针对光照强度和负载等因素变化引起的光伏功率波动较大、跟踪速度较慢的问题,提出了一种基于改进模糊算法的复合Boost光伏系统最大功率点跟踪(maximum power point tracking,MPPT)策略。分析系统光伏特性和复合Boost电路原理,构建光伏...针对光照强度和负载等因素变化引起的光伏功率波动较大、跟踪速度较慢的问题,提出了一种基于改进模糊算法的复合Boost光伏系统最大功率点跟踪(maximum power point tracking,MPPT)策略。分析系统光伏特性和复合Boost电路原理,构建光伏系统模型;结合模糊控制理论提出光伏MPPT模糊控制方法,增加模糊量隶属度函数并优化模糊规则,以提高功率跟踪精度和收敛速度;对比分析该算法与粒子群优化算法及扰动观察法的功率跟踪效果,验证了所提策略的有效性。展开更多
In this paper, a mathematical model of the photovoltaic （PV） pumping system＇s main components is firstly established. Then, the design of maximum power point tracking （MPPT） stage that ensures battery charging is...In this paper, a mathematical model of the photovoltaic （PV） pumping system＇s main components is firstly established. Then, the design of maximum power point tracking （MPPT） stage that ensures battery charging is described. This work is motivated by the need of photovoltaic generator （PVG） that efficiently extracts maximum power. The PVG is a special source of energy which has nonlinear current-voltage characteristics depending on variations in temperature and solar irradiance. In order to achieve the MPPT operating goals, a special interest is focused on the variable structure sliding mode （SM） control strategy and the classic perturb and observe （P＆O） algorithm. The permanent magnet synchronous motor （PMSM） is selected as a pump driver. The field oriented control is performed as the motor drive strategy. Simulation results show a high level of efficiency, obtained with the proposed PV based pumping system. The performance comparison between SM controller and P＆O controller has been carried out to demonstrate the effectiveness of the former in drawing more energy and a fast response against irradiation disturbances.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
文摘针对光照强度和负载等因素变化引起的光伏功率波动较大、跟踪速度较慢的问题,提出了一种基于改进模糊算法的复合Boost光伏系统最大功率点跟踪(maximum power point tracking,MPPT)策略。分析系统光伏特性和复合Boost电路原理,构建光伏系统模型;结合模糊控制理论提出光伏MPPT模糊控制方法,增加模糊量隶属度函数并优化模糊规则,以提高功率跟踪精度和收敛速度;对比分析该算法与粒子群优化算法及扰动观察法的功率跟踪效果,验证了所提策略的有效性。
文摘In this paper, a mathematical model of the photovoltaic （PV） pumping system＇s main components is firstly established. Then, the design of maximum power point tracking （MPPT） stage that ensures battery charging is described. This work is motivated by the need of photovoltaic generator （PVG） that efficiently extracts maximum power. The PVG is a special source of energy which has nonlinear current-voltage characteristics depending on variations in temperature and solar irradiance. In order to achieve the MPPT operating goals, a special interest is focused on the variable structure sliding mode （SM） control strategy and the classic perturb and observe （P＆O） algorithm. The permanent magnet synchronous motor （PMSM） is selected as a pump driver. The field oriented control is performed as the motor drive strategy. Simulation results show a high level of efficiency, obtained with the proposed PV based pumping system. The performance comparison between SM controller and P＆O controller has been carried out to demonstrate the effectiveness of the former in drawing more energy and a fast response against irradiation disturbances.
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.
