In this paper,a computer-controlled photovoltaic(PV)array simulator consisted of a synchronous buck DC converter and its associate control software is proposed and developed to simulate the current-voltage(I-V)output ...In this paper,a computer-controlled photovoltaic(PV)array simulator consisted of a synchronous buck DC converter and its associate control software is proposed and developed to simulate the current-voltage(I-V)output characteristics of a real-time PV array with actual loads connected.The main advantage of this simulator is its ability in simulating different types and sizes of arrays under various illumination and temperature conditions.It can replace the actual PV array and perform all the simulations indoor instead of outside field testing.The mathematical model implemented in this system requires minimum manufacturer's data.This system is a very cost effective and reliable laboratory tool to investigate the output characteristics of PV array under various weather conditions,and is helpful for developing new maximum power point tracking(MPPT)algorithms.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 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 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.展开更多
The output power of the photovoltaic （PV） array changes with the change in external environment and load. Therefore, maximum power point tracking （MPPT） technology is needed to maximize the efficiency of the PV de...The output power of the photovoltaic （PV） array changes with the change in external environment and load. Therefore, maximum power point tracking （MPPT） technology is needed to maximize the efficiency of the PV device. At present, existing methods have realized MPPT to some extent. However, the tracking precision and speed remain to be improved. In the current paper, the chaos search theory is first applied on the MPPT technology of the PV system. The chaos search algorithm based on dual carrier increases the adequacy of chaos search and overcomes the blindness of the traditional chaos search, thereby improving the search efficiency. Comparative tests show that the proposed method can quickly and accurately track the step response, and can obtain better optimization results. The simulation and experimentalresults show the effectiveness and good performance of the proposed method.展开更多
PV power production is highly dependent on environmental and weather conditions,such as solar irradiance and ambient temperature.Because of the single control condition and any change in the external environment,the f...PV power production is highly dependent on environmental and weather conditions,such as solar irradiance and ambient temperature.Because of the single control condition and any change in the external environment,the first step response of the converter duty cycle of the traditional MPPT incremental conductance algorithm is not accurate,resulting in misjudgment.To improve the efficiency and economy of PV systems,an improved incremental conductance algorithm of MPPT control strategy is proposed.From the traditional incremental conductance algorithm,this algorithm is simple in structure and can discriminate the instantaneous increment of current,voltage and power when the external environment changes,and so can improve tracking efficiency.MATLAB simulations are carried out under rapidly changing solar radiation level,and the results of the improved and conventional incremental conductance algorithm are compared.The results show that the proposed algorithm can effectively identify the misjudgment and avoid its occurrence.It not only optimizes the system,but also improves the efficiency,response speed and tracking efficiency of the PV system,thus ensuring the stable operation of the power grid.展开更多
To extract the maximum power from a photovoltaic （PV） energy system, the real-time maximum power point （MPP） of the PV array must be tracked closely. The non-linear and time-variant characteristics of the PV array...To extract the maximum power from a photovoltaic （PV） energy system, the real-time maximum power point （MPP） of the PV array must be tracked closely. The non-linear and time-variant characteristics of the PV array and the non-linear and non-minimum phase characteristics of a boost converter make it difficult to track the MPP for traditional control strategies. We propose a fuzzy neural network controller （FNNC）, which combines the reasoning capability of fuzzy logical systems and the learning capability of neural networks, to track the MPP. With a derived learning algorithm, the parameters of the FNNC are updated adaptively. A gradient estimator based on a radial basis function neural network is developed to provide the reference information to the FNNC. Simulation results show that the proposed control algorithm provides much better tracking performance compared with the filzzy logic control algorithm.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
文摘In this paper,a computer-controlled photovoltaic(PV)array simulator consisted of a synchronous buck DC converter and its associate control software is proposed and developed to simulate the current-voltage(I-V)output characteristics of a real-time PV array with actual loads connected.The main advantage of this simulator is its ability in simulating different types and sizes of arrays under various illumination and temperature conditions.It can replace the actual PV array and perform all the simulations indoor instead of outside field testing.The mathematical model implemented in this system requires minimum manufacturer's data.This system is a very cost effective and reliable laboratory tool to investigate the output characteristics of PV array under various weather conditions,and is helpful for developing new maximum power point tracking(MPPT)algorithms.
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.
文摘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.
基金supported by the Scientific Research Foundation of State Key Laboratory of Power Transmission Equipment and System Security (No.2007DA10512709211)the Fundamental Research Funds for the Central Universities (No. CDJXS10151151)
文摘The output power of the photovoltaic （PV） array changes with the change in external environment and load. Therefore, maximum power point tracking （MPPT） technology is needed to maximize the efficiency of the PV device. At present, existing methods have realized MPPT to some extent. However, the tracking precision and speed remain to be improved. In the current paper, the chaos search theory is first applied on the MPPT technology of the PV system. The chaos search algorithm based on dual carrier increases the adequacy of chaos search and overcomes the blindness of the traditional chaos search, thereby improving the search efficiency. Comparative tests show that the proposed method can quickly and accurately track the step response, and can obtain better optimization results. The simulation and experimentalresults show the effectiveness and good performance of the proposed method.
基金The Project Supported by Natural Science Basic Research Plan in Shaanxi Province of China(Program No.2019JM-544).
文摘PV power production is highly dependent on environmental and weather conditions,such as solar irradiance and ambient temperature.Because of the single control condition and any change in the external environment,the first step response of the converter duty cycle of the traditional MPPT incremental conductance algorithm is not accurate,resulting in misjudgment.To improve the efficiency and economy of PV systems,an improved incremental conductance algorithm of MPPT control strategy is proposed.From the traditional incremental conductance algorithm,this algorithm is simple in structure and can discriminate the instantaneous increment of current,voltage and power when the external environment changes,and so can improve tracking efficiency.MATLAB simulations are carried out under rapidly changing solar radiation level,and the results of the improved and conventional incremental conductance algorithm are compared.The results show that the proposed algorithm can effectively identify the misjudgment and avoid its occurrence.It not only optimizes the system,but also improves the efficiency,response speed and tracking efficiency of the PV system,thus ensuring the stable operation of the power grid.
基金Project (No. 20576071) supported by the National Natural Science Foundation of China
文摘To extract the maximum power from a photovoltaic （PV） energy system, the real-time maximum power point （MPP） of the PV array must be tracked closely. The non-linear and time-variant characteristics of the PV array and the non-linear and non-minimum phase characteristics of a boost converter make it difficult to track the MPP for traditional control strategies. We propose a fuzzy neural network controller （FNNC）, which combines the reasoning capability of fuzzy logical systems and the learning capability of neural networks, to track the MPP. With a derived learning algorithm, the parameters of the FNNC are updated adaptively. A gradient estimator based on a radial basis function neural network is developed to provide the reference information to the FNNC. Simulation results show that the proposed control algorithm provides much better tracking performance compared with the filzzy logic control algorithm.
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.
