Maximum Power Point Tracking Control Method Research Articles

Maximum Power Point Tracking Control Method of Photovoltaic Cell under Shadow Influence

In view of the poor effect of battery power tracking control in the current solar power generation system, the maximum power point tracking (MPPT) control method of photovoltaic cell under the influence of shadow is proposed. The MPPT control method of photovoltaic cell is optimized by using the influence of shadow, the structural characteristics of photovoltaic cell are optimized, and the voltage rise and fall DC / DC conversion circuit is adopted, The maximum power identification algorithm of photovoltaic cells is set, and the voltage disturbance method is used to realize the MPPT, so that the solar photovoltaic cells always maintain the maximum power output, so as to ensure the control effect. Finally, the experiment shows that the MPPT control method of photovoltaic cells has high practicability and fully meets the research requirements.

A PV MPPT control method based on async-PSO and INC algorithm under shading condition

For the time being, solar energy has received considerable attention and development on account of its distinct advantages, such as rich reserves and no geographical restrictions. Nevertheless, in practical applications, the photovoltaic module is easily affected by external environments, which gives rise to a decrease in photovoltaic power. The maximum power point tracking (MPPT) technology for PV power system is an effective method to elevate the efficacy of photovoltaic electricity conversion. The frequently used control methods include the perturb and observe (P&O) algorithm and the incremental conductance (INC) method, and so forth; these methods vary tremendously in terms of the required parameters, algorithm complexity, tracking speed, tracking accuracy, hardware requirements etc. This work puts forth a MPPT control method on the basis of Async-PSO and INC algorithm to achieve a better performance in the MPPT. To reflect the change of light amplitude and temperature in a day, the temperature varies from 25℃ to 60℃ and irradiance from 450W/m2 to 900W/m2 . An extensively used mono-crystalline silicon PV module with 240W was considered as the research object to compare the capability of the recommended MPPT control method. MATLAB/Simulink software was adopted to model and simulate the algorithm. Aside from that, comprehensive comparisons were made with other MPPT methods to test and verify the recommended algorithm has significantly improved the tracking speed and accuracy at the maximum power point with smaller oscillations under various conditions.

Laboratory Tests Assessment of a Mechanical Sensor-less MPPT Control Strategy for Tidal Turbines

The purpose of this study is to demonstrate through towing tank experiments the effectiveness of a novel sensor-less Maximum Power Point Tracking (MPPT) control for Tidal Stream Turbines (TST) under fluctuations of the onset flow. Ocean energies will play a crucial role in the renewable energy sector over the next decades. Instream turbines for tidal currents are a rapidly maturing technology to exploit a highly predictable energy source. However, short-term fluctuations on the inflow velocity caused by waves or turbulence determine fatigue loads that affect system reliability. Power control strategies to maximize the energy yield can be also used to mitigate the effects of transient loading on drivetrain components. Aim of this paper is to present a straightforward and robust MPPT control method based on the linear relationship between the current and voltage squared of the generator's DC outputs. The method requires pre-determined turbine characteristics to establish the control reference that is effective across operating conditions. The proposed MPPT model was derived mathematically through linearization and simplifications of the turbine power conversion system and validated by model tests carried out in the wave-towing tank facility of CNR-INM in Rome, Italy, using the 1.5 m diameter Tidal Turbine Testing (TTT) device developed at the Queen’s University Belfast (QUB). In the study, a conventional TSR control method was also considered in order to perform a comparative analysis of system response to inflow speed fluctuations with time scales comparable to turbine revolution periods. TSR control was tested using two control references: TSR = 5 (design point) and TSR = 6 (over-speed zone) to verify the operation of the turbine under different loading conditions. The tests were conducted in two scenarios: calm water (steady state) and unsteady inflow with a regular (sinusoidal or monochromatic) waveform, with amplitude chosen to simulate an extreme wave case. The power output was measured from the turbine during regular wave conditions and compared to results from steady flow to assess the impact of wave-induced velocity on turbine performance (Fig. 1). Test results showed that by using the proposed MPPT control strategy, the algorithms converged to the maximum power coefficient (Fig. 2), which validates the proposed methodology. Results also demonstrated the capability of the proposed MPPT to significantly reduce mechanical loads fluctuations as compared to the TSR control. In the full-length paper, the proposed MPPT control strategy is outlined, the test methodology, set-up and conditions are described, and main results are presented and discussed.

Maximum power point tracking control of wind turbines based on equivalent sinusoidal wind

The optimal parameter model method for maximum power point tracking (MPPT) control of wind turbines has good wind energy capture performance. However, there is a precondition that the quantitative relationship between optimal control parameters and turbulence characteristics is accurately described. The resolution of the existing turbulence frequency characterization indicators are insufficient. Therefore, a large number of sample data need to be obtained to clearly show the statistical relationship between them and the optimal control parameters, which is extremely time-consuming, and has a negative impact on the optimization results of control parameters. This paper equates the turbulent wind to the sinusoidal wind with the objective of the results of both acting on wind turbines are the same, so as to realize the extraction and index description of the dominant turbulent frequency components strongly related to the optimal control parameters. On this basis, a MPPT control method based on equivalent sinusoidal wind is proposed. This method greatly reduces the required sample size, and makes the setting of control parameters closer to the optimal value, which can further improve the efficiency of wind energy capture. Simulation analysis and experimental results based on wind turbine simulator verify the effectiveness of the proposed method.

Design of the particle swarm optimization simulated annealing MPPT control method based on motion shadow

Under the same environmental conditions, photovoltaic arrays at different operating voltages will significantly affect the size of solar power. To obtain as much power as possible, the maximum power point tracking (MPPT) control method has been invented. Previous studies focused on the tracking problem under local shadow conditions, but the dynamic shadow problem with rapid changes in local shadow was rarely discussed. To solve the tracking problem that the maximum power point has multi-peak and fast-changing characteristics under this condition, this paper proposes a simulated annealing MPPT control method based on particle swarm optimization, which compensates the disadvantages of the memoryless Markov chain in the optimization algorithm by adaptive asymmetric memory factor, thus improving the local search ability and convergence speed in the later stage. The control effect is verified by modeling and simulation in Simulink of MATLAB, and the adaptability of the heuristic control method is reflected by simulating the tracking mode under the moving shadow condition through the actual hardware deployment on the moving car.

Application of a Novel Synergetic Control for Optimal Power Extraction of a Small-Scale Wind Generation System with Variable Loads and Wind Speeds

The synergetic control technique (SCT) has the solution for understanding the symmetry inherent in the non-linear properties of wind turbines (WTs); therefore, they achieve excellent performance and enhance the operation of the WT. Small-scale WTs are efficient and cost-effective; they are usually installed close to where the generated electricity is used. This technology is gaining popularity worldwide for off-grid electricity generation, such as in rural homes, farms, small factories, and commercial properties. To enhance the efficiency of the WT, it is vital to operate the WT at its maximum power. This work proposes an efficient and fast maximum power point tracking (MPPT) technique based on the SCT to eradicate the drawbacks of the conventional methods and enhance the operation of the WT at the MPP regardless of wind speed and load changes. The SCT has advantages, such as robustness, simplified design, fast response, no requirement for knowledge of WT characteristics, no need for wind sensors or intricate power electronics, and straightforward implementation. Furthermore, it improves speed convergence with minimal steady-state oscillations at the MPP. The investigated configuration involves a wind-driven permanent magnet synchronous generator (PMSG), uncontrolled rectifier, boost converter, and variable load. The two converters are used to integrate the PMSG with the load. Three scenarios (step changes in wind speed, stochastic changes in wind speed, and variable electrical load) are studied to assess the SCT. The results prove a high performance of the suggested MPPT control method for a fast convergence speed, boosted WT efficacy, low oscillation levels, and applicability under a variety of environmental situations. This work used the MATLAB/Simulink program and was then implemented on a dSPACE 1104 control board to assess the efficacy of the SCT. Furthermore, experimental validation on a 1 kW Darrieus-type WT driving a PMSG was performed.

Maximum Power Extraction Control Algorithm for Hybrid Renewable Energy System

In this research, a modified fractional order proportional integral derivate (FOPID) control method is proposed for the photovoltaic (PV) and thermoelectric generator (TEG) combined hybrid renewable energy system. The faster tracking and steady-state output are aimed at the suggested maximum power point tracking (MPPT) control technique. The derivative order number (µ) value in the improved FOPID (also known as PIλDµ) control structure will be dynamically updated utilizing the value of change in PV array voltage output. During the transient, the value of µ is changeable; it’s one at the start and after reaching the maximum power point (MPP), allowing for strong tracking characteristics. TEG will use the freely available waste thermal energy created surrounding the PV array for additional power generation, increasing the system’s energy conversion efficiency. A high-gain DC-DC converter circuit is included in the system to maintain a high amplitude DC input voltage to the inverter circuit. The proposed approach’s performance was investigated using an extensive MATLAB software simulation and validated by comparing findings with the perturbation and observation (P&O) type MPPT control method. The study results demonstrate that the FOPID controller-based MPPT control outperforms the P&O method in harvesting the maximum power achievable from the PV-TEG hybrid source. There is also a better control action and a faster response.

Implementation of Solar Panel Static Mppt on Partial Shading Conditions Based on the Boost Topology Converter with Firefly Algorithm

Indonesia has a large potential for new and renewable energy, one of which is solar energy. Solar energy can be converted into electrical energy using solar panels. The output power of a photovoltaic (PV) system is primarily affected by ambient temperature, solar irradiation, and the angle of incidence of the sun. Differences in the level of solar irradiation received by PV modules can be caused by cloudy weather, trees, buildings, and other objects that can cover the surface of the solar panels. When a PV module is partially shaded, the power output of the module becomes imbalanced. Unbalanced output power can cause multiple peaks on the PV characteristic curve, reducing overall output power. To obtain global-peak, a method for maximizing solar panel output power and an algorithm are required. The method is MPPT (Maximum Power Point Tracking). The goal of this research is to determine the maximum power point of PV in the condition of a partially shaded PV module and to design a boost converter. In this study, the MPPT control method with the Firefly algorithm is used to analyze solar panel output power in partially shaded conditions in order to avoid being trapped in the local peak. At 950 W/m2 irradiation and 35°C temperature, the maximum power output generated by the MPPT system on a 200 WP solar panel with the value of 56 Ω and 100 Ω loads is 82.85 W and 82.99 W. In partial shaded conditions on the solar panel by 25% at a temperature of 35ᴼC, the maximum power output generated by MPPT is 40.98 W and 40.82 W. In partial shaded conditions on the solar panel by 50% at a temperature of 35ᴼC, the maximum power output generated by MPPT is 38.81 W and 38.95 W. Partial shading conditions affect the maximum power point gain. The maximum output power of the panel will decrease as the panel surface is partially shaded.

Stochastic maximum power point tracking of photovoltaic energy system under partial shading conditions

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.

Modelling and Simulation of Energy Supply System of Photovoltaic Hybrid RTG Cranes

Background: In marine ports, the task of loading, unloading, and stacking containers is completed by Rubber-Tired Gantry (RTG) cranes. How to make the RTG cranes work efficiently and reduce their emissions, is a hot research topic. Objective: Because current RTG cranes still need a large capacity of diesel engine for energy supply, renewable energy sources, such as solar energy, are introduced to reduce further the capacity of the diesel engine. Methods: A photovoltaic hybrid power supply system for RTG cranes is proposed. A MATLAB/Simulink simulation model for the crane with a 10kW solar panel is built, and a power predictive control method is proposed to realize Maximum Power Point Tracking (MPPT). The power variation of photovoltaic panels under different irradiance is studied. Results: The simulation results show that the proposed MPPT control method is better than the other two perturb and observe methods. When the irradiance changes cause the photovoltaic output to vary, the lithium battery changes its output correspondingly to compensate for the photovoltaic change, and the load power is still met. The capacity of the diesel engine is 40 kW, which is smaller than the former 50 kW one. Based on the irradiance condition in Shanghai, China, the RTG crane can have an 11.4 % fuel reduction yearly by introducing the photovoltaic system. Conclusions: The results show that it is feasible to add the photovoltaic system into the RTG crane, which can reduce the capacity and emissions of the diesel engine.

MPPT of Permanent Magnet Synchronous Generator in Tidal Energy Systems Using Support Vector Regression

In this paper, an improved Maximum Power Point Tracking (MPPT) algorithm for a tidal power generation system using a Support Vector Regression (SVR) is proposed. To perform this MPPT, a tidal current speed sensor is needed to track the maximum power. The use of these sensors has a lack of reliability, requires maintenance, and has a disadvantage in terms of price. Therefore, there is a need for a sensorless MPPT control algorithm that does not require information on tidal current speed and rotation speed that improves these shortcomings. Sensorless MPPT control methods, such as SVR, enables the maximum power to be output by comparing the relationship between the output power and the rotational speed of the generator. The performance of the SVR is influenced by the selection of its parameters which is optimized during the offline training stage. SVR has a strength and better response than the neural network since it ensures the global minimum and avoids being stuck at local minima. This paper proposes a high-efficiency grid-connected tidal current generation system with a permanent magnet synchronous generator back-to-back converter. The proposed algorithm is verified experimentally and the results confirm the excellent control characteristics of the proposed algorithm.

A robust maximum power point tracking control for PV panel using adaptive PI controller based on fuzzy logic

Most methods of maximum power point tracking (MPPT) for photovoltaic (PV) focus only on tracking performance while robustness against disturbances hasrarely been addressed. This paper proposes a new MPPT control method that provides robustness against direct current (DC) link voltage disturbance as well as good tracking performance. The method uses indirect MPPT control topology which incorporates two controllers. For the external controller, we use an adaptive proportional-integral (PI) control which is real-time tuned by fuzzy logic (FL). New membership functions and rule base are proposed using only one fuzzy input variable and 10 fuzzy rules. The internal controller is a PI controller. The PV panelis connected to a boost DC-DC converter. The proposed MPPT control iscompared with the fuzzy logic controller (FLC). Performance is evaluated under DC link voltage disturbance, steady-state condition, and rapid solar radiation changes. Simulation results indicate that the proposed method provides 41.2 % better robustness against DC link voltage disturbance as compared to the direct FLC. Experimental results under natural climate conditions with real solar radiation validate that the proposed method works well in regulating the MPP at steady-state solar irradiance as well as in tracking the MPP towards rapid solar irradiance changes. It yields the PV power tracking speed of 95.75 W/s.

Optimization and Comparison of Photovoltaic MPPT

Maximum Power Point Tracking (MPPT), as the contral core of the output power of photovoltaic power generation system, is extremely crucial to the entire photovoltaic power generation system. In this paper, a number of common MPPT control methods are analyzed in comparison, and the traditional conductance increment method is improved as well. By means of comparative analysis in the simulation software MATLAB/Simulink, it turns out that the improved conductance increment method excels the traditional method with regards to optimization speed and stability.

Comparative study of maximum power point tracking techniques for hybrid renewable energy system

ABSTRACTThe power generation demand is increasing day-by-day throughout the world, therefore, the use of hybrid systems becomes a significant solution. The hybrid renewable energy system (HRES) is used for delivering power in various regions in order to overcome intermittence of wind and solar resources. Because of increasing environmental problems, for example, greenhouse gas emission and energy cost have interested novel research into substitute methods in favour of electrical power generation. Maximum Power Point Tracking (MPPT) control method is a vast deal of novel research used for enhancing the efficiency of HRES. The authors have revealed that the hybrid techniques i.e. Global MPPT, fuzzy-neuro systems, Adaptive Neuro-Fuzzy Inference System (ANFIS), Perturbed and Observe (P&O) + Adaptive Neural Network (ANN) etc. can provide best results as compared to other MPPT control methods. This paper offering a state of art review of MPPT control techniques for HRES.

Design and Hardware Implementation of New Adaptive Fuzzy Logic-Based MPPT Control Method for Photovoltaic Applications

An adaptive fuzzy logic (FL)-based new maximum power point (MPP) tracking (MPPT) methodology for controlling photovoltaic (PV) systems is proposed, designed, and implemented in this paper. The existing methods for implementing FL-based MPPTs lack for adaptivity with the operating point, which varies in wide range in practical PV systems with operating irradiance and ambient temperature. The new proposed adaptive FL-based MPPT (AFL-MPPT) algorithm is simple, accurate, and provides faster convergence to optimal operating point. The effectiveness and feasibility verifications of the proposed AFL-MPPT methodology are validated with considering various operating conditions at slow and fast change of solar radiation. In addition, the simplified implementation of the proposed algorithm is carried out using C-block in PSIM software environment, wherein the proposed algorithm and system are simulated. Additionally, experimental results are performed using a floating-point digital signal processing (DSP) controller (TMS320F28335) for verifying the feasibility of the proposed AFL-MPPT methodology. The results of simulations and experimental prototypes show great consistency and prove the capability of the new AFL-MPPT methodology to extract MPPT rapidly and precisely. The new proposed AFL-MPPT method achieves accurate output power of the PV system with smooth and low ripple. In addition, the new proposed AFL-MPPT method benefits fast dynamics and it reaches steady state within 0.01 s.

Comparative Study of Optimization Techniques for Renewable Energy System

There is a sudden fluctuations in wind speed and change of direction that affects the generator speed thus power generation of wind turbine system, so a controller like maximum power point tracking (MPPT) algorithm is essential in tracking the maximum power out of the available wind speed. MPPT algorithm can be classified into two categories such as with and without sensor as well as according to the algorithms used to find the maximum peak. A comparative analysis of different types of MPPT control methods on the basis of different speed responses and ability to obtain maximum power has been conducted. The literature based on the simulation results points out that the optimal torque control is a better MPPT control method for achieving the maximum power from wind turbine energy system against the most frequently used perturb and observe (P&O) method. The P&O method on the other hand is flexible and easy to implement but provide fluctuations about the maximum power point and is less efficient. The different types of MPPT techniques have been studied for wind turbine renewable energy system. The study points out that MPPT may also include of different dc–dc power converter and various control methods, and hybrid renewable energy system can be developed with multi-input energy systems.

Adaptive Step Size Based Hill-Climb Search Algorithm for MPPT Control of DFIG-WECS With Reduced Power Fluctuation and Improved Tracking Performance

One of the major challenges in harnessing wind energy is to extract maximum power from intermittent generation of wind farms as wind power generation strongly depends on wind speed variation. Among different maximum power point tracking (MPPT) algorithms, traditionally, hill climb search (HCS) method is widely used because of its simple implementation and turbine parameter-independence. However, the conventional HCS algorithm has some drawbacks such as power fluctuation and speed-efficiency tradeoff. Similarly constant tip-speed ratio (TSR) MPPT control method requires precise knowledge of optimal TSR of the turbine. Therefore, in this paper a new adaptive step size based HCS controller is proposed to mitigate the deficiencies of other techniques by incorporating wind speed measurement. The function-based adaptive control scheme evaluates the step size by the variation of the wind speed and extracted power range. The proposed variable step size based HCS-MPPT system is simulated at variable wind speed. A prototype system is also built with a low-power doubly-fed induction generator (DFIG). It is found from the results that the proposed controller reduces the steady-state power fluctuation of the DFIG based wind energy conversion system significantly compared to the conventional HCS-MPPT controller and constant TSR based MPPT controller at variable wind speeds.

Overview of Maximum Power Point Tracking Control Method for Wind Power Generation System

The maximum power point tracking (MPPT) is one of the most important control issues in the wind power, which aims to maintain the maximum power output as the wind speed is lower than the rated one and thus improve the utilization efficiency of the wind energy. The principle of the MPPT is firstly introduced based on the characteristics of the wind turbine. Next, several MPPT control methods are reviewed. Then, the advantages and disadvantages as well as their respective improvements for each method are analysed. Finally, the development trend and research prospect of MPPT have been pointed out.

A nonlinear maximum power point tracking technique for DFIG-based wind energy conversion systems

This paper presents a nonlinear control method for maximum power point tracking (MPPT) of doubly fed induction generator-based wind energy conversation systems. The proposed control structure is wind speed sensorless and independent from turbine characteristics and parameters such as optimal power-speed curve and optimum tip-speed-ratio. The presented MPPT scheme is designed based on adaptive backstepping control method and shown to be robust and stable against parametric uncertainties and wind speed disturbances. The validity, effectiveness and robustness of the proposed MPPT control method is demonstrated through simulation studies in the MATLAB® software environment.

Comparative analysis of maximum power point tracking controller for wind energy system

ABSTRACTThis paper proposes an adaptive maximum power point tracking (MPPT) control method to achieve the maximum power from the wind turbine (WT) power generation system. The MPPT control method has a vital role to find the maximum power point, and also compute the simulation results in both analysis such as offline using MATLAB/SIMULINK™ and online using OPAL-RT simulator. The proposed adaptive perturb and observe (P&O) algorithm provides better results using the OPAL-RT simulator compared to the P&O method using MATLAB/SIMULINK™. The power generation through doubly fed induction generator (DFIG) WT system is becoming important day by day throughout the world. The simulation result by OPAL-RT simulator showed that the efficiency of WT-DFIG has been enhanced.