Maximum Power Point Tracking Based on Improved Kepler Optimization Algorithm and Optimized Perturb&Observe under Partial Shading Conditions

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.

Probabilistic Global Maximum Power Point Tracking Algorithm for Continuously Varying Partial Shading Conditions on Autonomous PV Systems

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.

Acquisition,Pointing and Tracking System for Shipborne Space Laser Communication without Prior Information

A space laser communication acquisition,pointing and tracking(APT)system based on the beacon laser is designed without prior information.And then,a new target scanning method and a pointing and tracking algorithm are proposed.The target scanning mode is the round-trip triangular wave scanning,and it means that scanning track of the PAN-TILT platform follows the triangular wave repeatedly.For the pointing and tracking algorithm,the beacon laser is used as the auxiliary aiming light source.The position of the beacon laser in the viewfield of the complementary metal oxide semiconductor(CMOS)camera is calculated by the centroid algorithm.In order to realize the target tracking,the joint control method of the angle control and the angular velocity control is used.The simulation and experimental results show that the APT system can achieve full coverage scanning in the scanning area and capture the target in one scanning cycle successfully.After capturing the PAN-TILT platform,the pointing and tracking algorithm can track the PAN-TILT platform quickly and accurately,and the tracking accuracy is up to 0.22 mrad.

Comparative assessment of maximum power point tracking procedures for photovoltaic systems

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.

Maximum Power Point Tracking in Variable Speed Wind Turbine Based on Permanent Magnet Synchronous Generator Using Maximum Torque Sliding Mode Control Strategy

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).

Overview of Maximum Power Point Tracking Control Methods for PV Systems

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.

Comprehensive review and performance evaluation of maximum power point tracking algorithms for photovoltaic system

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.

Maximum power point tracking of a photovoltaic energy system using neural fuzzy techniques

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.

Maximum Power Point Tracking Control Using Neural Networks for Stand-Alone Photovoltaic Systems

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.

On maximum power point tracking control strategy for variable speed constant frequency wind power generation

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.

Drosophila models used to simulate human ATP1A1 gene mutations that cause Charcot-Marie-Tooth type 2 disease and refractory seizures

Certain amino acids changes in the human Na^(+)/K^(+)-ATPase pump,ATPase Na^(+)/K^(+)transporting subunit alpha 1(ATP1A1),cause Charcot-Marie-Tooth disease type 2(CMT2)disease and refractory seizures.To develop in vivo models to study the role of Na^(+)/K^(+)-ATPase in these diseases,we modified the Drosophila gene homolog,Atpα,to mimic the human ATP1A1 gene mutations that cause CMT2.Mutations located within the helical linker region of human ATP1A1(I592T,A597T,P600T,and D601F)were simultaneously introduced into endogenous Drosophila Atpαby CRISPR/Cas9-mediated genome editing,generating the Atpα^(TTTF)model.In addition,the same strategy was used to generate the corresponding single point mutations in flies(Atpα^(I571T),Atpα^(A576T),Atpα^(P579T),and Atpα^(D580F)).Moreover,a deletion mutation(Atpα^(mut))that causes premature termination of translation was generated as a positive control.Of these alleles,we found two that could be maintained as homozygotes(Atpα^(I571T)and Atpα^(P579T)).Three alleles(Atpα^(A576T),Atpα^(P579)and Atpα^(D580F))can form heterozygotes with the Atpαmut allele.We found that the Atpαallele carrying these CMT2-associated mutations showed differential phenotypes in Drosophila.Flies heterozygous for Atpα^(TTTF)mutations have motor performance defects,a reduced lifespan,seizures,and an abnormal neuronal morphology.These Drosophila models will provide a new platform for studying the function and regulation of the sodium-potassium pump.

Maximum Power Point Tracking Using the Incremental Conductance Algorithm for PV Systems Operating in Rapidly Changing Environmental Conditions

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.

Variable Parameter Nonlinear Control for Maximum Power Point Tracking Considering Mitigation of Drive-train Load

Since mechanical loads exert a significant influence on the life span of wind turbines, the reduction of transient load on drive-train shaft has received more attention when implementing a maximum power point tracking U+0028 MPPT U+0029 controller. Moreover, a trade-off between the efficiency of wind energy extraction and the load level of drive-train shaft becomes a key issue. However, for the existing control strategies based on nonlinear model of wind turbines, the MPPT efficiencies are improved at the cost of the intensive fluctuation of generator torque and significant increase of transient load on drive train shaft. Hence, in this paper, a nonlinear controller with variable parameter is proposed for improving MPPT efficiency and mitigating transient load on drive-train simultaneously. Then, simulations on FAST U+0028 Fatigue, Aerodynamics, Structures, and Turbulence U+0029 code and experiments on the wind turbine simulator U+0028 WTS U+0029 based test bench are presented to verify the efficiency improvement of the proposed control strategy with less cost of drive-train load. © 2017 Chinese Association of Automation.

Application of Adaptive Reduced Sigma Points Unscented Kalman Filter to the Tracking of Maneuvering Target

Based on the principle of statistical linear regression, a set of n ＋ 2 sigma points instead of 2n ＋ 1 sigma points used in the unscented Kalman filter （UKF）, is constructed to approximate the system state. And filter accuracy is second order. Real-time of modified UKF is improved. In order to describe accurately the maneuvering target, the ＂current＂ statistical model is used. And the equation of acceleration error covariance is modified at every sample time of the filter. The modified adaptive UKF is presented for estimating the position, velocity and acceleration of maneuvering target. Monte Carlo simulations show the modified adaptive UKF acquires good performance for tracking position of maneuvering target. The modified adaptive UKF has better computational efficiency than UKF.

A Reverse-Design Strategy for the Track Error of the Qi Tai Telescope Based on Pointing Accuracy

The Qi Tai Telescope(QTT),which has a 110 m aperture,is planned to be the largest scale steerable tele-scope in the world.Ideally,the telescope’s repeated pointing accuracy error should be less than 2.5 arc seconds(arcsec);thus,the telescope structure must satisfy ultra-high precision requirements.In this pur-suit,the present research envisages a reverse-design method for the track surface to reduce the difficulty of the telescope’s design and manufacture.First,the distribution characteristics of the test data for the track error were verified using the skewness coefficient and kurtosis coefficient methods.According to the distribution characteristics,the azimuth track error was simulated by a two-scale model.The error of the long period and short amplitude was characterized as large-scale and described by a trigonometric function,while the short period and high amplitude error was characterized as small-scale and simulated by a fractal function.Based on the two-scale model,effect of the error on the pointing accuracy was deduced.Subsequently,the relationship between the root mean square(RMS)of the track error and the RMS of the pointing accuracy error of the telescope was deduced.Finally,the allowable RMS value of the track error was derived from the allowable pointing accuracy errors.To validate the effectiveness of the new design method,two typical radio telescopes(the Green Bank Telescope(GBT)and the Large Millimeter Telescope(LMT))were selected as experimental examples.Through comparison,the theoretical calculated values of the pointing accuracy of the telescope were consistent with the measured values,with a maximum error of less than 10%.

Parasitic Effects on the Performance of DC-DC SEPIC in Photovoltaic Maximum Power Point Tracking Applications

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.

A Fuzzy Logic Controller for Maximum Power Point Tracking with 8-Bit Microcontroller

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.

列控车载ATP设备操作培训平台关键技术研究与软件实现

为提高列控车载ATP设备的操作培训质量,考虑培训设备操作反应真实、故障模拟场景丰富、司机视角显示准确等需求,提出一种基于真实列控车载ATP设备应用软件的操作培训平台设计方案。通过运行脚本和软件插桩2种故障注入方式,实现操作培训平台的故障模拟;设计基于PID控制的司机视角同步跟踪显示算法,对司机视角的显示内容进行精准控制,并从视觉显示流畅度和列车位置准确度两方面验证算法的可行性。该培训平台与现场真实设备反应一致,具备模拟多种故障场景、沉浸式操作等优点,可为其他类似培训平台的设计提供参考。

Maximum Power Point Tracking With Fractional Order High Pass Filter for Proton Exchange Membrane Fuel Cell

Proton exchange membrane fuel cell (PEMFC) is widely recognized as a potentially renewable and green energy source based on hydrogen. Maximum power point tracking (MPPT) is one of the most important working conditions to be considered. In order to improve the performance such as convergence and robustness under disturbance and uncertainty, a fractional order high pass filter (FOHPF) is applied for the MPPT controller design based on the traditional extremum seeking control (ESC). The controller is designed with integerorder integrator (IO-I) and low pass filter (IO-LPF) together with fractional order high pass filter (FOHPF), by substituting the normal HPF in the original ESC system. With this FOHPF ESC, better convergence and smoother performance are achieved while maintaining the robust specifications. First, tracking stability is discussed under the commensurate-order condition. Then, simulation results are included to validate the proposed new FOHPF ESC scheme under disturbance. Finally, comparison results between FOHPF ESC and the traditional ESC method are also provided. © 2014 Chinese Association of Automation.