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Under partial shading conditions (PSCs), the output characteristic curve of PV system fluctuates, hence contains multiple peaks. The higher efficiency of the Global Maximum Power Point(GMPP) tracking technique becomes a must to the Photovoltaic(PV) system, therefore, an algorithm based on Tuna Swarm Optimization (TSO) is proposed in this study. Then, it is applied to track the global MPPT of PV system under partial shading conditions, six shading scenarios have been considered. This method is on a PV system consisting of five panels that are formed in a MATLAB/Simulink platform. And then Particle Swarm Optimization(PSO) algorithm, Black Widow Spider(BWO), Squirrel Search Algorithm(SSA) and TSO are compared, the outcomes are analyzed in detail. The proposed algorithm reached maximum power of over 97% under the six PSCs. And the response time in all six scenarios were between 0.2s and 0.4s. This value is good compared to the other three algorithms. Finally, hardware verification demonstrate the performance and feasibility of the proposed MPPT. The proposed method reached maximum power over 91% in the Hardware-in-loop(HIL) and Rapid Control Prototype(RCP) platform. [Display omitted] • A novel MPPT method based on TSO technique is proposed, which can operate stably and efficiently in PV system. • TSO has not been reported in the application of MPPT for PV systems under shading conditions. • Improve various performance indicators in the MPPT process, such as convergence speed and tracking accuracy are significantly improved, tracking efficiency is effectively improved, and the process is stable. • Six shading scenarios and three other control methods are constructed to compare and analyze the performance parameters of all methods in MATLAB/Simulink platform. • The PV system model is divided into three parts. The three parts are uploaded into Starsim-HIL, FPGA and Starsim-RCP. [ABSTRACT FROM AUTHOR]

• Amount of power processing determines the efficiency in power converter. • There are two types power processing techniques: full power and differential power. • Control requirement and complexity can be negligible in full power processing. • Differential power processing is low rated and cost. • Photovoltaic power optimizers on the market usually support module-based MPPT. Maximum power point tracking (MPPT) procedure in photovoltaic (PV) systems can be realized with many different methods. Especially in arrays consisting of PV modules (PVMs) connected in series; the maximum power point (MPP) may change due to partial shading conditions (PSC), aging, degradation, fabrication production differences etc. In addition, even in small power systems containing a single PVM, the difference in shading and irradiation between submodules affects the maximum power potential of the PVM. In this study, power electronics-based power processing methods in distributed MPPT (DMPPT) systems are emphasized. Power electronics-based hardware MPPT solutions are examined in two groups as full power processing (FPP) and differential power processing (DPP). In addition, commercially available power optimizers have been examined under many criteria. The literature on the subject has been analyzed in a broad perspective, and it has been comprehensively evaluated according to criteria such as power processing level, converter configuration, MPPT algorithm, MPPT application level and control approaches. This study is an important guide for scientists and hardware engineers doing academic studies on the subject. This study, which examines the topologies and control approaches used in application-oriented studies, has the feature of triggering future studies. The features that commercial power optimizers should have and the examination of the products in the market within the framework of some criteria is one of the original aspects of the study. It is expected that this study will contribute to the PV industry in building applied and building integrated studies, where extreme shading scenario occurs. [ABSTRACT FROM AUTHOR]

• Typical DC microgrid configuration uses two operation modes: normal and saturated. • This design problem implies a large-scale of photovoltaic-battery system applications. • Saturation management strategy involves dissipation system and regenerative break. • Power balance control ensures the energy distribution available from sources to load. • The control includes two methods: maximum power point tracking and power load tracking. Because of the considerable fluctuations of the power generation and load in Photovoltaic (PV) - Battery (BAT) systems, power management strategies become indispensable since BAT is needed to maintain the generation/load balance, and to regulate the DC bus. Indeed, energy management strategies must take into account the limits of the system, i.e. the nominal PV/BAT power rating and the state of charge (SOC) of BAT. However, the actual use might be different from the intended one, forcing the system to attain its limits. This paper is mainly focused on the limits control and energy saturation management applying to a sample standalone DC micro grid. It consists to share accurately the variable power loads among sources according to their ratings, including the regenerative breaking in minimum SOC'BAT case and the full supply of power load demand in maximum SOC'BAT case. Furthermore, the DC bus voltage is regulated to its predefined level, as a design parameter. The proposed control algorithms are detailed, and the system design during overstress and nominal conditions is given. The main advantage of this algorithm is its simplicity. The efficiency of the control strategy for energy saturation management is verified and analyzed through simulation/experimental system using Matlab/Simulink and DSpace. The results obtained show that the proposed technique can intelligently manage the energy flows and thus ensure that the system operates correctly and safely in the different modes: normal mode and saturated mode. [ABSTRACT FROM AUTHOR]

• Solar PV water pumping system was analyzed. • Performance equation for the system was generated. • Hourly variation in electrical performance of the system was determined. • Hourly variation in hydraulic performance of the system was studied. This paper proposes a method for the modelling, simulation and analysis of solar PV water pumping system. A submersible type variable speed DC water pump system is considered in this study under different pumping heads (50 m, 60 m and 70 m) and for 8S × 3P PV array configuration. The hourly electrical performance of the PV array was estimated from the maximum power points of the I-V curves, as the maximum power point tracking (MPPT) controller continuously optimizes the output power of the PV array. The performance equation which relates the flow rate of the pump with pump head and power input to the pump is modelled from the manufacturer's performance curve with curve fitting technique. Using the generated equation and the calculated hourly power output data, the hourly performance of the solar driven water pump system was estimated for of different pump head. The analysis and simulation results show that a lower pump head results in higher flow rate regardless of the variation in solar irradiation level. The obtained result also indicated that an increase in solar radiation intensity resulted in an increasing of the pump flow rate, pump efficiency and system performance. [ABSTRACT FROM AUTHOR]

• Eight global maximum power point techniques are evaluated experimentally. • The performance of the MPPT algorithms is investigated under partial shading. • The ability to extract the maximum power, efficiency, and settling time are analyzed. Shading plays an important role in the operation of photovoltaic (PV) systems, especially when one of the cells or modules in the string is submitted to lower irradiance levels due to partial shading (PS). As a result of this condition, the cells or modules absorb the power generated by the unshaded parts, thus causing hot spots that can irreversibly damage the device. In order to mitigate this problem, bypass diodes (BDs) are often connected in parallel with the cells or modules to limit the reverse voltage and the power loss as a consequence. However, the occurrence of multiple peaks in the power versus voltage (P - V) curve is observed. Although conventional maximum power point tracking (MPPT) algorithms are successfully used when PV arrays operate under uniform irradiance conditions, they may fail to determine the global maximum power point (GMPP) if PS comes to occur. Considering that several MPPT algorithms for the operation under PS have been proposed during the last few years, this work presents a detailed analysis of some techniques dedicated to global maximum power tracking (GMPPT), aiming at defining which one presents the best performance. A dc-dc single-ended primary inductance converter (SEPIC) associated with microprocessor ATmega328P is employed to track the GMPP and assess the operation of each technique experimentally. The performance of the well-known perturb and observe (P&O) algorithm is also evaluated under PS condition for comparison purposes. [ABSTRACT FROM AUTHOR]

• A new photovoltaic hydrogen production system topology has been proposed to reduce the energy loss of the entire system during energy transmission. Stable operation can be achieved. • Based on the three-phase shift modulation of the DAB converter, MPPT control of photovoltaics is achieved, achieving efficient utilization of photovoltaics at the lowest loss of the converter. • The equivalent impedance of DAB coupled PEM electrolytic cells was studied, and the reasons for the excessive input current of the electrolytic cells under TPS modulation of MPPT were analyzed. • Considering the time delay characteristics of the electrolytic cell and the electrical spring characteristics, a voltage pre control strategy was designed to effectively reduce the input current ripple of the electrolytic cell and achieve load matching when the photovoltaic output fluctuates. The adaptive adjustment of the input current in proton exchange membrane electrolyzers (PEMEL) can provide several benefits, including the enhancement of PEMEL efficiency and the extension of its operating lifespan within an optimal range. This study presents a novel configuration for a photovoltaic (PV) hydrogen generation system that allows for the direct integration of PV. Moreover, the utilization of the triple-phase shift (TPS) modulation technique is implemented in order to achieve maximum power point tracking (MPPT) control within dual active bridge (DAB) DC/DC converters. The proposed strategy offers a pre-control approach for active adjustment of flexible loads to mitigate the mismatch between power output and load caused by fluctuations in renewable energy sources. This mismatch can lead to excessive current ripple, which in turn can impact the safe functioning of the PEMEL. In tandem with the analysis of the factors that contribute to ripple and the properties of the Electrical Spring (ES), relevant multiple variables are selected as control signals for the control strategy. This is done to effectively regulate the magnitude of non-essential loads and consequently reduce the ripple in the PEMEL system. The use of the ES pre-control technique effectively addresses the issue of delayed response of the PEMEL to PV oscillations, which is attributed to the large time-lag characteristics of electrolyzers. The simulation results at steady-state conditions and sudden changes in lighting conditions demonstrate concurrently that the overall control strategy yields a reduction in current stress in the DAB to 30.09% and 51.59%, respectively, enables MPPT in PV systems, and decreases the input current ripple of PEMEL to 80.1% and 57.67%, showing stronger anti-disturbance ability. [ABSTRACT FROM AUTHOR]

• A modified INC using p-v curve region shifting based MPPT algorithm is developed to track global power peak under partial shading conditions. • Modeling of SEPIC converter is described to implement an adaptive variable sampling time for faster operation of proposed tracking algorithm under partial shading conditions. • Irradiance forecast is also introduced in MPPT algorithm flow chart to decide the starting point on p-v curve from where the tracking begins. • Proposed algorithm is validated on TMS320F28027 LAUNCHPAD using Process-In-the-Loop approach for practical applications. This paper proposes modifications to Incremental Conductance (INC) concept to track global maximum power point under partial shading conditions of photovoltaic (PV) systems. The proposed algorithm determines the p-v curve as a combination of regions, and tracks global peak by shifting operating point from one region to another without using any nature inspired intelligent techniques like particle swarm optimization (PSO) and other related algorithms. Additionally, a variable sampling time concept is introduced in the algorithm for faster tracking of global peak under extreme partial shading conditions arising due to random shading pattern of PV modules. MATLAB /SIMULINK platform was used to model PV module in conjunction with SEPIC converter for battery charging application. Proposed algorithm was tested under different shading patterns to observe the tracking speed and accuracy of the tracker. Finally, the concept behind proposed algorithm was validated on TMS320F28027 LAUNCHPAD DSP board using Process-in- loop (PIL) approach for practical applications. Results demonstrate the usefulness of proposed algorithm in terms of less computational time as compared to latest reported work in this field. [ABSTRACT FROM AUTHOR]

Highlights • This paper proposes a few novel MPPT techniques, which include Adaptive Cuckoo Search Optimization Algorithm (ACOA), General Regression Neural Network GRNN) with Fruit fly Optimization algorithm (FFOA), and Dragonfly Optimization Algorithm (DFO) to track the MPP under various weather condition. • The proposed techniques enhance the performance of the PV system, save the computational time and greatly reduce the oscillation around the global maximum power point. • For the validation of the proposed techniques, comparative analysis of their results with the Bio-inspired Particle Swarm Optimization (PSO), Cuckoo Search Optimization (CS), Artificial Bee Colony Algorithm (ABC) and PSO Gravitational search Optimization (PSOGS) is presented. • The comparison shows that proposed techniques are better in term of quick power tracking, stability, and high efficiency under various weather conditions, and also demonstrates that the proposed techniques can efficiently locate the GM (global maxima) under the PS and Dynamic Partial Shading (DPS) conditions. Abstract In PV systems, the non-uniform irradiance and diversified unpredictable weather conditions fall into the category of Partial Shading (PS). Under PS, it is challenging for PV systems to obtain the maximum output through Maximum Power Point Tracking (MPPT), i.e., the parameters of the controller are adjusted online to yield the maximum power. In the literature, various techniques have been proposed to track the MPP (Maximum Power Point) under the uniform irradiance. On the contrary, few techniques have been proposed to efficiently track MPP under PS. In this paper, a few novel MPPT techniques have been proposed, which include Adaptive Cuckoo Search Optimization Algorithm (ACOA), General Regression Neural Network GRNN) with Fruit fly Optimization algorithm (FFOA), and Dragonfly Optimization Algorithm (DFO) to track the MPP under various weather condition. The proposed techniques enhance the performance of the PV system, save the computational time and greatly reduce the oscillation around the global maximum power point. For the validation of the proposed techniques, comparative analysis of their results with the Bio-inspired Particle Swarm Optimization (PSO), Cuckoo Search Optimization (CS), Artificial Bee Colony Algorithm (ABC) and PSO Gravitational search Optimization (PSOGS) is presented. The comparison shows that the proposed techniques are better in term of quick power tracking, stability, and high efficiency under various weather conditions. The comparison also demonstrates that the proposed techniques can efficiently locate the GM (global maxima) under the PS and Dynamic Partial Shading (DPS) conditions. Furthermore, statistical analysis is presented to check the stability, sensitivity and robustness of the proposed techniques. [ABSTRACT FROM AUTHOR]

Highlights • Considering renewable energy resources. • Proposing fuzzy logic controllers (FLC) to improve the MPPT in PV system. • Implementing fuzzy logic controller to improve the dynamic performance. • Reporting optimized using Firefly Algorithm (FA) to generate the proper duty cycle. Abstract P-V characteristic of the solar cells are nonlinear and depends on the environmental conditions such as irradiations, sunlight incident angle, cell temperature, and load conditions. Therefore it is crucial to operate the photovoltaic module at its maximum power point (MPP) all the time. Hence, a Maximum power point tracking (MPPT) methods are used to maximize the PV module output power by tracking continuously the MPP. In this paper, fuzzy logic controllers (FLC) are designed for maximum power point tracking (MPPT) in a photovoltaic system and then fuzzy membership functions of the fuzzy controller are optimized using Firefly Algorithm (FA) to generate the proper duty cycle. FA which is inspired by natural species to optimize nonlinear functions is one of the most successful and low-cost algorithms in this field. Finally, PV system with FLC-FA is compared with other methods like perturbation and observation (P&O) and fuzzy controller- Particle swarm optimization (PSO). According to the simulation results, asymmetric fuzzy membership functions based on FA increase tracking speed of MPPT and improve tracking accuracy compared to P&O, symmetric fuzzy membership functions and asymmetric fuzzy membership functions based on PSO. [ABSTRACT FROM AUTHOR]

Highlights • This paper focuses on the improvement of dynamic performance of DC to AC converter. • Active and reactive power flow control of grid-tied three-phase inverter is achieved for PV generations system. • A Lyapunov function Based Model Predictive Control algorithm is used to track the maximum power point of the PV system. • Step load performance analyzed. Abstract In this paper, a predictive direct power control (PDPC) method based on Lyapunov function approach is developed for control of grid connected photovoltaic (PV) converter. The predictive control algorithm utilizes the discrete model of the PV converter and predicts the future active and reactive power of the system by calculating a cost function for all voltage vectors. Subsequently, the optimal voltage vector that minimizes the cost function is selected to calculate the model variables in the next sampling instant. The proposed controller predicts error before the switching signal is applied to the high-gain multilevel PV converter and thus is able to choose the next switch event to minimize error between the commanded and actual converter operation. This technique improves the speed at which the controller can track rapid changes in solar insolation and results in an increase in the overall system output power. In the proposed technique, there is no need to adjust the control parameters under changing loads or model parameters uncertainties. Also, the use of many classical controllers is eliminated and only one PI controller is used for DC link voltage. Moreover, contrary to the conventional PDPC, the optimal switching vector is determined only based on active and reactive power and hence, the computation burden is significantly reduced and the convergence is speed up. The detail modeling and design of the proposed controller are verified through computer simulations under different operating conditions. Also, the robustness of the control approach is illustrated in the presence of parameters uncertainties and change in solar irradiations. Simulation results show that the proposed control strategy maintains the active and reactive powers as close as possible to the desired values under different operation mode. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • BI-MPPT is a novel maximum power point tracker based on probabilistic inference. • BI-MPPT inherently accounts for random noise in the system. • The proposed tracker has high dynamic efficiencies for versatile weather conditions. • Dynamic efficiency of BI-MPPT is 10 p.p higher than optimized P&O at low illumination. • Upto 4 p.p higher dynamic efficiency is seen with high-irradiance outdoor measurement. Abstract We introduce a Bayesian inference based maximum power point tracker (BI-MPPT) and demonstrate it under static and dynamic irradiance conditions. BI-MPPT is based on a probability inference technique which uses the model of the photovoltaic (PV) module and accounts for noise in the system. Owing to the model-based approach, the tracker converges fast to the maximum power point of the PV module and is capable of tracking dynamically varying irradiance. We compare the proposed BI-MPPT to an optimized model-based P&O tracker and show that the proposed tracker consistently outperforms the latter. In experiments conducted with an in-house built solar emulator, at low illumination, the BI-MPPT achieves a static efficiency of 99.9% and a dynamic efficiency of at the least 97.4% and outperforms the optimized P&O tracker by about 10 percent point. When BI-MPPT is applied to I-V curve measurements of an outdoor PV installation, at moderate and high irradiances, the dynamic efficiency is between 98.92% and 99.61% yielding a 3 to 4 percent point improvement over the optimized P&O. [ABSTRACT FROM AUTHOR]

• Increasing solar output power using tracking system is investigated. • A hybrid control approach is utilized. • The results show an enhancement up to 35 %. Due to its capacity to maximize the power produced by photovoltaic (PV) panels, solar tracking systems have grown in popularity. However, erratic weather conditions, like cloudy or overcast days, change the panel's preferred orientation. On sunny days, the panel is turned to face the sun's radiation; however, on cloudy or overcast days, diffused radiation alters the optimal position. This has increased the necessity for new search algorithms that control the orientation of the panel to generate the most power feasible regardless of the weather conditions. This study aims at developing a sun-tracking system that can adjust the solar panel's orientation to generate the maximum possible electrical output from solar energy in Jordan, regardless of the local climate. To achieve this; a hybrid controller has been created that combines an open-loop sun monitoring system with a dynamic feedback controller built on an active search algorithm. The suggested algorithm is built on the real-time measurement of the PV panels' waning solar irradiance by using small solar cell 0.6 W. The system switches to the recently proposed circular path finding method to locate the Maximum Power Point Tracking (MPPT) if the instantaneous irradiance level falls below a predetermined threshold (DNI irradiance). As a result of the testing phase, the generated power of a solar panel increased by about 35%, confirming the effectiveness of the newly proposed sun tracker hybrid control system. During experimental test, positive irradiance current noises are appeared, using average filter taking the mean of 100 values for one measurement. [ABSTRACT FROM AUTHOR]

Highlights • A modified perturb-and-observe-based-MPPT method is proposed. • The proposed method (PM) is tested under step/ramp changes of irradiation level. • Tracking speed by the PM is 0.025 ms against 35–52.5 ms for other 18 methods. • Steady-state efficiency by the PM is 99.48% versus 83.6–98.5% for other methods. • Dynamic efficiency by the PM is 98.03% against 83–96.33% for other methods. Abstract The present paper studies thoroughly the performance of the classical perturb-and-observe (P&O) method under fast-changing solar irradiation, including increase or decrease of the irradiation level with small or large steps, when the initial operating point lies to the right or left of the MPP. In sixteen case studies of sudden variation of solar irradiation, the classical P&O method fails to track MPP properly in four cases. The classical P&O tracker does not work properly under a ramp change of irradiation level. A modified P&O-based-MPP tracking method is proposed and tested under step and ramp changes of irradiation irrespective of the value and direction of the perturbation in irradiation level and the location of the initial operating point. The proposed method succeeds in capturing the MPP under a ramp or slow change of irradiation level. The proposed method tracks correctly the MPP in the above-mentioned case studies and shows better performance in tracking speed, steady state efficiency, dynamic efficiency and tracking accuracy when compared with the classical P&O method and other modified methods reported in the literature. [ABSTRACT FROM AUTHOR]

Partial shading and mismatch among the Photovoltaic (PV) modules is an important issue, which decreases the harvested power from the PV modules, and causes an efficiency problem for renewable energy systems. Several power electronics topologies that allow charge redistribution between the PV modules, have been proposed to balance PV modules which are connected in series. Differential Power Processing (DPP) is a technique which improves the overall efficiency of the power balance system by processing only a fraction of the module power. In this study, the power loss analysis of the switched-capacitor (SC) converter, which is configured in ladder architecture with the PV sub-modules for power balancing purpose, is derived and verified by simulation and experimental works. The proposed loss model predicts the percentage of power loss of the SC converter working under arbitrary partial shading conditions. Switched-Capacitor converter prototype was built and tested using a 140 W photovoltaic module. It is found that for 0–25% overall partial shading the overall efficiency remains above 98%. The experimentally obtained loss is in reasonable agreement with its theoretical counterpart. [ABSTRACT FROM AUTHOR]

Due to the worldwide energy crisis and environmental issues, the so-called green ship is recently urgent to be developed for energy-saving and emission-reduction. When a photovoltaic (PV) system is installed on a ship, solar generation can provide auxiliary energy as backup of engine. However, different from the land-based PV system with fixed position, the marine PV system always suffers from complex and frequently-changed environmental conditions, e.g. the partial and dynamic shading, so a maximum power point tracking (MPPT) approach with higher accuracy and faster response is required. In this paper, a novel configuration of large-scale PV array on green ocean-going ship is studied, and its MPPT problem is described as a large-scale optimization model. Then, a meta -heuristic optimization is employed to solve this model offline, and the model predictive control is employed to achieve the online MPPT control in real-time. Result of simulation experiments shows that the proposed configuration and MPPT approach can achieve effective performance, and also can improve the output power under complex environmental conditions significantly. [ABSTRACT FROM AUTHOR]

The photovoltaic system is widely introduced into ocean-going ships to utilize the abundant solar resources on the ocean, reduce the ship’s fuel consumption and pollutant emission. As the uncertainty of navigation environment, ship’s attitude and climate conditions, the dynamic partial shading or even complex illumination conditions probably occur during the long time voyage. In this paper, a large-scale photovoltaic (PV) system is introduced into the ocean-going green ship to modify the traditional structure of ship’s power grid. Specifically, a novel structure of large-scale PV array based on the ship’s illumination unit (SIU), ship’s photovoltaic group (SPG), operating point controlling device (OPCD) and batteries is proposed, and layout of the array on ocean-going green ship is researched as well. Besides, the MPPT of all the SIUs is modeled as a large-scale global optimization (LSGO) problem, and a meta-heuristic optimization called the DCDE is employed to solve this problem offline. Performance of the DCDE is verified by numerical experiments, and result of simulation also shows that with the application of the proposed structure and its controlling methods, the green ship can make full use of solar resources and achieve its operational safety and efficiency under complex environmental conditions. [ABSTRACT FROM AUTHOR]

Taking into account the nonlinear feature of a PV array, a Maximum Power Point Tracking (MPPT) algorithm is required in a PV system leading the operation at the Maximum Power Point (MPP) and as a result maximizing the generated power. In this paper, a robust MPPT technique using second order sliding mode control strategy is presented. A super twisting algorithm is used to design second order sliding mode. This algorithm has been developed, in the case where the relative degree of system is equal to one, to eliminate chattering phenomenon. Second order sliding mode presents an adequate mean for control action of nonlinear systems since it overcomes chattering phenomenon of the classical first order sliding mode controller and ensures higher accuracy even with system imperfections. The stability analysis of the proposed controller is performed using a Lyapunov function. We compare second order sliding mode with classical first order sliding mode controller which are both designed for the same PV system. This comparison proves that the second order gives fast response and less chattering. The robustness and stability of the proposed controller are investigated against weather changes. Simulation results with real data, under MATLAB-SIMULINK, are given to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In order to maximize the conversion efficiency of photovoltaic systems, it is usually essential to design a maximum power point tracking controller. In this paper, a new second-order fuzzy sliding-mode controller is designed for this purpose. Since the proposed scheme is based on the second-order sliding-mode control law, it can handle nonlinear dynamics of photovoltaic systems. Compared to previously introduced controllers, the proposed control law does not depend on model parameters and thus is robust to system uncertainties. The gain of the control signal is determined using a fuzzy gain tunning algorithm. Therefore, not only the robustness of the system will be improved, but also chattering amplitude will be suppressed. The proposed scheme does not require asymptotic observers, and thus its analysis and implementation are fairly simple. The performance of the proposed control system is verified through simulation and experiment. Compared to terminal sliding mode control system, the proposed system can increase the efficiency up to 1.5%. [ABSTRACT FROM AUTHOR]

A novel standalone hybrid solar/wind/fuel cell (FC) power generation system is designed and constructed. The contribution of this work is that the large-scale constructed hybrid system combines two renewable resources (solar and wind energy) with a FC system used as a standby power source to produce electric energy. Moreover, it maximally converts solar and wind energy into electric power because it uses a novel fast and highly accurate unified maximum power point tracking (MPPT) technique which concurrently tracks the maximum power points of both photovoltaic (PV) system and wind energy conversion system (WECS) implemented in the hybrid system. Few hybrid solar/wind/FC power sources reported in the literature are simulated models, and moreover, there is not any new MPPT consideration in them. It is experimentally verified that the constructed hybrid system efficiently produces electric energy for a remote area under different environmental conditions such as cloudy sky. The MPPT technique implemented in the standalone hybrid solar/wind/FC system is also compared to the state-of-the-art MPPT methods, the comparison explicitly demonstrates that the technique provides the highest MPPT efficiencies of 99.60% and 99.28% along with the shortest tracking convergence times of 12 ms and 15 ms respectively in PV systems and WECSs. [ABSTRACT FROM AUTHOR]

In this study, a novel grid-connected solar powered electric vehicle (EV) charging station with vehicle-to-grid (V2G) technology is designed and constructed. The solar powered EV charging station consists of a photovoltaic (PV) array, a DC/DC converter dedicated to the PV array, a maximum power point tracking (MPPT) controller, 15 bidirectional DC/DC converters dedicated to the 15 charging stations provided for charging EVs, and a bidirectional DC/AC inverter connected between the charging station and grid. The contribution of this work is that the grid-connected solar powered EV charging station presented in this work optimally converts solar energy into electric energy because it uses a novel proposed fast and highly accurate MPPT technique. Furthermore, this work includes experimental results obtained from the daily operation of the constructed EV charging station, while other works are only simulation based. It is experimentally verified that the EV charging station not only produces enough electric energy to charge EVs during sunny days but also balances load demand in the local grid during cloudy days. [ABSTRACT FROM AUTHOR]

A compact 150 W photovoltaic inverter was developed using SiC devices, which integrated a maximum power point tracking charge controller and a direct current (DC) - alternating current (AC) converter into a single module. The DC-AC converter circuit was built with four SiC metal-oxidesemiconductor field-effect transistors, while the DC-DC converter circuit built with four SiC Schottky barrier diodes. An increase of the switching frequency led to the module of a reduced size (250 × 180 × 28 mm 3 ), which is just one third volume of a commercial Si-based inverter available today. Besides being compact, the conversion efficiency of the DC-AC converter was approximately 3% higher than that of the commercial Si-based inverter. In addition, the MPPT controller showed a conversion efficiency exceeding 96%, which raised the total efficiency under practical operation conditions up to 86%. [ABSTRACT FROM AUTHOR]

This paper presents Takagi-Sugeno (T-S) Fuzzy based approach for operating the solar panel in Standalone Photovoltaic (SPV) system at Maximum Power Point (MPP). The SPV system incorporated with T-S Fuzzy algorithm can be represented by four local models and each model in turn is characterized by an optimal operating point. This optimal operating point of local models pave a way to compute the optimal operating point of PV panel. The duty cycle of the boost converter placed between the panel and load has to be appropriately varied based on the computed value, allowing the panel to provide optimal power. The performance of T-S Fuzzy algorithm applied to the boost converter present in SPV system is tested in simulation for various operating conditions and compared with the performance obtained using Incremental Conductance Algorithm. The results indicate the effectiveness of the proposed T-S Fuzzy algorithm in tracking maximum power than the Incremental Conductance Algorithm. [ABSTRACT FROM AUTHOR]

This study deals with a three-phase double-stage multifunctional grid-connected inverter interfaced with a photovoltaic system. The studied system consists of a photovoltaic array, a dc-dc boost converter and a three-phase voltage source inverter connected to the utility at the point of common coupling. To ensure the multifunctional feature, we propose a predictive current control which uses a discrete-time model of the system to predict the future value of the filter current for different voltage vectors. Selection of the optimal voltage vector aims to minimize the error between reference and predicted current by using a cost function. Then, perturb and observe Maximum Power Point Tracking is applied to the dc-dc boost converter to extract maximum power from the photovoltaic array. The main benefits of the proposed system are: harmonic and reactive current elimination, reactive power compensation and feeding photovoltaic power into the utility. The proposed control algorithm is performed on a Matlab ⧹ Simulink™ environment, simulation and experimental results confirm the effectiveness of the proposed control method in term of total harmonic distortion and power factor correction. The performance of the proposed control has been compared with hysteresis and direct power control strategies. Dynamic state results show that the proposed method provides a better performance and more stability under fast environmental conditions changing than hysteresis current control. [ABSTRACT FROM AUTHOR]

For the purpose of control and monitoring of a Photovoltaic (PV) system its current-voltage (I-V) characteristic curve is traced. Usually such a test involves the interruption of the normal operation of the PV systems. In this paper a method for tracing the I-V curve from on-site measurements is proposed. During the measurement of the characteristic curve the normal operation of the PV system is not interrupted. The subjects of tracing the characteristic curve and Maximum Power Point Tracking (MPPT) of PV arrays are generally dealt with separately but the proposed method performs the measurement of the characteristic curve quickly and so it can also be utilized for MPPT purposes. Simulations and experiments have been conducted to confirm the operation of the proposed method. [ABSTRACT FROM AUTHOR]