italy). This project is inspired by the needs of the DUNE Vertical Drift detector, where the VUV light of liquid argon must be collected at the cathode, i.e. on a surface whose voltage exceeds 300 kV. We developed a cryogenic system, which is solely based on optoelectronic devices and a single laser input line, to power both the Photon Detection devices and its electronic amplifier. The Milano-Bicocca setup employ a commercial GaAs laser source with 2 W maximum power and a photovoltaic power converter with efficiency of ∼ 30% at liquid nitrogen temperature. The results obtained in Milano Bicocca will be presented with emphasis on performance and potential application in the field of applied physics.

Modeling and manufacturing of solar modules of different designs for energy supply of biogas plant

The article presents a description of the modeling and manufacturing of solar modules of photovoltaic, thermal and photovoltaic thermal designs intended to supply energy to a biogas plant intended for the production of biohydrogen and biomethane. Mathematical modeling of the photovoltaic module was carried out and the calculated temperature of the photovoltaic converters was determined, and also the photovoltaic module was manufactured using the process of sealing the photovoltaic converters with a two-component polysiloxane compound. Mathematical modeling of a solar thermal collector with water radiators in the form of a round copper tube, an oval copper tube, as well as a rectangular water cooling channel (“water jacket”) was also carried out, in which pressure losses and the amount of water heating were assessed. The distances between the rectangular channels of the water-cooling radiator for uniform heat removal were determined, and mathematical modeling of the thermal state of a solar thermal collector with a semicircular cross-section of the water-cooling radiator channel was carried out, after which the solar thermal collector was manufactured. Mathematical modeling of the total displacements of the components of a photovoltaic thermal module, the values of which do not exceed acceptable limits, was carried out, after which a photovoltaic thermal module was manufactured using the process of sealing photovoltaic converters with a two-component polysiloxane compound.

Design and Implementation of a Modified Cascaded Z-Source High Step-Up Boost Converter for Photovoltaic (PV) Applications

To improve the voltage gain of step-up converters, the cascaded technique is considered as a possible solution in this paper. By considering the concept of cascading two Z- source networks in a conventional boost converter, the proposed topology takes the advantages of both impedance source and cascaded converters. By applying some modifications, the proposed converter provides high voltage gain while the voltage stress of the switch and diodes is still low. Moreover, the low input current ripple of the converter makes it absolutely appropriate for photovoltaic applications in expanding the lifetime of PV panels. After analyzing the operation principles of the proposed converter, we present the simulation and experimental results of a 100 W prototype to verify the proposed converter performance.

Optimization study of an energy storage system supplied solar and wind energy sources for green campus

This comprehensive study aimed to develop a hybrid system capable of fulfilling the yearly energy demand of the Erciyes University Campus, which amounts to 30.4 GWh. The hybrid system consists of photovoltaic (PV) panels, wind turbines, converters and batteries. An optimization process was carried out to find the most suitable system configuration considering various criteria, including net present cost (NPC), levelized cost of energy (COE), operating cost, initial cost, and cost associated with the battery to be used in the system. The study was also conducted to determine the most suitable energy storage solution for a hybrid system that uses both wind and solar energy sources. This study presented an innovative approach to optimizing the selection of the most suitable energy storage battery for such systems. The wind and solar potential of the specified area were taken from the NASA database using HOMER Pro. The optimized system generated a power of 52.7 MWh with a COE of $0.352, it covered the annual electricity needs of Erciyes University, and the produced excess energy of 18.6 MWh/yr was utilized with the energy storage system.

Power-over-fiber-based optical wireless communication systems towards 6G

This paper reports two implementations of power-over-fiber (PoF) solutions applied to radio-over-fiber (RoF) and optical wireless communication (OWC) systems, in the context of an industrial environment. We employ a conventional 62.5-µm multimode fiber (MMF) to deliver optical power to different communication links based on RoF, free-space optics (FSO), and visible light communication (VLC) technologies aiming beyond 5G (B5G) and 6G applications. First, a 3.5-GHz 5G New Radio (5G NR) signal is transmitted throughout a 20-km single-mode optical fiber (SMF) link using RoF technology. Regarding the PoF system, a 5-W optical power is transmitted through a 100-m MMF link. A photovoltaic power converter (PPC) and a DC/DC converter are employed to convert the power from the optical to the electrical domain and adjust the voltage level, respectively, with the purpose of energizing a remote RoF module. The attainable optical and electrical power transmission efficiencies (OPTE and PTE) are 80% and 19%, respectively. Posterior, a second PoF system is implemented to power a hybrid RoF/FSO/VLC B5G system, comprising a 200-m MMF and an additional DC/DC converter. Over 10.5 W of optical power is transmitted to feed an electrical amplifier (EA) and a white LED from the VLC link. In this configuration, we achieve 78% and 18.5% of OPTE and PTE, respectively. Furthermore, a performance investigation based on the root mean square error vector magnitude (EVMRMS) metric is conducted to evaluate the signal using the implemented PoF systems and a conventional electrical power supply. In the first implementation, a throughput of 600 Mbps is achieved with 100-MHz bandwidth without performance degradation, when compared to the conventional-powered RoF system, whereas, in the second implementation, 60-Mbps throughput is achieved when employing the FSO and VLC technologies simultaneously, demonstrating the applicability and potential of the PoF technique for B5G and 6G industrial communications.

Demonstration of an In-Flight Entertainment System Using Power-over-Fiber

The use of optical fibers is increasing in modern aircraft because this helps solve challenges of size, weight, communication, and reliability in new generation aircraft. This study describes a video and power transmission system using optical fibers (PoF) for in-flight entertainment (IFE) system application. We present the benefits and the limitations of this application, and we perform two practical experiments to demonstrate their performance. We used off-the-shelf devices in the experiments, such as one 15-Watt semiconductor laser operating at 808 nm, GaAs photovoltaic converters, optical transmitters and receivers, and video monitors. The power and video signals were transmitted using two 50-m length multimode fibers. In addition, we proposed and tested two types of energy transformation units (ETUs), which are responsible for supplying electrical energy to the IFE video monitor and the optical fiber receiver.

Battery-less uncertainty-based control of a stand-alone PV-electrolyzer system

Solar photovoltaic (PV) energy is variable. The output power can change considerably in a matter of minutes, imposing challenges on the control of systems connected downstream. The power from these systems can be smoothed using electric storage, potentially increasing the system cost. An alternative is to deliberately curtail the power before it starts to change. This strategy relies on ultra-short-term forecasting to determine the curtailment point. Unfortunately, forecasting is prone to errors and high uncertainty even in the very short-term, leading to control errors. We propose an active power curtailment control strategy for a stand-alone solar photovoltaic system powering an electrolyzer. Our work’s novelty relies on the controller’s ability to deal with large forecasting errors and high uncertainty, combining artificial intelligence for predicting the power ramps and fuzzy logic to account for imperfect prediction. We validated our approach using a hardware emulator of the photovoltaic system, power converter and electrolyzer. Under clear sky conditions, the curtailment results in unnecessary energy loss, while under variable irradiance, the controller successfully smooths the power ramps within 10% of the PV system’s nominal power. Although our approach was designed for a stand-alone system, its concept can be directly applied to grid-connected systems as well.

Enhancing power generation via an adaptive neuro-fuzzy and backstepping maximum-power-point tracking approach for photovoltaic single-ended primary inductor converter system

Abstract The distinct characteristics of photovoltaic generators related to power and current present a complex problem in terms of optimizing their power output. To tackle this, maximum-power-point tracking techniques such as the adaptive neuro-fuzzy inference system are frequently utilized for their swift adaptability and reduced fluctuations. In addition, the backstepping controller is often selected to handle both linear and non-linear systems due to its exceptional reliability. The purpose of this research is to propose an innovative method that merges the adaptive neuro-fuzzy inference system and backstepping controller to refine the tracking of the optimal power point and to bolster the stability of the photovoltaic system in the face of unpredictable scenarios, such as those presented by the Ropp irradiance examination, which utilizes a single-ended primary inductor converter as a stage for power electronics adaptation. Simulations conducted using MATLAB®/Simulink® demonstrate that the combination of adaptive neuro-fuzzy inference system and backstepping controller achieves an impressive efficiency of 99.6% and exhibits fast, robust, and accurate responses compared with other algorithms such as artificial neural networks combined with the backstepping controller and conventional perturb and observe algorithm.

Design and Characterization of a 53.5% Efficient Gallium Indium Phosphide‐Based Optical Photovoltaic Converter under 637 nm Laser Irradiation at 10 W cm−2

High‐power optical transmission (HPOT) technology has emerged as a promising alternative among far‐field wireless power transmission approaches, enabling the transfer of kilowatts of power over kilometer‐scale distances. Its exceptional adaptability allows operation in challenging scenarios where traditional electrical wiring is impractical or unfeasible, thereby opening up a vast array of potential applications previously considered utopian. An important pending assignment in enhancing the performance of laser‐based HPOT systems is achieving efficient photovoltaic conversion of high power densities (≥10 W cm−2). In this sense, there is a pressing need for the advancement of optical photovoltaic converters (OPCs) capable of enduring intense monochromatic irradiances. This work presents the design optimization, manufacturing, and characterization processes of a gallium indium phosphide (GaInP)‐based OPC under varying 637 nm laser power at room temperature. In addition, methods to evaluate the impact of temperature on performance are provided. The findings reveal a maximum efficiency of 53.5% at 10 W cm−2, surpassing literature results for GaInP converters by over 9%abs at those light intensities. Remarkably, this device withstands unmatched irradiances within GaInP OPCs up to 60 W cm−2, maintaining 42.3% efficiency. This study aims to push forward the development of wide‐bandgap power converters with recordbreaking efficiencies paving the way for new applications.

Optimizing the deep learning parameters using metaheuristic algorithms for PV-battery-based DC nanogrids

This paper presents an implementation of metaheuristic algorithms to optimise deep learning neural networks (DNNs) for sensor-less control of photovoltaic (PV) Converters in DC nanogrids. Using a Fixed Forward Neural Network (FFNN), it estimates PV output current (IPV ) based on three days of real data. Given the vulnerability of current sensors in DC system measurements, accurately replicating current sensor data is vital. The data exhibits dynamic nonlinear relationships with inputs like solar irradiance, temperature, and voltage. The study assesses the effectiveness of Evolutionary Mating Algorithm (EMA) and Sand Cat Swarm Optimisation (SCSO), comparing them with Adaptive Moment Estimation (ADAM), Genetic Algorithm (GA), and Particle Swarm Optimisation (PSO). The research leverages these metaheuristic algorithms to optimise machine learning integration, addressing regression estimation problems, and enhancing system reliability by eliminating sensors. Key findings indicate that the EMA-DNN combination achieved remarkable performance, with the lowest Mean Squared Error (MSE) of 0.5906, the lowest Mean Absolute Error (MAE) of 0.4680, and the lowest Mean Absolute Percentage Error (MAPE) of 12.1780%. These results offer valuable insights into how the metaheuristic-DNN approach can solve regression estimation problems and reduce the number of sensors in PV battery-based nanogrids’ control layers.

Evaluation of the efficiency of energy complexes with the production of hydrogen, oxygen, heat and electricity

RELEVANCE of the research. The global trend of decarbonization of the national economies of the leading countries of the world implies an increase in energy production due to renewable energy sources and hydrogen. The most environmentally friendly way to produce hydrogen is the electrolysis of water using wind and solar energy. Combined production of thermal, electric energy, hydrogen and oxygen carried out by energy complexes ensures reduction of harmful emissions and increase of their economic efficiency.METHODS. In solving this problem, the method of computational experiment was used, taking into account the geographical and climatic data of the location of the energy complex, as well as the nature of consumption of thermal, electric energy and hydrogen. The calculation was implemented in Visual Basic.RESULTS. The article describes the relevance of the topic, examines the influence of the installed capacity of photovoltaic converters, geographical, climatic and cost characteristics on the efficiency of the energy complex.CONCLUSION. The structure is determined and a schematic diagram of a multi-purpose energy complex is proposed. A methodology for calculating quantitative and economic indicators of the installation has been developed. In the course of the study, it was noted that there is an optimal value of the installed capacity of a photovoltaic installation, further increase of which is inexpedient from an economic point of view. It was also determined that the combination of hydrogen gas stations based on solar installations with traditional sources of energy supply can reduce the cost of hydrogen produced, which in the future may be a solution to the problem of creating a hydrogen infrastructure.

Power Flow Analysis Using Fuzzy for Single Phase Transformer Less PV System Connected with a Nine-Level Converter

Power electronics technology advancements and growing environmental concerns worldwide have made photovoltaic (PV) systems more visible in distributed generation systems. Photovoltaics, or solar PV, is an important component of solar energy for generating electricity. Grid-connected inverters must be able to regulate the amount of power they inject into the grid, track maximum power points, be highly efficient, and inject currents into the grid with minimal harmonic distortion. Two step-down converters were used to construct an inverter without a single-phase transformer. This study investigates two multi-sequence inverter types that use different voltages and are based on single-phase grid-connected photovoltaic (PV) technology. A new nine-level grid-connected transformer-less photovoltaic converter was proposed in this study. MATLAB was used to construct the complicated FFT simulation using fuzzy logic controls. Analyzing efficiency through simulation in order to enhance efficiency. This work aims to replace PI controllers with fuzzy controlled systems so that single-stage operation can be improved with reduced switches in an economic manner. An improvement of 10% over the existing system is achieved by implementing fuzzy computing.

Design and hardware verification of photovoltaic converter based on adaptive P&O with snubber and BJT circuits

The efficient utilization of renewable energy is a key technology area of high domestic and international concern, and the research and development of DC–DC photovoltaic converters with high conversion efficiency is of great significance for improving performance and reducing the cost of solar power generation systems. In order to improve the conversion efficiency of solar energy, this paper proposes the design of a high-efficiency photovoltaic DC–DC converter with a non-isolated DC–DC converter as the object of the study. Solar power conversion is accomplished by designing a simple and reliable snubber circuit and a triode auxiliary circuit and tracking the maximum power point by combining the perturbation observation method with variable step size. The snubber circuit can effectively suppress the problems of pulse spikes and oscillations, and the triode auxiliary circuit prevents the reverse current and improves the switching speed, which reduces the switching loss and combines with the perturbation observation method with variable step size for fast and stable tracking of the maximum power point. In order to verify the feasibility of the converter, a 600 W prototype is designed. The experimental results show that using the snubber circuit reduces the pulse spike by 4.2 V and the overshoot is reduced by 4.3%. The maximum conversion efficiency is increased by 0.88% with the use of the transistor-assisted circuit, and the tracking efficiency of the MPPT is still stable under cloudy conditions. The maximum conversion efficiency of the prototype is finally measured to be up to 98.12%.

Maximizing thermal and electrical efficiency with thermoelectric generators and hybrid photovoltaic converters: Numerical, economic, and machine learning analysis

In this paper, we introduce an innovative thermoelectric, photovoltaic hybrid system and investigate its performance under various radiation intensities and heat transfer coefficients outside the cavity. Our findings reveal that the proposed system yields twice the power output compared to a traditional plate thermoelectric, photovoltaic hybrid system. Through economic analysis, we project a 45 % reduction in energy cost with this novel structure compared to a full hybrid system. Notably, positioning the hybrid system at the bottom of the cavity, where maximum radiation occurs, is deemed optimal. Our heat transfer analysis demonstrates a significant increase in power generation due to convection outside the cavity, with approximately 9 % of incoming radiation reflected and a further 59 % reflected without the cavity. Utilizing artificial neural networks, we predict thermal and electrical power generation, achieving a Mean Absolute Error (MAE) below 3 % and an R-squared value exceeding 0.98. Additionally, our model's predictions closely match experimental results, validating its accuracy and practical utility. This comprehensive study advances the field by offering a novel hybrid system design that outperforms existing solutions while providing insights into optimizing placement and enhancing power generation through sophisticated modeling techniques.

Modeling and control of a single-phase grid-tied medium-frequency isolated converter for active and reactive power management in photovoltaic applications

A single-phase photovoltaic converter formed by the full-bridge dc–dc converter with a capacitive output filter and a grid-tied full-bridge inverter is studied in this paper. The switched model, the average model based on a modified-conventional approach, and the linear state-space model of the dc stage operating in discontinuous conduction mode are presented and compared with the behavior of the state variables obtained from a simulator. A duty-ratio constraint is obtained from the modified average model, which is eliminated by expressing its dependency on the control and the state variables. In addition, the modeling of the ac stage is carried out in the dq reference frame. Linear controllers are designed to guarantee the maximum power point tracking, the regulation of the dc-link voltage, the injection of the active power generated, and the reactive power management as an ancillary function. The controllers proposed, according to the transfer functions derived from the linear models, are validated via simulation for a 1.41 kVA converter.