A PSO‐based maximum power point tracking for photovoltaic systems under environmental and partially shaded conditions

To increase the efficiency of photovoltaic (PV) systems, maximum power point (MPP) tracking of the solar arrays is needed. Solar arrays output power depends on the solar irradiance and temperature. Also the mismatch phenomenon caused by partial shade will affect the output power of solar systems and lead to the incorrect operation of conventional MPP tracker. Under partially shaded conditions, the solar array power–current characteristic has multiple maximum. This paper presents a maximum power point tracking (MPPT) with particle swarm optimization method for PV systems under partially shaded condition. The performance of the proposed method is compared with perturb and observe (P&O), improved P&O, voltage‐based maximum power point tracking and current‐based maximum power point tracking algorithms, especially, under partially shaded condition. Simulation results confirm that proposed MPPT algorithm with high accuracy can track the peak power point under different insolation, temperature and partially shaded conditions, and it has the best performance in comparison with four mentioned MPPT algorithms. Also under rapidly changing atmospheric conditions, the P&O algorithm is diverged. Copyright © 2013 John Wiley & Sons, Ltd.     

Performance evaluation of a MPPT controller with model predictive control for a photovoltaic system

ABSTRACT

Efficiency has been a major factor in the growth of photovoltaic (PV) systems. Different control techniques have been explored to extract maximum power from PV systems under varying environmental conditions. This paper evaluates the performance of a new improved control technique known as model predictive control (MPC) in power extraction from PV systems. Exploiting the ability of MPC to predict future state of controlled variables, MPC has been implemented for tacking of maximum power point (MPP) of a PV system. Application of MPC for maximum power point tracking (MPPT) has been found to result into faster tracking of MPP under continuously varying atmospheric conditions providing an efficient system. It helps in reducing unwanted oscillations with an increase in tracking speed. A detailed step by step process of designing a model predictive controller has been discussed. Here, MPC has been applied in conjunction with conventional perturb and observe (P&O) method for controlling the dc-dc boost converter switching, harvesting maximum power from a PV array. The results of MPC controller has been compared with two widely used conventional methods of MPPT, viz. incremental conductance method and P&O method. The MPC controller scheme has been designed, implemented and tested in MATLAB/Simulink environment and has also been experimentally validated using a laboratory prototype of a PV system.     

Optimized Maximum Power Point Tracker for Fast-Changing Environmental Conditions

This paper presents a high-performance maximum power point tracker (MPPT) optimized for fast cloudy conditions, e.g., rapidly changing irradiation on the photovoltaic panels. The rapidly changing conditions are tracked by an optimized hill-climbing MPPT method called dP-P&O. This algorithm separates the effects of the irradiation change from the effect of the tracker's perturbation and uses this information to optimize the tracking according to the irradiation change. The knowledge of the direction of the irradiation change enables the MPPT to use different optimized tracking schemes for the different cases of increasing, decreasing, or steady irradiance. When the irradiance is changing rapidly this strategy leads to faster and better tracking, while in steady-state conditions it leads to lower oscillations around the MPP. The simulations and experimental results show that the proposed dP-P&O MPPT provides a quick and accurate tracking even in very fast changing environmental conditions.     

Improvement of maximum power point tracking in photovoltaic arrays in different environments using hybrid algorithms

When the photovoltaic(PV) system is generating PV power, the partial shading(PS) condition will cause multiple peaks in the power-voltage curve, and changes in light intensity and ambient temperature will cause the curve to shift. Traditional maximum power point tracking(MPPT) methods, such as the incremental conductance(INC) method, have the problem of being trapped in the local optimal solution. Biomimetic optimization algorithms, such as particle swarm optimization(PSO), have problems with os...     

Cheap Joint Probabilistic Data Association with Adaptive Neuro-Fuzzy Inference System State Filter for Tracking Multiple Targets in Cluttered Environment

The cheap joint probabilistic data association (CJPDA) with the adaptive neuro-fuzzy inference system state filter (ANFISSF) is presented for tracking multiple targets in the presence of low and high cluttered environments. The state update step of the CJPDA filter (CJPDAF) is realized with the ANFISSF instead of Kalman filter. The adaptive neuro-fuzzy inference system (ANFIS) has the advantages of expert knowledge of fuzzy inference system and learning capability of neural networks. A hybrid learning algorithm, which combines the least square method and the backpropagation algorithm, is used to identify the parameters of ANFIS. The tracks estimated by using the method proposed in this paper for different tracking scenarios are in very good agreement with the original tracks.     

Experimental Performance of MPPT Algorithm for Photovoltaic Sources Subject to Inhomogeneous Insolation

Photovoltaic (PV) power system performance depends on local irradiance conditions. PV systems are sometimes subject to partial shading, which may produce a nonideal characteristic curve, presenting true and local power maxima in the P -I curve. Traditional maximum power point tracking (MPPT) algorithms can converge to local maximum, which is not the true MPP. In order to solve the problem, this paper investigates the effects of nonuniform solar irradiance distribution on a PV source. An MPPT algorithm that is able to optimize the source instantaneous operating power under nonuniform irradiance is proposed. The ability of the algorithm and its increased performance with respect to traditional algorithms are evaluated by means of experimental tests performed on a real PV power system.     

Real-Time Identification of Optimal Operating Points in Photovoltaic Power Systems

Photovoltaic power systems are usually integrated with some specific control algorithms to deliver the maximum possible power. Several maximum power point tracking (MPPT) methods that force the operating point to oscillate have been presented in the past few decades. In the MPPT system, the ideal operation is to determine the maximum power point (MPP) of the photovoltaic (PV) array directly rather than to track it by using the active operation of trial and error, which causes undesirable oscillation around the MPP. Since the output features of a PV cell vary with environment changes in irradiance and temperature from time to time, real-time operation is required to trace the variations of local MPPs in PV power systems. The method of real-time estimation proposed in this paper uses polynomials to demonstrate the power–voltage relationship of PV panels and implements the recursive least-squares method and Newton–Raphson method to identify the voltage of the optimal operating point. The effectiveness of the proposed methods is successfully demonstrated by computer simulations and experimental evaluations of two major types of PV panels, namely: 1) crystalline silicon and 2) copper–indium–diselenide thin film.     

Global maximum power point tracking based on new extremum seeking control scheme

A new perturbed‐based extremum seeking control (PESC) scheme is proposed in this paper to track the global maximum power point (GMPP). The PESC scheme has two control loops based on power of the photovoltaic (PV) array: the first loop operates as usually to track the maximum power point and the second sweeps all local MPPs to locate the GMPP. Once the GMPP is located based on its uniqueness (after the PV pattern is quickly scanned many times, depending on the PV pattern's profile), the GMPP is accurately tracked based on first control loop. The used PV patterns have the profile of the PV power characteristics obtained for PV array under partially shaded conditions (PSCs). This PESC scheme is proposed to track the GMPP in the PV applications, but also in other multimodal problems from industry, being a good motif to revive the specialists' interest for the extremum seeking control field. The results obtained here are very promising for both search speed and tracking accuracy performances of the GMPP under different PSCs simulated on the PV array. Thus, the energy efficiency of PV array controlled with the proposed PESC scheme will increase with more than 1.2% in comparison with that obtained with the other MPP algorithms because of better performance shown by this PESC scheme. A 99.6% tracking accuracy is obtained here in comparison with a maximum 98.4% tracking accuracy reported in the literature. Furthermore, 100% hit and high search speed are obtained here for the GMPP localization. Copyright © 2015 John Wiley & Sons, Ltd.     

Power controller design for maximum power tracking in solar installations

A state space approach to the design of a maximum power point (MPP) tracking system for photovoltaic energy conversion is presented. The problem of optimal-power control of a nonlinear time-varying system is reduced to an ordinary problem of dynamic system stability in state space by applying MPP conditions in controller design. The resulting tracking system searches for the reference point and tunes the converter for maximum power delivery to a load that may represent an end-user, or an energy-storage element, or a power grid-interface. The proposed design procedure for the MPP tracking system ensures a global asymptotic stability under certain conditions, and a minimum degree of the dynamic feedback. The design is verified using the virtual test bed, demonstrating accurate MPP tracking capability under unpredictable weather change, parameter variation, and load disturbance. The tracking system can be applied either to a stand-alone or grid-connected photovoltaic installations, and can be implemented in either analog circuitry or a digital microcontroller.     

A novel analytical model for determining the maximum power point of thin film photovoltaic module

Achieving the maximum power output from photovoltaic (PV) modules is indispensable for the operation of grid‐connected PV power systems under varied atmospheric conditions. In recent years, the study of PV energy for different applications has attracted more and more attention because solar energy is clean and renewable. We propose an efficient direct‐prediction method to enhance the utilization efficiency of thin film PV modules by tackling the problem of tracking time and overcoming the difficulty of calculation. The proposed method is based on the p–n junction recombination mechanism and can be applied to all kinds of PV modules. Its performance is not influenced by weather conditions such as illumination or temperature. The experimental results show that the proposed method provides high‐accuracy estimation of the maximum power point (MPP) for thin film PV modules with an average error of 1.68% and 1.65% under various irradiation intensities and temperatures, respectively. The experimental results confirm that the proposed method can simply and accurately estimate the MPP for thin film PV modules under various irradiation intensities and temperatures. In future, the proposed method will be used to shed light on the optimization of the MPP tracking control model in PV systems. Copyright © 2012 John Wiley & Sons, Ltd.     

A new algorithm for rapid tracking of approximate maximum power point in photovoltaic systems

This paper presents a new algorithm for tracking maximum power point in photovoltaic systems. This is a fast tracking algorithm, where an initial approximation of maximum power point is (MPP) quickly achieved using a variable step-size. Subsequently, the exact maximum power point can be targeted using any conventional method like the hill-climbing or incremental conductance method. Thus, the drawback of a fixed small step-size over the entire tracking range is removed, resulting in reduced number of iterations and much faster tracking compared to conventional methods. The strength of the algorithm comes from the fact that instead of tracking power, which does not have a one-to-one relationship with duty cycle, it tracks an intermediate variable /spl beta/, which has a monotonically increasing, one-to-one relationship. The algorithm has been verified on a photovoltaic system modeled in Matlab-Simulink software. The algorithm significantly improves the efficiency during the tracking phase as compared to a conventional algorithm. It is especially suitable for fast changing environmental conditions. The proposed algorithm can be implemented on any fast controller such as the digital signal processor. All the details of this study are presented.     

Current Source Inverter Based Grid Connected Hybrid PV-Wind Power Generation Unit

ABSTRACT

This paper presents a current source inverter (CSI)-based hybrid power generation system, which uses wind turbine and photovoltaic cells (PVs). A permanent magnet synchronous generator (PMSG) is connected to the CSI using a diode rectifier and a buck converter that is used to control the speed of the rotor. Another buck converter is used to control the maximum power point tracking of PVs. The operation of proposed system is studied under normal and grid voltage dip conditions. According to new grid codes, most power generating units are supposed to remain connected to the grid during voltage sag conditions and inject reactive current to grid as defined by grid codes. The CSI has fault current limiting capability that makes it appropriate to use in grid-connected applications and during voltage sag conditions in particular. The proposed system tracks the maximum power point of wind turbine and PVs under normal mode and injects required reactive current to the grid during voltage drop. However, incorporation of CSI with the inherent behaviour of wind turbine and PVs causes fault current to be within the tolerable range for power electronic devices. Simulations are carried out by using PSCAD/EMTDC software to verify the proposed system.     

Comparative study of maximum power point tracking techniques for hybrid renewable energy system

The power generation demand is increasing day-by-day throughout the world, therefore, the use of hybrid systems becomes a significant solution. The hybrid renewable energy system (HRES) is used for delivering power in various regions in order to overcome intermittence of wind and solar resources. Because of increasing environmental problems, for example, greenhouse gas emission and energy cost have interested novel research into substitute methods in favour of electrical power generation. Maximum Power Point Tracking (MPPT) control method is a vast deal of novel research used for enhancing the efficiency of HRES. The authors have revealed that the hybrid techniques i.e. Global MPPT, fuzzy-neuro systems, Adaptive Neuro-Fuzzy Inference System (ANFIS), Perturbed and Observe (P&O) + Adaptive Neural Network (ANN) etc. can provide best results as compared to other MPPT control methods. This paper offering a state of art review of MPPT control techniques for HRES.     

基于短路电流和扰动观察的光伏最大功率跟踪

在光伏最大功率跟踪（maximum power point tracking,MPPT）系统中,针对传统的扰动观察法（perturbation and observation,P＆O）难以同时满足跟踪速度和精度要求的问题,在原有的短路电流法的基础上,引入一种改进的扰动观察法,该算法不仅能够消除最大功率点附近的震荡,而且还能有效地提高响应速度.利用MATLAB/Simulink平台进行仿真,实验结果表明了算法的有效性.     

Analytic Solution to the Photovoltaic Maximum Power Point Problem

Photovoltaic (PV) power has been successfully used for over five decades. Whether in dc or ac form, photovoltaic cells provide power for systems in many applications on earth and space. Its principles of operation are therefore well understood, and circuit equivalents have been developed that accurately model the nonlinear relationship between the current and voltage of a photovoltaic cell. With the improved efficiencies of power electronics converters, it is now possible to operate photovoltaic system about its maximum power point (MPP) in order to improve the overall system efficiency. Hitherto, this problem has been tackled using tracking (MPPT) algorithms that iteratively find the point of maximum power and respond to changes in solar irradiance accordingly. A mathematical manipulation that uses the mean value theorem is presented here that provides the analytic solution of a point in a close neighborhood of the MPP. It is thoroughly proved that this point is enclosed in a ball of small radius that also contains the MPP and therefore can practically be considered as the MPP. Since the solution is analytic, no iterative schemes are necessary, and only a periodic measurement is required to adjust to changes in solar irradiance. A circuit is implemented that shows the validity of the theory and the accuracy of the solution.     

Low-Complexity MPPT Technique Exploiting the PV Module MPP Locus Characterization

This paper proposes a method for tracking the maximum power point (MPP) of a photovoltaic (PV) module that exploits the relation existing between the values of module voltage and current at the MPP (MPP locus). Experimental evidence shows that this relation tends to be linear in conditions of high solar irradiation. The analysis of the PV module electrical model allows one to justify this result and to derive a linear approximation of the MPP locus. Based on that, an MPP tracking strategy is devised which presents high effectiveness, low complexity, and the inherent possibility to compensate for temperature variations by periodically sensing the module open circuit voltage. The proposed method is particularly suitable for low-cost PV systems and has been successfully tested in a solar-powered 55-W battery charger circuit.     

An enhanced scanning-based MPPT approach for DMPPT systems

In this paper, an improved maximum power point tracking (MPPT) approach being low parameter dependency, simple structure and limited search interval has been presented for distributed MPPT photovoltaic (PV) systems. Basically, this approach is based on scanning of power–voltage (P-V) characteristic curve of PV modules in a limited duty ratio interval which makes tracking operation simple, fast and efficiently available in both uniform irradiance and partial shading conditions (PSCs). By limiting the scanning interval of maximum and minimum values of duty ratio via some analyses related to P-V characteristic for PSCs, global MPPT (GMPPT) is achieved in an efficient way. So as to validate performance of the proposed approach, a single-ended primary inductance converter has been used in both simulation and experimental studies. PV simulator has been used as a PV source to obtain different module characteristics with different number of bypass diodes and PV power levels. Both simulation and experimental results clarify that improved MPPT approach realises GMPPT effectively. Due to the high performance results, this approach can be an alternative technique in module-integrated converters, smart modules and PV power optimisers in which single module is used.     

基于改进多元宇宙优化算法的光伏系统最大功率点跟踪

在局部遮蔽条件下,光伏阵列的功率输出曲线呈现多峰特性,传统控制算法无法持续准确地跟踪最大功率输出点,该文提出一种基于改进多元宇宙优化(MVO)算法跟踪全局最大功率点的方法(IMVO)。引入螺旋更新和自适应压缩因子,增强了算法的全局搜索能力;改变旅行距离率的更新方式,加快了算法的收敛速度,3方面改进有效提高了算法的寻优能力。仿真结果表明:在均匀光照、局部遮蔽和变光照强度3种条件下,改进多元宇宙优化算法均能持续稳定地跟踪最大功率点,在收敛时间和收敛精度上均有较大提高,由此验证了该算法在最大功率点跟踪控制中的可行性。     

Application of Centered Differentiation and Steepest Descent to Maximum Power Point Tracking

This paper concentrates on two critical aspects to improve the performance of maximum power point tracking (MPPT). One improvement is to accurately locate the position of the maximum power point (MPP) by using the centered differentiation. Another effort is to reduce the oscillation around the MPP in steady state by controlling active perturbations. This paper also adopts the method of steepest descent for MPPT, which shows faster dynamic response and smoother steady state than the method of hill climbing. Comprehensive experimental evaluations have successfully illustrated the effectiveness of the proposed algorithm.     

Parallel-Connected Solar PV System to Address Partial and Rapidly Fluctuating Shadow Conditions

Solar photovoltaic (PV) arrays in portable applications are often subject to partial shading and rapid fluctuations of shading. In the usual series-connected wiring scheme, the residual energy generated by partially shaded cells either cannot be collected (if diode bypassed) or, worse, impedes collection of power from the remaining fully illuminated cells (if not bypassed). Rapid fluctuation of the shading pattern makes maximum power point (MPP) tracking difficult; generally, there will exist multiple local MPPs, and their values will change as rapidly as does the illumination. In this paper, a portable solar PV system that effectively eliminates both of the aforementioned problems is described and proven. This system is capable of simultaneously maximizing the power generated by every PV cell in the PV panel. The proposed configuration consists of an array of parallel-connected PV cells, a low-input-voltage step-up power converter, and a simple wide bandwidth MPP tracker. Parallel-configured PV systems are compared to traditional series-configured PV systems through both hardware experiments and computer simulations in this paper. Study results demonstrate that, under complex irradiance conditions, the power generated by the new configuration is approximately twice that of the traditional configuration. The solar PV system can be widely used in many consumer applications, such as PV vests for cell phones and music players.