Maximum Power Tracking Control Research Articles

Maximum Power Point Tracking control of a variable speed wind turbine via a T-S fuzzy model-based approach

This paper proposes a multi-objective H2/H ∞ maximum power tracking control of a variable speed wind turbine to minimize the H2 tracking error and ensure the H ∞ model reference-tracking performance, simultaneously. The optimal condition is obtained via a boost converter use, which adapts the load impedance to the wind turbine generator. Thus, based on the fuzzy T-S model, a multi-objective Maximum Power Point Tracking (MPPT) controller is developed, ensuring maximum power transfer, despite wind speed variation and system uncertainty. To specify the optimal trajectory to follow, a TS reference model is proposed taking as input the optimal rectified DC current. The conditions of stability and stabilization are expressed in terms of linear matrix inequality (LMI) for uncertain and disturbed T-S models leading to determining the controller gains. Finally, an example of MPP tracking applied to a Wind Energy Conversion System (WECS) illustrates the effectiveness of the proposed fuzzy control law.

Current Trends and Innovations in Enhancing the Aerodynamic Performance of Small-Scale, Horizontal Axis Wind Turbines: A Review

Abstract Wind energy has proven to be one of the most promising resources to meet the challenges of rising clean energy demand and mitigate environmental pollution. The global new installation of wind turbines in 2022 was 77.6 GW, bringing the total installed capacity to 906 GW, documenting an astounding 9% growth in just one year (Lee and Zhao, 2023, Global Wind Report, GWEC. Global Wind Energy Council). Sizeable research continues to focus on improving wind energy conversion, safety, and capacity. However, funding allocations and research have not matched this sustained market growth observed over the last few decades. This is particularly the case for small-size wind turbines. We define small-scale wind turbines as those with an output power of 40 kW or less that can nonetheless be interconnected to provide larger power output. Thus, the paper focuses on small-scale horizontal-axis wind turbines (HAWT) with emphasis on current technology trends including data gathering, aerodynamic performance analysis of airfoils and rotors, as well as computational approaches. The paper also highlights the challenges associated with small-scale HAWTs thereby conjecturing about future research directions on the subject. The literature review suggests that small-scale HAWT wind turbines are suitable for harnessing energy in communities with limited resources where grid-supplied power is out of reach. The power coefficient of these turbines ranges from 0.2 to 0.45 which shows that it could greatly benefit from research, built on targeting these modest performance scales by using efficient airfoils, mixed airfoils, optimizing the blade geometry, shrouding the wind turbine rotor, using maximum power tracking control, etc. This review paper is an attempt to prioritize and layout strategies toward evaluating and enhancing the aerodynamic performance of small-scale HAWTs.

Maximum power tracking strategy of a wind energy conversion system based on resonant with active disturbance rejection control

PurposeThis study aims to construct a novel maximum power tracking control system for the direct drive permanent magnet synchronous generator (PMSG) of the wind energy conversion system (WECS) to solve the following problems: how to effectively eliminate the system’s model parameter disturbances and speed up the dynamic performance of the system; and how to eliminate harmonics in WECS under different wind speeds.Design/methodology/approachTo obtain the maximum output power of PMSG at WECS under different wind speeds, the following issues should be considered: (1) how to effectively eliminate the system’s model parameter disturbances and speed up the dynamic performance of the system; and (2) how to suppress system harmonics. For Problem 1, adding d–q compensation factors to active disturbance rejection control (ADRC) for the current loop realizes the d–q axis decoupling control, which speeds up the dynamic performance of the system. For Problem 2, the resonant controller is introduced into the ADRC for the current loop to suppress harmonic current in WECS under different wind speeds.FindingsThe simulation results demonstrate that the proposed control method is simpler and more reliable than conventional controllers for maximum power tracking.Originality/valueCompared with traditional controllers, the proposed controller can speed up the dynamic performance of the system and suppress the current harmonic effectively, thus better achieving maximum power tracking.

Chimp Optimized Fractional-Order Tilt Integral Derivative Controller (NFO-TIDC) Assisted Battery for EV Charging

The vast usage of electric vehicles (EVs) has raised to minimize the dependency on fossil fuels. The Photovoltaic (PV) is used in the charging station to supply the required power to the EV. Batteries’ charging and discharging control have become a major challenge in RES interconnected EV charging stations. To tackle this issue, a novel fractional-order tilt integral derivative controller (NFO-TIDC) is used in the battery-connected bidirectional converter. Moreover, special considerations of the NFO-TIDC are accomplished with an improved Chimp optimization algorithm. In addition, the enhanced seagull optimized maximum power tracking controller has been proposed for maximizing the power from PV under varying irradiance. The proposed method is implemented on MATLAB/Simulink, and the obtained results verify the superiority of the controller.

Improved climbing algorithm with variable step size in tidal energy Application of maximum power tracking control technique for power generation system

In the context of carbon neutral carbon peak, in order to cope with climate change caused by environmental pollution and energy shortage caused by excessive use of fossil energy, the vigorous development of clean, low-carbon, and efficient renewable energy has become a major strategic direction. The development and utilization of tidal energy in China is still a certain gap with the European powerhouse, the efficiency of tidal energy generation at a low flow rate is low and the scale of development and utilization is small. The feasibility of the proposed strategy is verified by simulation analysis, and the results show that the improved variable step climbing algorithm can quickly track the maximum power point and operate stably at this point.

Research on coordinated control strategy of photovoltaic energy storage system

In this paper, the modular design is adopted to study the control strategy of photovoltaic system, energy storage system and flexible DC system, so as to achieve the design and control strategy research of the whole system of “photovoltaic + energy storage + DC + flexible DC”. This realizes the flexibility and diversity of networking. Due to space reasons, this article focuses on the detailed explanation of the photovoltaic energy storage system control strategy, including the maximum power tracking control strategy of photovoltaic power generation, photovoltaic power generation boost chopper circuit control strategy, photovoltaic power generation DC/AC converter control strategy, PCS device control strategy, PCS virtual impedance control algorithm, etc. Simulation experiments are carried out according to the specific case setting parameters. The simulation results prove that the proposed flexible DC system coordinated control strategy can ensure grid frequency stability and grid voltage stability, and improve the consumption capacity of distributed new energy.

Research on Improved PSO Algorithm for Multi-peak to Photovoltaic Maximum Power Tracking Control

To ensure the real-time output maximum power of a photovoltaic power producing system and improve the multi-peak MPPT management of a solar array under partial shadow, a maximum power tracking control strategy based on an Improved PSO algorithm is presented. To increase the stability of maximum power tracking and to promote the coordination performance of local development and global search, the adaptive inertia weight and learning factor are developed regarding the basic PSO algorithm. Besides, simulation studies are used to evaluate the MPPT control effects of the method with the fundamental PSO algorithm in various situations. The findings show that the improved PSO algorithm outperforms the traditional PSO technique in terms of tracking effectiveness. It can not only converge to the GMPP quickly in the case of various local shading and light mutations but also has higher power generation efficiency.

Improved variable-step incremental conductance MPPT algorithm applied to photovoltaic storage systems

For the traditional PV maximum power tracking control method in terms of tracking speed and stability, proposed an improved variable-step incremental conductance method. The method first speeds up the tracking speed by the constant voltage coefficient method to quickly locate around the MPP(Maximum power point,MPP) and dynamically adjusts the step size using the inverse tangent function value when the operating point is located to the left of the maximum power point, and dynamically adjusts the step size using the exponential function value when the operating point is located to the right. Given the characteristics of photovoltaic power generation, it usually constitutes a light storage system with an energy storage battery. To verify the effectiveness, the simulation experiments are carried out in Matlab/Simulink to build a photovoltaic energy storage system model, which contains an energy storage battery. Results indicate that the proposed new method achieves the optimization of tracking precision and speed according to the nature of the function and can make the energy storage battery charge and discharge stably, which verifies the practicality of the proposed improved algorithm.

Solar Maximum Power Point Tracking Algorithm Based on Wavelet Neural Network

With the development of human civilization, the shortage of resources and environmental pollution are increasing. Renewable energy is the only way to solve the problem of harmonious coexistence between human civilization and environment. More and more of them have come into our lives to reduce the burden of the earth and benefit mankind. Nowadays, due to the increasing gap of traditional power supply, solar energy has become a mainstream renewable energy, more and more applications, to provide us with green energy and improve our lives. The research on the application of solar energy system is of great academic value. This paper mainly studies the solar maximum power point tracking (MPPT) algorithm based on wavelet neural network (WNN). This paper analyzes several common maximum power tracking control methods, describes the structure design of WNN maximum power tracking control algorithm, and describes the structure and working principle of photovoltaic cells. In this paper, the output power of MPPT mode is analyzed and compared by simulating the use of solar photovoltaic system. In the meantime, the output voltage of solar charging panel in the charging process is studied. The experimental results show that the output power of the power supply in MPPT mode is kept at 0.2, and the output power of the solar panel is improved at every moment with the change of the external environment. At 9 o'clock, the output voltage of the solar panel is 3.6, and at 11 o'clock, the output voltage is 4.11.

Improvement and Analysis of Phase-Phase Failure of Double Feed Induction Generator Using Maximum Power Monitoring Method

This study presents an analysis and control method for the doubly fed induction generator (DFIG) based wind energy production under the conditions of sudden grid voltage dips. The control aims are as follows: limiting the rotor currents, suppressing the fluctuations in the torque and suppressing the dc-link voltage fluctuation via the converter controls and ensuring maximum power point tracking. Rotor side converter (RSC) and grid side converter (GSC) structures have been given in the article and their limitations have been specified. Maximum power tracking control block has also been included in the system and its structure has been given. In this study; while RSC is controlled in a way that it will suppress the fluctuations in the torque and rotor currents, GSC is controlled in a way that it will suppress the fluctuations in dc-link voltage while taking the rotor power impact into consideration. Crowbar unit has been used in the rotor side to minimize these impacts. This unit is activated at the moment when a grid dip occurs and deactivates the RSC side. In this way, RSC side will not be affected by the high current fluctuations. The detailed results of the study were carried out in the MATLAB/Simulink environment,and the effectiveness of the proposed method was supported by the graphic results.

Fuzzy model based multivariable predictive control design for rapid and efficient speed-sensorless maximum power extraction of renewable wind generators

Introduction. A wind energy conversion system needs a maximum power point tracking algorithm. In the literature, several works have interested in the search for a maximum power point wind energy conversion system. Generally, their goals are to optimize the mechanical rotation or the generator torque and the direct current or the duty cycle switchers. The power output of a wind energy conversion system depends on the accuracy of the maximum power tracking controller, as wind speed changes constantly throughout the day. Maximum power point tracking systems that do not require mechanical sensors to measure the wind speed offer several advantages over systems using mechanical sensors. The novelty. The proposed work introduces an intelligent maximum power point tracking technique based on a fuzzy model and multivariable predictive controller to extract the maximum energy for a small-scale wind energy conversion system coupled to the electrical network. The suggested algorithm does not need the measurement of the wind velocity or the knowledge of turbine parameters. Purpose. Building an intelligent maximum power point tracking algorithm that does not use mechanical sensors to measure the wind speed and extracts the maximum possible power from the wind generator, and is simple and easy to implement. Methods. In this control approach, a fuzzy system is mainly utilized to generate the reference DC-current corresponding to the maximum power point based on the changes in the DC-power and the rectified DC-voltage. In contrast, the fuzzy model-based multivariable predictive regulator follows the resultant reference current with minimum steady-state error. The significant issues of the suggested maximum power point tracking method, such as the detailed design process and implementation of the two controllers, have been thoroughly investigated and presented. The considered maximum power point tracking approach has been applied to a wind system driving a 5 kW permanent magnet synchronous generator in variable speed mode through the simulation tests. Practical value. A practical implementation has been executed on a 5 kW test bench consisting of a dSPACEds1104 controller board, permanent magnet synchronous generator, and DC-motor drives to confirm the simulation results. Comparative experimental results under varying wind speed have confirmed the achievable significant performance enhancements on the maximum wind energy generation and overall system response by using the suggested control method compared with a traditional proportional integral maximum power point tracking controller.

HOSMD and neural network based adaptive super-twisting sliding mode control for permanent magnet synchronous generators

To solve the maximum power tracking (MPT) control problem of the direct-driven wind power system, a super-twisting integral sliding mode controller with adaptive parameter estimation is designed. A high-order sliding mode differentiator is introduced as the virtual control variate filter, which solves the difficulty of obtaining the derivative of the control variate and the controller saturation in the nonlinear system with disturbances. Since the speed loop of permanent magnet synchronous generator (PMSG) is susceptible to disturbances, a radial basis function neural network (RBFNN) approximator and its adaptive algorithm are proposed to observe the unmodeled part of the system and external disturbances. In addition, the super-twisting algorithm is introduced to improve the robust performance. An improved adaptive parameter estimation algorithm is used to obtain real-time estimated values in the circumstances of uncertain stator parameters and parameters perturbation during operation, which enhances control accuracy and reduces undesirable chatting. The errors of RBFNN approximation and parameter estimation are taken into Lyapunov functions to guarantee the stability of the whole system. The effect of the proposed scheme is verified as compared to the adaptive backstepping terminal and new reaching law sliding mode controllers.

HIL-Simulation을 이용한 50kW PV 시스템의 MPPT 제어 성능 검증

This paper proposes a maximum power tracking control algorithm based on the incremental conductance method with a variable step size coefficient that is not affected by the insolation of 50kW PV system. A PV module for consisting 50kW PV system is modeled as a single module considering the real-time calculation of RTBOX, and a control module is modeled to control MPPT and load balance of three-phase interleaved converter. HILS system consists of RTBOX, TMS320F28379D, and interface board. Through PLECS simulation and HILS, under the conditions of changes in insolation, performance of MPPT efficiency, tracking time to the maximum power point, and load balance of interleaved converter are verified.

A REVIEW ON COMPARISON STUDY OF DIFFERENT CONVERTER WITH VARIOUS CONTROL TECHNIQUES AND VARIOUS MPPT TECHNIQUES

There are various DC-DC converters used in Solar PV system for matching the impedance between the source and the load. This document describes the many types of converters used in photovoltaic solar systems, including their applications, advantages, and downsides. This article presents a study of the literature of the majority recent results in artificial intelligence algorithms for maximum power tracking control. MPPT algorithms are used to match the load resistance to the source input resistance to increase the power delivered from the PV system. This paper gives reviews of different control techniques for DC-DC Interleaved Boost Converter for power level conversion. Different control schemes, including linear and non-linear control. Moreover, various control techniques are compared in terms of Advantages and disadvantages of each.

Design of optimal controller for photovoltaic maximum power point tracking applications

ABSTRACT Photovoltaic (PV) maximum power point tracking (MPPT) technology is one of the key technologies that affect the energy utilization of PV power generation systems. How to achieve PV maximum power output quickly, accurately, and simply during the process of changing insolation and temperature conditions is a key problem in current research. At present, the traditional model-free maximum power tracking algorithm suffers from slow response, steady-state oscillations, and large influence of control parameters, whereas the model-based maximum power point tracking algorithm has the advantages of a simple control rate calculation and excellent control performance; however, the nonlinear characteristics of PV cells and power electronic converters lead to difficult controller design and often require a reference value of the maximum power point to be given. In this study, a mathematical model of a PV system was used, and a new PV maximum power tracking algorithm that does not require a reference value to be specified was proposed. The algorithm maps the nonlinear state-space description of the PV power generation system into a linear space through the state feedback linearization design. This solves the problem of difficult controller design for a nonlinear PV power generation system. Starting with the PV maximum power point as the extreme value point of the U-P curve, optimal control theory is applied to derive the PV maximum power tracking control rate, which overcomes the difficulty caused by the model-based control method requiring a reference to be specified. Compared with the traditional method, the proposed maximum power point tracking method improves the response speed by approximately 3–20 times and the tracking accuracy by approximately 3% or less. In addition, the method has a certain amount of immunity to DC bus voltage fluctuations.

Prescribed performance finite‐time control of wind energy conversion systems with input constraint and system uncertainty

In this paper, the maximum wind power tracking control problem for the wind energy conversion system is considered and two effective algorithms are presented to solve it. The main contributions are as follows: (a) An improved prescribed performance control algorithm is proposed. By using a new performance function and a new error transformation scheme, the proposed controller can solve overshoot problems and guarantee tracking error to reach its stability region within finite time. (b) The nonsingular terminal sliding mode prescribed performance control algorithm is proposed. In order to solves finite time convergence and avoid the generation of singularity for wind energy conversion system, a finite-time stable controller is designed by combining the nonsingular terminal sliding mode technique and a finite-time prescribed performance function. Furthermore, a finite-time observer is used to estimate the system uncertainties. An auxiliary system is introduced to solve the problem of control input saturation. The stability of the system is proved by using Lyapunov theory. The feasibility of the proposed methods is verified by the simulation results. The research conducted in this paper will make great significance for the study of maximum wind power tracking control problem.

An adaptive constant current and voltage mode P&O-based Maximum Power Point Tracking controller IC using 0.5-[formula omitted] HV CMOS

Photovoltaic (PV) energy harvesting has been widely used in the application of energy storage for battery charging. The more solar energy effectively harvested by the harvesting circuit, the more efficient charging will take place. Many papers used different MPPT methods that enhance PV harvesting that require ADC and MCU which is costly and also requires a long period of tracking. A high-voltage energy harvesting circuit with adaptive constant current (ACC), constant voltage (CV), and maximum power tracking (MPPT) control for 20V/ 5 W solar panels is proposed to carry out the constant current charging (CC) and constant voltage (CV) charging modes of lithium-ion batteries when the solar panel’s maximum power point changes. Pulse width modulation (PWM) and pulse frequency modulation (PFM) are implemented under different light intensity conditions to improve the efficiency. The ACC mode controlled by perturb-and-observe (PBO) MPPT algorithm improved the efficiency during insufficient light source or low battery power. When the battery is fully charged, the over-charging damage is prevented to the lithium-ion battery when CV mode is activated. TSMC 0.5-μm UHV process is used to fabricate the energy harvesting circuit. For the photocurrent range of 0.1 A to 0.3 A, this design achieved a peak efficiency of 98%.

Research on Maximum Power Tracking Control Method of 10MW MVSPMSG Based on Neutral Point Potential Balance

In order to meet safety and stability grid-connected requirementsof high-power offshore wind turbines, the 10 MW wind power generation system composed of medium voltage six phase permanent magnet synchronous generator (MVSPMSG) and distributed neutral point clamped (NPC) converter is adopted. On the basis, a maximum power point tracking control (MPPT) method of 10 MW MVSPMSG based on neutral point potential balance is studied in the paper.Firstly, the optimal reference torque of MVSPMSG is calculated according to speed feedback, and the double d-q current control loop of stator is designed based on the doubly fed decoupling. The MPPT of MVSPMSG is realized by the closed-loop combination of torque loop and double d-q current loop. Secondly, in order to suppress the fluctuation of DC neutral point potential, a midpoint potential balance coordinated control method based on modulation coefficients and vector group selection is proposed. The mid-point potential fluctuations is suppressed by adjusting the magnitude of the modulation coefficient in the normal range. The vector group selection method is collaboratively added to the midpoint potential balance control based on small vectors when the modulation coefficient exceeds the limit. Finally, the effectiveness of the proposed MPPT control strategy and midpoint potential balance strategy are verified, which provides a theoretical reference for the control of high-power permanent magnet wind turbine.

Design of solar light tracking system Research on energy autonomy system design of outdoor patrol car based on solar energy

The Inner Mongolia has abundant solar energy and electricity resources. Because of the long distance between cities, transmission lines are too long, making it difficult to check lines. In order to solve the problems existing in the inspection work, this paper studies a kind of outdoor inspection vehicle using solar energy, the energy system of the inspection vehicle can independently complete the charge and discharge, so as to realize the inspection task. This paper focuses on the energy autonomy of the on-site inspection vehicle for solar energy. According to the design requirements of the inspection vehicle, appropriate parts are selected to build an energy autonomy inspection system for the inspection vehicle. Then the solar tracking algorithm and maximum power tracking control algorithm are used to improve the conversion rate of solar panels and achieve fast charging. Finally, the hardware and software of the solar controller are designed, and the corresponding functions are debugged.

MPPT control based on improved mayfly optimization algorithm under complex shading conditions

Abstract The output power curve of the photovoltaic array presents a multi-peak characteristic under partial shading conditions, which causes the traditional maximum power point tracking technology to fail to guarantee the maximum power output of the photovoltaic cell. In response to this problem, this paper proposes to apply the improved Mayfly Optimization Algorithm (MA) to the maximum power tracking control. By introducing the gravity factor and limiting the search space of male mayfly, the optimization accuracy of the algorithm is enhanced, the vibration of the algorithm near the MPP is reduced, and the occurrence of premature phenomenon is avoided. Three test functions are selected to verify the algorithm, and under the conditions of rapid irradiance changes and complex shadow occlusion, an MPPT model based on the Boost circuit is established to verify the effectiveness of the algorithm. The simulation results show that the improved MA algorithm can effectively converge to MPP under complex shading conditions, and the output efficiency of photovoltaic arrays can be maintained above 99.96%. The average tracking time for different shading patterns is about 0.15 s.