Power Control Method Research Articles

Feasible Power Control Method with a Low Sampling Frequency for Bidirectional Wireless Power Transfer in Battery-Powered Railway Vehicle Systems

Feasible Power Control Method with a Low Sampling Frequency for Bidirectional Wireless Power Transfer in Battery-Powered Railway Vehicle Systems

Switched Auto-Regressive Neural Control (S-ANC) for Energy Management of Hybrid Microgrids

Switched model predictive control (S-MPC) and recurrent neural networks with long short-term memory (RNN-LSTM) are powerful control methods that have been extensively studied for the energy management of microgrids (MGs). These methods ease constraint satisfaction, computational demands, adaptability, and comprehensibility, but typically one method is chosen over the other. The S-MPC method dynamically selects optimal models and control strategies based on the system’s operating mode and performance objectives. On the other hand, integration of auto-regressive (AR) control with these powerful control methods improves the prediction accuracy and the adaptability of the system conditions. This paper compares the two control approaches and proposes a novel algorithm called switched auto-regressive neural control (S-ANC) that combines their respective strengths. Using a control formulation equivalent to S-MPC and the same controller model for learning, the results indicate that pure RNN-LSTM cannot provide constraint satisfaction. The novel S-ANC algorithm can satisfy constraints and deliver comparable performance to MPC, while enabling continuous learning. The results indicate that S-MPC optimization increases power flows within the MG, resulting in efficient utilization of energy resources. By merging the AR and LSTM, the model’s computational time decreased by nearly 47.2%. In addition, this study evaluated our predictive model’s accuracy: (i) the R-squared error was 0.951, indicating a strong predictive ability, and (ii) mean absolute error (MAE) and mean square error (MSE) values of 0.571 indicate accurate predictions, with minimal deviations from the actual values.

Thermal Stress Analysis and Control Method for Surface Acoustic Wave Atomizer

To prevent the potential failure of the surface acoustic wave (SAW) atomizer caused by the concentration of thermal stresses, this study investigates the thermal elevation process inherent to the operation of the surface wave atomizer. Subsequently, a method for temperature regulation is proposed. By collecting the temperature rise data of SAW atomizers with water, olive oil, and glycerol at 5/6/7 Watts (W) of power, the temperature curves of the atomizer surface under different conditions are obtained, and the stress changes in the working process are simulated additionally. The results indicate that although the stress generated by surface acoustic wave atomizers varies for different media, there is always a problem of rapid heating during the initial working stage in all cases. To address the above issues, this study analyzed the time when the maximum stress occurred and proposed control methods based on experimental data. The simulation results show that by controlling the driving power within 4 s after the start of atomization, the problem of excessive stress during the heating stage can be avoided. Finally, the feasibility of the control method was verified through a simple power control method (limiting the driving power to 3 W in the first 2 s), proving that this method can effectively reduce the thermal stress during the working process of the atomizer and prevent the atomizer from cracking.

Optimal allocation of hybrid energy storage capacity of DC microgrid based on model predictive control algorithm

To effectively enhance the safety, stability, and economic operation capability of DC microgrids, an optimized control strategy for DC microgrid hybrid energy storage system (HESS)(The abbreviation table is shown in Table 2) based on model predictive control theory is proposed. Based on the characteristics of supercapacitors and batteries, system safety requirements, and various constraints, a predictive model for a hybrid energy storage DC microgrid is established. By defining its optimization indicators, designing an energy optimization management strategy, and transforming it into a quadratic programming problem for solution, the reasonable scheduling of power in the DC microgrid has been achieved. In addition, a power control method was proposed for the system without constraints. The simulation experiment results show that at the initial sampling time, the system operates normally, and the MPC algorithm allocates two types of energy storage devices to discharge to meet the net load demand, without absorbing electricity from the external network. At the 30th sampling point, the net load increases, and the MPC controller obtains the optimal solution of the control problem based on the known net load prediction data at the previous sampling time. It outputs the operating reference values of each output unit at the next time. Starting from the 100th to 199th sampling points, SOC UC falls below the lower limit of the safety interval, and the system enters situation 4 mode. The external network output assists the battery in working. At the 131st sampling point, the net load decreases, the system enters Situation 3 mode, and the battery operates independently. Until the 179th point, SOC B was also below the lower limit of its safety interval, and the system entered situation 5 mode, completely maintaining system power balance by external network power. Starting from point 201, the net load becomes negative, and the system charges the HESS according to instructions and stops the external power grid energy transmission. Conclusion: The feasibility and effectiveness of the proposed optimization management strategy have been verified.

A study on quality control check of dose distribution in blood bags irradiated by 137Cs source blood irradiator by using EBT3 radiochromic film dosimetry

In this study, the dose homogeneity in the blood bags delivered by a137Cs blood irradiator is investigated by using EBT3 radiochromic film dosimetry. The dose delivered to blood bags is an important factor for protection to TA-GVHD patients during transfusion in medicine. To do this, the dose results experimentally determined by EBT3 films were then compared with those of a MCNPX simulation in which the irradiation canister containing the blood bags was irradiated with a MSD Gammacell 3000 Elan. In the simulation, two different irradiation situations were modeled; one is the canister full with blood bags and the other is half-full of blood bags. The simulation dose results showed that when the canister was filled fully with blood bags, a dose of 24.4 ± 0.1 Gy was estimated in the canister center line. When the canister was half-full with the bags, a 28.8 ± 0.1 Gy dose was estimated in the canister center line. Whereas the dose of 31.3 ± 0.6 Gy dose was experimentally determined in the canister center line when the canister was filled (3 blood bags) half full. As a result, the dose homogeneity in the irradiated blood bags can easily checked by means of a two-dimensional EBT3 film dosimetry technique. Hence, this study showed that EBT3 film dosimetry is still powerful method for quality control check of dose homogeneity of any blood bags before it was used in patient.

Power Injection and Free Resonance Decoupled Wireless Power Transfer System with Double-Switch

This article presents a type of power injection and free resonance decoupled wireless power transfer (WPT) system, the double-switch independent power injection and free resonance wireless power transfer (IPIFR-WPT) system working in CCM. Based on the stroboscopic mapping model, the theoretical results show that the operation point of the proposed WPT system is determined by itself instead of the switching control strategy. Specifically, once the voltage on the primary capacitance does not decrease to the input voltage in the free-resonance process, the diode in series would not turn on and the system would not switch to the power injection process. Therefore, there is a wide soft-switching margin to ensure the system operating in soft-switching states. Another characteristic of the proposed WPT system is the monotonicity between output power and operation cycle, which presents a simple power control method. And since the soft-switching margin may have intersection under dynamic coupling coefficient, the proposed system maintains soft-switching states with a fixed switching strategy and presents advantage to resist the dynamic change of coupling coefficient. All the characteristics of the proposed WPT system mentioned above have been verified in both theory and experiment.

Special Issue on Monitoring and Diagnostics of Renewable Energy Systems

Concerns about global warming and recent advances in the integration of renewable energy sources into power systems have necessitated the timely need for more powerful control and monitoring methods. The detection and diagnosis of potential to failures, at their onsets, in such power systems would improve their availability thus, increases the generation of clean energy and reduces the carbon footprint. This special issue is devoted to collection of state-of-the-art on modelling, data processing, condition monitoring, and preventive maintenance methods for renewable energy systems, including wind turbines, electric vehicle batteries and solar panels, to enhance their performance and overall effectiveness. The guest editorial would like to thank all the contributing authors for making their research outputs publicly available via this special issue. Thanks also extended to reviewers for their valuable comments for improving the quality of the submitted articles. We also would like to thank the journal’s production teams and editorial board for their assistance with the special issue.

Evaluation of technical and financial benefits of battery energy storage system control strategies

The recent increase in renewable energy generation can balance consumption and reduce carbon emissions. With battery energy storage optimizing supply and demand, it is more important than ever to manage charge control to the benefit of all stakeholders. In this paper, the developed and proposed energy management control methods based on the technical operating criteria of battery energy storage (BESS) and considering self-consumption rate (SCR), self-supply rate (SSR) and curtailment rate are compared in terms of environmental index and economics for daily and annual demand profiles for various household prosumer demand profiles in Istanbul and Antalya. Considering the supply-demand matching based on demand profile, feed-in damping, fixed feed-in, schedule mode, schedule mode with constant charging power and self-consumption control methods are proposed for optimum operation for each prosumer profile. The results show that feed-in damping and fixed feed-in methods can reduce household prosumer costs by up to 22.3% in the daily analysis. Moreover, similar control methods can increase SCR by up to 29.5% and reduce costs by up to 10.62% for higher irradiances in the annual analysis. Proper management of BESS charge control can facilitate sustainable development goals by assisting plans of many stakeholders.

New energy grid connection power control method based on predictive tuning performance and embedded system

Nowadays, due to the cleanliness and high efficiency of grid-connected new energy, it has become more and more popular in the market. However, there are still some problems in grid-connected power control and cannot be well supervised. Therefore, this paper studies a new energy grid-connected power control method based on predictive regulation performance and embedded systems, aiming to control new energy grid-connected power through predictive regulation performance and embedded systems. In this paper, the predictive regulation performance and energy conversion rate of the embedded system new energy grid connection are tested. In the experiment, the energy conversion rate was between 60% and 70%, while the traditional new energy grid connection rate was between 40% and 60%. The maximum power generation efficiency of new energy grid-connected with predictive regulation performance and embedded systems was 83%, while the maximum power generation efficiency of traditional new energy grid-connected was 68%. It can be seen from these experimental results that predictive regulation performance and embedded systems have good effects on new energy grid-connected power control.

Power Mismatches Elimination Strategy for MMC-Based Photovoltaic System and Lightweight Design

For the modular multilevel converter (MMC) based photovoltaic system (MMC-PV), when the sub-modules (SMs) of MMC are connected to distributed photovoltaic (PV), power mismatches between legs and arms is the inherent problem. To eliminate the power mismatches, this article proposes a lightweight MMC-based grid-connected energy router (MGER) integrated PV and energy storage (ES). Large-scale PV and centralized ES are connected to horizontal three SMs through four-terminal dual-active-bridges (FDAB). The primary three full-bridges of which adopts synchronous switching to achieve mismatch power elimination between horizontal SMs, so legs power balance can be realized. In addition, the SMs three-phase symmetrical ripple-power can also cancels each other out under synchronous switching of primary FDAB, so as to achieve low capacitance and lightweight of MGER, and the MMC arms 2nd-order circulating current can be also eliminated from root cause. In this article, the power mismatches analysis, MGER configuration, power mismatches elimination, control method, and lightweight implementation are discussed in detail. Finally, the correctness and effectiveness of proposed scheme are verified by simulation and experiment.

Torque Ripple Reduction of Nonsinusoidal Brushless DC Motor Based on Super-Twisting Sliding Mode Direct Power Control

In this paper, a second-order sliding mode control, based on super-twisting algorithm, is proposed for direct power control of the brushless DC (BLDC) motor. The proposed controller uses a super-twisting scheme that requires only sliding surface information and can handle system uncertainties and external disturbances, well. This scheme can improve the BLDC motor torque ripple by solving the disadvantages of the conventional sliding mode control method, such as the chattering effect and high frequency switching control. This method is simple and robust for the BLDC motor’s biggest challenge, torque ripple, which does not require any voltage and current control loops or complex reference frame transformations. The simulation results of the proposed method are compared with the direct power control (DPC) and model predictive control (MPC) methods, which indicate the superiority of the proposed method in both the steady- and transient-states. Moreover, the motor parameters variation in the tracking of active and reactive power are discussed. In addition, the practical results of the proposed method in both cases of speed and load variation show the effectiveness of this method in reducing power (torque) ripple and current total harmonic distortion (THD) and increasing the system’s efficiency compared to other methods.

A receiver-side power control method for series-series magnetic topology in inductive contactless electric vehicles battery charger application

Wireless power transfer (WPT) can be used to charge the battery conveniently and efficiently. In this paper, the investigation of high-efficiency S/S resonant magnetic topology in inductive wireless battery charging of electric vehicles (EVs) is analyzed, designed, and controlled. To regulate the output power efficiently rather than controlling the supply voltage, novel bidirectional switches are introduced to control the output power by using the duty cycle control method. The output power of the secondary side is derived and discussed based on the fundamental harmonic approximation (FHA) approach. A 1.5 kW, 120 mm distance, and 85 kHz resonance frequency are verified in MATLAB/Simulink.

Adaptive Power Control Method for Distributed Generators in DC Microgrids

The model-free control strategy based on the adaptive observer is presented to manage load power distribution for distributed generators in DC microgrids. By dynamically linearizing the modeling of the microgrid system, the model-free secondary control signal is designed to coordinate the distributed power sources, so that the load power is distributed proportionally to the rated capacity. In addition, the desired output voltage is introduced to restore the system bus voltage. The control scheme cannot depend on the structural details of the object system, which is structurally simple and easily implemented. Finally, the feasibility of the proposed data-driven scheme is demonstrated through case test results based on the RTDS experimental platform.

Maximum Power Control Method for Two-branch Online Energy Extraction System

Aiming at the problem that the fluctuation of the current on the cable causes the change of the parameters in the magnetic core, that is, the excitation inductance and the excitation resistance change, and the energy extraction system cannot maintain the resonance and the maximum power output, an online power extraction method combining the dual branch topology and the resonance power control is proposed. By controlling the PWM rectifier circuit, the load impedance is changed so that it is always equivalent to the matching impedance of CT. The parallel resonance state is maintained when the transmission line current changes in a wide range, so that more active power flows to the energy-taking branch to achieve the maximum energy-taking power and assure the normal operation of the energy source. The correctness of the proposed method is verified by Maxwell/Simulink software simulation.

A safe power controlling method for a phase-shift migration inverter to drive a high-power ultrasonic transducer.

The aim of this work is to investigate and analyze the operation mechanism and power control principle of a bolted Langevin type (BLT)-loaded phase-shifted control inverter and to find a safe power control method for a phase-shifted control inverter used to drive a high-power BLT by preventing the differential current (shock current) from occurring in the right branches of a phase-shifted full-bridge circuit. In this paper, by allowing the inverter operating frequency to operate under inductive loads that coincide with the zero points of voltage and current rather than the resonant frequency of the BLT, which results in the generation of a shock current in the right branch of the full-bridge circuit, the switches of the right-branch also enabled zero-voltage, zero-current switching on (ZVZCS turn-on). The proposed method can fundamentally eliminate the generation of shock current by realizing ZVZCS turn-on on the right-branch switch elements of the inverter. The phase-shift angle control limit for power control by this scheme is 90° and the power control range is 20%-100%.

Research on the overvoltage suppression strategy of single-phase photovoltaic grid-connected systems based on FCS-MPDPC

For the overvoltage problem brought by the access of high-penetration photovoltaic power plants to the low-voltage distribution network, this paper chooses to deal with it by using the reactive power regulation capability of photovoltaic power plant inverters, which reduces the equipment investment in distribution line voltage regulation. Based on the reactive power regulation theory of the inverter, a finite set model predictive direct power control method is proposed by constructing a virtual voltage vector, taking a single-phase cascaded 2H bridge grid-connected inverter as an example, to realize independent control of active and reactive power. By setting different power reference values, the inverter can be made to have two functions: grid-connected per-unit power factor and reactive power control during overvoltage. Finally, the two modes of inverter operation are verified by Simulink simulation, and the verification by example shows that the method can limit the grid-connected voltage deviation to within 7% and meet the requirements of grid-connected regulations.

Tracking Photovoltaic Power Output Schedule of the Energy Storage System Based on Reinforcement Learning

The inherent randomness, fluctuation, and intermittence of photovoltaic power generation make it difficult to track the scheduling plan. To improve the ability to track the photovoltaic plan to a greater extent, a real-time charge and discharge power control method based on deep reinforcement learning is proposed. Firstly, the photovoltaic and energy storage hybrid system and the mathematical model of the hybrid system are briefly introduced, and the tracking control problem is defined. Then, power generation plans on different days are clustered into four scenarios by the K-means clustering algorithm. The mean, standard deviation, and kurtosis of the power generation plant are used as the features. Based on the clustered results, the state, action, and reward required for reinforcement learning are set. In the constraint conditions of various variables, to increase the accuracy of the hybrid system for tracking the new generation schedule, the proximal policy optimization (PPO) algorithm is used to optimize the charging/discharging power of the energy storage system (ESS). Finally, the proposed control method is applied to a photovoltaic power station. The results of several valid experiments indicate that the average errors of tracking using the Proportion Integral Differential (PID), model predictive control (MPC) method, and the PPO algorithm in the same condition are 0.374 MW, 0.609 MW, and 0.104 MW, respectively, and the computing time is 1.134 s, 2.760 s, and 0.053 s, respectively. The consequence of these indicates that the proposed deep reinforcement learning-based control strategy is more competitive than the traditional methods in terms of generalization and computation time.

Fully-Decoupled Radio Access Networks: A Resilient Uplink Base Stations Cooperative Reception Framework

To cope with the even more urgent spectrum and energy efficiency challenge for trillion-level terminal access and data uploading in the next generation mobile communication network (6G), in this paper, we investigate the uplink transmission in an original fully-decoupled radio access networks (FD-RAN) architecture. Specifically, we propose a resilient uplink base station cooperative reception framework in FD-RAN, which is a large-scale fading based two-tier signal combination approach for the uplink transmission, including the localized signal combination at the base station and centralized signal combination at the edge cloud, respectively. Then, we formulate a weighted sum-rate maximization problem for the uplink transmission optimization, and decompose it into two subproblems. A spectrum-efficiency maximized virtual service cluster selection (SEMVS) algorithm is designed by leveraging the channel statistical information for solving subproblem one, and a fractional programming based power control (FPPC) algorithm is introduced for the power optimization of subproblem two. Compared to the typical RAN architectures with corresponding access and power control methods, simulation results demonstrate the significant performance improvements of uplink FD-RAN with the proposed solution.

Power-Compensated Triple-Vector Model Predictive Direct Power Control Strategy for Nonredundant Fault-Tolerant Rectifiers

A power compensated triple-vector model predictive direct power control (PCTV-MPDPC) strategy is proposed in this paper for non-redundant fault-tolerant three-phase rectifiers. The system fault tolerance ability and post-fault control performance are enhanced with low hardware complexity. By defining the negative conjugate of complex power as the control variable, a straight-forward pattern of power-voltage relationship analysis is obtained. Besides, a novel voltage vector selection method is put forward based on the location of the error vector between the reference and real control variables. The sector identification process can be omitted to derive a unified expression for duty ratio calculation. On top of that, an intuitive power compensation architecture is proposed to eliminate the dc-bus voltage deviation so that its utilization rate can be maximized. With the proposed PCTV-MPDPC strategy, the power ripples and input current harmonics can be significantly reduced. Superior steady-state and dynamic performance can be achieved compared with the conventional finite-control-set MPDPC (FCS-MPDPC) scheme and a recently proposed multiple-vector model predictive power control (MV-MPPC) method, along with excellent dc-bus voltage deviation suppression effect. Furthermore, simulation validation in Matlab/Simulink and experimental verification on a four-switch three-phase rectifier are carried out to demonstrate the effectiveness of the proposed PCTV-MPDPC strategy.

Adaptive Coordination Control Based on Alkaline Water Electrolyzers and Battery Driven by Wind Power

With the widespread use of clean energy sources, there has been a growing interest in obtaining green and pure hydrogen from wind power. However, wind energy is characterized by randomness and volatility, which results in a low grid connection rate for wind turbines and makes it difficult to integrate wind energy into the power grid. In this context, this article proposes an adaptive coordinated control strategy considering the wind turbine, alkaline electrolyzer, battery, and local loads. Using the DC bus voltage as the connecting signal, adaptive power control and voltage control methods are developed for the wind turbine, energy storage battery, and electrolyzer to achieve power matching in the system. Finally, the proposed research results are validated through Matlab/Simulink simulation module.