Power Control Method Research Articles

Robust Direct Power Control of Three-Phase PWM Rectifier with Mismatched Disturbances

To effectively eliminate the impacts of both matched and mismatched power disturbances in a three-phase PWM rectifier, this paper proposes a robust direct power control (RDPC) method with a single-loop control structure. Firstly, a nonlinear power model of the three-phase PWM rectifier is established. Then, using the exact feedback linearization method, a linearized power model including matched and mismatched power disturbances is derived and achieves the decoupling of active and reactive power. Secondly, to regulate the DC bus voltage, a sliding-mode controller (SMC) combined with a nonlinear disturbance observer (NDO) is proposed. The proposed SMC combined with an NDO (SMC + NDO) method features a single-loop control structure, which enables a faster response and simpler structure compared to the dual-loop DPC method. By incorporating estimated mismatched power disturbance into the sliding-mode surface, it overcomes the SMC’s defect in incompletely suppressing mismatched disturbances and enables the simultaneous regulation of voltage and active power. Additionally, it effectively reduces sliding-mode chattering. To regulate reactive power, a sliding-mode controller based on the exponential convergence law is designed to suppress matched reactive power disturbances. Finally, the simulation and experimental comparative results demonstrate that the proposed controller exhibits stronger robustness against matched and mismatched power disturbances, as well as a better performance under the constant power load (CPL).

Deployment Protection for Interference of 5G Base Stations with Aeronautical Radio Altimeters.

In this manuscript, we present a novel deployment protection method aimed at safeguarding aeronautical radio altimeters (RAs) from interference caused by fifth-generation (5G) telecommunication base stations (BSs). Our methodology involves an integrated interference model for defining prohibited zones and utilizes power control and angle shutoff methods to mitigate interference. First, to ensure reliable protection, we define both horizontal and vertical prohibited zones and investigate their variations to immunize RA against 5G interference. Second, we validate the effectiveness of the model in various operational scenarios, analyzing the influence of factors such as base station types, antenna parameters, flight altitude, and aircraft attitudes to cover a wide range of real-world scenarios. Third, to mitigate interference, we propose and analyze the power control and angle shutoff methods through simulation for the RMa prohibited zone. Our results demonstrate the efficacy of the deployment protection method in safeguarding RAs from 5G interference, providing guidance for interference protection during civil aviation operations and base station deployment near airports.

Composing MPC With LQR and Neural Network for Amortized Efficiency and Stable Control

Model predictive control (MPC) is a powerful control method that handles dynamical systems with constraints. However, solving MPC iteratively in real time, i.e., implicit MPC, remains a computational challenge. To address this, common solutions include explicit MPC and function approximation. Both methods, whenever applicable, may improve the computational efficiency of the implicit MPC by several orders of magnitude. Nevertheless, explicit MPC often requires expensive pre-computation and does not easily apply to higher-dimensional problems. Meanwhile, function approximation, although scales better with dimension, still requires pre-training on a large dataset and generally cannot guarantee to find an accurate surrogate policy, the failure of which often leads to closed-loop instability. To address these issues, we propose a triple-mode hybrid control scheme, named Memory-Augmented MPC, by combining a linear quadratic regulator, a neural network, and an MPC. From its standard form, we derive two variants of such hybrid control scheme: one customized for chaotic systems and the other for slow systems. The proposed scheme does not require pre-computation and is capable of improving the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">amortized</i> running time of the composed MPC with a well-trained neural network. In addition, the scheme maintains closed-loop stability with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">any</i> neural networks of proper input and output dimensions, alleviating the need for certifying optimality of the neural network in safety-critical applications. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article was motivated by the need to reduce the amortized cost of MPC in repetitive industrial robotic applications, where long-term operational cost is important and safety is critical. Examples of such applications include factory robotic arm manipulation and fixed-route quadcopter payload transport. Unlike explicit MPC or function approximation, our approach does not require any pre-computation or pre-training. Rather, it attains task proficiency over time by learning a surrogate neural network on the spot and by gradually replacing the costly MPC with the more efficient surrogate model so long as safety permits. Consequently, the proposed scheme incurs a learning cost during the initial phase of the deployment but usually becomes more adept on the task afterwards, leading to amortized efficiency.

High-Speed Controller to Enhance Responsiveness and Stability of Dynamic Characteristics for DC–DC Converter

In general, the DC load is electrically sensitive to the input voltage and current compared to the AC load. As the demand for digital systems that require DC power increases rapidly, the importance of stable DC power supply methods is increasing. Various elements such as renewable energy and load are configured in the power grid that supplies DC, and they are connected in various forms and power patterns. These elements have different starting and operating characteristics, which can be disadvantageous to the design of controllers for power converters to maintain a stable bus voltage in the DC power grid. Therefore, in a DC power system, an energy storage system with active bi-directional power control technology that can minimize transient conditions, such as overshoot, which can occur when a load is connected or power accelerates rapidly, is significantly important. This paper proposes a novel power control method capable of compensating for the instability of the DC bus voltage owing to the transient state in the DC power supply system. This method minimizes overshoot and ensures fast responsiveness and system stability by calculating the flux linkage of an inductor in a bi-directional DC/DC converter and applying an excitation voltage without pulse-width modulation (PWM) switching. The performance and validity of the proposed transient high-speed controller (THSC) were verified through simulations and experiments.

Direct power control of dual three-phase permanent magnet synchronous motor based on multiple vectors

In response to the traditional mode of dual three-phase permanent magnet synchronous generator switch form vector direct power control (DPC), the current harmonics are large, the active (P) and reactive (Q) harmonic oscillations are large, and the unstable losses of each phase current are large. A virtual voltage vector direct power control method based on duty cycle modulation is proposed. This method compares and synthesizes the two vectors of the outermost and second layers of the PWM rectifier, as well as three large vector synthesis methods, to obtain 12 new virtual voltage vectors. Then, the combined voltage vector is directly modulated into the deadbeat switching table, and the optimal predicted vector value is calculated based on the principle of the deadbeat formula, further suppressing the problem of large fluctuations in active and reactive power. Results show that the proposed multi-vector composite odd even quadrant DPC can effectively reduce current harmonics and power ripple, make the phase current more stable, reduce motor operating losses, and significantly improve the motor.

Power screw-assisted reconfigurable reflective metasurface with spatial modulation

Reconfigurable reflective metasurfaces (RRMs) have garnered significant attention due to their capability to control reflection characteristics. While conventional metasurfaces manipulate the phase and amplitude of the reflected beam through the arrangement of sub-wavelength scatterers in a periodic array, achieving dynamic manipulation typically necessitates external stimuli. Alternatively, spatial modulation within a metasurface introduces gaps in the metastrips, enabling a spatial phase shift across the reflected beam and facilitating real-time beam steering and shaping. This paper proposes a novel power screw-assisted reconfigurable reflective metasurface for achieving beam control and spatial modulation. The design integrates a power screw into the metasurface structure, providing controlled displacement and continuous beam scanning capabilities. Experimental results demonstrate that the proposed metasurface can scan from ±32° to ±15° at 28 GHz. Unlike current designs requiring complex external control systems for beam scanning, this approach offers a simpler yet powerful method for real-time control of the reflected beam. The novelty of this work lies in the integration of the power screw mechanism, presenting a promising advancement in the field of reconfigurable reflective metasurfaces with potential applications in communication systems, energy harvesting, and adaptive optics.

Integrated Active and Reactive Power Control Methods for Distributed Energy Resources in Distribution Systems for Enhancing Hosting Capacity

Recently, there has been a significant increase in the integration of distributed energy resources (DERs) such as small-scale photovoltaic systems and wind turbines in power distribution systems. When the aggregated outputs of DERs are combined, excessive reverse current may occur in distribution lines, leading to overvoltage issues and exceeding thermal limits of the distribution lines. To address these issues, it is necessary to limit the output of DERs to a certain level, which results in constraining the hosting capacity of DERs in the distribution system. In this paper, coordination control methodologies of DERs are developed and executed to mitigate the overvoltage and overcurrent induced by DERs, thereby increasing the hosting capacity for DERs of the distribution system. This paper proposes three coordinated approaches of active and reactive power control of DERs, namely Var Precedence, Watt Precedence, and Integrated Watt and Var Control. The Var and Watt Precedence prioritizes reactive power for voltage (Q–V) and active power for current (P–I) to address network congestion, thereby enhancing hosting capacity. Conversely, the Integrated Var and Watt Precedence propose a novel algorithm that combines four control indices (Q–V, P–V, Q–I, and P–I) to solve network problems while maximizing hosting capacity. The three proposed methods are based on the sensitivity analysis of voltage and current to the active and reactive power outputs at the DER installation locations on the distribution lines, aiming to minimize DER active power curtailment. Each sensitivity is derived from linearized power equations at the operating points of the distribution system. To minimize the computation burden of iterative computation, each proposed method decouples active and reactive power and proceeds with sequential control in its own unique way, iteratively determining the precise output control of distributed power sources to reduce linearization errors. The three proposed algorithms are verified via case studies, evaluating their performance compared to conventional approaches. The case studies exhibit superior control effectiveness of the proposed DER power control methods compared to conventional methods when issues such as overvoltage and overcurrent occur simultaneously in the distribution line so that the DER hosting capacity of the system can be improved.

Collaborative Control of Reactive Power and Voltage in a Coupled System Considering the Available Reactive Power Margin

This article proposes a hierarchical collaborative reactive power and voltage control method aimed at meeting the internal voltage requirements of a coupled system composed of centralized new energy stations such as wind and solar power and traditional thermal power units, with particular attention paid to the reactive power regulation ability of power units in new energy stations. This method is implemented in two layers: At the transmission layer, the overall reactive power compensation capacity of thermal power units and stations on the transmission lines within the system is determined according to the engineering requirements of different node voltages in the coupled system, the regulation voltages of the high-voltage grid-connected points and the point of common coupling (PCC) of the stations are found, and the actual regulation voltages of the PCCs of the stations are given as commands. At the station layer, based on determining reactive power distribution between power units and continuous reactive power compensation devices within each station, voltage optimization is carried out using the voltage command issued by the transmission layer as a reference. At the same time, consistency coordination between the transmission layer and the station layer is achieved based on the Analytical Target Cascading (ATC) method at different layers. Finally, simulation analysis was conducted on a regional coupled system in Dalian. The results showed that the method proposed in this paper can effectively control the voltage safety requirements of each region and PCC in the coupled system and, to some extent, improve the economic efficiency of system operation.

Distributed Computation Offloading and Power Control for UAV-Enabled Internet of Medical Things

The advancement of the Internet of Medical Things (IoMT) has led to the emergence of various health and emotion care services, e.g., health monitoring. To cater to increasing computational requirements of IoMT services, Mobile Edge Computing (MEC) has emerged as an indispensable technology in smart health. Benefiting from the cost-effectiveness of deployment, unmanned aerial vehicles (UAVs) equipped with MEC servers in Non-Orthogonal Multiple Access (NOMA) have emerged as a promising solution for providing smart health services in proximity to medical devices (MDs). However, the escalating number of MDs and the limited availability of communication resources of UAVs give rise to a significant increase in transmission latency. Moreover, due to the limited communication range of UAVs, the geographically-distributed MDs lead to workload imbalance of UAVs, which deteriorates the service response delay. To this end, this paper proposes a UAV-enabled Distributed computation Offloading and Power control method with Multi-Agent, named DOPMA, for NOMA-based IoMT environment. Specifically, this paper introduces computation and transmission queue models to analyze the dynamic characteristics of task execution latency and energy consumption. Moreover, a credit assignment scheme-based reward function is designed considering both system-level rewards and rewards tailored to each MD, and an improved multi-agent deep deterministic policy gradient algorithm is developed to derive offloading and power control decisions independently. Extensive simulations demonstrate that the proposed method outperforms existing schemes, achieving \(7.1\% \) reduction in energy consumption and \(16\% \) decrease in average delay.

Wind turbine emulator using three-phase IM controlled through an adaptive reactive power estimator fed by soft-VSI topology

PurposeThe purpose of this paper aims to design a robust wind turbine emulator (WTE) based on a three-phase induction motor (3PIM).Design/methodology/approachThe 3PIM is driven by a soft voltage source inverter (VSI) controlled by a specific space vector modulation. By adjusting the appropriate vector sequence selection, the desired VSI output voltage allows a real wind turbine speed emulation in the laboratory, taking into account the wind profile, static and dynamic behaviors and parametric variations for theoretical and then experimental analysis. A Mexican hat profile and a sinusoidal profile are therefore used as the wind speed system input to highlight the electrical, mechanical and electromagnetic system response.FindingsThe simulation results, based on relative error data, show that the proposed reactive power control method effectively estimates the flux and the rotor time constant, thus ensuring an accurate trajectory tracking of the wind speed for the wind emulation application.Originality/valueThe proposed architecture achieves its results through the use of mathematical theory and WTE topology combine with an online adaptive estimator and Lyapunov stability adaptation control methods. These approaches are particularly relevant for low-cost or low-power alternative current (AC) motor drives in the field of renewable energy emulation. It has the advantage of eliminating the need for expensive and unreliable position transducers, thereby increasing the emulator drive life. A comparative analysis was also carried out to highlight the online adaptive estimator fast response time and accuracy.

High order sliding mode observer-based fault-tolerant control scheme for DFIG in wind energy applications with model predictive controller

This research presents a novel fault-tolerant predictive power control method for a Doubly-fed induction generator (DFIG) used in wind turbine control systems. Due to the proposed control mechanism, the system can continue to function effectively despite open-circuit or short-circuit faults in the insulated-gate bipolar transistors (IGBTs) of the MPC controller. Depending on the type of problem and its location, the tolerant IGBT overcomes power oscillations and limits the power converter's potential switching states. By monitoring the optimal generator speed, wind turbine control systems strive to maximize power output. For wind turbines operating in the partial-load area, a fault-tolerant model predictive control strategy is recommended in order to achieve control goals despite disturbances, uncertainties, sensor, and actuator difficulties. A high order sliding mode observer (HOSMO) is used to evaluate both the actual states and sensor-faults at the same time. A high order sliding mode (HOSM) control strategy based on the MPC controller is used to regulate the speed of wind turbines in order to harness the wind's maximum power.

A New Thermal Management Strategy of IGBT in DFIG for Economic Benefit Maximization

Wind speed fluctuation generally shortens the lifetime of the insulated gate bipolar transistor (IGBT) module in the doubly fed induction generator (DFIG), which leads to frequent component replacement and cost increase of wind power generation. Conventional power control strategies consider solely the wind turbine output power maximization, and existing junction temperature thermal management strategies focus on IGBT lifetime extension, both of which are not effective under turbulent wind speed conditions and ignore the trade-off between the device reliability and output power for the overall DFIG economic benefit. To bridge the gap between the IGBT reliability and the output power under turbulent wind speed conditions, we propose a novel IGBT thermal management strategy for optimal economic benefit. Specifically, we first smooth the output power through a linear power control (LPC) method with conditions on the wind speed and turbine speed to reduce the IGBT low-frequency junction temperature fluctuation, which extends IGBT lifetime. We then propose a grid encirclement and suppression search (GESS) method that maximizes the economic benefit defined by LPC-smoothed output power and IGBT lifetime. Simulation shows that our proposed LPC-GESS strategy outperforms a competing strategy at economic benefit by a large margin, up to 15.3%. Our proposed strategy can potentially be used in wind power stations for fast and reliable economic benefit-oriented IGBT thermal management.

Voltage Drop Compensation Technology for High-Voltage and High-Power DC Energy Storage Power Supply System

This paper presents an output voltage drop compensation technology for high-voltage and high-power DC energy storage system (DC-ESS). This technology is used to improve the output voltage stability of high-voltage high-power DC-ESS in high rate discharge. The proposed output voltage drop compensation technology includes an ESS architecture and a corresponding control method. The proposed ESS architecture adopts DC dynamic voltage regulator (DC-DVR) to compensate for output voltage drop. DC-DVR adopts 6-phase interleaved parallel buck converter. This architecture not only maintains the system output voltage stability, but also reduces the system cost. Moreover, the proposed ESS architecture does not change the original energy storage capacity. The dynamic power flow of the proposed ESS architecture is analyzed and a direct power control method based on full response power compensation is proposed. The steady-state power and dynamic power of the proposed ESS architecture are compensated respectively, so that the input power can quickly track the change of the output power. The proposed control method improves the stability and dynamic response speed in the system dynamic process. Simulation and experiment verify the effectiveness of the proposed ESS architecture and control method.

Model Predictive Based Direct Power Control Method Using Switching State Preference for Independent Phase Loss Decrease of Three-Phase Pulsewidth Modulation (PWM) Rectifiers

Model Predictive Based Direct Power Control Method Using Switching State Preference for Independent Phase Loss Decrease of Three-Phase Pulsewidth Modulation (PWM) Rectifiers

An Energy-Feed Type Split-Capacitor Three-Phase Four-Wire Power Electronic Load Compatible with Various Load Demands

Energy-feed power electronic loads can precisely control the phase and magnitude of the power supply output current, achieving the emulation of loads. Moreover, they can feed energy back to the grid for energy regeneration, demonstrating significant research value. This article proposes an energy-fed power electronic load topology and control method that can realize the static and dynamic simulation of linear and non-linear loads and take into account the simulation needs of single-phase, three-phase three-wire, and three-phase four-wire loads. The main circuit uses a two-stage back-to-back AC/DC/AC structure: the front side is a three-phase four-wire split capacitor PWM rectifier bridge, which is used to simulate loads under various operating conditions; the back side is a three-phase three-wire PWM inverter bridge, which realizes the energy feeding back to the grid and reduces the waste of energy; and the intermediate side uses a split capacitor to equalize the voltage and achieve voltage stabilization. The topology is analyzed under the simulation demands of three-phase balanced, three-phase unbalanced, single-phase and non-linear loads. Finally, a MATLAB(R2022a)/Simulink simulation platform is built for a power electronic load with a rated capacity of 200 kVA. The simulation results verify the effectiveness, feasibility, and advancement of the power electronic load proposed in this article.

Reactive power optimization control for multi-energy system considering source-load uncertainty

Reactive power control in power systems is an important way to ensure stable system operation. However, as the coupling between multi-energy systems increases, the uncertainty of supply and demand in the power system poses new challenges for reactive power control. Therefore, the main objective of this study is to perform reactive power balance control of the grid in a multi-energy system. Firstly, we studied the characteristics of reactive power demand during the energy transport of a multi-energy system. In addition, we studied the reactive power output characteristics of various power sources and their uncertainties. The reactive power balance of the multi-energy system and its uncertainty model are established. Then, we studied the adjustable pressure limits of the energy medium transmission pipelines of the heat supply network and the gas pipeline network. The reactive power demand capacity of the system is determined according to the system's energy condition and safe operation boundary. Finally, we established a reactive power optimization simulation model of the multi-energy system, considering the heat-gas network constraints. The study proposes that the optimal reactive power control method can improve the voltage stability of the multi-energy system.

Multi-UAV Airborne UV Area Coverage and Task Assignment Method

To address the area coverage problem in large-scale reconnaissance and detection tasks, Unmanned Aerial Vehicles(UAVs) utilize Ultraviolet(UV) light for flight guidance. Additionally, a UV light power control method is implemented to assist UAVs in adapting to various terrains. Based on the flight characteristics of quadrotor UAVs, the target area is divided into a grid-like format. This transformation helps convert the area coverage task into a multi-UAV path planning problem on a raster map. To address this, constraints are established for assigning tasks to multiple UAVs. An algorithm is proposed to assign the target area uniformly based on the initial position of the UAV, ensuring full coverage. Additionally, the algorithm considers the differences in endurance among multiple UAVs. This improved algorithm is highly suitable for real-life application scenarios. The simulation results demonstrate the power control changes in wireless UV-guided UAV flight. Moreover, the assignment results of the improved algorithm align closely with the theoretical assignment results, considering different parameters like the number of UAVs, initial position, and endurance capacity.

Learning-based model predictive energy management for fuel cell hybrid electric bus with health-aware control

Advanced energy management strategy (EMS) can ensure healthy, stable, and efficient operation of the on-board energy systems. Model Predictive Control (MPC) and Deep Reinforcement Learning (DRL) are two powerful control methods that have been extensively researched in the field of vehicle energy management. However, there are some problems with both approaches. On the one hand, MPC is difficult to cope with the complex systems and the excessive computational load caused by the non-linear solving over long prediction horizon, on the other hand, DRL lacks adaptability to different driving conditions and is poorly interpretable. Therefore, this paper innovatively proposes a learning-based model predictive (L-MPC) EMS for fuel cell hybrid electric bus (FCHEB) with health-aware control. This method effectively merges the advantages of control theory and machine learning. Specifically, firstly, the precise aging models for vehicular energy systems are established and incorporated into the optimization framework along with hydrogen consumption related metrics. Secondly, the principles of the learning-based MPC algorithm are thoroughly elucidated. In addition, to ensure driving details under future conditions, a speed predictor based on a double-layer Bi-directional Long Short-Term Memory (BiLSTM) is proposed at the strategy supervision layer. Finally, the superiority of the proposed strategy in prolonging the lifespan of the energy systems and reducing overall vehicle operating cost is verified by comprehensive comparisons with state-of-the-art MPC and DRL methods under real-world collected driving condition.

A Three-Coil Constant Output Wireless Power Transfer System Based on Parity–Time Symmetry Theory

In a three-coil wireless power transfer system with relay coils, the transmission efficiency and output power of the system decreases with changes in the adjacent coupling coefficients. Controlling the power of three-coil wireless power transfer systems is also a significant challenge. To solve these issues, a three-coil wireless power transfer system based on parity–time symmetry is proposed in this paper. First, a three-coil parity–time wireless power transfer system was modeled based on a circuit model. Then, the transmission and gain characteristics of the three-coil parity–time wireless power transfer system were analyzed. It was found that when the system is in a parity–time-exact region, it can maintain a constant transmission efficiency and output power, and its output power is independent of the coupling coefficient. In addition, based on the output characteristics of the three-coil parity–time wireless power transfer system, a power control method and a working range detection method were proposed to attain a constant power output. Finally, a three-coil parity–time wireless power transfer system was experimentally tested.

Base Station Dataset-Assisted Broadband Over-the-Air Aggregation for Communication-Efficient Federated Learning

This paper proposes an over-the-air aggregation framework for federated learning (FL) in broadband wireless networks where not only edge devices but also a base station (BS) has its own local dataset. The proposed framework leverages the BS dataset to improve communication efficiency of FL by reducing the number of channel uses required for the model convergence as well as avoiding the signaling overhead incurred by power scale coordination among edge devices. We analyze the convergence to a stationary point without convexity assumption on the objective function. The analysis result reveals that the utilization of BS dataset improves the convergence rate and the update distortion caused by the limited power budget is a crucial factor hindering the model convergence. To facilitate the convergence, we develop an optimized power control method by solving the distortion minimization problem without assumptions on power scale coordination and global CSI at BS. Our simulation results validate that BS dataset is beneficial to reducing the number of channel uses for the model convergence and the developed power control method outperforms the conventional method in terms of both convergence rate and converged test accuracy. Furthermore, we identify some scenarios where the compression of local update can be helpful to reduce communication resources for model training.