Under the partial shading conditions(PSC)of Photovoltaic(PV)modules in a PV hybrid system,the power output curve exhibits multiple peaks.This often causes traditional maximum power point tracking(MPPT)methods to fall ...Under the partial shading conditions(PSC)of Photovoltaic(PV)modules in a PV hybrid system,the power output curve exhibits multiple peaks.This often causes traditional maximum power point tracking(MPPT)methods to fall into local optima and fail to find the global optimum.To address this issue,a composite MPPT algorithm is proposed.It combines the improved kepler optimization algorithm(IKOA)with the optimized variable-step perturb and observe(OIP&O).The update probabilities,planetary velocity and position step coefficients of IKOA are nonlinearly and adaptively optimized.This adaptation meets the varying needs of the initial and later stages of the iterative process and accelerates convergence.During stochastic exploration,the refined position update formulas enhance diversity and global search capability.The improvements in the algorithmreduces the likelihood of falling into local optima.In the later stages,the OIP&O algorithm decreases oscillation and increases accuracy.compared with cuckoo search(CS)and gray wolf optimization(GWO),simulation tests of the PV hybrid inverter demonstrate that the proposed IKOA-OIP&O algorithm achieves faster convergence and greater stability under static,local and dynamic shading conditions.These results can confirm the feasibility and effectiveness of the proposed PV MPPT algorithm for PV hybrid systems.展开更多
This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mod...This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mode Control(GFISMC)is proposed based on the tip speed ratio method and sliding mode control.The algorithm uses fast integral sliding mode surface and fuzzy fast switching control items to ensure that the offshore wind power generation system can track the maximum power point quickly and with low jitter.An offshore wind power generation system model is presented to verify the algorithm effect.An offshore off-grid wind-solar hybrid power generation systemis built in MATLAB/Simulink.Compared with other MPPT algorithms,this study has specific quantitative improvements in terms of convergence speed,tracking accuracy or computational efficiency.Finally,the improved algorithm is further analyzed and carried out by using Yuankuan Energy’s ModelingTech semi-physical simulation platform.The results verify the feasibility and effectiveness of the improved algorithm in the offshore wind-solar hybrid power generation system.展开更多
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 pane...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.展开更多
Partial shading conditions(PSCs)caused by uneven illumination become one of the most common problems in photovoltaic(PV)systems,which can make the PV power-voltage(P-V)characteristics curve show multi-peaks.Traditiona...Partial shading conditions(PSCs)caused by uneven illumination become one of the most common problems in photovoltaic(PV)systems,which can make the PV power-voltage(P-V)characteristics curve show multi-peaks.Traditional maximum power point tracking(MPPT)methods have shortcomings in tracking to the global maximum power point(GMPP),resulting in a dramatic decrease in output power.In order to solve the above problems,intelligent algorithms are used in MPPT.However,the existing intelligent algorithms have some disadvantages,such as slow convergence speed and large search oscillation.Therefore,an improved whale algorithm(IWOA)combined with the P&O(IWOA-P&O)is proposed for the MPPT of PV power generation in this paper.Firstly,IWOA is used to track the range interval of the GMPP,and then P&O is used to accurately find the MPP in that interval.Compared with other algorithms,simulation results show that this method has an average tracking efficiency of 99.79%and an average tracking time of 0.16 s when tracking GMPP.Finally,experimental verification is conducted,and the results show that the proposed algorithm has better MPPT performance compared to popular particle swarm optimization(PSO)and PSO-P&O algorithms.展开更多
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 ...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.展开更多
Maximum power point tracking (MPPT) controllers play an important role in photovoltaic systems. They maximize the output power of a PV array for a given set of conditions. This paper presents an overview of the differ...Maximum power point tracking (MPPT) controllers play an important role in photovoltaic systems. They maximize the output power of a PV array for a given set of conditions. This paper presents an overview of the different MPPT techniques. Each technique is evaluated on its ability to detect multiple maxima, convergence speed, ease of implementation, efficiency over a wide output power range, and cost of implementation. The perturbation and observation (P & O), and incremental conductance (IC) algorithms are widely used techniques, with many variants and optimization techniques reported. For this reason, this paper evaluates the performance of these two common approaches from a dynamic and steady state perspective.展开更多
In order to ensure that the photovoltaic(PV) array always works at the global maximum point of power to increase the system's overall efficiency, this paper leads the study on maximum power point tracking(MPPT) in...In order to ensure that the photovoltaic(PV) array always works at the global maximum point of power to increase the system's overall efficiency, this paper leads the study on maximum power point tracking(MPPT) in redundant load mode. A new control system is designed by combining the redundant electronic load module, embedded controller, supportive capacitor and boost circuit. The system adjusts duty ratio of boost circuit dynamically based on the maximum power point parameter provided by redundant load unit in order to realize MPPT. An experiment shows that no matter whether system is under an even illumination or partly perturbed by shadow, this method can find the exact maximum power point.展开更多
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...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.展开更多
The employment of maximum power point tracking techniques in the photovoltaic power systems is well known and even of immense importance. There are various techniques to track the maximum power point reported in sever...The employment of maximum power point tracking techniques in the photovoltaic power systems is well known and even of immense importance. There are various techniques to track the maximum power point reported in several literatures. In such context, there is an increasing interest in developing a more appropriate and effective maximum power point tracking control methodology to ensure that the photovoltaic arrays guarantee as much of their available output power as possible to the load for any temperature and solar radiation levels. In this paper, theoretical details of the work, carried out to develop and implement a maximum power point tracking controller using neural networks for a stand-alone photovoltaic system, are presented. Attention has been also paid to the command of the power converter to achieve maximum power point tracking. Simulations results, using Matlab/Simulink software, presented for this approach under rapid variation of insolation and temperature conditions, confirm the effectiveness of the proposed method both in terms of efficiency and fast response time. Negligible oscillations around the maximum power point and easy implementation are the main advantages of the proposed maximum power point tracking (MPPT) control method.展开更多
This paper presents an analysis of the effect of parasitic resistances on the performance of DC-DC Single Ended Pri- mary Inductor Converter (SEPIC) in photovoltaic maximum power point tracking (MPPT) applications. Th...This paper presents an analysis of the effect of parasitic resistances on the performance of DC-DC Single Ended Pri- mary Inductor Converter (SEPIC) in photovoltaic maximum power point tracking (MPPT) applications. The energy storage elements incorporated in the SEPIC converter possess parasitic resistances. Although ideal components significantly simplifies model development, but neglecting the parasitic effects in models may sometimes lead to failure in predicting first scale stability and actual performance. Therefore, the effects of parasitics have been taken into consideration for improving the model accuracy, stability, robustness and dynamic performance analysis of the converter. Detail mathematical model of SEPIC converter including inductive parasitic has been developed. The performance of the converter in tracking MPP at different irradiance levels has been analyzed for variation in parasitic resistance. The converter efficiency has been found above 83% for insolation level of 600 W/m2 when the parasitic resistance in the energy storage element has been ignored. However, as the parasitic resistance of both of the inductor has increased to 1 ohm, a fraction of the power managed by the converter has dissipated;as a result the efficiency of the converter has reduced to 78% for the same insolation profile. Although the increasing value of the parasitic has assisted the converter to converge quickly to reach the maximum power point. Furthermore it has also been observed that the peak to peak load current ripple is reduced. The obtained simulation results have validated the competent of the MPPT converter model.展开更多
光伏阵列P-U特性曲线在局部遮阴状态下呈现多峰状态,传统的最大功率追踪算法容易陷入局部最优状态。针对此问题,提出了一种基于改进麻雀搜索算法的最大功率点跟踪(maximum power point tracking,MPPT)方法。在麻雀搜索算法中引入遗传算...光伏阵列P-U特性曲线在局部遮阴状态下呈现多峰状态,传统的最大功率追踪算法容易陷入局部最优状态。针对此问题,提出了一种基于改进麻雀搜索算法的最大功率点跟踪(maximum power point tracking,MPPT)方法。在麻雀搜索算法中引入遗传算法和Lévy飞行策略,使算法的全局搜索能力得以增强,并且可以跳出局部最优解。在MATLAB/Simulink中建立仿真模型,并与粒子群优化算法和原始麻雀搜索算法进行比较。仿真结果表明,基于改进麻雀搜索算法的MPPT方法在不同光照条件下均显示出更高的效率和稳定性。展开更多
光伏阵列在局部阴影条件下P-U曲线会出现多个峰值,传统的粒子群优化PSO(particle swarm optimization)算法无法快速精确地搜寻到最大功率点。针对这种情况,本文提出1种基于混沌映射和高斯扰动的改进粒子群优化算法最大功率点跟踪MPPT(ma...光伏阵列在局部阴影条件下P-U曲线会出现多个峰值,传统的粒子群优化PSO(particle swarm optimization)算法无法快速精确地搜寻到最大功率点。针对这种情况,本文提出1种基于混沌映射和高斯扰动的改进粒子群优化算法最大功率点跟踪MPPT(maximum power point tracking)控制策略。首先引入混沌Sine映射构造1种非线性随机递增惯性权重,并在粒子群的“个体认知”部分引入高斯扰动,同时利用对数函数构造学习因子,形成基于混沌映射和高斯扰动的改进粒子群算法;通过对6种典型单峰、多峰函数的测试,证明该算法收敛速度更快,不易陷入局部最优;将算法应用于MPPT控制中,并进一步通过不同算法MPPT控制进行对比仿真研究。对比仿真结果表明:在均匀光照强度、局部静态遮荫和动态遮荫3种情况下,基于混沌映射和高斯扰动的改进粒子群优化算法MPPT控制策略均具有更快的收敛速度和更小的搜索振荡幅度,能准确地搜寻到最大功率点,具有更高的寻优精度,从而提高了MPPT系统的发电效率。展开更多
目的光伏电池在实际应用中接收的光照可能会被遮挡,光伏阵列会在局部遮阴条件下运行,造成光伏系统输出功率出现多峰值的情况。针对传统最大功率点追踪(Maximum Power Point Tracking,MPPT)算法全局追踪能力弱,以及难以兼顾追踪速度和精...目的光伏电池在实际应用中接收的光照可能会被遮挡,光伏阵列会在局部遮阴条件下运行,造成光伏系统输出功率出现多峰值的情况。针对传统最大功率点追踪(Maximum Power Point Tracking,MPPT)算法全局追踪能力弱,以及难以兼顾追踪速度和精度的问题,提出了猎人猎物优化算法(Hunter-Prey Optimization,HPO)与变步长扰动观察法(Improved Perturbation and Observation,IP&O)的结合算法。方法首先利用HPO算法,初始化种群之后得到光伏系统的初始最大功率,并将其定义为整个算法的全局最优值;之后每次更新输出功率都要与最优值比较,保留功率较大的作为全局最优值;当满足算法切换条件时,认为HPO算法已经追踪到最大功率点附近,切换到IP&O算法在最大功率点附近扰动,直至输出最优值;当光伏系统接收到光照发生变化时,可以通过重启条件快速重启HPO-IP&O算法。结果为验证所提算法的可靠性,在MATLAB/Simlink中建立光伏系统仿真模型;在不同的光照条件下,分别将粒子群算法(Particle Swarm Optimization,PSO)、鲸鱼算法(Whale Optimization Algorithm,WOA)和所提算法对比;仿真结果表明:HPO-IP&O算法不会陷入局部极值,同时其追踪精度也优于WOA算法,但是与PSO算法相差不大;在追踪速度上,HPO-IP&O算法均快于WOA和PSO算法,且功率越大,HPO-IP&O所用时间越短。结论HPO-IP&O算法解决了传统MPPT算法易陷入局部最优值、无法兼顾追踪速度和精度的问题,通过仿真实验验证了所提算法在不同光照条件下的可行性和可靠性。展开更多
基金funding from the Graduate Practice Innovation Program of Jiangsu University of Technology(XSJCX23_58)Changzhou Science and Technology Support Project(CE20235045)Open Project of Jiangsu Key Laboratory of Power Transmission&Distribution Equipment Technology(2021JSSPD12).
文摘Under the partial shading conditions(PSC)of Photovoltaic(PV)modules in a PV hybrid system,the power output curve exhibits multiple peaks.This often causes traditional maximum power point tracking(MPPT)methods to fall into local optima and fail to find the global optimum.To address this issue,a composite MPPT algorithm is proposed.It combines the improved kepler optimization algorithm(IKOA)with the optimized variable-step perturb and observe(OIP&O).The update probabilities,planetary velocity and position step coefficients of IKOA are nonlinearly and adaptively optimized.This adaptation meets the varying needs of the initial and later stages of the iterative process and accelerates convergence.During stochastic exploration,the refined position update formulas enhance diversity and global search capability.The improvements in the algorithmreduces the likelihood of falling into local optima.In the later stages,the OIP&O algorithm decreases oscillation and increases accuracy.compared with cuckoo search(CS)and gray wolf optimization(GWO),simulation tests of the PV hybrid inverter demonstrate that the proposed IKOA-OIP&O algorithm achieves faster convergence and greater stability under static,local and dynamic shading conditions.These results can confirm the feasibility and effectiveness of the proposed PV MPPT algorithm for PV hybrid systems.
基金supported by the 2022 Sanya Science and Technology Innovation Project,China(No.2022KJCX03)the Sanya Science and Education Innovation Park,Wuhan University of Technology,China(Grant No.2022KF0028)the Hainan Provincial Joint Project of Sanya Yazhou Bay Science and Technology City,China(Grant No.2021JJLH0036).
文摘This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mode Control(GFISMC)is proposed based on the tip speed ratio method and sliding mode control.The algorithm uses fast integral sliding mode surface and fuzzy fast switching control items to ensure that the offshore wind power generation system can track the maximum power point quickly and with low jitter.An offshore wind power generation system model is presented to verify the algorithm effect.An offshore off-grid wind-solar hybrid power generation systemis built in MATLAB/Simulink.Compared with other MPPT algorithms,this study has specific quantitative improvements in terms of convergence speed,tracking accuracy or computational efficiency.Finally,the improved algorithm is further analyzed and carried out by using Yuankuan Energy’s ModelingTech semi-physical simulation platform.The results verify the feasibility and effectiveness of the improved algorithm in the offshore wind-solar hybrid power generation system.
文摘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.
基金supported in part by the Natural Science Foundation of Jiangsu Province under Grant BK20200969(L.Z.,URL:http://std.jiangsu.gov.cn/)in part by Basic Science(Natural Science)Research Project of Colleges and Universities in Jiangsu Province under Grant 22KJB470025(L.R.,URL:http://jyt.jiangsu.gov.cn/)in part by Social People’s Livelihood Technology Plan General Project of Nantong under Grant MS12021015(L.Q.,URL:http://kjj.nantong.gov.cn/).
文摘Partial shading conditions(PSCs)caused by uneven illumination become one of the most common problems in photovoltaic(PV)systems,which can make the PV power-voltage(P-V)characteristics curve show multi-peaks.Traditional maximum power point tracking(MPPT)methods have shortcomings in tracking to the global maximum power point(GMPP),resulting in a dramatic decrease in output power.In order to solve the above problems,intelligent algorithms are used in MPPT.However,the existing intelligent algorithms have some disadvantages,such as slow convergence speed and large search oscillation.Therefore,an improved whale algorithm(IWOA)combined with the P&O(IWOA-P&O)is proposed for the MPPT of PV power generation in this paper.Firstly,IWOA is used to track the range interval of the GMPP,and then P&O is used to accurately find the MPP in that interval.Compared with other algorithms,simulation results show that this method has an average tracking efficiency of 99.79%and an average tracking time of 0.16 s when tracking GMPP.Finally,experimental verification is conducted,and the results show that the proposed algorithm has better MPPT performance compared to popular particle swarm optimization(PSO)and PSO-P&O algorithms.
文摘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.
文摘Maximum power point tracking (MPPT) controllers play an important role in photovoltaic systems. They maximize the output power of a PV array for a given set of conditions. This paper presents an overview of the different MPPT techniques. Each technique is evaluated on its ability to detect multiple maxima, convergence speed, ease of implementation, efficiency over a wide output power range, and cost of implementation. The perturbation and observation (P & O), and incremental conductance (IC) algorithms are widely used techniques, with many variants and optimization techniques reported. For this reason, this paper evaluates the performance of these two common approaches from a dynamic and steady state perspective.
基金the National Natural Science Foundation of China(No.61107064)the Leading Academic Discipline Project of Communication and Information System(No.XXKZD1605)
文摘In order to ensure that the photovoltaic(PV) array always works at the global maximum point of power to increase the system's overall efficiency, this paper leads the study on maximum power point tracking(MPPT) in redundant load mode. A new control system is designed by combining the redundant electronic load module, embedded controller, supportive capacitor and boost circuit. The system adjusts duty ratio of boost circuit dynamically based on the maximum power point parameter provided by redundant load unit in order to realize MPPT. An experiment shows that no matter whether system is under an even illumination or partly perturbed by shadow, this method can find the exact maximum power point.
基金supported by the National Natural Science Foundation of China (Grant No.20576071)
文摘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.
基金supported by the National Natural Science Foundation of China(61203129,61174038,61473151,51507080)the Fundamental Research Funds for the Central Universities(30915011104,30920130121010,30920140112005)
文摘The employment of maximum power point tracking techniques in the photovoltaic power systems is well known and even of immense importance. There are various techniques to track the maximum power point reported in several literatures. In such context, there is an increasing interest in developing a more appropriate and effective maximum power point tracking control methodology to ensure that the photovoltaic arrays guarantee as much of their available output power as possible to the load for any temperature and solar radiation levels. In this paper, theoretical details of the work, carried out to develop and implement a maximum power point tracking controller using neural networks for a stand-alone photovoltaic system, are presented. Attention has been also paid to the command of the power converter to achieve maximum power point tracking. Simulations results, using Matlab/Simulink software, presented for this approach under rapid variation of insolation and temperature conditions, confirm the effectiveness of the proposed method both in terms of efficiency and fast response time. Negligible oscillations around the maximum power point and easy implementation are the main advantages of the proposed maximum power point tracking (MPPT) control method.
文摘This paper presents an analysis of the effect of parasitic resistances on the performance of DC-DC Single Ended Pri- mary Inductor Converter (SEPIC) in photovoltaic maximum power point tracking (MPPT) applications. The energy storage elements incorporated in the SEPIC converter possess parasitic resistances. Although ideal components significantly simplifies model development, but neglecting the parasitic effects in models may sometimes lead to failure in predicting first scale stability and actual performance. Therefore, the effects of parasitics have been taken into consideration for improving the model accuracy, stability, robustness and dynamic performance analysis of the converter. Detail mathematical model of SEPIC converter including inductive parasitic has been developed. The performance of the converter in tracking MPP at different irradiance levels has been analyzed for variation in parasitic resistance. The converter efficiency has been found above 83% for insolation level of 600 W/m2 when the parasitic resistance in the energy storage element has been ignored. However, as the parasitic resistance of both of the inductor has increased to 1 ohm, a fraction of the power managed by the converter has dissipated;as a result the efficiency of the converter has reduced to 78% for the same insolation profile. Although the increasing value of the parasitic has assisted the converter to converge quickly to reach the maximum power point. Furthermore it has also been observed that the peak to peak load current ripple is reduced. The obtained simulation results have validated the competent of the MPPT converter model.
文摘光伏阵列P-U特性曲线在局部遮阴状态下呈现多峰状态,传统的最大功率追踪算法容易陷入局部最优状态。针对此问题,提出了一种基于改进麻雀搜索算法的最大功率点跟踪(maximum power point tracking,MPPT)方法。在麻雀搜索算法中引入遗传算法和Lévy飞行策略,使算法的全局搜索能力得以增强,并且可以跳出局部最优解。在MATLAB/Simulink中建立仿真模型,并与粒子群优化算法和原始麻雀搜索算法进行比较。仿真结果表明,基于改进麻雀搜索算法的MPPT方法在不同光照条件下均显示出更高的效率和稳定性。
文摘光伏阵列在局部阴影条件下P-U曲线会出现多个峰值,传统的粒子群优化PSO(particle swarm optimization)算法无法快速精确地搜寻到最大功率点。针对这种情况,本文提出1种基于混沌映射和高斯扰动的改进粒子群优化算法最大功率点跟踪MPPT(maximum power point tracking)控制策略。首先引入混沌Sine映射构造1种非线性随机递增惯性权重,并在粒子群的“个体认知”部分引入高斯扰动,同时利用对数函数构造学习因子,形成基于混沌映射和高斯扰动的改进粒子群算法;通过对6种典型单峰、多峰函数的测试,证明该算法收敛速度更快,不易陷入局部最优;将算法应用于MPPT控制中,并进一步通过不同算法MPPT控制进行对比仿真研究。对比仿真结果表明:在均匀光照强度、局部静态遮荫和动态遮荫3种情况下,基于混沌映射和高斯扰动的改进粒子群优化算法MPPT控制策略均具有更快的收敛速度和更小的搜索振荡幅度,能准确地搜寻到最大功率点,具有更高的寻优精度,从而提高了MPPT系统的发电效率。
文摘目的光伏电池在实际应用中接收的光照可能会被遮挡,光伏阵列会在局部遮阴条件下运行,造成光伏系统输出功率出现多峰值的情况。针对传统最大功率点追踪(Maximum Power Point Tracking,MPPT)算法全局追踪能力弱,以及难以兼顾追踪速度和精度的问题,提出了猎人猎物优化算法(Hunter-Prey Optimization,HPO)与变步长扰动观察法(Improved Perturbation and Observation,IP&O)的结合算法。方法首先利用HPO算法,初始化种群之后得到光伏系统的初始最大功率,并将其定义为整个算法的全局最优值;之后每次更新输出功率都要与最优值比较,保留功率较大的作为全局最优值;当满足算法切换条件时,认为HPO算法已经追踪到最大功率点附近,切换到IP&O算法在最大功率点附近扰动,直至输出最优值;当光伏系统接收到光照发生变化时,可以通过重启条件快速重启HPO-IP&O算法。结果为验证所提算法的可靠性,在MATLAB/Simlink中建立光伏系统仿真模型;在不同的光照条件下,分别将粒子群算法(Particle Swarm Optimization,PSO)、鲸鱼算法(Whale Optimization Algorithm,WOA)和所提算法对比;仿真结果表明:HPO-IP&O算法不会陷入局部极值,同时其追踪精度也优于WOA算法,但是与PSO算法相差不大;在追踪速度上,HPO-IP&O算法均快于WOA和PSO算法,且功率越大,HPO-IP&O所用时间越短。结论HPO-IP&O算法解决了传统MPPT算法易陷入局部最优值、无法兼顾追踪速度和精度的问题,通过仿真实验验证了所提算法在不同光照条件下的可行性和可靠性。
