Maximum photovoltaic power tracking for the PV array using the fractional-order incremental conductance method

This paper proposes maximum photovoltaic power tracking (MPPT) for the photovoltaic (PV) array using the fractional-order incremental conductance method (FOICM). Since the PV array has low conversion efficiency, and the output power of PV array depends on the operation environments, such as various solar radiation, environment temperature, and weather conditions. Maximum charging power can be increased to a battery using a MPPT algorithm. The energy conversion of the absorbed solar light and cell temperature is directly transferred to the semiconductor, but electricity conduction has anomalous diffusion phenomena in inhomogeneous material. FOICM can provide a dynamic mathematical model to describe non-linear characteristics. The fractional-order incremental change as dynamic variable is used to adjust the PV array voltage toward the maximum power point. For a small-scale PV conversion system, the proposed method is validated by simulation with different operation environments. Compared with traditional methods, experimental results demonstrate the short tracking time and the practicality in MPPT of PV array.     

New algorithm using only one variable measurement applied to a maximum power point tracker

A novel algorithm for seeking the maximum power point of a photovoltaic (PV) array for any temperature and solar irradiation level, needing only the PV current value, is proposed. Satisfactory theoretical and experimental results are presented and were obtained when the algorithm was included on a 100 W 24 V PV buck converter prototype, using an inexpensive microcontroller. The load of the system used was a battery and a resistance. The main advantage of this new maximum power point tracking (MPPT), when is compared with others, is that it only uses the measurement of the photovoltaic current, I_PV.     

A novel on-line MPP search algorithm for PV arrays

A novel maximum power point (MPP) search algorithm for photovoltaic (PV) array power systems is introduced. The proposed algorithm determines the maximum power point of a PV array for any temperature and solar irradiation level using an online procedure. The method needs only the online values of the PV array output voltage and current, which can be obtained easily by using just current and voltage transducers. The algorithm requires neither the measurement of temperature and solar irradiation level nor a PV array model that is mostly used in look-up table based algorithms. Satisfactory results were obtained with the proposed algorithm in a laboratory prototype implementation scheme consisting of a PV array computer emulation model, a chopper controlled permanent magnet DC motor, and a DT2827 data acquisition board with the ATLAB software drivers for interfacing     

Artificial neural network-polar coordinated fuzzy controller based maximum power point tracking control under partially shaded conditions

The one of main causes of reducing energy yield of photovoltaic systems is partially shaded conditions. Although the conventional maximum power point tracking (MPPT) control algorithms operate well under uniform insolation, they do not operate well in non-uniform insolation. The non-uniform conditions cause multiple local maximum power points on the power?voltage curve. The conventional MPPT methods cannot distinguish between the global and local peaks. Since the global maximum power point (MPP) may change within a large voltage window and also its position depends on shading patterns, it is very difficult to recognise the global operating point under partially shaded conditions. In this paper, a novel MPPT system is proposed for partially shaded PV array using artificial neural network (ANN) and fuzzy logic with polar information controller. The ANN with three layer feed-forward is trained once for several partially shaded conditions to determine the global MPP voltage. The fuzzy logic with polar information controller uses the global MPP voltage as a reference voltage to generate the required control signal for the power converter. Another objective of this study is to determine the estimated maximum power and energy generation of PV system through the same ANN structure. The effectiveness of the proposed method is demonstrated under the experimental real-time simulation technique based dSPACE real-time interface system for different interconnected PV arrays such as series-parallel, bridge link and total cross tied configurations.     

基于改进扰动观察法的光伏电池最大功率跟踪

有效地提高光伏电池的利用率对光伏系统至关重要,为此建立了具有通用性的光伏电池工程实用模型及相应的Boost转换电路,采用改进的扰动观察法控制Boost电路占空比实现光伏电池最大功率跟踪(MPPT),阐述了其实现策略并进行仿真验证。结果表明,外界温度、光照变化条件下该方法可精确跟踪光伏电池的最大功率点,实现光伏电池的高效转换。     

A high efficiency photovoltaic module integrated converter with the asymmetrical half-bridge flyback converter

A module integrated converter (MIC) for a photovoltaic (PV) cell is important part of power conditioning system (PCS). It performs maximum power point tracking of a PV cell to generate the power as much as possible from solar energy. There are several methods for connection between the PV modules and the MICs. In order to avoid partial shading effects, converter-per-module approach was proposed. The MIC that performs maximum power point tracking (MPPT), if it is low efficiency, is no use. The MIC whose output is connected to the output of PV module was proposed for high efficiency. However, there are some problems. In this study, an asymmetrical half-bridge flyback converter is proposed instead of the original flyback converter with same method to solve the problems. The proposed MIC was built to verify the performance. The new topology using soft switching technique showed good performance for the efficiency. At the higher power, the efficiency of the proposed converter is higher than existing converter.     

Polar coordinated fuzzy controller based real-time maximum-power point control of photovoltaic system

It is crucial to improve the photovoltaic (PV) system efficiency and to develop the reliability of PV generation control systems. There are two ways to increase the efficiency of PV power generation system. The first is to develop materials offering high conversion efficiency at low cost. The second is to operate PV systems optimally. However, the PV system can be optimally operated only at a specific output voltage and its output power fluctuates under intermittent weather conditions. Moreover, it is very difficult to test the performance of a maximum-power point tracking (MPPT) controller under the same weather condition during the development process and also the field testing is costly and time consuming. This paper presents a novel real-time simulation technique of PV generation system by using dSPACE real-time interface system. The proposed system includes Artificial Neural Network (ANN) and fuzzy logic controller scheme using polar information. This type of fuzzy logic rules is implemented for the first time to operate the PV module at optimum operating point. ANN is utilized to determine the optimum operating voltage for monocrystalline silicon, thin-film cadmium telluride and triple junction amorphous silicon solar cells. The verification of availability and stability of the proposed system through the real-time simulator shows that the proposed system can respond accurately for different scenarios and different solar cell technologies.     

Comprehensive review and performance evaluation of maximum power point tracking algorithms for photovoltaic system

A photovoltaic array is environmentally friendly and a source of unlimited energy generation. However, it is presently a costlier energy generation system than other non-renewable energy sources. The main reasons are seasonal variations and continuously changing weather conditions, which affect the amount of solar energy received by the solar panels. In addition, the non-linear characteristics of the voltage and current outputs along with the operating environment temperature and variation in the solar radiation decrease the energy conversion capability of the photovoltaic arrays. To address this problem, the global maxima of the PV arrays can be tracked using a maximum power point tracking algorithm (MPPT) and the operating point of the photovoltaic system can be forced to its optimum value. This technique increases the efficiency of the photovoltaic array and minimizes the cost of the system by reducing the number of solar modules required to obtain the desired power. However, the tracking algorithms are not equally effective in all areas of application. Therefore, selecting the correct MPPT is very critical. This paper presents a detailed review and comparison of the MPPT techniques for photovoltaic systems, with consideration of the following key parameters: photovoltaic array dependence, type of system (analog or digital), need for periodic tuning, convergence speed, complexity of the system, global maxima, implemented capacity, and sensed parameter(s). In addition, based on real meteorological data (irradiance and temperature at a site located in Addis Ababa, Ethiopia), a simulation is performed to evaluate the performance of tracking algorithms suitable for the application being studied. Finally, the study clearly validates the considerable energy saving achieved by using these algorithms.     

Photovoltaic field emulation including dynamic and partial shadow conditions

In this paper the development of a new laboratory prototype for the emulation of a photovoltaic (PV) field is presented. The proposed system is based on a DC/DC step-down converter topology and allows to obtain the solar array I–V curves, taking into account the environmental changes in solar irradiance and cell temperature. The DC/DC converter control strategy is deduced by using a comprehensive mathematical model of the PV field whose parameters are obtained from the knowledge of: (a) maximum power point data, measured when the PV plant power converter is running, (b) open circuit voltage and short-circuit current, measured off-line. This approach allows the most accurate representation of the PV source. Computer simulations and experimental results demonstrate that the proposed circuit acts as a highly accurate and efficient laboratory simulator of the photovoltaic array electrical characteristics both in steady state and transient conditions. Partial shading and fluctuating conditions can be reproduced too. Moreover the dynamic behaviour of the proposed laboratory emulator is suitable to its effective connection to power electronic interface to the utility or to load through a DC/DC boost converter.     

Bidirectional energy storage photovoltaic grid-connected inverter application system

A novel topology of the bidirectional energy storage photovoltaic grid-connected inverter was proposed to reduce the negative impact of the photovoltaic grid-connected system on the grid caused by environmental instability. Using the proposed Inverter as a UPS power supply in case of a grid failure, storage electrical energy and regulating the energy delivered to the grid for reducing the pressure on the grid. A new artificial fish-swarm algorithm and variable step voltage perturbation method were presented to track the maximum power point of the solar panels. Analysis was done to reduce the output ripple of the inverter and sinusoidal pulse width modulation (SPWM) was selected to control the inverter. Model simulation was performed using PSpice software to obtain the volt-ampere characteristic curve of the solar panel output. The solar array simulator was used to verify the effect of maximum power point tracking at different light intensities. The study concludes that the maximum power point tracking (MPPT) efficiency of the bidirectional energy storage photovoltaic grid-connected inverter designed was as high as 99.9%. The distortion rate of the grid-connected current waveform was within 2% and the DC current component was less than 0.5%. The output voltage and power were in full compliance with the grid connection standard.     

A novel maximum power point tracking technique based on fuzzy logic for photovoltaic systems

Maximum power point tracking (MPPT) techniques are considered a crucial part in photovoltaic system design to maximise the output power of a photovoltaic array. Whilst several techniques have been designed, Perturb and Observe (P&O) is widely used for MPPT due to its low cost and simple implementation. Fuzzy logic (FL) is another common technique that achieves vastly improved performance for MPPT technique in terms of response speed and low fluctuation about the maximum power point. However, major issues of the conventional FL-MPPT are a drift problem associated with changing irradiance and complex implementation when compared with the P&O-MPPT. In this paper, a novel MPPT technique based on FL control and P&O algorithm is presented. The proposed method incorporates the advantages of the P&O-MPPT to account for slow and fast changes in solar irradiance and the reduced processing time for the FL-MPPT to address complex engineering problems when the membership functions are few. To evaluate the performance, the P&O-MPPT, FL-MPPT and the proposed method are simulated by a MATLAB-SIMULINK model for a grid-connected PV system. The EN 50530 standard test is used to calculate the efficiency of the proposed method under varying weather conditions. The simulation results demonstrate that the proposed technique accurately tracks the maximum power point and avoids the drift problem, whilst achieving efficiencies of greater than 99.6%.     

Resiliency oriented control of a smart microgrid with photovoltaic modules

The resiliency of a standalone microgrid is of considerable issue because the available regulation measures and capabilities are limited. Given this background, this paper presented a new mathematical model for a detailed photovoltaic (PV) module and the application of new control techniques for efficient energy extraction. The PV module employs a single-stage conversion method to integrate it with the utility grid. For extraction the maximum power from PV and integrate it to power grid, a three-phase voltage source converter is used. For obtaining the maximum power at a particular irradiance a maximum power point tracking (MPPT) scheme is used. The fuzzy logic control and adaptive network-based fuzzy inference system are proposed for direct current (DC) link voltage control. The proposed model and control scheme are validated through a comparison with the standard power-voltage and current–voltage charts for a PV module. Simulation results demonstrate that the system stability can be maintained with the power grid and in the island mode, in contrast with the MPPT.     

The coupling factor: A new metric for determining and controlling the efficiency of solar photovoltaic power utilization

The production of electricity and hydrogen in a renewable fashion, such as using solar energy, can provide a clean and sustainable energy source for electric-powered vehicles, including fuel-cell and battery-electric vehicles. Our research on generating hydrogen and charging batteries using renewable solar photovoltaic (PV) electricity has led to the development of a simple and convenient new metric called the coupling factor that describes the fraction of the maximum PV power transferred to electrical loads. The keystone of the coupling factor concept is a regression model to calculate the maximum PV voltage, current, and power as a function of the instantaneous incident solar irradiance and the photovoltaic module temperature. The coupling factor can range from zero to one, i.e., no transfer of power from the PV system to the load, to complete transfer of the PV power. We describe the derivation of regression models to compute important PV electrical output variables, such as the open circuit voltage, the short circuit current, the maximum power point voltage, the maximum power point current, and the coupling factor as a function of the fundamental measured variables affecting those quantities. The models are derived for PV modules used in our previous research to power an electrolyzer and charge high-voltage batteries. In addition, we develop models for other modules using PV cell technologies different from those used in our PV system. Some of the calculated quantities are compared to measurements for our PV system. The usefulness of these quantities, and especially the coupling factor, in rating the transfer of PV power to electrolyzer and battery loads, is illustrated. Finally, we discuss how the predicted maximum power point voltage can be used for real-time control and efficiency optimization of a dynamic PV-load system.     

Analysis and enhancement of PV efficiency with incremental conductance MPPT technique under non-linear loading conditions

This paper presents experimental evaluations for variation in the efficiency of energy extracted from a photovoltaic (PV) module (under non-linear loading) incorporated with an incremental conductance(IC) maximum power point tracking (MPPT) algorithm. The focus is on the evaluation of the PV panel under non-linear loading conditions using the experimental installation of a 100W_p photovoltaic array connected to a DC–DC converter and a KVA inverter feeding a non-linear load. Under the conditions of non-linear loading, both the simulation and experiment show that the MPPT technique fails to attain maximum power point due to the presence of ripples in the current leading eventually to a reduction in efficiency. In this paper, panel current is taken as a function of load impedance in the MPPT algorithm to eradicate power variation, as load impedance varies with supply voltage under non-linear conditions. The system is simulated for different non-linear loads using MATLAB-Simulink. A TMDSSOLAREXPKIT was used for MPPT control. In case 2, the inverter is connected to a single phase grid. When a voltage swell occurs in the grid, PV power drops. This power loss is reduced using the proposed MPPT method. The results of simulations and experimental measurements and cost efficiency calculations are presented.     

Brushless DC motor drives supplied by PV power system based on Z-source inverter and FL-IC MPPT controller

This paper discusses operation performance of a water pumping system consist of a brushless dc (BLDC) motor coupled a centrifugal pump and accompanying a Z-source inverter (ZSI) fed by a photovoltaic (PV) array, to be improved. Despite conventional double-stage power converters, this paper proposes utilizing a single-stage ZSI to extract the maximum power of the PV array and supply the BLDC motor simultaneously. Utilizing the ZSI provides some inherent advantages such as high efficiency and low cost, which is very promising for PV systems due to its novel voltage buck/boost capability. In addition, in order to precisely perform the maximum power point tracking (MPPT) of the PV array the fuzzy logic-incremental conductance (FL-IC) MPPT scheme is proposed. The proposed FL-IC MPPT scheme provides enough modification to the conventional IC method to enjoy an appropriate variable step size MPPT control signal for the ZSI. Moreover, direct torque control (DTC) is found more effective in comparison with hysteresis current control with current shaping to drive the BLDC motor, because it benefits from faster torque response, reduced torque ripple, less sensitivity to parameters variations, and simple implementation. In the mean time, due to the frequently variations of the PV power generation; delivered mechanical power to the centrifugal pump is variable. Thus, the BLDC motor should be driven with variable reference speed. In order to improve the speed transient response of the BLDC motor and enhance the energy saving aspect of the system, it should enjoy a high quality dynamic response characteristic. Therefore, to realize these purposes, particle swarm optimization (PSO) has been proposed to regulate the proportional-integral-derivative (PID) parameters of the BLDC motor speed controller. The system configuration, operation principle and control methods are presented in detail. Finally, the proposed system was simulated in different operation conditions of the PV array by computer simulations and the effectiveness of the proposed control strategies has been validated by comparative studies and simulation results.     

Optimization of fuzzy-based MPPT controller via metaheuristic techniques for stand-alone PV systems

Due to the alteration of power-voltage characteristics of solar module output under multiple environmental conditions such as solar irradiation and ambient temperature, these systems hardly function at maximum power point (MPP). However, maximum power point tracking (MPPT) plays a significant role in their efficiency. On the other hand, solar module characteristics are extremely nonlinear and their slope on either side of MPP is asymmetric. Thus using a nonlinear control method which has the potential of adapting the operating point of the system to MPP seems useful. This has motivated authors to present MPPT method which maximizes PV's output power by tracking MPP continuously. In the present study, a fuzzy logic controller (FLC) is presented for MPPT in photovoltaic systems. Four optimization algorithms are presented in this paper for optimizing fuzzy membership functions (MFs) and generating proper duty cycle for MPPT. The presented algorithms include: Teaching Learning Based Optimization (TLBO), Firefly Algorithm (FFA), Biogeography based optimization (BBO), and Particle Swarm Optimization (PSO), which are all described and simulated. Finally, to validate performance of the proposed optimized FLC, it is compared with other algorithms such as symmetrical fuzzy logic controller (SFLC) and conventional Perturbation and Observation (P&O). According to the simulation results, P&O algorithm shows significant oscillations, energy loss, and in some cases, it cannot obtain MPP. Simulation results also indicate that TLBO and FFA based asymmetric fuzzy MFs not only increase MPPT convergence speed but also enhance tracking accuracy in comparison with symmetric fuzzy MFs and asymmetric fuzzy MFs based on BBO and PSO.     

Fractional order extremum seeking approach for maximum power point tracking of photovoltaic panels

Due to the high interest in renewable energy and diversity of research regarding photovoltaic (PV) array, a great research effort is focusing nowadays on solar power generation and its performance improvement under various weather conditions. In this paper, an integrated framework was proposed, which achieved both maximum power point tracking (MPPT) and minimum ripple signals. The proposed control scheme was based on extremum-seeking (ES) combined with fractional order systems (FOS). This auto-tuning strategy was developed to maximize the PV panel output power through the regulation of the voltage input to the DC/DC converter in order to lead the PV system steady-state to a stable oscillation behavior around the maximum power point (MPP). It is shown that fractional order operators can improve the plant dynamics with respect to time response and disturbance rejection. The effectiveness of the proposed controller scheme is illustrated with simulations using measured solar radiation data.     

An improved thermal and electrical model for a solar photovoltaic thermal (PV/T) air collector

In this paper, an attempt is made to investigate the thermal and electrical performance of a solar photovoltaic thermal (PV/T) air collector. A detailed thermal and electrical model is developed to calculate the thermal and electrical parameters of a typical PV/T air collector. The thermal and electrical parameters of a PV/T air collector include solar cell temperature, back surface temperature, outlet air temperature, open-circuit voltage, short-circuit current, maximum power point voltage, maximum power point current, etc. Some corrections are done on heat loss coefficients in order to improve the thermal model of a PV/T air collector. A better electrical model is used to increase the calculations precision of PV/T air collector electrical parameters. Unlike the conventional electrical models used in the previous literature, the electrical model presented in this paper can estimate the electrical parameters of a PV/T air collector such as open-circuit voltage, short-circuit current, maximum power point voltage, and maximum power point current. Further, an analytical expression for the overall energy efficiency of a PV/T air collector is derived in terms of thermal, electrical, design and climatic parameters. A computer simulation program is developed in order to calculate the thermal and electrical parameters of a PV/T air collector. The results of numerical simulation are in good agreement with the experimental measurements noted in the previous literature. Finally, parametric studies have been carried out. Since some corrections have been down on thermal and electrical models, it is observed that the thermal and electrical simulation results obtained in this paper is more precise than the one given by the previous literature. It is also found that the thermal efficiency, electrical efficiency and overall energy efficiency of PV/T air collector is about 17.18%, 10.01% and 45%, respectively, for a sample climatic, operating and design parameters.     

Enhancement of grid-connected photovoltaic system using ANFIS-GA under different circumstances

In recent years, many different techniques are applied in order to draw maximum power from photovoltaic (PV) modules for changing solar irradiance and temperature conditions. Generally, the output power generation of the PV system depends on the intermittent solar insolation, cell temperature, efficiency of the PV panel and its output voltage level. Consequently, it is essential to track the generated power of the PV system and utilize the collected solar energy optimally. The aim of this paper is to simulate and control a grid-connected PV source by using an adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA) controller. The data are optimized by GA and then, these optimum values are used in network training. The simulation results indicate that the ANFIS-GA controller can meet the need of load easily with less fluctuation around the maximum power point (MPP) and can increase the convergence speed to achieve the MPP rather than the conventional method. Moreover, to control both line voltage and current, a grid side P/Q controller has been applied. A dynamic modeling, control and simulation study of the PV system is performed with the Matlab/Simulink program.