Control Scheme For Regulation Research Articles

Various Techniques for Charging Lithium-Ion Batteries in Electric Vehicles Using Wireless Power Transfer Chargers

Precise voltage and current regulation is essential to ensure the required power output and maximum efficiency in charging stations, particularly those utilizing Wireless Power Transfer (WPT) systems. Effective regulation techniques are necessary to manage voltage and current in Battery Electric Vehicles (BEVs) operating under various charging modes. This study outlines the controller design for different methods for charging lithium-ion batteries in a WPT charger. Initially, the fundamental concepts of WPT systems and their equivalent circuit are introduced. Subsequently, the control strategy for current regulation is detailed for the Constant Current (CC) mode, the Multi-stage Current Method (MCM), and the Pulse Charging Method (PCM). Finally, the resilience and validity of this innovative approach to controlling various techniques for charging lithium-ion batteries are demonstrated through simulations.

Study on adaptive VSG parameters and SOC control strategy for PV-HESS primary frequency regulation

Hybrid energy storage plays a critical role in primary frequency regulation during large-scale renewable energy integration. Rational power distribution between multiple types of energy storage, as well as the use of a VSG control technique, are effective approaches to improving primary frequency regulation capability. To that end, this paper presents an adaptive Virtual Synchronous Generator (VSG) characteristics and state of charge (SOC) management technique for photovoltaic (PV) - hybrid energy storage system (HESS) primary frequency regulation. First, a power distribution mechanism for HESS on the direct current side is implemented. Second, a primary frequency control strategy is proposed based on adaptive rotational inertia and damping coefficient of VSG and SOC regulation of energy storage. Finally, a simulation analysis confirms the feasibility of the proposed primary frequency control strategy under transient conditions. The relevant results are presented as follows. Compared to traditional control strategies, the improved adaptive VSG parameter and energy storage SOC control strategy reduces the overshoot and adjustment time of VSG active power and frequency response by 68.57%, 23.94%, 19.05% and 9.80%, respectively. The decline in SOC of battery energy storage is decreased by 3.18%. The proposed control strategy also limits grid frequency fluctuation within ±0.2 Hz, with a recovery time of less than 0.5 seconds. The overall root mean square error of frequency fRMSE is a maximum of 0.02 Hz. The primary frequency regulation capability of the PV-HESS is enhanced, ensuring the operational safety of energy storage systems and effectively improving the stability while also improving grid stability and security.

Comparative Study of Linear Control Strategies for Regulation, Tracking of Unstable Systems and the Scope for LQR Infusion in Optimisation Problems

Comparative Study of Linear Control Strategies for Regulation, Tracking of Unstable Systems and the Scope for LQR Infusion in Optimisation Problems

Optimal control of grid-connected overvoltage of distributed photovoltaic power generation based on cluster division

To address the overvoltage problem caused by the reverse flow of current when a high proportion of distributed photovoltaic (PV) is connected to the distribution network, this paper proposes a grid-connected voltage regulation control strategy based on the cluster division of the Distributed Model Predictive Control (DMPC) algorithm. Firstly, the overvoltage responsibility of each node is calculated using the Shapley value method. This is combined with k-means clustering to achieve effective cluster division, enabling dynamic adjustment of the active and reactive power of photovoltaic power generation units to stabilize regional voltage. Secondly, a group grid-connected voltage control strategy is introduced. This strategy controls the active and reactive power outputs by integrating real-time power output and voltage information from PV generating units in the region with the DMPC algorithm, ensuring overall voltage stability of the grid-connected system. Finally, actual overvoltage data from a 10 kV distribution line in the Dingxi power grid, Gansu Province, is used to verify that under the proposed control strategy, PV grid-connected overvoltage nodes are maintained within 1.06 p.u. The control effect is improved by a margin of 0.05 compared to traditional control methods. This demonstrates the effectiveness of the grouped grid-connected voltage regulation control strategy, achieving smoother voltage regulation performance in distributed PV grid-connected systems.

Remote Temperature Monitoring and Control System Using SCADA for Large Industrial Environment

In large-scale food companies to ensure product quality and protection, precise temperature control must be maintained. This research presents the design and implementation of a SCADA (Supervisory Control and Data Acquisition) system integrated with a PID (Proportional-Integral-Derivative) control strategy for effective temperature regulation. The system offers operators a comprehensive Human-Machine Interface (HMI) for real-time visualization and control, processes temperature data through a PID controller to maintain a setpoint of 85°C, and continually monitors temperature data in real-time. The simulation results demonstrate that despite outside disruptions, the system can maintain the required temperature within close tolerances, assuring ideal process conditions. Large-scale industrial applications of SCADA systems are emphasized by their function in advanced data analysis, supervisory control, alarm management, and data collecting.

Coordinated control strategy for improving frequency security of LCC[sbnd]HVDC sending-end system with large-scale wind power

To improve the frequency security of the LCCHVDC sending-end system with high penetration of wind power system and achieve optimal utilization of frequency regulation resources, a cooperative control strategy involving wind power and LCCHVDC in frequency regulation is proposed. Firstly, under a variety of scenarios, the power support requirements of LCCHVDC sending-end system are analyzed according to the power regulation margin of various frequency regulation resources and the disturbance power, and a multi-time scale frequency regulation control strategy for DFIG based wind farms is proposed, which combines the advantages of variable speed control and variable pitch angel control. And a cooperative control strategy of DFIG and LCCHVDC considering the frequency regulation deadband is proposed. Then, based on the maximum power regulation margin of synchronous generators and wind farms, the key control parameters of relative control links are designed to enable them autonomously adjust the active power according to various scenarios to involve in inertia response and primary frequency regulation task. Finally, the effectiveness of the control strategy is verified by the simulation model of LCCHVDC sending-end system with large-scale wind power, which significantly improves the frequency security and stability.

Intelligent Driving Vehicle Trajectory Tracking Control Based on an Improved Fractional‐Order Super‐Twisting Sliding Mode Control Strategy

ABSTRACTAiming at resolving trajectory tracking control challenges during high‐speed lane changes in intelligent driving vehicles, an innovative fractional‐order sliding mode control approach is introduced in the present study. The control strategy comprises upper and lower‐level controls. First, the upper‐level control designs the vehicle trajectory tracking controller, integrating a non‐singular terminal sliding mode (NTSM) surface with a fractional‐order fast super‐twisted sliding mode control (FOF‐STSMC) algorithm. The NTSM surface properties ensure rapid convergence of the system tracking error to zero within a finite time, while the fractional‐order control extends the control system's regulation range and enhances algorithm flexibility. Additionally, the integration with the super‐twisting algorithm effectively mitigates oscillation issues in the control input, achieving a smooth input. Second, the lower‐level control aims to enhance vehicle driving stability. Utilizing the reference yaw rate, and sideslip angle and accounting for tire force saturation, a fractional‐order sliding mode control (FOSMC) algorithm is developed to compute the external yaw moment. Through dynamic load allocation, considering the vertical load for each tire, intelligent external yaw moment distribution significantly improves vehicle stability. Finally, the results of the Carsim–Simulink co‐simulation demonstrate that, compared to the STSMC strategy, the FOSMC strategy with front‐wheel‐only steering, and the linear quadratic regulator (LQR) control strategy, the proposed control strategy in this paper reduces the tracking error by 77%, 61%, and 58%, respectively, achieving more precise and stable trajectory tracking under high‐speed conditions.

Towards non-virtual inertia control of renewable energy for frequency regulation: Modeling, analysis and new control scheme

Currently, when renewable generation participates in frequency regulation, the traditional control method is to emulate synchronous generators through virtual inertia control. However, virtual inertia has a time delay, so essentially, it is a fast power response. Meanwhile, virtual inertia control is likely to be affected by frequency fluctuation since it responds to the derivative of frequency. Hence, it’s worth exploring non-virtual inertia control for renewable energy when participating in frequency regulation. For this reason, a novel two-segment droop control scheme for renewable energy frequency regulation is proposed in this research. Firstly, the extended system frequency regulation (SFR) model, which contains virtual inertia with time delay, is built and analytically solved by order decrement based on the Routh approximation method. Afterwards, according to the analytical solution, time delay affects the frequency response of renewable energy. It can also be analytically proved that the non-virtual inertia control, e.g., sole droop control, could replace virtual inertia under the same frequency deviation. Still, more energy may be needed for frequency regulation. Furthermore, a novel two-segment droop control is presented, and to analytically prove its ability to replace virtual inertia, the impulse function balancing principle and the integration by parts algorithm were adopted to address the initial conditions of the differential equation. Based on the analytical expression, it can be analytically proved that a lower frequency deviation can be obtained under the same frequency regulation energy. Accordingly, a parameter-setting method for two-segment droop control was proposed. Finally, the effectiveness of the proposed method is verified by using a two-area system frequency response model, and the results reveal that it can be used to replace virtual inertia and has better performance.

Adaptive fixed‐time prescribed performance regulation for switched stochastic systems subject to time‐varying state constraints and input delay

AbstractIn this article, the adaptive fixed‐time prescribed performance (FTPP) regulation is investigated for a class of time‐varying state constrained switched stochastic systems with input delay. The time‐varying barrier Lyapunov function and a compensation system are presented, respectively, to deal with the design problems caused by the existence of both time‐varying state constraints and input delay. Some radial basis function neural networks are used to approximate unknown functions, and the common Lyapunov function method is displayed to handle the switched signals. Besides, by designing a fixed‐time prescribed performance function, the desired adaptive neural controller is constructed. Compared with the existing works for state constrained control problem, the FTPP regulation control scheme is first proposed for time‐varying state constrained stochastic switched systems under input delay, and the adaptive dynamic surface control scheme with the nonlinear filter is designed to solve the problem of “explosion of complexity.” Based on the stochastic stability theory, the FTPP of system output is achieved, other system state variables are restricted in the predefined regions, and all signals of this closed‐loop system remain bounded in probability. Finally, the availability of the proposed control scheme is illustrated via two simulation examples.

Study of parabolic trough collector with crucial analysis on controller and estimator with variable mirror efficiency

Solar Thermal Power (STP) plants are a crucial technology for converting solar energy into electricity. Among the STP, the Parabolic Trough Collector (PTC) is one of the integral parts of STP systems for electrical power generation. Maximizing PTC performance is a challenge due to dynamic and unpredictable solar radiation and environmental disturbances, such as cloud cover and dust accumulation. The optical efficiency parameter of the PTC is critical for calculating the desired heat gain, which is difficult to measure in real-time, necessitating sophisticated control and estimation strategies for optimal heat regulation. This study introduces two control mechanisms for the PTC system and comparing their efficacy. A classical PI controller supplemented by Static Feed-Forward (SFF) control demonstrates improved performance with an optimal transfer function model. In contrast, Nonlinear Model Predictive Control (NMPC) excels in disturbance rejection and setpoint tracking, considering operational constraints. The NMPC controller notably outperforms the PI controller with SFF in performance metrics, with the Integral Time Squared Error (ITSE) decreasing by approximately 99% across case studies. Also, in the case of heat gain, NMPC controller exhibits percentage increases when compared to the PI controller. Furthermore, since the measurement of optical efficiency is essential, but due to difficulty in the measurement for various reasons, the estimator is used as a virtual sensor to estimate those optical efficiency. The unmeasured states and parameters, including optical efficiencies of the PTC, are estimated using Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) techniques, with UKF exhibiting superior accuracy. However, considering the average computation time, EKF is preferred for real-time applications.

A Narrative Review of Control Strategies for Blood Glucose Regulation

A Narrative Review of Control Strategies for Blood Glucose Regulation

Participation of wind-storage combined system in the secondary frequency regulation control strategy of power grid

Abstract The secondary frequency modulation of the unit, that is, the automatic generation control (AGC), is the process of increasing or decreasing the power of the power generation unit by the power plant unit according to the dispatching command issued by the power grid dispatching center, and then using the frequency modulator to restore the frequency. Based on the principle of AGC, this paper establishes a frequency dynamic response model of the secondary frequency modulation of the traditional unit and the wind storage participation system including load frequency control (LFC) and traditional proportional-integral-derivative (PID) controllers, determines the frequency modulation control strategy of wind storage, and uses the distribution mode based on Area Control Error (ACE) signal to assist in the secondary frequency modulation. In order to solve the parameter optimization problem of the classical PID controller when the wind-storage combined system participates in the secondary frequency modulation under the large load disturbance, a parameter optimization model of the controller with PID was established, and the ITAE evaluation index was finally selected as the fitness function by comparing different fitness evaluation indexes. To overcome the problem that the conventional Particle Swarm Optimization (PSO) is prone to local extremum, the inertia weights and learning factors are adjusted nonlinearly to balance and optimize the global and local optimization capabilities and improve the search efficiency, and the parameters of the PID controller are optimized by the improved PSO algorithm. The simulation results show that the proposed algorithm improves the secondary frequency modulation effect under the background of a high proportion of renewable energy connected to the power grid.

Acceleration Slip Regulation Control Method for Distributed Electric Drive Vehicles under Icy and Snowy Road Conditions

To achieve a rapid and stable dynamic response of the drive anti-slip system for distributed electric vehicles on low-friction surfaces, this paper proposes an adaptive acceleration slip regulation control strategy based on wheel slip rate. An attachment coefficient fusion estimation algorithm based on an improved singular value decomposition unscented Kalman filter is designed. This algorithm combines Sage–Husa with the unscented Kalman filter for adaptive improvement, allowing for the quick and accurate determination of the road friction coefficient and, subsequently, the optimal slip rate. Additionally, a slip rate control strategy based on dynamic adaptive compensation sliding mode control is designed, which introduces a dynamic weight integral function into the control rate to adaptively adjust the integral effect based on errors, with its stability proven. To verify the performance of the road estimator and slip rate controller, a model is built with vehicle simulation software, and simulations are conducted. The results show that under icy and snowy road conditions, the designed estimator can reduce estimation errors and respond rapidly to sudden changes. Compared to traditional equivalent controllers, the designed controller can effectively reduce chattering, decrease overshoot, and shorten response time. Especially during road transitions, the designed controller demonstrates better dynamic performance and stability.

Dynamic pH regulation drives Nitrosomonas for high-rate stable acidic partial nitritation

How to intensify the ammonia oxidation rate (AOR) is still a bottleneck impeding the technology development for the innovative acidic partial nitritation because the eosinophilic ammonia-oxidizing bacteria (AOB), such as Nitrosoglobus or Nitrosospira, were inhibited by the high-level free nitrous acid (FNA) accumulation in acidic environments. In this study, an innovative approach of dynamic acidic pH regulation control strategy was proposed to realize high-rate acidic partial nitritation driven by common AOB genus Nitrosomonas. The acidic partial nitrification process was carried out in a laboratory-scale sequencing batch moving bed biofilm reactor (SBMBBR) for long-term (700 days) to track the effect of dynamic acidic pH on nitrifying bacterial activity. The results indicated that the influent NH4+-N concentration was about 100 mg/L, the nitrite accumulation ratio was exceeding 90%, and the maximum AOR can reach 14.5 ± 2.6 mg N L−1h−1. Although the half-saturation inhibition constant of NOB (KI_FNA(AOB)) reached 0.37 ± 0.10 mg HNO2N/L and showed extreme adaptability in FNA, the inactivation effect of FNA (6.1 mg HNO2N/L) for NOB was much greater than that of AOB, with inactivation rates of 0.61 ± 0.08 h−1 and 0.06 ± 0.01 h−1, respectively. The effluent pH was gradually reduced to 4.5 by ammonia oxidation process and the periodic FNA concentration reached 6.5 mg HNO2N/L to inactivate nitrite-oxidizing bacteria (NOB) without negatively affecting Nitrosomonas during long-term operation. This result provides new insights for the future implementation of high-rate stabilized acidic partial nitritation by Nitrosomonas.

An Adaptive Multi-Functional Control Strategy for Power Management and Voltage-Frequency Regulation of PV, BESS, and Hybrid Units in a Microgrid

An Adaptive Multi-Functional Control Strategy for Power Management and Voltage-Frequency Regulation of PV, BESS, and Hybrid Units in a Microgrid

Research on Mathematical Model of Energy Storage Assisted Wind Turbine Frequency Regulation Control Strategy

Abstract This paper proposes an improved frequency regulation strategy for the Doubly-Fed Induction Generator (DFIG) to mitigate the impact of wind power integration on system frequency. An energy storage system is used on the wind side to participate in the frequency regulation. The influence of wind power integration on the power system frequency is analyzed and an improved frequency control strategy for the DFIG is proposed. A control strategy for energy storage devices to support wind turbine frequency control is proposed. An energy storage device model is established that considers power correction based on the state of charge to avoid excessive charging and discharging. According to the operating state of the DFIG, a control strategy for the frequency regulation of the energy storage device is proposed. According to different wind speeds, a control strategy is proposed for the participation of the joint wind storage system in the frequency regulation. This control strategy can provide frequency support to the system when the wind turbine cannot participate in frequency regulation according to the different operating conditions of the wind turbine. After the wind turbine uses the improved frequency control strategy, it accelerates the recovery of the DFIG rotor speed while avoiding a secondary drop in the system frequency. In addition, when the energy storage device has a poor state of charge and the system frequency is good, it charges to restore the state of charge.

LQR control strategy for virtual synchronous generator adapted to stiff grid

Virtual synchronous generators (VSG) exhibit good small-signal stability in low short-circuit ratio (SCR) grids. However, the small-signal stability of the grid decreases as its SCRs increase, and there is even a risk of sub-synchronous resonance (SSR). The VSG sequence impedance model considering the frequency coupling effect is developed. The reasons for SSR caused by VSG integration into a stiff grids are analyzed using the sequence impedance analysis method and the Nyquist criterion. To enhance the grid-connected stability of VSG under stiff grids conditions, a linear quadratic regulator (LQR) control strategy with full-state feedback was proposed. The control strategy of LQR can effectively improve the phase margin of VSG output impedance in the low-frequency region, and it also exhibits strong robustness to variations in grid short-circuit ratios. It can also significantly improve the stability margin of the grid-tied system consisting of VSG and stiff grid, and effectively suppress the occurrence of SSR. Finally, the effectiveness and reliability of LQR control strategy are verified by OPAL-RT experimental platform.

Optimal control scheme for multi-terminal high-voltage direct current system to improve robust grid frequency regulations

This paper proposes an optimal control scheme for robust frequency regulation (FR) in power networks that utilize multi-terminal high-voltage direct current (MT-HVDC) systems to interconnect AC grids. The proposed scheme involves the development of a Linear Quadratic Gaussian (LQG) controller to minimize FR in each grid. A state space model of the MT-HVDC grids is derived to design the controller, considering the DC-link voltage and active power controls at the rectifier and inverter, respectively. Additionally, the model incorporates inertia emulation (IE) and droop controllers. Based on the derived state-space model, an LQG controller is designed to achieve optimal frequency control. The stability of the proposed scheme is analyzed through sensitivity and eigenvalue analysis, with a focus on the influence of grid parameters and control gains. Comparative case studies demonstrate that the proposed scheme outperforms conventional strategies in terms of improving the effectiveness and robustness of real-time FR in MT-HVDC grids. The proposed control scheme involves an LQG controller that considers various factors and demonstrates superior performance compared to conventional methods, as supported by comparative case studies.

Wavelet LQR based gain scheduling for power regulation and vibration control of floating horizontal axis wind turbine with double-pitched rotor

This paper introduces a wavelet-based linear quadratic regulator (LQR) control strategy for double-pitched rotor systems of an offshore horizontal axis wind turbines. A comprehensive aero-servo-elastic model incorporating bending-torsion coupling is developed to assess the performance of the proposed controller under combined turbulent wind and wave loading. The weight matrices of the classical LQR algorithm are optimized using a nonlinear optimization scheme. Additionally, frequency-dependent gain scheduling is proposed using wavelet transform where the analytic Morse wavelet serves as the basis function. The resulting LQR algorithm operates in the time-frequency domain and solves scale-dependent Algebraic Riccati equations to determine optimal gains. Numerical simulations demonstrate the superior performance of the proposed gain scheduling compared to the classical LQR approach. The effectiveness of the algorithm is evaluated across various flow conditions and wind-wave misalignment, with benchmark results used for performance comparison.

Integrated control strategy for 5G base station frequency regulation considering spatio-temporal variations in communication load

The decreasing system inertia and active power reserves caused by the penetration of renewable energy sources and the displacement of conventional generating units present new challenges to the frequency stability of modern power systems. Vast quantities of 5G base stations, featuring largely dormant battery storage systems and advanced communication technology, represent a high-quality fast frequency regulation resource for the power system. This paper proposes a double-layer clustering method for 5G base stations and an integrated centralized-decentralized control strategy for their participation in frequency regulation, considering the variability of available frequency regulation capacity due to spatial and temporal variations in base station communication loads. The proposed capacity model and control methods are evaluated using a case study of a two-machine test system with 10,000 real 5G base stations, demonstrating the effectiveness of the clustering method and the integrated control strategy in improving frequency stability.