For a standalone PV （photovoltaic） power generation system, the author previously proposed a new MPPT （maximum power point tracking） control method in which the I-V characteristics are scanned with a detection int...For a standalone PV （photovoltaic） power generation system, the author previously proposed a new MPPT （maximum power point tracking） control method in which the I-V characteristics are scanned with a detection interval control that operates at specified intervals and monitors the maximum power point. The author has obtained satisfactory results using this new MPPT control method. This paper investigates the application of the new MPPT control method for a PCS （power conditioning system） in a grid-connected type PV power generation system. The experimental results clearly demonstrate that the developed PCS offers outstanding effectiveness in tracking the maximum power point in partially shaded environments.展开更多
Solar energy is a fast growing energy resource among the renewable energy resources in the market and potential for solar power is huge to contribute towards the power demand almost in all the countries. To capture th...Solar energy is a fast growing energy resource among the renewable energy resources in the market and potential for solar power is huge to contribute towards the power demand almost in all the countries. To capture the maximum power from the sun light in order to generate maximum power from the inverter, control system must be an equally efficient with the well designed power electronic circuits. Maximum power point tracking (MPPT) control system in general is taking care of extraction of maximum power from the sun light whereas current controller is mainly designed to optimize the inverter power to feed to power grid. In this paper, a novel MPPT algorithm using neuro fuzzy system is presented to ensure the maximum MPPT efficiency in order to ensure the maximum power across the inverter terminals. Simulation and experimental results for residential solar system with power electronic converters and analysis have been presented in this paper in order to prove the proposed algorithm.展开更多
文章设计了一种光伏控制器,采用STM32F103RBT6单片机作为控制单元,采用降压式Buck变换电路作为控制主电路。控制器通过采集光伏板的输出电压和电流,计算输出功率,通过扰动观察算法保持充电功率的最大值,实现了最大功率点跟踪技术(Maximu...文章设计了一种光伏控制器,采用STM32F103RBT6单片机作为控制单元,采用降压式Buck变换电路作为控制主电路。控制器通过采集光伏板的输出电压和电流,计算输出功率,通过扰动观察算法保持充电功率的最大值,实现了最大功率点跟踪技术(Maximum Power Point Tracking,MPPT),提高光伏转换效率。文章加入温度检测,实现温度补偿,动态调整控制程序充放电阈值,防止蓄电池过充过放,提高蓄电池利用率。展开更多
The Maximum Power Point Tracker (MPPT) is the optimum operating point of a photovoltaic module. It plays a very important role to obtain the maximum power of a solar panel as it allows an optimal use of a photovoltaic...The Maximum Power Point Tracker (MPPT) is the optimum operating point of a photovoltaic module. It plays a very important role to obtain the maximum power of a solar panel as it allows an optimal use of a photovoltaic system, regardless of irradiation and temperature variations. In this research, we present a novel technique to improve the control’s performances optimization of the system consisting of a photovoltaic panel, a buck converter and a load. Simulations of different parts of the system are developed under Matlab/Simulink, thus allowing a comparison between the performances of the three studied controllers: “Fuzzy TS”, “P&O” and “PSO”. The three algorithms of MPPT associated with these techniques are tested in different meteorological conditions. The obtained results, in different operating conditions, reveal a clear improvement of controlling performances of MPPT of a photovoltaic system when the PSO tracking technique is used.展开更多
Renewable energy sources like solar,wind,and hydro are becoming increasingly popular due to the fewer negative impacts they have on the environment.Because,Since the production of renewable energy sources is still in ...Renewable energy sources like solar,wind,and hydro are becoming increasingly popular due to the fewer negative impacts they have on the environment.Because,Since the production of renewable energy sources is still in the process of being created,photovoltaic(PV)systems are commonly utilized for installation situations that are acceptable,clean,and simple.This study presents an adaptive artificial intelligence approach that can be used for maximum power point tracking(MPPT)in solar systems with the help of an embedded controller.The adaptive method incorporates both the Whale Optimization Algorithm(WOA)and the Artificial Neural Network(ANN).The WOA was implemented to enhance the process of the ANN model’s training,and the ANN model was developed using the WOA.In addition to this,the inverter circuit is connected to the smart grid system,and the strengthening of the smart grid is achieved through the implementation of the CMCMAC protocol.This protocol prevents interference between customers and the organizations that provide their utilities.Using a protocol known as Cross-Layer Multi-Channel MAC(CMCMAC),the effect of interference is removed using the way that was suggested.Also,with the utilization of the ZIGBEE communication technology,bidirectional communication is made possible.The strategy that was suggested has been put into practice,and the results have shown that the PV system produces an output power of 73.32 KW and an efficiency of 98.72%.In addition to this,a built-in regulator is utilized to validate the proposed model.In this paper,the results of various experiments are analyzed,and a comparison is made between the suggested WOA with the ANN controller approach and others,such as the Particle Swarm Optimization(PSO)based MPPT and the Cuckoo Search(CS)based MPPT.By examining the comparison findings,it was determined that the adaptive AI-based embedded controller was superior to the other alternatives.展开更多
在局部阴影条件下,常规的最大功率点跟踪MPPT(maximum power point tracking)算法因含有容易陷入局部极值、跟踪精度低等弊端,使其无法及时、精确地跟踪光伏发电系统的最大功率点,因此,提出了一种基于改进型鲸鱼优化算法的光伏发电系统M...在局部阴影条件下,常规的最大功率点跟踪MPPT(maximum power point tracking)算法因含有容易陷入局部极值、跟踪精度低等弊端,使其无法及时、精确地跟踪光伏发电系统的最大功率点,因此,提出了一种基于改进型鲸鱼优化算法的光伏发电系统MPPT控制策略。首先,采用混沌映射初始化种群,增加种群的多样性。其次,通过引入非线性收敛因子使局部寻优能力和全局搜索能力达到均衡。最后,通过引入非线性时变的自适应权重使系统及时跳出局部最优解,并提高搜索的精度。经仿真验证,与粒子群优化算法、狮群优化算法、传统的鲸鱼优化算法等相比,改进的鲸鱼算法在跟踪速度、精度、稳定性等方面均有更显著的效果。展开更多
文摘For a standalone PV （photovoltaic） power generation system, the author previously proposed a new MPPT （maximum power point tracking） control method in which the I-V characteristics are scanned with a detection interval control that operates at specified intervals and monitors the maximum power point. The author has obtained satisfactory results using this new MPPT control method. This paper investigates the application of the new MPPT control method for a PCS （power conditioning system） in a grid-connected type PV power generation system. The experimental results clearly demonstrate that the developed PCS offers outstanding effectiveness in tracking the maximum power point in partially shaded environments.
文摘Solar energy is a fast growing energy resource among the renewable energy resources in the market and potential for solar power is huge to contribute towards the power demand almost in all the countries. To capture the maximum power from the sun light in order to generate maximum power from the inverter, control system must be an equally efficient with the well designed power electronic circuits. Maximum power point tracking (MPPT) control system in general is taking care of extraction of maximum power from the sun light whereas current controller is mainly designed to optimize the inverter power to feed to power grid. In this paper, a novel MPPT algorithm using neuro fuzzy system is presented to ensure the maximum MPPT efficiency in order to ensure the maximum power across the inverter terminals. Simulation and experimental results for residential solar system with power electronic converters and analysis have been presented in this paper in order to prove the proposed algorithm.
文摘文章设计了一种光伏控制器,采用STM32F103RBT6单片机作为控制单元,采用降压式Buck变换电路作为控制主电路。控制器通过采集光伏板的输出电压和电流,计算输出功率,通过扰动观察算法保持充电功率的最大值,实现了最大功率点跟踪技术(Maximum Power Point Tracking,MPPT),提高光伏转换效率。文章加入温度检测,实现温度补偿,动态调整控制程序充放电阈值,防止蓄电池过充过放,提高蓄电池利用率。
文摘The Maximum Power Point Tracker (MPPT) is the optimum operating point of a photovoltaic module. It plays a very important role to obtain the maximum power of a solar panel as it allows an optimal use of a photovoltaic system, regardless of irradiation and temperature variations. In this research, we present a novel technique to improve the control’s performances optimization of the system consisting of a photovoltaic panel, a buck converter and a load. Simulations of different parts of the system are developed under Matlab/Simulink, thus allowing a comparison between the performances of the three studied controllers: “Fuzzy TS”, “P&O” and “PSO”. The three algorithms of MPPT associated with these techniques are tested in different meteorological conditions. The obtained results, in different operating conditions, reveal a clear improvement of controlling performances of MPPT of a photovoltaic system when the PSO tracking technique is used.
基金funding this research work through the Small Group Research Project under Grant Number RGP1/70/44.
文摘Renewable energy sources like solar,wind,and hydro are becoming increasingly popular due to the fewer negative impacts they have on the environment.Because,Since the production of renewable energy sources is still in the process of being created,photovoltaic(PV)systems are commonly utilized for installation situations that are acceptable,clean,and simple.This study presents an adaptive artificial intelligence approach that can be used for maximum power point tracking(MPPT)in solar systems with the help of an embedded controller.The adaptive method incorporates both the Whale Optimization Algorithm(WOA)and the Artificial Neural Network(ANN).The WOA was implemented to enhance the process of the ANN model’s training,and the ANN model was developed using the WOA.In addition to this,the inverter circuit is connected to the smart grid system,and the strengthening of the smart grid is achieved through the implementation of the CMCMAC protocol.This protocol prevents interference between customers and the organizations that provide their utilities.Using a protocol known as Cross-Layer Multi-Channel MAC(CMCMAC),the effect of interference is removed using the way that was suggested.Also,with the utilization of the ZIGBEE communication technology,bidirectional communication is made possible.The strategy that was suggested has been put into practice,and the results have shown that the PV system produces an output power of 73.32 KW and an efficiency of 98.72%.In addition to this,a built-in regulator is utilized to validate the proposed model.In this paper,the results of various experiments are analyzed,and a comparison is made between the suggested WOA with the ANN controller approach and others,such as the Particle Swarm Optimization(PSO)based MPPT and the Cuckoo Search(CS)based MPPT.By examining the comparison findings,it was determined that the adaptive AI-based embedded controller was superior to the other alternatives.
文摘研究了一种基于太阳能光伏电池的双输入Boost变换器。首先介绍了常见的双输入Boost变换器拓扑结构,详细分析了双输入Boost变换器工作在电感电流连续导电模式(Continuous Conduction Mode,CCM)和断续导电模式(Discontinuous Conduction Mode,DCM)时的工作原理和工作过程。由于太阳能光伏电池具有供电不稳定的特点,根据太阳能光伏电池输出功率与负载功率的关系,在稳定输出电压和功率的基础上实现对新能源的优先利用。根据太阳能光伏模块P-V特性的非线性,采用扰动观察法实现对光伏模块的最大功率点跟踪(Maximum Power Point Tracking,MPPT)。基于PSIM仿真平台,搭建基于MPPT控制算法的双输入Boost变换器的仿真电路,并对仿真结果进行了分析。研究结果表明,所搭建的MPPT算法模型实现了最大功率点的跟踪。
文摘在局部阴影条件下,常规的最大功率点跟踪MPPT(maximum power point tracking)算法因含有容易陷入局部极值、跟踪精度低等弊端,使其无法及时、精确地跟踪光伏发电系统的最大功率点,因此,提出了一种基于改进型鲸鱼优化算法的光伏发电系统MPPT控制策略。首先,采用混沌映射初始化种群,增加种群的多样性。其次,通过引入非线性收敛因子使局部寻优能力和全局搜索能力达到均衡。最后,通过引入非线性时变的自适应权重使系统及时跳出局部最优解,并提高搜索的精度。经仿真验证,与粒子群优化算法、狮群优化算法、传统的鲸鱼优化算法等相比,改进的鲸鱼算法在跟踪速度、精度、稳定性等方面均有更显著的效果。
