A New Flower Pollination Algorithm Strategy for MPPT of Partially Shaded Photovoltaic Arrays

Photovoltaic(PV)systems utilize maximum power point tracking(MPPT)controllers to optimize power output amidst varying environmental conditions.However,the presence of multiple peaks resulting from partial shading poses a challenge to the tracking operation.Under partial shade conditions,the global maximum power point(GMPP)may be missed by most traditional maximum power point tracker.The flower pollination algorithm(FPA)and particle swarm optimization(PSO)are two examples of metaheuristic techniques that can be used to solve the issue of failing to track the GMPP.This paper discusses and resolves all issues associated with using the standard FPA method as the MPPT for PV systems.The first issue is that the initial values of pollen are determined randomly at first,which can lead to premature convergence.To minimize the convergence time and enhance the possibility of detecting the GMPP,the initial pollen values were modified so that they were near the expected peak positions.Secondly,in the modified FPA,population fitness and switch probability values both influence swapping between two-mode optimization,which may improve the flower pollination algorithm’s tracking speed.The performance of the modified flower pollination algorithm(MFPA)is assessed through a comparison with the perturb and observe(P&O)method and the standard FPA method.The simulation results reveal that under different partial shading conditions,the tracking time for MFPA is 0.24,0.24,0.22,and 0.23 s,while for FPA,it is 0.4,0.35,0.45,and 0.37 s.Additionally,the simulation results demonstrate that MFPA achieves higher MPPT efficiency in the same four partial shading conditions,with values of 99.98%,99.90%,99.93%,and 99.26%,compared to FPA with MPPT efficiencies of 99.93%,99.88%,99.91%,and 99.18%.Based on the findings from simulations,the proposed method effectively and accurately tracks the GMPP across a diverse set of environmental conditions.

Comparative assessment of maximum power point tracking procedures for photovoltaic systems

The fast growing demands and increasing awareness for the environment, PV systems are being rapidly installed for numerous applications.However, one of the important challenges in utilizing a PV source is the maximum power harnessing using various maximum power point tracking techniques available. With the large number of MPPT techniques, each having some merits and demerits, confusion is always there for their proper selection. Discussion on various proposed procedures for maximum power point tracking of photovoltaic array has been done. Based on different parameters analysis of MPPT techniques is carried out. This assessment will serve as a suitable reference for selection, understanding different ways and means of MPPT.

MPPT research based on fuzzy adaptive PID control

In order to improve the efficiency and precision of maximum power point tracking(MPPT)control,a new method is proposed.Based on original MPPT technology of photovoltaic cells,the fuzzy adaptive proportion-integral-differential(PID)control has less fluctuation and higher stability.The simulation circuit using Simulink is established,and output power curves under constant temperature or constant sunlight are obtained.The superiority of the fuzzy PID control method has been proved by means of the simulation results,and it makes the solar system approach maximum power point quickly and smoothly.

Maximum power point tracking of a photovoltaic energy system using neural fuzzy techniques

In order to improve the output efficiency of a photovoltaic （PV） energy system, the real-time maximum power point （MPP） of the PV array should be tracked closely. The non-linear and time-variant characteristics of the photovoltaic array and the non-linear and non-minimum phase characteristics of a boost converter make it difficult to track the MPP as in traditional control strategies. A neural fuzzy controller （NFC） in conjunction with the reasoning capability of fuzzy logical systems and the learning capability of neural networks is proposed to track the MPP in this paper. A gradient estimator based on a radial basis function neural network is developed to provide the reference information to the NFC. With a derived learning algorithm, the parameters of the NFC are updated adaptively. Experimental results show that, compared with the fuzzy logic control algorithm, the proposed control algorithm provides much better tracking performance.

基于boost电路和Fibonacci-MPPT方法的设计实现

采用芯片STM32F103控制系统实现最大功率点追踪,BOOST电路作为DC-DC主电路,对1500w的太阳能电池进行Fibonacci-MPPT方法实现,设计结果验证了Fibonacci-MPPT算法,得到了寻优快速、动态性能较好的系统功率输出曲线。

Maximum Power Point Tracking Using the Incremental Conductance Algorithm for PV Systems Operating in Rapidly Changing Environmental Conditions

Maximum Power Point Tracking (MPPT) is an important process in Photovoltaic (PV) systems because of the need to extract maximum power from PV panels used in these systems. Without the ability to track and have PV panels operate at its maximum power point (MPP) entails power losses;resulting in high cost since more panels will be required to provide specified energy needs. To achieve high efficiency and low cost, MPPT has therefore become an imperative in PV systems. In this study, an MPP tracker is modeled using the IC algorithm and its behavior under rapidly changing environmental conditions of temperature and irradiation levels is investigated. This algorithm, based on knowledge of the variation of the conductance of PV cells and the operating point with respect to the voltage and current of the panel calculates the slope of the power characteristics to determine the MPP as the peak of the curve. A simple circuit model of the DC-DC boost converter connected to a PV panel is used in the simulation;and the output of the boost converter is fed through a 3-phase inverter to an electricity grid. The model was simulated and tested using MATLAB/Simulink. Simulation results show the effectiveness of the IC algorithm for tracking the MPP in PV systems operating under rapidly changing temperatures and irradiations with a settling time of 2 seconds.

Enhancement of Solar PV Panel Efficiency Using Double Integral Sliding Mode MPPT Control

The extraction of maximum power from the solar panels,using the sliding mode control scheme,becomes popular for partial weather atmospheric conditions due to its effective dynamic duty cycle ratio.However,the sliding mode control scheme was sophisticated with single integral and double integral sliding mode control scheme,which offer enhanced maximum power extraction and support enhanced solar panel efficiency in partial weather conditions.The operation of the sliding mode control scheme depends on the selection of a sliding surface selection based on the atmospheric weather condition,which enables the effective sliding duty cycle ratio operation for the DC/DC boost converter.The duty cycle ratio of the sliding mode control resembles the usual dynamic behavior to achieve enhanced efficiency compared to the various maximum power point tracking(MPPT)schemes.The major limitation of the sliding mode control scheme is to achieve the steady state voltage error of the solar panel in minimum settling time duration.The single integral sliding mode control scheme achieves the expected steady state voltage error limit but fails to achieve minimum settling time duration.Hence,the single integral sliding mode control is extended to a double integral sliding mode control scheme to achieve both steady state voltage error limits within the minimum settling time duration.This double integral sliding mode control scheme allows us to obtain the higher sliding surface duty cycle ratio which acts as the input signal to the boost converter.This activates the enhanced stable and reliable system operation,and nullifies the lacuna of maximum solar panel efficiency under partial weather conditions.Hence,this paper aims to present the design and performance operation of the double integral sliding mode(DISM)MPPT control scheme.To validate the performance analysis of the proposed DISM MPPT control scheme,the MATLAB/Simulink model is designed and verified.Also,the performance analysis of the proposed DISM MPPT control scheme is compared with the sliding mode controller(SMC)scheme and single integral sliding mode controller(SiSMC)scheme.The performance analysis of the proposed double integral sliding mode controller(DISMC)scheme attains 99.10%of efficiency and a very less setting time of 0.035s when compared to other existingmethods.

A Review of State-of-the-art Flexible Power Point Tracking Algorithms in Photovoltaic Systems for Grid Support:Classification and Application

To maximize conversion efficiency,photovoltaic(PV)systems generally operate in the maximum power point tracking(MPPT)mode.However,due to the increasing penetra tion level of PV systems,there is a need for more developed control functions in terms of frequency support services and voltage control to maintain the reliability and stability of the power grid.Therefore,flexible active power control is a manda tory task for grid-connected PV systems to meet part of the grid requirements.Hence,a significant number of flexible pow er point tracking(FPPT)algorithms have been introduced in the existing literature.The purpose of such algorithms is to real ize a cost-effective method to provide grid support functional ities while minimizing the reliance on energy storage systems.This paper provides a comprehensive overview of grid support functionalities that can be obtained with the FPPT control of PV systems such as frequency support and volt-var control.Each of these grid support functionalities necessitates PV sys tems to operate under one of the three control strategies,which can be provided with FPPT algorithms.The three control strate gies are classified as:①constant power generation control(CP GC),②power reserve control(PRC),and③power ramp rate control(PRRC).A detailed discussion on available FPPT algo rithms for each control strategy is also provided.This paper can serve as a comprehensive review of the state-of-the-art FPPT algorithms that can equip PV systems with various grid support functionalities.

基于蚁群算法的局部阴影光伏最大功率跟踪算法

针对局部阴影情况下光伏输出曲线非线性和多峰值的特性,提出基于蚁群算法的光伏多峰值最大功率跟踪算法.通过对光伏输出曲线的结构及均匀分布特性的分析,构建蚁群极值寻优过程,对特定区间进行极值点搜索,最后求出最大功率点.仿真表明,该算法能够有效地跟踪全局最大功率点,避免其收敛于局部最优解,与传统全局扫描算法不同,其收敛速度及精度不受光伏曲线形状的影响.

基于数模混合控制的快速光伏模拟器

针对目前光伏电池最大功率点跟踪(MPPT)算法扰动频率越来越高的问题,设计了一种基于数模混合控制的快速光伏模拟器。模拟器的数字部分采用数字信号处理器(DSP)实现,所提出的算法首先使用四段折线法拟合光伏电池的伏安特性曲线,线性化的拟合结果可简化运算过程;接着采样输出电压、电流,计算出了负载阻抗;最后利用负载阻抗定位法,只用一个运算周期确定光伏模拟器的静态工作点。模拟部分主功率电路为同步BUCK,控制算法采用峰值电流控制以提高电路的响应速度,且其输出电压和电流可跟踪数字部分输出的具有光伏特性的参考值。建立模型分析模拟器的响应时间为0.22 ms,满足光伏变流器的MPPT算法要求。仿真和实验结果表明,理论分析准确,所设计的光伏模拟器具有实用性。

Comparative Performance of Fixed-Speed and Variable-Speed Wind Turbine Generator Systems

In the early development of the wind energy, the majority of the wind turbines have been operated at constant speed. Subsequently, the number of variable-speed wind turbines installed in wind farms has increased. In this paper, a comparative performance of fixed and variable speed wind generators with Pitch angle control has been presented. The first is based on a squirrel cage Induction Generator （IG） of 315 kW rated power, connected directly to the grid. The second incorporated a Permanent Magnet Synchronous Generator （PMSG） of 750 kW rated power. The performances of each studied wind generator are evaluated by simulation works and variable speed operation is highlighted as preferred mode of operation.

Direct driven wind energy conversion system based on hybrid excitation synchronous machine

A novel direct-drive type wind power generation system based on hybrid excitation synchronous machine（HESM）is introduced in this paper.The generator is connected to an uncontrollable rectifier,and a fully controlled voltage-sourceinverter is used to connect the system to utility grid.An intermediate DC bus exists between the rectifier and inverter.A new control strategy is proposed which achieves the maximum power point tracking（MPPT） with the control of excitation current of HESM and stabilizes the DC link voltage with the control of inverter output current simultaneously.Specially-designed buck circuit is used to control the excitation current of HESM,and grid voltage-oriented vector control strategy is employed to realize the decoupling of the inverter output power.Simulation results and experiment in 3 kW lab prototype show an excellent static and dynamic performance of the proposed system.

Optimal Control of Hybrid Photovoltaic-Thermometric Generator System Using GEPSO

Recently the concern about energy consumption across the globe has become more severe due to global warming. One essential way to address this problem is to maximize the efficiency of existing renewable energy resources and effectively eliminate their power losses. The previous studies on energy harvesting of photovoltaic (PV) modules try to cope with this problem using gradient-based control techniques and pay little attention to the significant loss of solar energy in the form of waste heat. To reconcile these waste-heat problems, this paper investigates hybrid photovoltaic-thermoelectric generation (PV-TEG) systems. We implement the generalized particle swarm optimization (GEPSO) technique to maximize the power of PV systems under dynamic conditions by utilizing the waste heat to produce electricity through embedding the thermoelectric generator (TEG) with the PV module. The removal of waste heat increases the efficiency of PV systems and also adds significant electrical power. As a control method, the proposed GEPSO can maximize the output power. Simulations confirm that GEPSO outperforms some state-of-the-art methods, e.g., the perturb and observe (PO), cuckoo search (CS), incremental conductance (INC), and particle swarm optimization (PSO), in terms of accuracy and tracking speed.

An Improved Perturb and Observe Maximum Power Point Tracking Algorithm for Photovoltaic Power Systems

This paper aims to improve the performance of the conventional perturb and observe(P&O)maximum power point tracking(MPPT)algorithm.As the oscillation around the maximum power point(MPP)is the main disadvantage of this technique,we introduce a modified P&O algorithm to conquer this handicap.The new algorithm recognizes approaching the peak of the photovoltaic(PV)array power curve and prevents the oscillation around the MPP.The key to achieve this goal is testing the change of output power in each cycle and comparing it with the change in array terminal power of the previous cycle.If a decrease in array terminal power is observed after an increase in the previous cycle or in the opposite direction,an increase in array terminal power is observed after a decrease in the previous cycle;it means we are at the peak of the power curve,so the duty cycle of the boost converter should remain the same as the previous cycle.Besides,an optimized duty cycle is introduced,which is adjusted based on the operating point of PV array.Furthermore,a DC-DC boost converter powered by a PV array simulator is used to test the proposed concept.When the irradiance changes,the proposed algorithm produces an averageηMPPT of nearly 3.1%greater than that of the conventional P&O algorithm and the incremental conductance(In C)algorithm.In addition,under strong partial shading conditions and drift avoidance tests,the proposed algorithm produces an averageηMPPT of nearly 9%and 8%greater than that of the conventional algorithms,respectively.

Improved MPPT Control Strategy for PV Connected to Grid Using IncCond-PSO-MPC Approach

This paper proposes a new hybrid maximum power point tracking(MPPT)control strategy for grid-connected solar systems based on Incremental conductance—Particle Swarm Optimization and Model Predictive Controller(IncCond-PSOMPC).The purpose of the suggested method is to create as much power as feasible from a PV system during environmental changes,then transfer it to the power grid.To accomplish this,a hybrid combination of incremental conductance(IncCond)and particle swarm optimization(PSO)is proposed to locate maximum power,followed by model predictive control(MPC)to track maximum power and control the boost converter to achieve high performance regardless of parameter variations.A two-level inverter,likewise,controlled by Model Predictive Control,is employed to inject the PV power generated.In this application,the MPC is based on minimizing the difference between the reference and prediction powers,which is computed to select the switching state of the inverter.The proposed system is simulated and evaluated in a variety of dynamic conditions using Matlab/Simulink.Results reveal that the proposed control mechanism is effective at tracking the maximum power point(MPP)with fewer power oscillations.

Adaptive perturb and observe maximum power point tracking with current predictive and decoupled power control for gridconnected photovoltaic inverters

In order to improve maximum power point tracking(MPPT) performance, a variable and adaptive perturb and observe(P&O)method with current predictive control is proposed. This is applied in three-phase threelevel neutral-point clamped(NPC) photovoltaic(PV)generation systems. To control the active power and the reactive power independently,the decoupled power control combined with a space vector modulation block is adopted for three-phase NPC inverters in PV generation systems.To balance the neutral-point voltage of the three-phase NPC grid-connected inverter, a proportional and integral control is used by adj usting the dwell time of small voltage vectors. A three-phase NPC inverter rated at 12 kVA was established. The performance of the proposed method was tested and compared with the fixed perturbation MPPT algorithm under different conditions. Experimental results confirm the feasibility and advantages of the proposed method.

Analysis and research on Maximum Power Point Tracking of Photovoltaic Array with Fuzzy Logic Control and Three-point Weight Comparison Method

The Photovoltaic Array has a best optimal operating point where the array operating can obtain the maximum power.However, the optimal operating point can be compromised by the strength of solar radiation,angle,and by the change of environment and load.Due to the constant changes in these conditions,it has become very difficult to locate the optimal operating point by following a mathematical model.Therefore,this study will focus mostly on the application of Fuzzy Logic Control theory and Three-point Weight Comparison Method in effort to locate the optimal operating point of solar panel and achieve maximum efficiency in power generation. The Three-point Weight Comparison Method is the comparison between the characteristic curves of the voltage of photovoltaic array and output power;it is a rather simple way to track the maximum power.The Fuzzy Logic Control,on the other hand,can be used to solve problems that cannot be effectively dealt with by calculation rules,such as concepts,contemplation, deductive reasoning,and identification.Therefore,this paper uses these two kinds of methods to make simulation successively. The simulation results show that,the Three-point Comparison Method is more effective under the environment with more frequent change of solar radiation;however,the Fuzzy Logic Control has better tacking efficiency under the environment with violent change of solar radiation.

Optimal Estimation and Tracking Control for Variable-speed Wind Turbine with PMSG

Designing an optimal tracking controller and system observer is a nonlinear problem in the variable-speed wind energy conversion system(WECS).In this paper,an adjusted feedforward and feedback optimal controller with extended Kalman filter(EKF)is introduced to estimate and control the permanent magnet synchronous generator(PMSG)for the maximum power point tracking(MPPT)with several disturbances of the wind speed.An augmented model of wind turbine and PMSG is expanded,and then the parameters of the optimal controller and estimator are obtained.The dynamic stability of the closed-loop system with feedback-feedforward controller(FFC),EKF and speed controller are analyzed.To compare the dynamic performance of EKF and FFC with the conventional controllers,numerical results are demonstrated with the disturbances of the wind speed and faults in power grid.

Optimized Fuzzy Controller for MPPT of Grid-connected PV Systems in Rapidly Changing Atmospheric Conditions

Due to nonlinear behavior of power production of photovoltaic(PV)systems,it is necessary to apply the maximum power point tracking(MPPT)techniques to generate the maximum power.The conventional MPPT methods do not function properly in rapidly changing atmospheric conditions.In this study,a fuzzy logic controller(FLC)optimized by a combination of particle swarm optimization(PSO)and genetic algorithm(GA)is proposed to obtain the maximum power point(MPP).The proposed FLC uses the ratio of power variations to voltage variations and the derivative of power variations to voltage variations as inputs and uses the duty cycle as the output.The range of changes in fuzzy membership functions and fuzzy rules are proposed as an optimization problem optimized by the PSO-GA.The proposed design is validated for MPPT of a PV system using MATLAB/Simulink software.The results indicate a better performance of the proposed FLC compared to the common methods.

Unified MPPT Controller for Partially Shaded Panels in a Photovoltaic Array

The power output of the photovoltaic(PV) system having multiple arrays gets reduced to a great extent when it is partially shaded due to environmental hindrances. The maximum power trackers which are conventionally used may not be competent enough to find the maximum power point(MPP) during partially shaded conditions. The sensible reason for the failure of conventional trackers is during partial shaded conditions the PV arrays exhibit multi peak power curves, thereby making simple maximum power point tracking(MPPT) algorithms like perturb and observe(P&O) to get stuck with local maxima instead of capturing global maxima.Therefore, global search MPPT aided by evolutionary and swarm intelligence algorithms will be conducive to find global power point during partially shaded conditions. This work suggests a unified controller which feeds control signal to its power electronic conditioner placed at each module. The evolutionary algorithm which is taken into consideration in this work is differential evolution(DE).The performance of the proposed method is compared to the classical un-dimensional search controller and it is evident from the Matlab/Simulink results that the unified controller prevails over the distributed counterpart.