A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there ...A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there is a need for a control schema to force the PV string to operate at global maximum power point (GMPP). While a lot of tracking methods have been proposed in the literature, they are usually complex and do not fully take advantage of the available characteristics of the PV array. This work highlights how the voltage at operating point and the forward voltage of the bypass diode are considered to design a global maximum power point tracking (GMPPT) algorithm with a very limited global search phase called Fast GMPPT. This algorithm successfully tracks GMPP between 94% and 98% of the time under a theoretical evaluation. It is then compared against Perturb and Observe, Deterministic Particle Swarm Optimization, and Grey Wolf Optimization under a sequence of irradiance steps as well as a power-over-voltage characteristics profile that mimics the electrical characteristics of a PV string under varying partial shading conditions. Overall, the simulation with the sequence of irradiance steps shows that while Fast GMPPT does not have the best convergence time, it has an excellent convergence rate as well as causes the least amount of power loss during the global search phase. Experimental test under varying partial shading conditions shows that while the GMPPT proposal is simple and lightweight, it is very performant under a wide range of dynamically varying partial shading conditions and boasts the best energy efficiency (94.74%) out of the 4 tested algorithms.展开更多
The present study was carried out in order to track the maximum power point in a variable speed turbine by minimizing electromechanical torque changes using a sliding mode control strategy. In this strategy, first, th...The present study was carried out in order to track the maximum power point in a variable speed turbine by minimizing electromechanical torque changes using a sliding mode control strategy. In this strategy, first, the rotor speed is set at an optimal point for different wind speeds. As a result of which, the tip speed ratio reaches an optimal point, mechanical power coefficient is maximized, and wind turbine produces its maximum power and mechanical torque. Then, the maximum mechanical torque is tracked using electromechanical torque. In this technique, tracking error integral of maximum mechanical torque, the error, and the derivative of error are used as state variables. During changes in wind speed, sliding mode control is designed to absorb the maximum energy from the wind and minimize the response time of maximum power point tracking(MPPT). In this method, the actual control input signal is formed from a second order integral operation of the original sliding mode control input signal. The result of the second order integral in this model includes control signal integrity, full chattering attenuation, and prevention from large fluctuations in the power generator output. The simulation results, calculated by using MATLAB/m-file software, have shown the effectiveness of the proposed control strategy for wind energy systems based on the permanent magnet synchronous generator(PMSG).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
A photovoltaic array is environmentally friendly and a source of unlimited energy generation.However,it is presently a costlier energy generation system than other non-renewable energy sources.The main reasons are sea...A photovoltaic array is environmentally friendly and a source of unlimited energy generation.However,it is presently a costlier energy generation system than other non-renewable energy sources.The main reasons are seasonal variations and continuously changing weather conditions,which affect the amount of solar energy received by the solar panels.In addition,the non-linear characteristics of the voltage and current outputs along with the operating environment temperature and variation in the solar radiation decrease the energy conversion capability of the photovoltaic arrays.To address this problem,the global maxima of the PV arrays can be tracked using a maximum power point tracking algorithm(MPPT)and the operating point of the photovoltaic system can be forced to its optimum value.This technique increases the efficiency of the photovoltaic array and minimizes the cost of the system by reducing the number of solar modules required to obtain the desired power.However,the tracking algorithms are not equally effective in all areas of application.Therefore,selecting the correct MPPT is very critical.This paper presents a detailed review and comparison of the MPPT techniques for photovoltaic systems,with consideration of the following key parameters:photovoltaic array dependence,type of system(analog or digital),need for periodic tuning,convergence speed,complexity of the system,global maxima,implemented capacity,and sensed parameter(s).In addition,based on real meteorological data(irradiance and temperature at a site located in Addis Ababa,Ethiopia),a simulation is performed to evaluate the performance of tracking algorithms suitable for the application being studied.Finally,the study clearly validates the considerable energy saving achieved by using these 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
Based on the characteristic of AC-excited variable speed constant frequency(VSCF)wind power generation,the vector control technique was applied in a doubly fed induction generator(DFIG).Maximum wind energy or maximum ...Based on the characteristic of AC-excited variable speed constant frequency(VSCF)wind power generation,the vector control technique was applied in a doubly fed induction generator(DFIG).Maximum wind energy or maximum output power point can be tracked by decoupling control of active power and reactive power.The research result shows that the net power of generation system delivered to grid in maximum wind energy tracking mode is not the most.We presented a novel maximum power point tracking(MPPT)control strategy by analyzing the DFIG mathematic model and power relations which delivered the maximum power to the grid.The maximum power point could be tracked automatically without measuring wind speed in the control strategy and the control was independent of optimal turbine power curve,which had excellent dynamic and static performances and robustness.Simulation and experimental results testify the accuracy and validity of the control strategy.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
This paper presents the implementation of maximum power point tracking （MPPT） with fuzzy logic controller. For cost consideration, an inexpensive 8-bit microcontroller, PIC 16F877A, is selected and programmed with C...This paper presents the implementation of maximum power point tracking （MPPT） with fuzzy logic controller. For cost consideration, an inexpensive 8-bit microcontroller, PIC 16F877A, is selected and programmed with C language and integer variables For evaluation, the implemented fuzzy logic controller （FLC） is compared with the MPPT controller of using perturbation and observation （P＆O）. Both types of MPPT controllers are tested on the same voltage source with a series-connected resistor. Experimental results show that the implemented FLC with appropriate design meets the control requirements of MPPT. The FLC based on linguistic fuzzy rules has more flexibility and intelligence than conventional P＆O controller, but the FLC spends more RAM and ROM spaces than the P＆O tracker does.展开更多
Solar power is mostly influenced by solar irradiation,weather conditions,solar array mismatches and partial shading conditions.Therefore,before installing solar arrays,it is necessary to simulate and determine the pos...Solar power is mostly influenced by solar irradiation,weather conditions,solar array mismatches and partial shading conditions.Therefore,before installing solar arrays,it is necessary to simulate and determine the possible power generated.Maximum power point tracking is needed in order to make sure that,at any time,the maximum power will be extracted from the photovoltaic system.However,maximum power point tracking is not a suitable solution for mismatches and partial shading conditions.To overcome the drawbacks of maximum power point tracking due to mismatches and shadows,distributed maximum power point tracking is util-ized in this paper.The solar farm can be distributed in different ways,including one DC-DC converter per group of modules or per module.In this paper,distributed maximum power point tracking per module is implemented,which has the highest efficiency.This technology is applied to electric vehicles(EVs)that can be charged with a Level 3 charging station in<1 hour.However,the problem is that charging an EV in<1 hour puts a lot of stress on the power grid,and there is not always enough peak power reserve in the existing power grid to charge EVs at that rate.Therefore,a Level 3(fast DC)EV charging station using a solar farm by implementing distributed maximum power point tracking is utilized to address this issue.Finally,the simulation result is reported using MATLAB®,LTSPICE and the System Advisor Model.Simulation results show that the proposed 1-MW solar system will provide 5 MWh of power each day,which is enough to fully charge~120 EVs each day.Additionally,the use of the proposed photovoltaic system benefits the environment by removing a huge amount of greenhouse gases and hazardous pollutants.For example,instead of supplying EVs with power from coal-fired power plants,1989 pounds of CO_(2) will be eliminated from the air per hour.展开更多
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 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 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.展开更多
Tracking the maximum power point is a critical issue with solar systems.The power output of the solar panel varies due to variations in irradiance and temperature.Nonuniform irradiation due to partial shading conditio...Tracking the maximum power point is a critical issue with solar systems.The power output of the solar panel varies due to variations in irradiance and temperature.Nonuniform irradiation due to partial shading conditions has a direct impact on the characteristics of photovoltaic(PV)systems.To build a diversity of maximum power point tracking algorithms in solar PV systems,this work focuses on perturb and observe,incremental conductance,and fuzzy logic control methodologies.The suggested fuzzy logic control method outperformed the conventional incremental conductance and perturb and observe algorithms with a collection of 49 rules.This paper presents a novel series-parallel-cross-tied PV array configuration with a developed fuzzy methodology.To comment on the performance of a proposed system under various partial shading conditions,a series-parallel PV array configuration has been considered.The simulation result demonstrates that the fuzzy method has a percentage improvement in the global maximum power point tracking efficiency of 24.85%when compared to the perturb and observe method and a 65.5%improvement when compared to the incremental conductance method under long wide partial shading conditions.In the case of the middle partial shading condition,the fuzzy method has a percentage improvement in the global maximum power point tracking efficiency of 12.4%compared to the perturb and observe method and a 60.7%improvement compared to the incremental conductance method.展开更多
For maximum utilization of solar energy,photovoltaic(PV)power systems should be operated at the maximum power point(MPP)which can be achieved using maximum power point tracking(MPPT)methods.However,the occurrence of m...For maximum utilization of solar energy,photovoltaic(PV)power systems should be operated at the maximum power point(MPP)which can be achieved using maximum power point tracking(MPPT)methods.However,the occurrence of multi-peak on P-V curve of a PV array due to the changing environmental conditions such as being partially shaded increases the complexity of the tracking process.The global MPP cannot always be achieved by the conventional MPPT methods.Therefore a novel MPPT method for PV systems using flower pollination(FP)algorithm is proposed in this paper and the Levy flight is used to improve the convergence of FP algorithm.MPPT model of the PV system is established in MATLAB to verify the effectiveness of the proposed method,and the proposed method is compared with two well established MPPT methods.The simulation results indicate that the proposed MPPT method can quickly track the changes in external environment and effectively handle the partially shaded condition.展开更多
Solar energy has attracted a lot of attention because it is clean and has no pollution.However,due to the partially shaded condition,the photovoltaic array cannot work uniformly at the maximum power point,resulting in...Solar energy has attracted a lot of attention because it is clean and has no pollution.However,due to the partially shaded condition,the photovoltaic array cannot work uniformly at the maximum power point,resulting in a large power loss.To improve this problem,the research of the maximum power point tracking(MPPT)algorithm is discussed by scholars.In this paper,an improved particle swarm optimization(PSO)algorithm is proposed to achieve the goal of MPPT,which uses Newton interpolation-assisted conventional PSO.After tracking to the maximum power point,the Newton interpolation method is used to calculate the maximum power point,reduce the number of iterations of the conventional PSO algorithm and reduce the steady-state oscillation.The simulation is carried out in MATLAB^(■)/Simulink^(■)and compared with conventional PSO.The results show that the improved PSO has better tracking ac-curacy and speed than the conventional algorithm,and the initial tracking speed is increased by>30%.展开更多
This paper presents an annual performance evaluation of three maximum power point tracking (MPPT) methods. The used MPPT techniques (Perturb and Observe, Incremental Inductance and Sliding mode) are evaluated under an...This paper presents an annual performance evaluation of three maximum power point tracking (MPPT) methods. The used MPPT techniques (Perturb and Observe, Incremental Inductance and Sliding mode) are evaluated under an annual data of atmospheric conditions of the target site. The main contribution of this work is to consider real fluctuation conditions of solar irradiations, ambient temperatures and wind velocities. It was found that the Sliding mode provides higher energy yields independently of the period. Compared to the basic P&O and the IC techniques, sliding mode has the potential of generating up to 8.18% more electrical energy than other techniques.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
Partial shading and mismatch conditions among the series-connected modules/sub-modules suffer from a nonconvex power curve with multiple local maxima and decreased peak power for the whole string. Energy transfer betw...Partial shading and mismatch conditions among the series-connected modules/sub-modules suffer from a nonconvex power curve with multiple local maxima and decreased peak power for the whole string. Energy transfer between the sub-modules brings them to the same operating voltage, and this collective operation produces a convex power curve, which results in increased peak power for the string. The proposed topology benefits from the switched-capacitor （SC） converter concept and is an application for sub-module-level power balancing with some novelties, including stopping the switching in absence of shading, string-level extension, and a reduced number of power electronics components as compared to those in the literature. Reduction in the number of power electronics components is realized by the fact that two sub-modules share one SC converter. This leads to reduced power electronics losses as well as less cost and volume of the converter circuit. Insertion loss analysis of the topology is presented. The proposed topology is simulated in the PSpice environment, and a prototype is built for experimental verification. Both simulation and experimental results confirm the loss analysis. This proves that with the proposed topology it is possible to extract almost all the power available on the partially shaded string and transfer it to the load side.展开更多
This work presents a machine-learning(ML)algorithm for maximum power point tracking(MPPT)of an isolated photovoltaic(PV)system.Due to the dynamic nature of weather conditions,the energy generation of PV systems is non...This work presents a machine-learning(ML)algorithm for maximum power point tracking(MPPT)of an isolated photovoltaic(PV)system.Due to the dynamic nature of weather conditions,the energy generation of PV systems is non-linear.Since there is no specific method for effectively dealing with the non-linear data,the use of ML methods to operate the PV system at its maximum power point(MPP)is desirable.A strategy based on the decision-tree(DT)regression ML algorithm is proposed in this work to determine the MPP of a PV system.The data were gleaned from the technical specifications of the PV module and were used to train and test the DT.These algorithms predict the maximum power available and the associated voltage of the module for a defined amount of irradiance and temperature.The boost converter duty cycle was determined using predicted values.The simulation was carried out for a 10-W solar panel with a short-circuit current of 0.62 A and an open-circuit voltage of 21.50 V at 1000 W/m^(2) irradiance and a temperature of 25℃.The simulation findings demonstrate that the proposed method compelled the PV panel to work at the MPP predicted by DTs compared to the existing topologies such asβ-MPPT,cuckoo search and artificial neural network results.From the proposed algorithm,efficiency has been improved by>93.93%in the steady state despite erratic irradiance and temperatures.展开更多
A large portion of the available power generation of a photovoltaic (PV) array could be wasted due to partial shading, temperature and irradiance effects, which create current/voltage imbalance between the PV modules....A large portion of the available power generation of a photovoltaic (PV) array could be wasted due to partial shading, temperature and irradiance effects, which create current/voltage imbalance between the PV modules. Partial shading is a phenomenon which occurs when some modules in a PV array receive non-uniform irradiation due to dust, cloudy weather or shadows of nearby objects such as buildings, trees, mountains, birds etc. Maximum power point tracking (MPPT) techniques are designed in order to deal with this problem. In this research, a Markov Decision Process (MDP) based MPPT technique is proposed. MDP consists of a set of states, a set of actions in each state, state transition probabilities, reward function, and the discount factor. The PV system in terms of the MDP framework is modelled first and once the states, actions, transition probabilities, and reward function, and the discount factor are defined, the resulting MDP is solved for the optimal policy using stochastic dynamic programming. The behavior of the resulting optimal policy is analyzed and characterized, and the results are compared to existing MPPT control methods.展开更多
Under the trends to using renewable energy sources as alternatives to the traditional ones,it is important to contribute to the fast growing development of these sources by using powerful soft computing methods.In thi...Under the trends to using renewable energy sources as alternatives to the traditional ones,it is important to contribute to the fast growing development of these sources by using powerful soft computing methods.In this context,this paper introduces a novel structure to optimize and control the energy produced from a variable speed wind turbine which is based on a squirrel cage induction generator(SCIG)and connected to the grid.The optimization strategy of the harvested power from the wind is realized by a maximum power point tracking(MPPT)algorithm based on fuzzy logic,and the control strategy of the generator is implemented by means of an internal model(IM)controller.Three IM controllers are incorporated in the vector control technique,as an alternative to the proportional integral(PI)controller,to implement the proposed optimization strategy.The MPPT in conjunction with the IM controller is proposed as an alternative to the traditional tip speed ratio(TSR)technique,to avoid any disturbance such as wind speed measurement and wind turbine(WT)characteristic uncertainties.Based on the simulation results of a six KW-WECS model in Matlab/Simulink,the presented control system topology is reliable and keeps the system operation around the desired response.展开更多
文摘A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there is a need for a control schema to force the PV string to operate at global maximum power point (GMPP). While a lot of tracking methods have been proposed in the literature, they are usually complex and do not fully take advantage of the available characteristics of the PV array. This work highlights how the voltage at operating point and the forward voltage of the bypass diode are considered to design a global maximum power point tracking (GMPPT) algorithm with a very limited global search phase called Fast GMPPT. This algorithm successfully tracks GMPP between 94% and 98% of the time under a theoretical evaluation. It is then compared against Perturb and Observe, Deterministic Particle Swarm Optimization, and Grey Wolf Optimization under a sequence of irradiance steps as well as a power-over-voltage characteristics profile that mimics the electrical characteristics of a PV string under varying partial shading conditions. Overall, the simulation with the sequence of irradiance steps shows that while Fast GMPPT does not have the best convergence time, it has an excellent convergence rate as well as causes the least amount of power loss during the global search phase. Experimental test under varying partial shading conditions shows that while the GMPPT proposal is simple and lightweight, it is very performant under a wide range of dynamically varying partial shading conditions and boasts the best energy efficiency (94.74%) out of the 4 tested algorithms.
文摘The present study was carried out in order to track the maximum power point in a variable speed turbine by minimizing electromechanical torque changes using a sliding mode control strategy. In this strategy, first, the rotor speed is set at an optimal point for different wind speeds. As a result of which, the tip speed ratio reaches an optimal point, mechanical power coefficient is maximized, and wind turbine produces its maximum power and mechanical torque. Then, the maximum mechanical torque is tracked using electromechanical torque. In this technique, tracking error integral of maximum mechanical torque, the error, and the derivative of error are used as state variables. During changes in wind speed, sliding mode control is designed to absorb the maximum energy from the wind and minimize the response time of maximum power point tracking(MPPT). In this method, the actual control input signal is formed from a second order integral operation of the original sliding mode control input signal. The result of the second order integral in this model includes control signal integrity, full chattering attenuation, and prevention from large fluctuations in the power generator output. The simulation results, calculated by using MATLAB/m-file software, have shown the effectiveness of the proposed control strategy for wind energy systems based on the permanent magnet synchronous generator(PMSG).
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.
基金supported by the following project of the Addis Ababa Institute of Technology,African Railway Center of Excellence,and World Bank group:“A research on integration of renewable and Alternative Energy Sources into Ethiopian Railway System.”(AAITRS-GSR-7767-18).
文摘A photovoltaic array is environmentally friendly and a source of unlimited energy generation.However,it is presently a costlier energy generation system than other non-renewable energy sources.The main reasons are seasonal variations and continuously changing weather conditions,which affect the amount of solar energy received by the solar panels.In addition,the non-linear characteristics of the voltage and current outputs along with the operating environment temperature and variation in the solar radiation decrease the energy conversion capability of the photovoltaic arrays.To address this problem,the global maxima of the PV arrays can be tracked using a maximum power point tracking algorithm(MPPT)and the operating point of the photovoltaic system can be forced to its optimum value.This technique increases the efficiency of the photovoltaic array and minimizes the cost of the system by reducing the number of solar modules required to obtain the desired power.However,the tracking algorithms are not equally effective in all areas of application.Therefore,selecting the correct MPPT is very critical.This paper presents a detailed review and comparison of the MPPT techniques for photovoltaic systems,with consideration of the following key parameters:photovoltaic array dependence,type of system(analog or digital),need for periodic tuning,convergence speed,complexity of the system,global maxima,implemented capacity,and sensed parameter(s).In addition,based on real meteorological data(irradiance and temperature at a site located in Addis Ababa,Ethiopia),a simulation is performed to evaluate the performance of tracking algorithms suitable for the application being studied.Finally,the study clearly validates the considerable energy saving achieved by using these 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.
基金Funded by the National Natural Science Foundation of China(No.60974049)the Science and Technology Support Industrial Project of Jiangsu Province(No.BZ2008031,No.BE2008074,and No.BE2009090)+1 种基金the Nantong International Cooperative Project(No.W2009003)the Natural Science Foundation of Nantong University(No.08Z022 and No.08Z025).
文摘Based on the characteristic of AC-excited variable speed constant frequency(VSCF)wind power generation,the vector control technique was applied in a doubly fed induction generator(DFIG).Maximum wind energy or maximum output power point can be tracked by decoupling control of active power and reactive power.The research result shows that the net power of generation system delivered to grid in maximum wind energy tracking mode is not the most.We presented a novel maximum power point tracking(MPPT)control strategy by analyzing the DFIG mathematic model and power relations which delivered the maximum power to the grid.The maximum power point could be tracked automatically without measuring wind speed in the control strategy and the control was independent of optimal turbine power curve,which had excellent dynamic and static performances and robustness.Simulation and experimental results testify the accuracy and validity of the control strategy.
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.
文摘This paper presents the implementation of maximum power point tracking （MPPT） with fuzzy logic controller. For cost consideration, an inexpensive 8-bit microcontroller, PIC 16F877A, is selected and programmed with C language and integer variables For evaluation, the implemented fuzzy logic controller （FLC） is compared with the MPPT controller of using perturbation and observation （P＆O）. Both types of MPPT controllers are tested on the same voltage source with a series-connected resistor. Experimental results show that the implemented FLC with appropriate design meets the control requirements of MPPT. The FLC based on linguistic fuzzy rules has more flexibility and intelligence than conventional P＆O controller, but the FLC spends more RAM and ROM spaces than the P＆O tracker does.
基金support of the National Science Foundation(NSF)under Award Number:2115427 is gratefully acknowledged.SRS RN:Sustainable Transportation Electrification for an Equitable and Resilient Society(STEERS).
文摘Solar power is mostly influenced by solar irradiation,weather conditions,solar array mismatches and partial shading conditions.Therefore,before installing solar arrays,it is necessary to simulate and determine the possible power generated.Maximum power point tracking is needed in order to make sure that,at any time,the maximum power will be extracted from the photovoltaic system.However,maximum power point tracking is not a suitable solution for mismatches and partial shading conditions.To overcome the drawbacks of maximum power point tracking due to mismatches and shadows,distributed maximum power point tracking is util-ized in this paper.The solar farm can be distributed in different ways,including one DC-DC converter per group of modules or per module.In this paper,distributed maximum power point tracking per module is implemented,which has the highest efficiency.This technology is applied to electric vehicles(EVs)that can be charged with a Level 3 charging station in<1 hour.However,the problem is that charging an EV in<1 hour puts a lot of stress on the power grid,and there is not always enough peak power reserve in the existing power grid to charge EVs at that rate.Therefore,a Level 3(fast DC)EV charging station using a solar farm by implementing distributed maximum power point tracking is utilized to address this issue.Finally,the simulation result is reported using MATLAB®,LTSPICE and the System Advisor Model.Simulation results show that the proposed 1-MW solar system will provide 5 MWh of power each day,which is enough to fully charge~120 EVs each day.Additionally,the use of the proposed photovoltaic system benefits the environment by removing a huge amount of greenhouse gases and hazardous pollutants.For example,instead of supplying EVs with power from coal-fired power plants,1989 pounds of CO_(2) will be eliminated from the air per hour.
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.
文摘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.
文摘Tracking the maximum power point is a critical issue with solar systems.The power output of the solar panel varies due to variations in irradiance and temperature.Nonuniform irradiation due to partial shading conditions has a direct impact on the characteristics of photovoltaic(PV)systems.To build a diversity of maximum power point tracking algorithms in solar PV systems,this work focuses on perturb and observe,incremental conductance,and fuzzy logic control methodologies.The suggested fuzzy logic control method outperformed the conventional incremental conductance and perturb and observe algorithms with a collection of 49 rules.This paper presents a novel series-parallel-cross-tied PV array configuration with a developed fuzzy methodology.To comment on the performance of a proposed system under various partial shading conditions,a series-parallel PV array configuration has been considered.The simulation result demonstrates that the fuzzy method has a percentage improvement in the global maximum power point tracking efficiency of 24.85%when compared to the perturb and observe method and a 65.5%improvement when compared to the incremental conductance method under long wide partial shading conditions.In the case of the middle partial shading condition,the fuzzy method has a percentage improvement in the global maximum power point tracking efficiency of 12.4%compared to the perturb and observe method and a 60.7%improvement compared to the incremental conductance method.
文摘For maximum utilization of solar energy,photovoltaic(PV)power systems should be operated at the maximum power point(MPP)which can be achieved using maximum power point tracking(MPPT)methods.However,the occurrence of multi-peak on P-V curve of a PV array due to the changing environmental conditions such as being partially shaded increases the complexity of the tracking process.The global MPP cannot always be achieved by the conventional MPPT methods.Therefore a novel MPPT method for PV systems using flower pollination(FP)algorithm is proposed in this paper and the Levy flight is used to improve the convergence of FP algorithm.MPPT model of the PV system is established in MATLAB to verify the effectiveness of the proposed method,and the proposed method is compared with two well established MPPT methods.The simulation results indicate that the proposed MPPT method can quickly track the changes in external environment and effectively handle the partially shaded condition.
基金supported by a grant from the Science and Technology Research Project of Jilin Provincial Department of Education(no.JJKH20210260KJ).
文摘Solar energy has attracted a lot of attention because it is clean and has no pollution.However,due to the partially shaded condition,the photovoltaic array cannot work uniformly at the maximum power point,resulting in a large power loss.To improve this problem,the research of the maximum power point tracking(MPPT)algorithm is discussed by scholars.In this paper,an improved particle swarm optimization(PSO)algorithm is proposed to achieve the goal of MPPT,which uses Newton interpolation-assisted conventional PSO.After tracking to the maximum power point,the Newton interpolation method is used to calculate the maximum power point,reduce the number of iterations of the conventional PSO algorithm and reduce the steady-state oscillation.The simulation is carried out in MATLAB^(■)/Simulink^(■)and compared with conventional PSO.The results show that the improved PSO has better tracking ac-curacy and speed than the conventional algorithm,and the initial tracking speed is increased by>30%.
文摘This paper presents an annual performance evaluation of three maximum power point tracking (MPPT) methods. The used MPPT techniques (Perturb and Observe, Incremental Inductance and Sliding mode) are evaluated under an annual data of atmospheric conditions of the target site. The main contribution of this work is to consider real fluctuation conditions of solar irradiations, ambient temperatures and wind velocities. It was found that the Sliding mode provides higher energy yields independently of the period. Compared to the basic P&O and the IC techniques, sliding mode has the potential of generating up to 8.18% more electrical energy than other techniques.
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Project supported by the BAP Department of Karabuk University,Turkey(No.KBU-BAP-13/2-DR-010)
文摘Partial shading and mismatch conditions among the series-connected modules/sub-modules suffer from a nonconvex power curve with multiple local maxima and decreased peak power for the whole string. Energy transfer between the sub-modules brings them to the same operating voltage, and this collective operation produces a convex power curve, which results in increased peak power for the string. The proposed topology benefits from the switched-capacitor （SC） converter concept and is an application for sub-module-level power balancing with some novelties, including stopping the switching in absence of shading, string-level extension, and a reduced number of power electronics components as compared to those in the literature. Reduction in the number of power electronics components is realized by the fact that two sub-modules share one SC converter. This leads to reduced power electronics losses as well as less cost and volume of the converter circuit. Insertion loss analysis of the topology is presented. The proposed topology is simulated in the PSpice environment, and a prototype is built for experimental verification. Both simulation and experimental results confirm the loss analysis. This proves that with the proposed topology it is possible to extract almost all the power available on the partially shaded string and transfer it to the load side.
文摘This work presents a machine-learning(ML)algorithm for maximum power point tracking(MPPT)of an isolated photovoltaic(PV)system.Due to the dynamic nature of weather conditions,the energy generation of PV systems is non-linear.Since there is no specific method for effectively dealing with the non-linear data,the use of ML methods to operate the PV system at its maximum power point(MPP)is desirable.A strategy based on the decision-tree(DT)regression ML algorithm is proposed in this work to determine the MPP of a PV system.The data were gleaned from the technical specifications of the PV module and were used to train and test the DT.These algorithms predict the maximum power available and the associated voltage of the module for a defined amount of irradiance and temperature.The boost converter duty cycle was determined using predicted values.The simulation was carried out for a 10-W solar panel with a short-circuit current of 0.62 A and an open-circuit voltage of 21.50 V at 1000 W/m^(2) irradiance and a temperature of 25℃.The simulation findings demonstrate that the proposed method compelled the PV panel to work at the MPP predicted by DTs compared to the existing topologies such asβ-MPPT,cuckoo search and artificial neural network results.From the proposed algorithm,efficiency has been improved by>93.93%in the steady state despite erratic irradiance and temperatures.
文摘A large portion of the available power generation of a photovoltaic (PV) array could be wasted due to partial shading, temperature and irradiance effects, which create current/voltage imbalance between the PV modules. Partial shading is a phenomenon which occurs when some modules in a PV array receive non-uniform irradiation due to dust, cloudy weather or shadows of nearby objects such as buildings, trees, mountains, birds etc. Maximum power point tracking (MPPT) techniques are designed in order to deal with this problem. In this research, a Markov Decision Process (MDP) based MPPT technique is proposed. MDP consists of a set of states, a set of actions in each state, state transition probabilities, reward function, and the discount factor. The PV system in terms of the MDP framework is modelled first and once the states, actions, transition probabilities, and reward function, and the discount factor are defined, the resulting MDP is solved for the optimal policy using stochastic dynamic programming. The behavior of the resulting optimal policy is analyzed and characterized, and the results are compared to existing MPPT control methods.
文摘Under the trends to using renewable energy sources as alternatives to the traditional ones,it is important to contribute to the fast growing development of these sources by using powerful soft computing methods.In this context,this paper introduces a novel structure to optimize and control the energy produced from a variable speed wind turbine which is based on a squirrel cage induction generator(SCIG)and connected to the grid.The optimization strategy of the harvested power from the wind is realized by a maximum power point tracking(MPPT)algorithm based on fuzzy logic,and the control strategy of the generator is implemented by means of an internal model(IM)controller.Three IM controllers are incorporated in the vector control technique,as an alternative to the proportional integral(PI)controller,to implement the proposed optimization strategy.The MPPT in conjunction with the IM controller is proposed as an alternative to the traditional tip speed ratio(TSR)technique,to avoid any disturbance such as wind speed measurement and wind turbine(WT)characteristic uncertainties.Based on the simulation results of a six KW-WECS model in Matlab/Simulink,the presented control system topology is reliable and keeps the system operation around the desired response.
