A novel fuzzy logic control technique tuned by particle swarm optimization for maximum power point tracking for a photovoltaic system using a current-mode boost converter with bifurcation control

This paper presents a novel fuzzy logic control technique tuned by particle swarm optimization (PSO-FLC) for maximum power point tracking (MPPT) for a photovoltaic (PV) system. The proposed PV system composes of a current-mode boost converter (CMBC) with bifurcation control. An optimal slope compensation technique is used in the CMBC to keep the system adequately remote from the first bifurcation point in spite of nonlinear characteristics and instabilities of this converter. The proposed PSO technique allows easy and more accurate tuning of FLC compared with the trial-and-error based tuning. Consequently, the proposed PSO-FLC method provides faster tracking of maximum power point (MPP) under varying light intensities and temperature conditions. The proposed MPPT technique is simple and particularly suitable for PV system equipped with CMBC. Experimental results are shown to confirm superiority of the proposed technique comparing with the conventional PVVC technique and the trial-and-error based tuning FLC.     

Maximum power tracking of a generic photovoltaic system via a fuzzy controller and a two-stage DC–DC converter

This study presents a new two-stage DC–DC converter for maximum power point tracking (MPPT) and a voltage boost of a generic photovoltaic (PV) system. An intelligent MPPT of PV system based on fuzzy logic control (FLC) is presented to adaptively design the proposed fuzzy controlled MPPT controller (FC-MPPTC) while a voltage boost controller (VBC) is used to fix the output voltage to a voltage level that is higher than the required operating voltage to the back-end grid impedance. Modeling and simulation on the PV system and the DC–DC converter circuit are achieved by state-space and the software Powersim. The PV string considered has the rated power around 600?VA under varied partial shadings. The FC-MPPTC and VBC are designed and realized by a DSP module (TMS320F2812) to adjust the duty cycle in the two-stage DC–DC converter. A special FLC algorithm is forged to render an MPPT faster and more accurate than conventional MPPT technique, perturb and observe (P&O). The simulations are intended to validate the performance of the proposed FC-MPPTC. Experiments are conducted and results show that MPPT can be achieved in a fast pace and the efficiency reaches over 90?%, even up to 96?%. It is also found that the optimized tracking speed of the proposed FC-MPPTC is in fact more stable and faster than the general P&O method with the boost voltage capable of offering a stable DC output.     

New MPPT algorithm for PV applications based on hybrid dynamical approach

This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.     

PI controller design using ABC algorithm for MPPT of PV system supplying DC motor pump load

Maximum power point tracking (MPPT) is used in photovoltaic (PV) systems to maximize its output power. A new MPPT system has been suggested for PV–DC motor pump system by designing two PI controllers. The first one is used to reach MPPT by monitoring the voltage and current of the PV array and adjusting the duty cycle of the DC/DC converter. The second PI controller is designed for speed control of DC series motor by setting the voltage fed to the DC series motor through another DC/DC converter. The suggested design problem of MPPT and speed controller is formulated as an optimization task which is solved by artificial bee colony (ABC) to search for optimal parameters of PI controllers. Simulation results have shown the validity of the developed technique in delivering MPPT to DC series motor pump system under atmospheric conditions and tracking the reference speed of motor. Moreover, the performance of the ABC algorithm is compared with genetic algorithm for various disturbances to prove its robustness.

     

Control of Grid Connected Photovoltaic Systems with Microinverters: New Theoretical Design and Numerical Evaluation

This paper addresses the problem of controlling grid connected photovoltaic (PV) systems that are driven with microinverters. The systems to be controlled consist of a solar panel, a boost dc–dc converter, a DC link capacitor, a single‐phase full‐bridge inverter, a filter inductor, and an isolation transformer. We seek controllers that are able to simultaneously achieve four control objectives, namely: (i) asymptotic stability of the closed loop control system; (ii) maximum power point tracking (MPPT) of the PV module; (iii) tight regulation of the DC bus voltage; and (iv) unity power factor (PF) in the grid. To achieve these objectives, a new multiloop nonlinear controller is designed using the backstepping design technique. A key feature of the control design is that it relies on an averaged nonlinear system model accounting, on the one hand, for the nonlinear dynamics of the underlying boost converter and inverter and, on the other, for the nonlinear characteristic of the PV panel. To achieve the MPPT objective, a power optimizer is designed that computes online the optimal PV panel voltage used as a reference signal by the PV voltage regulator. It is formally shown that the proposed controller meets all the objectives. This theoretical result is confirmed by numerical simulation tests.     

Climatic sensorless maximum power point tracking in PV generation systems

The problem of maximum power point tracking (MPPT) is addressed for photovoltaic (PV) arrays considered in a given panel position. The PV system includes a PV panel, a PWM boost power converter and a storing battery. Although the maximum power point (MPP) of PV generators varies with solar radiation and temperature, the MPPT is presently sought without resorting to solar radiation and temperature sensors in order to reduce the PV system cost. The proposed sensorless control solution is an adaptive nonlinear controller involving online estimation of uncertain parameters, i.e. those depending on radiation and temperature. The adaptive control problem at hand is not a standard one because parameter uncertainty affects, in addition to system dynamics, the output-reference trajectory (expressing the MPPT purpose). Therefore, the convergence of parameter estimates to their true values is necessary for MPPT achievement. It is formally shown, under mild assumptions, that the developed adaptive controller actually meets the MPPT objective.     

Development and analysis of adaptive fuzzy controllers for photovoltaic system under varying atmospheric and partial shading condition

Control of power electronics converters used in PV system is very much essential for the efficient operation of the solar system. In this paper, a modified incremental conduction maximum power point tracking (MPPT) algorithm in conjunction with an adaptive fuzzy controller is proposed to control the DC–DC boost converter in the PV system under rapidly varying atmospheric and partial shading conditions. An adaptive hysteresis current controller is proposed to control the inverter. The proposed current controller provides constant switching frequency with less harmonic content compared with fixed hysteresis current control algorithm and sinusoidal PWM controller. The modeling and simulation of PV system along with the proposed controllers are done using MATLAB/SIMSCAPE software. Simulation results show that the proposed MPPT algorithm is faster in transient state and presents smoother signal with less fluctuations in steady state. The hardware implementation of proposed MPPT algorithm and inverter current control algorithms using Xilinx spartran-3 FPGA is also presented. The experimental results show satisfactory performance of the proposed approaches.     

ANN-based MPPT algorithm for solar PMSM drive system fed by direct-connected PV array

In this paper, artificial neural network (ANN) based on a maximum power point tracking (MPPT) algorithm is developed for a solar permanent magnet synchronous motor (PMSM) drive system used without a boost converter and batteries. The discontinuous space vector PWM technique is used to drive two-level inverter which is directly fed by three parallel-connected Kyocera KD205GX-LP PV modules. The ANN-based MPPT algorithm estimates the voltages and currents corresponding to maximum powers produced by PV array at the maximum power point (MPP) for swiftly changing situations such as solar radiance and temperature. These maximum powers are given as input signal to vector control algorithm of PMSM. The PMSM is designed by using Infolytica/MotorSolve software so that the phase-to-phase maximum value of its operating voltage is 20 V. The use of three-phase PMSM presents more efficient solutions to the trading solar systems with dc motor or induction motor. Thus, an effective solar system is achieved. The performance of developed ANN-based MPPT algorithm, designed PMSM, vector-controlled driver and solar system is analyzed by using MATLAB/SimPowerSystems blocks under the rapidly changing environmental conditions.

     

Hybrid Renewable Energy Source Combined Dynamic Voltage Restorer for Power Quality Improvement

In this paper, the hybrid photovoltaic-thermoelectric generator (PV-TEG) combined dynamic voltage restorer (DVR) system is proposed for the power quality disturbances compensation in a single-phase distribution system. The stable and precise level of input voltage is essential for the smooth and trouble-free operation of the electrically sensitive loads which are connected at the utility side to avoid system malfunctions. In this context, the hybrid PV-TEG energy module combined DVR system is proposed in this paper. With the support of the hybrid energy module, the DVR will perform the power quality disturbances compensation effectively with needed voltage and /or power. In the proposed system, the PV and TEG energy sources are connected electrically in series to produce adequate voltage for the DVR operation and the fractional factor-based variable incremental conduction (FFVINC) maximum power point tracking (MPPT) control algorithm is employed to extract the possible maximum power from the PV array. The intelligent fuzzy logic controller (FLC) is chosen for implementing the MPPT control algorithm. The half-bridge voltage source inverter (VSI) circuit and in-phase voltage compensation technique are used in the DVR for better power quality disturbances compensation. The performance and usefulness of the proposed DVR system are investigated by an extensive simulation study with four different modes of operation, the study results are confirmed that the proposed system promptly identifies the power quality disturbances for compensation. Moreover, the investigation proved that the combined PV and TEG energy module can provide better energy efficiency in converting solar irradiation into electricity.     

Output feedback control of sensorless photovoltaic systems,with maximum power point tracking

This paper presents an output feedback control of sensorless photovoltaic systems with maximum power point tracking (MPPT). The system consists of a Photovoltaic Generator (PVG) which supplies a DC centrifugal pump, via a DC/DC boost converter. This later being connected to the PVG by a long PV cable. Generally, PV systems are established near the control unit of the converter. The MPPT methods and control laws are based on the PVG voltage and current measurements. However, PV arrays must be located in a site that guarantees good solar radiation. In most cases, such a site is at great distance from the control unit. Thus, on the one hand, the PVG voltage and current measurements become difficult and, on the other hand, the PV cable parameters could significantly effect the MPPT control accuracy if only voltage and current measurements in the cable converter side are used. To overcome these issues, a state estimation for PV systems is considered in this paper. A high gain observer is designed on the basis of a PV system model that accounts for PV cable parameters. It provides estimates of PVG output voltage and current using only current and voltage measurements in the converter side of the cable. A backstepping controller is then synthesized with the view of ensuring the MPPT objective. The output feedback control convergence is formally analyzed and its performances are illustrated by simulation.     

Bond graph modeling and optimization of photovoltaic pumping system: Simulation and experimental results

Bond graphs are a promising possibility for modeling complex physical systems. This paper explores its potential by undertaking the analysis, modeling and design of a water pumping photovoltaic system. The effectiveness of photovoltaic water pumping systems depends on the sufficiency between the generated energy and the volume of pumped water. Another point developed in this paper presents the optimization of a photovoltaic (PV) water pumping system using maximum power point tracking technique (MPPT). The optimization is based on the detection of the optimal power. This optimization technique is developed to optimize the usage of power. The presented MPPT technique is used in photovoltaic water pumping system in order to increasing its efficiency. A buck–boost chopper allows an adaptation interface between the panel and the battery checked by a tracking mechanism known as the MPPT (Maximum Power Point Tracking). A new algorithm is presented to control a maximum power point tracker MPPT through a bond graph. From the chemical reactions in the batteries to the control laws of the power electronics structures, a bond graph model is proposed for every single part of the system. The model is used in simulations and the results compared to actual measurements. The model is used in simulations and the results compared to actual measurements, showing an accuracy of nearly 99%.     

Maximum Power Extraction Control Algorithm for Hybrid Renewable Energy System

In this research, a modified fractional order proportional integral derivate (FOPID) control method is proposed for the photovoltaic (PV) and thermoelectric generator (TEG) combined hybrid renewable energy system. The faster tracking and steady-state output are aimed at the suggested maximum power point tracking (MPPT) control technique. The derivative order number (µ) value in the improved FOPID (also known as PI^λD^µ) control structure will be dynamically updated utilizing the value of change in PV array voltage output. During the transient, the value of µ is changeable; it’s one at the start and after reaching the maximum power point (MPP), allowing for strong tracking characteristics. TEG will use the freely available waste thermal energy created surrounding the PV array for additional power generation, increasing the system’s energy conversion efficiency. A high-gain DC-DC converter circuit is included in the system to maintain a high amplitude DC input voltage to the inverter circuit. The proposed approach’s performance was investigated using an extensive MATLAB software simulation and validated by comparing findings with the perturbation and observation (P&O) type MPPT control method. The study results demonstrate that the FOPID controller-based MPPT control outperforms the P&O method in harvesting the maximum power achievable from the PV-TEG hybrid source. There is also a better control action and a faster response.     

DC–DC Converter with Pi Controller for BLDC Motor Fuzzy Drive System

The Brushless DC Motor drive systems are used widely with renewable energy resources. The power converter controlling technique increases the performance by novel techniques and algorithms. Conventional approaches are mostly focused on buck converter, Fuzzy logic control with various switching activity. In this proposed research work, the QPSO (Quantum Particle Swarm Optimization algorithm) is used on the switching state of converter from the generation unit of solar module. Through the duty cycle pulse from optimization function, the MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor) of the Boost converter gets switched when BLDC (Brushless Direct Current Motor) motor drive system requires power. Voltage Source three phase inverter and Boost converter is controlled by proportional-integral (PI) controller. Based on the BLDC drive, the load utilized from the solar generating module. Experimental results analyzed every module of the proposed grid system, which are solar generation utilizes the irradiance and temperature depends on this the Photovoltaics (PV) power is generated and the QPSO with Duty cycle switching state is determined. The Boost converter module is boost stage based on generation and load is obtained. Single Ended Primary Inductor Converter (SEPIC) and Zeta converter model is compared with the proposed logic; the proposed boost converter achieves the results. Three phase inverter control, PI, and BLDC motor drive results. Thus the proposed grid model is constructed to obtain the better performance results than most recent literatures. Overall design model is done by using MATLAB/Simulink 2020a.     

基于交错Buck变换器的光伏系统MPPT控制

具有最大功率点跟踪(MPPT)功能的控制器常采用单相Buck变换器,输出功率稳定性差;鉴于此,提出将交错并联技术应用于Buck变换器,并以两相交错并联Buck变换器为例进行研究,减小输出电压、电流纹波,提高了输出功率稳定性,有利于实现MPPT控制;然后针对固定步长扰动观察法跟踪速度与精度之间的矛盾,研究了一种自适应变步长的算法,MATLAB仿真结果表明,改进算法具有较好的跟踪速度和稳态性能。     

智能全功率MPPT风光互补路灯控制器设计

针对一类普通风光互补路灯控制器转换能效低、稳定性差等问题,设计一种智能全功率MPPT风光互补路灯控制器.采用双MCU处理器PIC16F877A单片机为控制器核心,硬件采用模块化的设计方法,整个控制器由主控制模块、从控制模块、风力发电机智能升压MPPT模块,以及风力发电机点刹控制模块、太阳能智能升压MPPT模块、蓄电池充/放电模块、负载LED灯模块组成,在分析光伏电池和风力发电机最大功率点跟踪问题的基础上,采用风力发电机和太阳能智能全功率MPPT跟踪控制策略.最后,在实验室搭建测试平台,测试结果表明,控制器可以可靠稳定运行,跟普通控制器相比,其充电效率与能源利用能效提高22.1％,能够实现能源的最大化利用.     

BUCK变换器带恒功率负载反馈精确线性化控制

对BUCK交换器带恒功率负载系统的非线性控制进行了研究.根据恒功率负载的非线性特性,推导出BUCK变换器带恒功率负载的精确线性化反馈控制规律,设计了系统非线性控制器.用SABER软件对控制律进行了仿真,结果表明反馈精确线性化技术可以实现对BUCK变换器带恒功率负载的控制,在电源及负载大范围变化时,保证系统的稳定运行,具有大信号稳定特性.     

基于Buck变换器的光伏发电系统MPPT 控制

介绍以Buck变换器为对象的太阳能光伏发电系统。用Buck变换器实现对光伏发电系统的最大功率跟踪,采用逐次逼近法的MPPT控制策略,通过调节Buck变换器的PWM占空比输出,使得负载的等效阻抗跟随光伏电池的输出阻抗,使光伏阵列在任何条件下获得最大功率输出,跟踪最大功率。仿真表明MPPT（最大功率跟踪）控制策略的可行性。     

Design of PWM with four transistor comparator for DC–DC boost converters

The DC-DC converter is used for different applications which needs higher voltages when compared to the input source. The boost converter is one of the most efficient methods to choose DC-DC Converter in different ways. The purpose of the proposed method is to reduce the area of VLSI design logic and power consumption. Boost converter topology is difficult because it has a large component. The proposed work of four transistor comparator based PWM (Pulse width Modulator) that can be used in DC-DC boost converter, which reduces the area, and power consumption of the entire system. This proposed work calculates the parameters of boost converter and the simulation performed using different duty cycle and parameters. Simulation results shows different duty cycles with different resistance and inductance parameters using boost converter. In addition to this the result carries out four transistor comparator output which is used to reduce the boost converter circuit design. PWM is based on the proposed four transistor comparator, which is used in the Cadence Virtuoso software using conventional CMOS technology.     

Performance Improvement of Fuel Cells Using Perturbation‐Based Extremum Seeking and Model Reference Adaptive Control

Nowadays, fuel cells (FCs) are considered suitable alternative sources for electrical energy applications. One major challenge encountered in FCs is relevant to the performance of the maximum power point tracking (MPPT) under FC parameter changes and load variations. This challenge is due to the nonlinearity and time‐varying dynamics of FC systems. In this paper, the MPPT is studied in a system composed of a FC and a DC‐DC converter. To improve the performance of the MPPT, application of perturbation‐based extremum seeking (PES) and model reference adaptive control (MRAC) is proposed. This control scheme can efficiently handle the uncertainties in the FC as well as the load, through two control levels. The first level is PES utilized to adjust the duty cycle of the DC‐DC converter; and the second level is MRAC employed to achieve the desired dynamic response. Using the proposed control strategy, design and analysis of the control levels can be realized independently, which results in easy implementation. This is achieved due to considerable differences between the time constants of the control levels. The simulation results are utilized to confirm the effectiveness of the proposed scheme in response to the variations of FC parameters and load. Also, comparative studies with a combination of PES and PID controller are provided in the simulation.     

A novel MPPT algorithm based on optimized artificial neural network by using FPSOGSA for standalone photovoltaic energy systems

Maximum power point tracking (MPPT) algorithms are used to maximize the output power of the photovoltaic (PV) panel under different temperature and irradiance conditions in photovoltaic energy sources (PVES). In this paper, a novel MPPT method based on optimized artificial neural network by using hybrid particle swarm optimization and gravitational search algorithm based on fuzzy logic (FPSOGSA) is proposed to track the operation of the PV panel in maximum power point (MPP). The performance of the proposed MPPT approach is tested by doing the simulation and experimental studies under different environmental conditions. The proposed method is compared with the conventional perturb and observation (P&O) method for standalone PVES. The results of the comparison the obtained from the simulation and experimental studies demonstrate that the proposed MPPT method provides the reduction oscillations around the MPP and the increased maximum power yield of the PV system in the steady state.