Power Tracking Control Research Articles

Energy Management Strategy for Direct Current Microgrids with Consideration of Photovoltaic Power Tracking Optimization

In response to the uncertainty of renewable energy output and the fluctuation of load, this paper proposes a hybrid energy storage management strategy based on the State of Charge (SOC) to smooth power fluctuations and thereby improve the power quality of photovoltaic energy storage DC microgrids. Firstly, a hybrid algorithm for power tracking control is formed by incorporating the Particle Swarm Optimization (PSO) algorithm into the variable step-size Incremental Conductance (INC) method, thereby optimizing the maximum power point tracking control system of the photovoltaic system. Then, a first-order filter is employed for the initial allocation of demand power. Taking the SOC of supercapacitors and energy storage batteries as a reference, a secondary power allocation energy management strategy based on rule-based control is proposed to ensure the service life and application safety of the hybrid energy storage system. Finally, simulation experiments are conducted in MATLAB/Simulink 23.2 (R2023b). The results indicate that the proposed energy management strategy can maintain the SOC of the hybrid energy storage system at a reasonable level and effectively smooth DC bus voltage fluctuations.

A Decentralized Demanded Power Tracking and Voltage Control Method for Wind Farms Based on Data-Driven Sensitivities

A Decentralized Demanded Power Tracking and Voltage Control Method for Wind Farms Based on Data-Driven Sensitivities

A modified P&O maximum power tracking control algorithm for independent wind energy conversion system

A modified P&O maximum power tracking control algorithm for independent wind energy conversion system

Photovoltaic Maximum Power Point Tracking Technology Based on Improved Perturbation Observation Method and Backstepping Algorithm

Photovoltaic power generation systems mainly use the maximum power tracking (MPPT) controller to adjust the voltage and current of the solar cells in the photovoltaic array, so that the photovoltaic array runs at the maximum power point (MPP) to achieve the purpose of maximum power output. At present, photovoltaic power stations mainly adopt the traditional method to track the maximum power point, but this fixed step method easily causes output power oscillation of the photovoltaic array when tracking the maximum power point, and it easily falls into the local extreme point under partial shadow conditions. In order to solve these problems, this paper proposes an improved perturbation observation method and backstepping method (IP&O-backstepping) to replace the traditional method applied to the MPPT controller to optimize the operating state of the solar cell, thereby improving the output power point of the photovoltaic array and increasing the output power of the photovoltaic array. The algorithm first uses the improved perturbation and observation (IP&O) method to search the maximum power point of the photovoltaic array and output the reference voltage. Secondly, the reference voltage is input into the backstepping algorithm for voltage tracking. Finally, the algorithm tracks the reference voltage and makes the photovoltaic array operate at the maximum power point. The simulation is carried out by using MATLAB/Simulink. The IP&O-backstepping algorithm is compared with the intelligent algorithm and the traditional method, and the results show that compared to the above algorithm, the IP&O-backstepping algorithm can not only track the maximum power point of the photovoltaic array, but also has a faster tracking speed, and the output power has almost no oscillation when the photovoltaic array runs at the maximum power point.

CPS-based power tracking control for distributed energy storage aggregator in demand-side management

The deployment of distributed energy storage on the demand side has significantly enhanced the flexibility of power systems. However, effectively controlling these large-scale and geographically dispersed energy storage devices remains a major challenge in demand-side management. In this paper, we propose a CPS-based framework for controlling a distributed energy storage aggregator (DESA) in demand-side management. Within this framework, a distributed power tracking control algorithm is designed to ensure both power tracking and state-of-charge (SoC) balancing among the energy storage units (ESUs) within the DESA. The proposed algorithm utilizes a distributed observation-based approach that relies solely on local communication. It is demonstrated that the algorithm achieves power tracking convergence within a fixed time, while asymptotically achieving SoC balancing when assuming a connected communication network among the storage units. To validate the theoretical analysis and demonstrate the effectiveness of the proposed control strategy, an example scenario comprising six ESUs is presented.

Research on Fourier Coefficient-Based Energy Capture for Direct-Drive Wave Energy Generation System Based on Position Sensorless Disturbance Suppression

In order to improve the energy capture efficiency of direct-drive wave power generation (DDWEG) systems and enhance the robustness of the reference power tracking control, a Fourier coefficient-based energy capture (FCBEC) and a position sensorless disturbance suppression (PSDS) control strategy are proposed. For energy capture, FCBEC is proposed to construct the objective function by maximizing the average power over a period of time and expanding the variables in the Fourier basis when the maximum power is captured, which is used as the basis for obtaining the reference trajectory. To address the limitations of the mechanical encoder, the position sensorless technique, based on a sliding mode observer (SMO), is used in the power tracking control, and the position information is obtained through an inverse tangent function. The perturbation caused by the inverse electromotive force error in the system is theoretically analyzed. A full-order terminal sliding mode approach is employed to design a current controller that suppresses the perturbation and ensures accurate tracking of the reference current. Simulation results show that the ocean-wave energy capture strategy proposed in this paper can make the energy captured by the PTO reach the optimal value under the impedance matching condition, and that the response speed and robustness of the full-order terminal sliding mode are better than the traditional PI control.

An Innovative AgNP-based Solar Panel Coating and Farmland Fertility Optimization (FFO) based Power Extraction Methodology for Grid Systems

In the power electronic system, coated solar panels attracted a lot of interest in present times. The proposed work aims to achieve two key objectives: maximal power extraction and solar panel coating. To reduce the cost of coating material for solar panels, Silver Nano Particles (AgNPs) are first collected from the leaves of Rose periwinkle plants. This strategy aims to achieve maximal power extraction by coating solar panels with green synthesized silver nanoparticles. To reduce the cost of coating material, Rosy periwinkle plant leaves are used to synthesize silver nanoparticles or AgNPs. To ascertain the framework's capacity for measuring energy both before and after the panels are coated with AgNP, this study theoretically analyses the data. The power current and voltage-current characteristics of the study were validated, enabling an examination of the study's effectiveness. The coated type outperformed the normal solar panel by 2%, according to the results. With a new approach called Farmland Fertility Optimization – Maximum Power Position Tracking, the precise peak site for increased energy yield is discovered. The bi-directional converter is also utilized to mitigate stress and increase voltage gain. To improve the power quality with fewer harmonics, the 3-phase inverter and the LC filtering circuits are used. Finally, a variety of performance measures are used to confirm the results of coated solar panels using power-tracking control techniques. The findings suggest that AgNP-coated solar panels provide the best possible electrical energy with improved voltage, current, and power quality. Performance evaluation shows that the coated solar panel's power tracking efficiency has increased to 99% with decreased harmonics of 2.52%.

Event-Triggered Power Tracking Control of Heterogeneous TCL Populations

Event-Triggered Power Tracking Control of Heterogeneous TCL Populations

A Study on An MPPT Control Approach Using Artificial Intelligence and the Perturb and Observe Method

A maximum power point tracking (MPPT) control procedure constructed based on the Artificial intelligence optimization algorithm is proposed. A mathematical model of photovoltaic cells was established under varying light intensity and ambient temperature. Maximal power tracking control for iterative search using an artificial intelligence (AI) optimization technique Excellent, the artificial intelligence-based MPPT algorithm's principle is presented. Simulation results it shows that the artificial intelligence algorithm can faster and exactly track the maximum power point and remains stable, and compared to Perturb and Observe algorithm under dynamic shadow conditions and artificial intelligence MPPT control method, which has higher tracking accuracy and faster convergence speed. Faster and smaller oscillation amplitude, which is the best response to sunlight conditions for photovoltaic maximum power point tracking technology Flexibility. Using Matlab/Simulink software to build a simulation model of an independent photovoltaic system. It controls variables by keeping the temperature continuous and changes the light intensity to simulate different lighting environments. The identical comparison was conducted between all based MPPT methods such as the fuzzy control approach, demonstrating that the fuzzy control based technique exhibits higher results in terms of efficiency.

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.

Power–Pitch Cascade Control-Based Approach for the Up/Down-Regulated Operation of Large Wind Turbines

Modern energy needs require controlled and clean power generation. This demands that the wind turbines be integrated into joint generation groups (wind farms) and the power supply passes be managed by the grid. In this case, the control system of both the wind farm and the individual machines needs the ability to decrease and increase the power output as required. This control system feature is normally implemented by changing control strategies and an associated switching logic. This makes the control system additionally complex and prone to errors. This paper proposes an integrated control configuration for torque and pitch based on a cascade power tracking control (PTC) approach that extends the traditional wind turbine control to enable or disable up/down-regulation. Hence, the resulting control system topology is not complex, and its theoretic dynamic behaviour is known and expected. The new control configuration is studied within a simulation environment with a 20 MW reference machine. The simulation results are very promising from the control performance viewpoint.

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.

Comparative Analysis of Two-Stage and Single-Stage Models in Batteryless PV Systems for Motor Power Supply

Implementing photovoltaic (PV) systems as direct power sources for motors without batteries is a complex process that requires a sophisticated control mechanism. The crucial aspect of PV systems is the Maximum Power Point Tracking (MPPT) process, which ensures that the installed PV system generates optimal energy output. A recent study has analyzed research related to PV systems supplying power to pump motors, and the results have successfully classified these systems into two main models: the two-stage and the single-stage. The two-stage model involves separate power tracking and load consumption control processes, while the single-stage model integrates power tracking and load consumption control into a single process. A comparative analysis of these two models has revealed that the two-stage model exhibits higher stability due to the separate power tracking and load consumption control processes. Aspects such as the MPPT process, motor power consumption, and the utilization of DC-link capacitors were examined in this study. The findings of this comparative study contribute valuable insights into the effectiveness and stability of two-stage and single-stage models in PV systems supplying power to motors without batteries. The results will significantly interest researchers and practitioners working in Photovoltaic systems and motor control, providing helpful information for designing and implementing more efficient and reliable PV systems.

Comparative study of maximum power point tracking control for PV arrays system integration process

Comparative study of maximum power point tracking control for PV arrays system integration process

Variable Power Tracking Control Strategy of Doubly Fed Induction Generators for Fast Frequency Responses

Frequency regulation and droop control of doubly fed induction generators (DFIGs) can quickly respond to frequency changes and reduce the maximum rate of frequency (MROFF) in power systems. However, due to real-time dynamic changes in the MPPT control loop, the ability to improve the lowest frequency point is limited. Therefore, this article first describes an in-depth analysis of the dynamic characteristics of the incremental power of frequency regulation with droop control using an equivalent linear model. The limitations of improving the lowest frequency point under the influence of dynamic changes in the MPPT control loop are revealed. Secondly, to address the impact of these dynamics, an improved decoupling frequency regulation (IDFR) strategy based on power tracking is proposed, aiming to increase the maximum frequency deviation (MFD) and MROCOF. Then, in order to overcome the difficulty of adjusting control coefficients in the IDFR strategy, an adaptive control coefficient tuning fuzzy control method based on frequency deviation and ROCOF was proposed to flexibly adjust control requirements under various working conditions, thereby improving the control stability and performance of the system and effectively solving the problem of control coefficient allocation. Finally, to verify the frequency regulation performance of the proposed IDFR strategy under various operating conditions, simulations were conducted based on different disturbances and wind conditions. The results show that the proposed IDFR strategy significantly improves the system MFD and MROCOF improvement ability under various conditions.

Sampling Time Modulation of a Photovoltaic Power Tracking Controller Based Upon Real-Time Monitoring of Converter Dynamics

Sampling Time Modulation of a Photovoltaic Power Tracking Controller Based Upon Real-Time Monitoring of Converter Dynamics

Model predictive control for automatic operation of space nuclear reactors: Design, simulation, and performance evaluation

Model predictive control for automatic operation of space nuclear reactors: Design, simulation, and performance evaluation

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.

Power Tracking Control of Heterogeneous Populations of Thermostatically Controlled Loads With Partially Measured States

Power Tracking Control of Heterogeneous Populations of Thermostatically Controlled Loads With Partially Measured States

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.