A fast and low cost analog maximum power point tracking method for low power photovoltaic systems

Low power photovoltaic (PV) systems are commonly used in stand-alone applications. For these systems, a simple and cost-effective maximum power point tracking (MPPT) solution is essential. In this paper, a fast and low cost analog MPPT method for low power PV systems is proposed. By using two voltage approximation lines (VALs) to approximate the maximum power point (MPP) locus, a low-complexity analog MPPT circuit can be developed. Theoretical derivation and detailed design procedure will be provided in this paper. The proposed method boasts the advantages such as simple structure, low cost, fast tracking speed and high tracking efficiency. To validate the correctness of the proposed method, simulation and experimental results of an 87 W PV system will also be provided to demonstrate the effectiveness of the proposed technique.     

High-accuracy maximum power point estimation for photovoltaic arrays

Quantitative information regarding the maximum power point (MPP) of photovoltaic (PV) arrays is crucial for determining and controlling their operation, yet it is difficult to obtain such information through direct measurements. PV arrays exhibit an extremely nonlinear current-voltage (I-V) characteristic that varies with many complex factors related to the individual cells, which makes it difficult to ensure an optimal use of the available solar energy and to achieve maximum power output in real time. Finding ways to obtain the maximum power output in real time under all possible system conditions are indispensable to the development of feasible PV generation systems. The conventional methods for tracking the MPP of PV arrays suffer from a serious problem that the MPP cannot be quickly acquired. Based on the p-n junction semiconductor theory, we develop a prediction method for directly estimating the MPP for power tracking in PV arrays. The proposed method is a new and simple approach with a low calculation burden that takes the resistance effect of the solar cells into consideration. The MPP of PV arrays can be directly determined from an irradiated I-V characteristic curve. The performance of the proposed method is evaluated by examining the characteristics of the MPP of PV arrays depending on both the temperature and irradiation intensity, and the results are discussed in detail. Such performance is also tested using the field data. The experimental results demonstrate that the proposed method helps in the optimization of the MPP control model in PV arrays.     

永磁电机式机械弹性储能机组储能运行控制策略研究

基于团队先前提出的以涡卷弹簧作为储能元件的机械弹性储能机组技术,简述了以永磁电机为储能电机的机组基本组成与工作原理,建立了永磁电机式机械弹性储能机组(mechanical elastic energy storage, MEES) 各模块数学模型,提出了机组储能过程的恒转速控制策略。利用Matlab/Simulink 构建的机组全仿真模型,对机组储能过程的恒转速控制进行了仿真。仿真结果证明了所搭建模型和控制策略的正确性与有效性。     

Analysis and development of a low-cost permanent magnet brushless DC motor drive for PV-array fed water pumping system

This paper deals with the analysis and development of a permanent magnet brushless DC (PMBLDC) motor drive coupled to a pump load powered by solar photovoltaic (PV) array for water pumping system. A simple low-cost prototype controller has been designed and developed without current and position sensors which reduces drastically the overall cost of the drive system. This controller is used to test the dynamic behavior of the PMBLDC motor drive system. The mathematical model of the system is developed with a view to carry out a comparison between experimental and simulated response of the drive system. A simple filter circuit incorporated in between PV-array and an inverter to reduce ripples and to improve the performance of the PV-array. The necessary computer algorithm is developed to analyze the performance under different conditions of varying solar insolation for a pump load.     

Combined maximum power point tracking and output current control for a photovoltaic-electrolyser DC/DC converter

This paper covers the design and the implementation of the control strategy of a DC/DC converter aimed for hydrogen production from photovoltaic sources. This control scheme provides tight control of the injected current to the electrolyser and, if required, maximum power point tracking of the photovoltaic source, by means of two independent external control loops. The two outer loops create a reference signal for an inner control loop, which adjusts the duty cycle of the DC/DC converter and sets the output inductor current to the desired value. Embedded design, which includes analog and digital electronics, has been considered for the practical implementation. Converter and control loop modelling, simulation and experimental validation are discussed in this work.     

A robust hybrid method for maximum power point tracking in photovoltaic systems

In this paper a new hybrid method for maximum power point tracking in PV systems has been proposed. This method combines offline and online methods in order to estimate duty cycle of converter in maximum power point. In the offline phase, temperature and radiation intensity are the inputs of the system to estimate the approximate maximum power based on analytical equations of solar cell. These equations which give the relation of maximum power with temperature and irradiation can be derived from characteristics of cell provided by manufacturer or experiments. Afterwards the duty cycle of converter would be estimated using circuit equations of measured Thevenin model of the load and battery. Measuring Thevenin equation results in robustness of method respecting variations of load and battery. In the online phase, the classic perturbation and observation (P&O) method will be utilized for fine tuning and tracking of maximum power point. The proposed method has been simulated in MATLAB/SIMULINK workspace and compared with some other MPPT methods. The results reveal that this hybrid method outperforms other methods in term of performance and speed of tracking.     

Modeling and maximum power point tracking (MPPT) method for PV array under partial shade conditions

Influenced by partial shade, PV module aging or fault, there are multiple peaks on PV array's output power–voltage (P–V) characteristic curve. Conventional maximum power point tracking (MPPT) methods are effective for single peak P–V characteristic under uniform solar irradiation, but they may fail in global MPP tracking under multi-peak P–V characteristics. Existing methods in literature for this problem are still unsatisfactory in terms of effectiveness, complexity and speed. In this paper, we first analyze the mathematical model of PV array that is suitable for simulation of complex partial shade situation. Then an adaptive MPPT (AMPPT) method is proposed, which can find real global maximum power point (MPP) for different partial shade conditions. When output characteristic of PV array varies, AMPPT will adjust tracking strategies to search for global peak area (GPA). Then it is easy for conventional MPPT to track the global MPP in GPA. Simulation and experimental results verify that the proposed AMPPT method is able to find real global MPP accurately, quickly and smoothly for complex multi-peak P–V characteristics. Comparison analysis results demonstrate that AMPPT is more effective for most shade types.     

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%.     

永磁直驱风力发电系统MPPT控制的研究

文章首先介绍了风力机模型。然后介绍了一种改进型的变步长爬山算法,通过该算法改变直驱风力发电系统三重交错并联Boost变换电路的占空比,从而实现最大功率跟踪,获取最大风能。最后,利用MATLAB/SIMULINK建立直驱永磁风力发电系统仿真模型并进行研究。试验结果表明,改进型变步长爬山算法比传统爬山算法能更快跟踪最大功率点,控制系统具有较好的控制精度和稳定性。     

分布式光伏发电系统最大功率点跟踪技术比较研究

基于当前光伏阵列最大功率点跟踪技术的研究现状,介绍了适用于分布式光伏发电系统最大功率点跟踪的各种常用控制方法,阐述了每一种控制方法的技术原理,分析和比较了这些常用控制方法的特点,总结了各自的优点和缺点,最后对分布式光伏发电系统最大功率点跟踪方法的选择问题进行了探讨,并指出了具体选择方法时应综合考虑的各种因素。     

Comparative study and performance evaluation of central and distributed topologies of photovoltaic system

In this paper, we present a new alternative for improving both the performance of photovoltaic (PV) systems and the efficiency of the energy conversion by using different configuration of power converters. For this purpose, a comparative study between two configurations is carried out. The first configuration consists of a classical PV generator with a single centralized high power converter and the second one concerns a distributed topology. For this latter we use a certain number of PV strings with low power converters attached in series, in parallel or in a combination of series and parallel. Obviously the string topology has some advantages. Each power converter can control the power conversion of each module individually, which results in increased overall energy conversion of the entire system. The MPPT control system in this case can react effectively to atmospheric variations, to shading effect and to changes in the load. The PV system still operates even in case of failure on one of the power converters in a string. We simulated and compared the different conversion configurations in order to find the best one in terms of efficiency and produced energy. The obtained results are very interesting and can lead to optimal sizing and selection of best PV topology for a given application.     

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.     

An accurate method for the PV model identification based on a genetic algorithm and the interior-point method

Due to the PV module simulation requirements as well as recent applications of model-based controllers, the accurate photovoltaic (PV) model identification method is becoming essential to reduce the PV power losses effectively. The classical PV model identification methods use the manufacturers provided maximum power point (MPP) at the standard test condition (STC). However, the nominal operating cell temperature (NOCT) is the more practical condition and it is shown that the extracted model is not well suited to it. The proposed method in this paper estimates an accurate equivalent electrical circuit for the PV modules using both the STC and NOCT information provided by manufacturers. A multi-objective global optimization problem is formulated using only the main equation of the PV module at these two conditions that restrains the errors due to employing the experimental temperature coefficients. A novel combination of a genetic algorithm (GA) and the interior-point method (IPM) allows the proposed method to be fast and accurate regardless the PV technology. It is shown that the overall error, which is defined by the sum of the MPP errors of both the STC and the NOCT conditions, is improved by a factor between 5.1% and 31% depending on the PV technology.     

Design of a robust and efficient power electronic interface for the grid integration of solar photovoltaic generation systems

Nowadays, the penetration of photovoltaic (PV) solar power generation in distributed generation (DG) systems is growing rapidly. This condition imposes new requirements to the operation and management of the distribution grid, especially when high integration levels are achieved. Under this scenario, the power electronics technology plays a vital role in ensuring an effective grid integration of the PV system, since it is subject to requirements related not only to the variable source itself but also to its effects on the stability and operation of the electric grid. This paper proposes an enhanced interface for the grid connection of solar PV generation systems. The topology employed consists of a three-level cascaded Z-source inverter that allows the flexible, efficient and reliable generation of high quality electric power from the PV plant. A full detailed model is described and its control scheme is designed. The dynamic performance of the designed architecture is verified by computer simulations.     

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.     

A maximum power point tracking for photovoltaic-SPE system using a maximum current controller

Processes to produce hydrogen from solar photovoltaic (PV)-powered water electrolysis using solid polymer electrolysis (SPE) are reported. An alternative control of maximum power point tracking (MPPT) in the PV-SPE system based on the maximum current searching methods has been designed and implemented.Based on the characteristics of voltage–current and theoretical analysis of SPE, it can be shown that the tracking of the maximum current output of DC–DC converter in SPE side will track the MPPT of photovoltaic panel simultaneously.This method uses a proportional integrator controller to control the duty factor of DC–DC converter with pulse-width modulator (PWM).The MPPT performance and hydrogen production performance of this method have been evaluated and discussed based on the results of the experiment.     

Vectorial command of an asynchronous motor fed by a photovoltaic generator

In order to promote renewable energy, Tunisia has developed a large program to exploitate photovoltaïc systems (PV) to provide electric power in rural electrification. These needs increase continually following standard of living improvements, from lighting and media communication (radio, TV) to motors, refrigeration and pumping. The fluctuation of solar energy on one hand, and the necessity to optimise available solar energy on the other, it is useful to develop new efficient and flexible modes to control motors. A vectorial control of an asynchronous motor fed by a photovoltaïc system is proposed. In this case, the control of the circulating current becomes an important objective in the algorithm design. This paper presents an efficient current controller scheme that can achieve high accuracy and a fast dynamic response of induction machine. This scheme uses voltage decoupling and proportional integral controller loops (PI). Furthermore, to operate the PV array at its maximum power point for every instant, the PV system must contain a maximum power point tracking controller (MPPT). Good static and dynamic performances were obtained in simulation of the proposed structure.     

Multi-objective design optimization of a large-scale directdrive permanent magnet generator for wind energy conversion systems

This paper presents a simultaneous multiobjective optimization of a direct-drive permanent magnet synchronous generator and a three-blade horizontal-axis wind turbine for a large scale wind energy conversion system. Analytical models of the generator and the turbine are used along with the cost model for optimization. Three important characteristics of the system i.e., the total cost of the generator and blades, the annual energy output and the total mass of generator and blades are chosen as objective functions for a multi-objective optimization. Genetic algorithm (GA) is then employed to optimize the value of eight design parameters including seven generator parameters and a turbine parameter resulting in a set of Pareto optimal solutions. Four optimal solutions are then selected by applying some practical restrictions on the Pareto front. One of these optimal designs is chosen for finite element verification. A circuit-fed coupled time stepping finite element method is then performed to evaluate the no-load and the full load performance analysis of the system including the generator, a rectifier and a resistive load. The results obtained by the finite element analysis (FEA) verify the accuracy of the analytical model and the proposed method.     

Improved fuzzy logic control-based energy management strategy for hybrid power system of FC/PV/battery/SC on tourist ship

An improved fuzzy-based energy management strategy (EMS) is proposed for a tourist ship used hybrid power system with multiple power sources consisting of fuel cell(FC)/photovoltaic cell(PV)/battery(BAT)/super-capacitor(SC). The power demand from propeller and user terminal is afforded by the power sources connecting to power converters. To obtain more superior performance of the power system, the maximum power point tracking (MPPT) algorithm is employed to optimize the PV. Meanwhile, the improved fuzzy logic control based on dynamic programming (DP) associated with wavelet analysis and PI control are employed to achieve the output power optimal distribution and online control. In particular, the MPPT algorithm can improve the utilization of solar energy, and the SC can well absorb the high frequency power and reduce the fluctuation of the battery and FC that exhibits the potential of their lifetime extension. The FC outputs the high and stable power satisfying the ship's power demand even under the extreme work conditions. The developed model is able to illustrate well in the operation process of the hybrid power system governed by the proposed EMS. In addition, compared with the rule-based strategy, the improved fuzzy-based EMS can reduce 14.39% hydrogen consumption and keep the consistency of battery SOC.     

A novel MPPT controller based PEMFC system for electric vehicle applications with interleaved SEPIC converter

The Proton Exchange Membrane Fuel Cells (PEMFCs) are one of the most effective and optimistic renewable energy source and they are extensively used in automotive applications. In the past, many researchers focused on solving the issues of extracting maximum power from fuel cell, controlling the speed and reducing the torque ripple of Brushless DC (BLDC) motor for fuel cell based Electric Vehicle (EV) systems. However, it is challenging to fine-tuning the gain parameters in the existing works MPPT approach and extracting maximum amount of energy. Additionally, it has limitations like unregulated voltage, problems of large overshoot, slow tracking speed, output power fluctuation, computational complexity and intricate modeling. Thus, the proposed work aims to create a revolutionary methodology called Unified Firefly Ersatz Neural Network (UFENN) - Maximum Power Point Tracking (MPPT). The UFENN is a kind of optimization-based machine learning technique that was created for efficiently optimizing the parameters to extract the maximum energy from the fuel cells. Furthermore, in order to control the output voltage with the least amount of power loss, an Interleaved SEPIC converter is also used in this work. During performance analysis, an extensive simulation results have been taken for validating the results of the proposed scheme by using various evaluation indicators.