Maximum Power Point Voltage Research Articles

Interleaved boost converter voltage regulation using hybrid ANFIS-PID controller for off-grid microgrid

The utilization of a microgrid with a photovoltaic (PV) and wind generation system presents a challenge due to their voltage and power output variations. This problem is majorly addressed within the converter section of the microgrid using maximum power point tracking (MPPT) algorithms and voltage regulation strategies. This paper presents an interleaved boost converter (IBC) modeling and voltage control using a hybrid adaptive neuro-fuzzy inference system-proportional plus integral plus derivative (ANFIS-PID) controller for an off-grid microgrid. The modeling used the interleaving technique to obtain the microgrid’s transfer function (TF) and case study simulation models within MATLAB and Simulink environments. The performance of the ANFIS-PID controller, which regulates voltage in the microgrid, was compared to that of the traditional proportional integral (PI) controller. Results indicated that the hybrid ANFIS-PID controller performed better than the PI controller in terms of reduced settling time, overshoot, rise time, and the ability to address the nonlinear dynamics of the microgrid.

High-Efficiency Photovoltaic Equipment for Agriculture Power Supply

Developing an energy supply based on resources whose use does not spoil the noosphere and the creation of such energy supply of efficient equipment whose operation does not cause any damage to nature and man is an urgent task. The need for such an approach is especially relevant and noticeable in agriculture. This article presents the final results of complex studies of new PV devices and PV systems based on them. Considered in the article are the best solutions we propose to improve PV equipment and make it more attractive for agricultural consumers. The developed vertical and planar high-voltage multijunction silicon PV cells and PV modules on their basis are presented. The first type of modules have a maximum power point voltage of up to 1000 V, specific power of up to 0.245 ± 0.01 W/cm2, and efficiency of up to 25.3% under a concentration ratio range of 10–100 suns. The samples of the second module type (60,156.75 × 156.75 mm PV cells) have an open-circuit voltage of 439.7 V, a short-circuit current of 0.933 A, and a maximum power of 348 W. Additionally, two types of newly designed solar energy concentrators are described in this article: one-dimensional double-wing concentrator ensuring low Fresnel optical losses and multi-zone parabolotoric microconcentrator with the uniform radiation distribution in the focal region, as well as modules based on these concentrators and the developed PV cells. For PV modules, the maximum power degradation is 0.2–0.24% per year in a wet ammonia environment. For concentrating PV modules, this degradation is 0.22–0.37% per year. This article sets out the principles of increasing the efficiency of PV systems by increasing the level of systematization and expanding the boundaries of PV systems. The thus-created PV systems satisfy 30–50% more consumer needs. Thanks to a higher output voltage and other specific features of the developed modules, PV system loss decreased by 12–15%, and maintenance losses also decreased.

A Multisource Collaborative Energy Extraction Circuit for Vibration, Ambient Light, and Thermal Energy With MPPT and Single Inductor

This paper presents a multi-source collaborative energy extraction circuit (MSC-EC) for vibration, ambient light and thermal energy with maximum power point tracking (MPPT) and a single inductor. The MSC-EC can simultaneously extract energy from the piezoelectric transducer (PZT) and Photovoltaic cell (PV) when the peak open-circuit (OC) voltage of the PZT is detected by the peak voltage detector and the voltage of PV is higher than the maximum power point (MPP) voltage of PV (MPP voltage is about 0.7 times the OC voltage of PV), which can also collaboratively extract energy from the thermoelectric generator (TEG) in the extraction of vibration energy or ambient light energy to improve the efficiency of thermal energy extraction. Experimental results indicate that the MPPT efficiency of PV is about 83%, and the maximum energy extraction efficiency of TEG is about 74%. The maximum output power of MSC-EC is 4.2 mW under certain conditions.

A photovoltaic system using supercapacitor energy storage for power equilibrium and voltage stability

<span lang="EN-US">In a photovoltaic system, a stable voltage and of tolerable power equilibrium is needed. Hence, a dedicated analog charge controller for a storage system which controls energy flow to impose power equilibrium, and therefore, voltage stability on the load is required. We demonstrate here our successful design considerations employing supercapacitors as main energy storage as well as a buffer in a standalone photovoltaic system, incorporating a dedicated supercapacitor charge controller for the first time. Firstly, we demonstrated a photovoltaic system employing supercapacitors as main energy storage as well as a buffer in a standalone photovoltaic system. Secondly, we design a constant voltage maximum power point tracker (MPPT) for peak power extraction from the photovoltaic generator. Thirdly, we incorporated a supercapacitor charge controller for power equilibrium and voltage stability through a dedicated analog charge controller in our design, the first of its kind. Fourthly, we analyzed the use of supercapacitor storage to mitigate disequilibrium between power supply and demands, which, in turn, causes overvoltage or under voltage across the load. Lastly, we then went ahead to demonstrate the control of the energy flow in the system so as to maintain rated voltage across a variant demand load.</span>

An Maximum Power Point Tracker of Photovoltaic Module Arrays Based on Improved Firefly Algorithm

In this paper, an improved firefly algorithm (FA) was proposed for application on photovoltaic module arrays (PVMAs) with partial modules under shading so that the maximum power point tracking (MPPT) could be implemented. Firstly, a new model of high voltage step-up converter was developed for executing the MPPT of the PVMA. For the energy storage inductor of the developed converter, the architecture of the coupled inductor was adopted so that the converter switch did not need to operate under an excessive duty cycle, which could increase the voltage gain and reduce the ripple of the output voltage at the same time. To prevent shading on the partial modules within the PVMA and generate more than one peak on the power-voltage (P-V) output characteristic curve, where the conventional MPPT could only track the local maximum power point (LMPP) and reduce the output power of the PVMA, the maximum power tracker, based on the improved FA, was proposed in this paper. Such a tracker could perform an automatic online adjustment on the FA iteration parameters, according to the slope of the P-V output characteristic curve, for the PVMA and, at the same time, perform at 0.8 times of the maximum power point (MPP) voltage for the module array under standard test condition (STC), serving as the initial tracking voltage for implementing the global maximum power point tracking (GMPPT). Lastly, the actual test results were applied to verify that the proposed converter indeed contained a high voltage step-up and low-ripple output voltage. The improved FA could also track GMPP faster and further improve the power-generating efficiency of the PVMA.

Power Gain from Energy Harvesting Sources at High MPPT Sampling Rates.

Energy harvesting (EH) sources require the tracking of their maximum power point (MPP) to ensure that maximum energy is captured. This tracking process, performed by an MPP tracker (MPPT), is performed by periodically measuring the EH transducer's output at a given sampling rate. The harvested power as a function of the sampling parameters has been analyzed in a few works, but the power gain achieved with respect to the case of a much slower sampling rate than the EH source's frequency has not been assessed so far. In this work, simple expressions are obtained that predict this gain assuming a Thévenin equivalent for the EH transducer. It is shown that the power gain depends on the relationship between the square of AC to DC open circuit voltage of the EH transducer. On the other hand, it is proven that harvested power increases, using a suitable constant signal for the MPP voltage instead of tracking the MPP at a low sampling rate. Experimental results confirmed the theoretical predictions. First, a function generator with a series resistor of 1 kΩ was used, emulating a generic Thévenin equivalent EH. Three waveform types were used (sinus, square, and triangular) with a DC voltage of 2.5 V and AC rms voltage of 0.83 V. A commercial MPPT with a fixed sampling rate of 3 Hz was used and the frequency of the waveforms was changed from 50 mHz to 50 Hz, thus effectively emulating different sampling rates. Experimental power gains of 11.1%, 20.7%, and 7.43% were, respectively, achieved for the sinus, square, and triangular waves, mainly agreeing with the theoretical predicted ones. Then, experimental tests were carried out with a wave energy converter (WEC) embedded into a drifter and attached to a linear shaker, with a sinus excitation frequency of 2 Hz and peak-to-peak amplitude of 0.4 g, in order to emulate the drifter's movement under a sea environment. The WEC provided a sinus-like waveform. In this case, another commercial MPPT with a sampling period of 16 s was used for generating a slow sampling rate, whereas a custom MPPT with a sampling rate of 60 Hz was used for generating a high sampling rate. A power gain around 20% was achieved in this case, also agreeing with the predicted gain.

Modelling of a PV system: a case study Kosovo

<span lang="EN-US">The modeling of a photovoltaic (PV) system used for the needs of the industrial sector is presented in this paper. Its analysis was done analytically using real one-year measurements during the system monitoring period and software-wise using premium PV*SOL software. System generated energy, maximum power point (MPP) voltage, final yield and average generated power are included in the analysis. The highest summer energy produced for real conditions is in July with 2811.86 kWh, the highest MPP voltage also presented in July with a value of 400 V. The final yield with a value of 103.07 kWh/kWp and the highest average power 16.6 kW as well. during the month of July. Where it can be seen that due to the Mediterranean atmospheric conditions in the place of application of the PV system, during the summer months the parameters are higher than during the winter months.</span>

Application of non-contact electrostatic voltmeter to identify underperforming modules in grid-connected photovoltaic systems

This paper presents a technique that uses maximum power point voltage (Vmpp) to quantitatively identify the underperformance photovoltaic (PV) modules in grid-connected PV systems using a non-contact Electrostatic Voltmeter (ESV). Unlike the other existing techniques, this technique doesn't require the module's disconnection from the grid or other modules in a string. First, in this work, the ESV was tested for the application of thin film modules (off-grid and on-grid), and a comparison of the ESV sensed voltages with the voltmeter voltage values indicated a difference of less than 2%. Second, the least power-producing module was identified by the IV curves analysis and the Vmpp technique, and the results were compared. The comparison of both characterization tools quantitatively pointed out to the same module as the lowest performance module. It is a contactless, time and cost-saving method and is useful for quantitatively determining defective and poor-performing PV modules in large power plants where continuity of the energy production is preferred during the testing.

Photovoltaic MPPT algorithm based on adaptive particle swarm optimization neural-fuzzy control

Since the BP neural network has poor performance and unstable learning rate in the maximum power point tracking (MPPT) algorithm of photovoltaic (PV) system, an adaptive particle swarm optimization BP neural network-fuzzy control PV MPPT algorithm (APSO-BP-FLC) is proposed in this paper. First, the inertia weight, learning factor and acceleration factor of particle swarm optimization (PSO) are self-updating, and the mutation operator is adopted to initialize the position of each particle. Second, the APSO algorithm is used to update the optimal weight threshold of BP neural network, where the input layer is irradiation and temperature, and the output layer is the maximum power point (MPP) voltage. Third, the fuzzy logical control (FLC) is employed to adjust the duty cycle of Boost converter. The inputs of FLC are voltage difference and duty ratio D(n-1) at the previous time, and the output is duty ratio D(n). Moreover, D(n-1) is optimized by |dP/dU| to improve the search range of FLC. The irradiation, temperature and MPP voltage of PV cell are adopted as the datasets for simulation in a city in Shaanxi province, China. Simulation results show that the proposed MPPT algorithm is superior to the APSO-BP, FLC and perturbation and observation (P&O) algorithm with tracking performance, steady state oscillation rate and efficiency. In addition, the efficiency of proposed MPPT algorithm is improved by 0.37%, 6.2%, and 6.8% as compared to APSO-BP, FLC and P&O algorithm.

A Convolutional Neural Network-Based Maximum Power Point Voltage Forecasting Method for Pavement PV Array

The shadows formed by fast-moving vehicles on a pavement PV array exhibit complex dynamic random distribution characteristics, which can cause a dynamic multipeak PV curve. Dynamic vehicle shadow will cause a reduction in pavement PV power, so the question is how to maximize the power in such conditions by operating at different maximum power point (MPP) quickly and continually. To address this issue, this article proposes an MPP voltage forecasting method based on convolutional neural network (CNN). This method inputs the environmental information of pavement PV array into the proposed CNN model for learning and then uses this model to forecast the MPP voltage. Finally, simulation and experimental test with ResNet, MLP, and CNN methods are carried out and the comparison results show that this model can accurately predict the MPP voltage of pavement PV array under different vehicle shading conditions.

Modeling and Control of PV Emulator with Different Controllers and Transient Load Conditions

To keep up with the pace of renewable energy, PV Emulators are encouraged during the design and installation stages. Short circuit current, maximum power point and open circuit voltage are required to analyze the complete characteristic plot of PV panel.This paper focuses on the modeling and control of PV Emulators, as well as the comparison of the results obtained by implementing P,PI, PID and FOPID as conventional controllers with AI-based PSOPI, PSOPID and ANFIS controllers. This work will aid in minimizing time, cost and on-site constraints, allowing timely installation of PV panels after covid. Another distinguishing feature of this paper is the comparative analysis of designed models with various control strategies and their associated performance indices over complete range of PV characteristics.

Computational Analysis of Temperature Effects on Monocrystalline PV Module using MATLAB

The world has moved from fossil fuels to renewable energy resources due to adverse environmental impacts, limited sources, and economic issues. It is not necessary that renewable energy sources have always led to many advantages but have drawbacks like weather dependency, unreliability, storage problems, and upfront costs. This study focuses on one of the major types of RES solar PV systems. The data is used from the specification of solar modules at Sukkur IBA University Sindh Pakistan. Solar photovoltaic output depends upon the weather conditions which vary from time to time resulting in variation in irradiance, temperature, power, and efficiency. This paper aims to observe the effects of the temperature ranging from 1 to 55°c on the efficiency of the monocrystalline photovoltaic module using MATLAB/Simulink. The performance parameters could be Open Circuit Voltage (VOC), Short Circuit Current (ISC), Maximum Power Point Current (IMP), Maximum Power Point Voltages (VMP), Fill Factor (FF), and Efficiency (η). Results from the simulation show that the estimated variation of silicon solar cell parameters such as VOC, IMP, series resistance, FF, and η decrease frequently with increasing temperature. And some parameters such as ISC, IMP, and temperature of the panel increase with rising ambient temperature.World has moved from fossil fuels to renewable energy resources due to adverse environmental impacts, limited sources, and economic issues. It is not necessary that renewable energy sources have always led to many advantages but have drawbacks like weather dependency, unreliability, storage problems and upfront costs. This study focusses on the one of the major types of RES solar PV system. The data is used from the specification of solar modules at Sukkur IBA University Sindh Pakistan. Solar Photovoltaic output depends upon the weather conditions which varies time to time resulting variation in irradiance, temperature, power, and efficiency. This paper aims to observe the effects of the temperature ranging 1 to 55°c on the efficiency of the mono-crystalline photovoltaic module using MATLAB/Simulink. The performance parameters could be as open circuit voltage (VOC), short circuit current (ISC), maximum power point current (IMP), maximum power point voltages (VMP), Fill Factor (FF) and efficiency (η). Results from simulation shows that the estimated variation of silicon solar cells parameters such as open circuit voltages, maximum power point voltages, series resistance, fill factor and efficiency decrease frequently with increasing temperature. And some parameters such as short-circuit current, maximum power point current and temperature of the panel increases with rising ambient temperature.

Feasibility of Photovoltaic Module Single-Diode Model Fitting to the Current–Voltage Curves Measured in the Vicinity of the Maximum Power Point for Online Condition Monitoring Purposes

Photovoltaic system condition monitoring can be performed via single-diode model fitting to measured current–voltage curves. Model parameters can reveal cell aging and degradation. Conventional parameter identification methods require the measurement of entire current–voltage curves, causing interruptions in energy production. Instead, partial curves measured near the maximum power point offer a promising option for online condition monitoring. Unfortunately, measurement data reduction affects fitting and diagnosis accuracy. Thus, the optimal selection of maximum power point neighbourhoods used for fitting requires a systematic analysis of the effect of data selection on the fitted parameters. To date, only one published article has addressed this issue with a small number of measured curves using symmetrically chosen neighbourhoods with respect to the maximum power. Moreover, no study has determined single-diode fit quality to partial curves constructed via other principles, e.g., as a percentage of the maximum power point voltage. Such investigation is justified since the voltage is typically the inverter reference quantity. Our work takes the study of this topic to a whole new scientific level by systematically examining how limiting the current–voltage curve measuring range to maximum power point proximity based on both power and voltage affects single-diode model parameters. An extensive dataset with 2400 measured curves was analysed, and statistically credible results were obtained for the first time. We fitted the single-diode model directly to experimental curves without measuring outdoor conditions or using approximations. Our results provide clear guidance on how the choices of partial curves affect the fitting accuracy. A significant finding is that the correct selection of maximum power point neighbourhoods provides promising real-case online aging detection opportunities.

Optimization of solar energy using MPPT techniques and industry 4.0 modelling

Solar energy is the energy discharged by the sun in the form of radiation of light which is then utilized by human beings using a diversity of method such as photovoltaic cells. It is unlimited source of energy such as solar energy does not belongs to anybody and so it is at no cost. The quantity of solar energy acknowledged by the world was considered to be 3000–50,000 EJ, which is much superior to the total world energy utilization of 600 EJ. Maximum Power Point Tracking (MPPT) can be integrated in controlling charge and further used to take out highest extractable and obtainable output from photovoltaic cells depending on few circumstances. The particular input for Photovoltaic module is capable of generating highest possible output power is called MPP (Maximum power point) or highest voltage. Maximum power changes with Sun's energy parameter of required temperature of PV module. Along with dissimilar tracking technique with P-O methods etc. Furthermore, several components were used to compute input parameters which had their own uncertainty. This uncertainty was removed by using devices equipped with sensors comprising of industry 4.0 techniques. The values were delivered back by sensors enabling error free solar energy estimation. This delivers admirable outcome and hence are employed. This system can be developed for charge controller by employing a microcontroller-based circuit for DC-DC buck converter and introducing MPPT.

A unified bus voltage regulation and MPPT control for multiple PV sources based on modified MPC in the DC microgrid

This study proposes a unified voltage regulation and maximum power point tracking (MPPT) method for photovoltaic (PV) sources in islanded direct current (DC) microgrids based on modified model predictive control (MPC). The method enables the PV sources to track the maximum power and serve as voltage sources for DC-bus voltage regulation when their available power is sufficient. Based on the proposed modified predictive model, the desired duty cycles can be calculated and directly applied to the PV sources in a constant switching frequency without a modulator. Real-time laboratory tests show that the PV sources can support the DC-bus voltage without energy storage (ES) and can proportionally share the load. Moreover, power oscillations and voltage ripples of the modified MPC get greatly attenuated compared with the traditional MPC under the same sampling frequency.

THE INFLUENCE OF TILT ANGLE ON THE PERFORMANCE OF SOLAR PANELS AS A SMART HELMET POWER SUPPLY IN A MOTORCYCLE SAFETY SYSTEM

The performance of a solar panel module is strongly influenced by its orientation and tilt angle. Tests have been carried out to track variations in the performance of the solar panel module and electrical parameters at various angles of inclination in the conditions of Karawang and Bogor. There are two experimental modes: 1) a varying slope module under a constant irradiance level, 2) a varying irradiation intensity at the optimal tilt setting. For the former schematic, the irradiation levels were carried out at 2 different locations, and for the later setup, the angle of inclination of the module was varied from 90° and 180° by using a single axis tracer At 90° tilted angle in Karawang test place at rest condition, morning experiment give the result of 5,69V on average while in Bogor the experiment gives 5,46V on average. At 180° tilted angle in Karawang test place at rest condition, morning experiment give the result of 5,49V on average while in afternoon experiment afternoon 3.026V on average. In Bogor test place morning experiment give solar panel 5,2V on average and 3,33V at afternoon experiment. In the electrical parameters of the module, the open circuit voltage, short circuit current, maximum power point voltage and maximum power point current decrease substantially with increasing slope angle, while the charge factor decreases somewhat gradually. Tests in both Karawang and Bogor in the afternoon and afternoon confirmed that the optimal tilt angle on cloudy on with UV index between 1-2 in the morning and 3-4 in the afternoon on average is 180° tilted and directing the solar panel module at this angle will maximize the captured solar energy and thereby improve its performance.

Photovoltaic Fuzzy Logical Control MPPT Based on Adaptive Genetic Simulated Annealing Algorithm-Optimized BP Neural Network

The P–U characteristic curve of the photovoltaic (PV) cell is a single peak curve with only one maximum power point (MPP). However, the fluctuation of the irradiance level and ambient temperature will cause the drift of MPP. In the maximum power point tracking (MPPT) algorithm of PV systems, BP neural network (BPNN) has an unstable learning rate and poor performance, while the genetic algorithm (GA) tends to fall into local optimum. Therefore, a novel PV fuzzy MPPT algorithm based on an adaptive genetic simulated annealing-optimized BP neural network (AGSA-BPNN-FLC) is proposed in this paper. First, the adaptive GA is adopted to generate the corresponding population and increase the population diversity. Second, the simulated annealing (SA) algorithm is applied to the parent and offspring with a higher fitness value to improve the convergence rate of GA, and the optimal weight threshold of BPNN are updated by GA and SA algorithm. Third, the optimized BPNN is employed to predict the MPP voltage of PV cells. Finally, the fuzzy logical control (FLC) is used to eliminate local power oscillation and improve the robustness of the PV system. The proposed algorithm is applied and compared with GA-BPNN, simulated annealing-genetic (SA-GA), particle swarm optimization (PSO), grey wolf optimization (GWO) and FLC algorithm under the condition that both the irradiance and temperature change. Simulation results indicate that the proposed MPPT algorithm is superior to the above-mentioned algorithms with efficiency, steady-state oscillation rate, tracking time and stability accuracy, and they have a good universality and robustness.

Effect of tilt angle on the performance and electrical parameters of a PV module: Comparative indoor and outdoor experimental investigation

• Indoor and outdoor investigation on the effect of tilt angle on PV performance. • Experimentally fixed optimum tilt angle of 15° for real-time Malaysian conditions. • Every 5° change in tilt cause a cell temperature drop by 2.70°C at outdoor. • PV electrical parameters emanate significantly low at indoor conditions. Photovoltaic (PV) system's performance is significantly affected by its orientation and tilt angle. Experimental investigation (indoor and outdoor) has been carried out to trace the variation in PV performance and electrical parameters at varying tilt angles in Malaysian conditions. There were two experimental modus: 1) varying module tilt under constant irradiation level, 2) varying irradiation intensity at the optimum tilt set up. For the former scheme, the irradiation level was maintained at 750 W/m 2 , and for the later arrangement, the module tilt angle was varied from 0 o to 80 o by means of a single-axis tracker. Results show that under constant irradiation of 750 W/m 2 , every 5 o increase in tilt angle causes a power drop of 2.09 W at indoor and 3.45 W at outdoor. In contrast, for the same condition, efficiency decreases by 0.54% for indoor case and by 0.76% at outdoor. On the other hand, for every 100 W/m 2 increase in irradiation, solar cell temperature rises by 7.52°C at indoor and by 5.67°C at outdoor. As of module electrical parameters, open-circuit voltage, short-circuit current, maximum power point voltage and maximum power point current drops substantially with increasing tilt angle, whereas fill factor drops rather gradually. Outdoor experimental investigation confirms that the optimum tilt angle at Malaysian conditions is 15 o and orienting a PV module this angle will maximize the sun's energy captured and thereby enhance its performance.

Investigation of the Temperature Sensitivity of 20-Years Old Field-Aged Photovoltaic Panels Affected by Potential Induced Degradation

One effect of moisture ingress on solar panels is potential induced degradation (PID). Solar panels affected by PID experience large leakage currents between the solar cells and the module’s frame, which leads to substantial power degradation. In the present work, the temperature coefficients of 3 old PV panels affected by PID were investigated. In the electroluminescence images, solar cells nearer to the edge of the modules appear darker due to ohmic shunting. IR thermal images acquired under clear sky outdoor conditions show that the majority of the warmer cells (hotspots) were located closer to the edge of the modules. The difference in cell temperature (∆T) due to PID effect ranges from 7 °C to 15 °C for the 3 field-aged modules. The average temperature coefficient of efficiency (βηm) was found to be −0.5%/°C. Also, it was observed that the temperature coefficients of open circuit voltage (βVoc = −0.4%/°C), maximum power point voltage (βVmpp = −0.5%/°C), and fill factor (βFF = −0.2%/°C), were the underlying factors for the degradation in the Pmax of the old solar panels affected by PID. This accounted for an average 1.2%/year overall degradation in the efficiency of these modules. Most notably, it was discovered that the PV modules affected by PID show negative temperature coefficients of maximum power point current (βJmpp) due to large leakage currents. This observed negative βJmpp we believe is characteristic of PV panels affected by PID.

A hybrid current modulated DAB DC/DC converter for connecting PV modules to DC grid considering partial shading

The Maximum Power Point (MPP) voltage of a PV module can decrease significantly under partial shading conditions. Hence, high voltage gain converters are required to connect PV modules to DC grid. Generally, two-stage boost-based converters are preferred for their simplicity. However, they utilize a high number of semiconductors with high withstand voltages, and require an input filter inductance. In this paper, a hybrid current modulation that uses triangular (TRM) and trapezoidal (TZM) current modulations is proposed for Dual Active Bridge (DAB) converter to connect PV modules to DC grid. The proposed converter provides soft switching, low number of semiconductors, and reduces the breakdown voltages of input semiconductors compared with the two-stage Boost Full Bridge Isolated Converter (BFBIC). It also eliminates the input inductance and uses a 36% smaller core size than the total core size of BFBIC. The proposed converter is realized by an experimental prototype, and analyses are verified.