Power Transfer System Research Articles

Joint beamforming design for STAR-RIS-assisted integrated sensing, communication, and power transfer systems

In the sixth-generation network, many low-power devices are predicted to be integrated into tasks incorporating communication and sensing. The integrated sensing and communication (ISAC) technology reuses a wireless signal for data transfer and radar sensing. Furthermore, wireless signals have the capacity to transmit energy, allowing for the simultaneous wireless information and power transfer (SWIPT). To enhance spectrum utilization, the deeper integration of SWIPT and ISAC has opened up novel investigate directions for integrated sensing, communication, and power transfer (ISCPT). This paper investigates a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) supported ISCPT system that solves the problem of traditional RIS not achieving full space wireless signal coverage. In particular, since the serious path loss issue of sensing, we propose a novel architecture for installing dedicated sensors on STAR-RIS. Under this setting, we jointly optimized the passive beamforming at STAR-RIS and the active beamforming at base station to minimize the Cramér-Rao bound (CRB) used to estimate the sensing target's two-dimensional direction of arrivals, while being constrained by the lowest signal-to-interference-plus-noise-ratio (SINR) of communication users (CUs), the lowest energy harvesting (EH) of energy users (EUs), and the maximum transmission power at base station. For complex non-convex problems, a proposed two-layer cyclic algorithm utilizes penalty dual decomposition (PDD) and block coordinate descent (BCD). Finally, the numerical outcomes verify the efficacy of our suggested design, which reveals the performance trade-off between communication, power transmission and sensing. Furthermore, compared to traditional RIS, the estimated CRB of this design is lower.

Enhanced Coil Design for Inductive Power-Transfer-Based Power Supply in Medium-Voltage Direct Current Sensors

This paper presents an integrated coil design method for inductive power-transfer (IPT) systems. Because a medium-voltage direct current (MVDC) distribution network transmits power at relatively high voltages (typically in the tens of kV), accurate fault diagnosis using high-performance sensors is crucial to improve the safety of MVDC distribution networks. With the increasing power consumption of high-performance sensors, conventional power supplies using optical converters with 5 W-class output characteristics face limitations in achieving the rated output power. Therefore, this paper proposes a safe and reliable power supply method using the principle of IPT to securely maintain the insulation distance between the distribution network and the current sensor-supply line. A 100 W prototype IPT system is investigated, and its feasibility is validated by comparing its performance with conventional optical converters.

A SHEPWM-based wireless information and power transfer system using a single inverter

A SHEPWM-based wireless information and power transfer system using a single inverter

Optimizing energy harvesting with diversity in cooperative simultaneous wireless information and power transfer systems

SummaryRadio frequency (RF) energy harvesting (EH) for wireless networks provides a green and sustainable solution and offers an energy‐efficient system. It is most crucial for fulfilling the power requirement of the rising number of low‐powered wireless devices and achieving sustainable development goals (SDG). It ensures the longevity of devices in the network even at inaccessible remote locations. Such RF‐EH‐based mechanisms are utilized in simultaneous wireless information and power transfer (SWIPT) systems. Most of the prevailing studies have analyzed the SWIPT system over conventional fading channels. However, due to the higher rate requirements, the current paradigm shift in frequency usage shifts towards the GHz band, which also offers better EH efficiency. Hence, SWIPT system analysis over the channel that is suitable for mm‐wave signal propagation is dealt with in this study. This study evaluates SWIPT performance over fluctuating two‐ray (FTR) fading channel that is crucial since it provides the best fit for characterizing GHz signal and also provides a generalized framework for most of the conventional fading channels. This study presents new analytical results assuming time switch relaying (TSR) protocol with (i) amplify and forward (AF) and (ii) decode and forward (DF) relaying. The results are also analyzed for H branches maximal ratio combining (MRC) diversity technique and evaluated the diversity gain for both AF and DF relays. The effectiveness of the system is measured in terms of system outage probability (SOP) to envisage the reliability of SWIPT based system. This work presents the simulation and modeling of such system and its obtained results are validated by Monte Carlo simulations for their accuracy.

Waveform Design for the Integrated Sensing, Communication, and Simultaneous Wireless Information and Power Transfer System.

Next-generation communication systems demand the integration of sensing, communication, and power transfer (PT) capabilities, requiring high spectral efficiency, energy efficiency, and low cost while also necessitating robustness in high-speed scenarios. Integrated sensing and communication systems (ISACSs) exhibit the ability to simultaneously perform communication and sensing tasks using a single RF signal, while simultaneous wireless information and power transfer (SWIPT) systems can handle simultaneous information and energy transmission, and orthogonal time frequency space (OTFS) signals are adept at handling high Doppler scenarios. Combining the advantages of these three technologies, a novel cyclic prefix (CP) OTFS-based integrated simultaneous wireless sensing, communication, and power transfer system (ISWSCPTS) framework is proposed in this work. Within the ISWSCPTS, the CP-OTFS matched filter (MF)-based target detection and parameter estimation (MF-TDaPE) algorithm is proposed to endow the system with sensing capabilities. To enhance the system's sensing capability, a waveform design algorithm based on CP-OTFS ambiguity function shaping (AFS) is proposed, which is solved by an iterative method. Furthermore, to maximize the system's sensing performance under communication and PT quality of service (QoS) constraints, a semidefinite relaxation (SDR) beamforming design (SDR-BD) algorithm is proposed, which is solved using through the SDR technique. The simulation results demonstrate that the ISWSCPTS exhibits stronger parameter estimation performance in high-speed scenarios compared to orthogonal frequency division multiplexing (OFDM), the waveform designed by CP-OTFS AFS demonstrates superior interference resilience, and the beamforming designed by SDR-BD strikes a balance in the overall performance of the ISWSCPTS.

A Light-Load Efficiency Improvement Technique for an Inductive Power Transfer System through a Reconfigurable Circuit

Constant voltage (CV) charging and efficiency improvement are the most basic and main targets to be achieved in inductive power transfer (IPT) systems. However, efficiency may be jeopardized as battery charging progresses, especially under a light-load condition, which accounts for most of the charging time. Traditional maximum-efficiency tracking (MET) control provides an effective solution to the above issues. However, MET control not only brings the difficulties of complicated control and increased cost/volume, but also increases the additional power losses because of the introduction of additional converters or hard-switching in dual-shift phase control. To address the above difficulty, a light-load efficiency improvement (LLEI) technique is presented in this study. Under a heavy-load condition, both the inverter and rectifier operate in conventional full-bridge mode with satisfactory efficiency. Under a light-load condition, both the rectifier and inverter are reconfigured as a voltage-doubler rectifier and half-bridge inverter, respectively, to achieve two targets: one is to keep the charging voltage roughly unchanged, and the other is to force the equivalent load resistance (ELR) approach to the optimal point to improve system power transfer efficiency. A demonstrative experimental prototype with a charging voltage of 60 V is constructed and tested to validate the LLEI method proposed in this study. The experimental results show that the proposal can ensure stable CV charging and significantly improve the system efficiency under a light-load condition over the whole charging process.

Beamforming Optimization with the Assistance of Deep Learning in a Rate-Splitting Multiple-Access Simultaneous Wireless Information and Power Transfer System with a Power Beacon

This study examined the implementation of rate-splitting multiple access (RSMA) in a multiple-input single-output system using simultaneous wireless information and power transfer (SWIPT) technology. The coexistence of a base station and a power beacon was considered, aiming to transmit information and energy to two sets of users. One set comprises users who solely harvest energy, whereas the other can decode information and energy using a power-splitting (PS) structure. The main objective of this optimization was to minimize the total transmit power of the system while satisfying the rate requirements for PS users and ensuring minimum energy harvesting (EH) for both PS and EH users. The non-convex problem was addressed by dividing it into two subproblems. The first subproblem was solved using a deep learning-based scheme, combining principal component analysis and a deep neural network. The semidefinite relaxation method was used to solve the second subproblem. The proposed method offers lower computational complexity compared to traditional iterative-based approaches. The simulation results demonstrate the superior performance of the proposed scheme compared to traditional methods such as non-orthogonal multiple access and space-division multiple access. Furthermore, the ability of the proposed method to generalize was validated by assessing its effectiveness across several challenging scenarios.

Joint Beamforming for RIS-Assisted Integrated Communication, Sensing and Power Transfer Systems

Joint Beamforming for RIS-Assisted Integrated Communication, Sensing and Power Transfer Systems

Operational Verification of Semi-Dynamic Wireless Power Transfer in Light-Rail Transit Systems

Operational Verification of Semi-Dynamic Wireless Power Transfer in Light-Rail Transit Systems

GMPP Tracking of Solar PV system using Spotted Hyena and Quadratic Approximation based Hybrid Algorithm under Partially shaded conditions

The demand for clean and renewable energy is increasing due to environmental concerns. Photovoltaic (PV) system is very popular from the renewable sources and its usage is increasing. The PV system power transfer efficiency depends on several factors such electrical characteristics of loads, solar irradiation, shading condition and panel temperature. The process of transferring maximum possible power to load from PV system by adjusting the system parameters is called maximum power point tracking (MPPT). Under the partially shaded conditions, multiple power peaks are created in the PV curves and makes the MPPT is a non-convex problem. It is a challenging problem to track the global maximum power point (GMPP) under partially shaded conditions. It is essential to recognize the GMPP and restart the string as early as possible to prevent the physical as well as economical damage. In this paper, a new hybrid algorithm for MPPT is proposed and called as QASHO, a combination of Spotted Hyena optimization (SHO) and Quadrature approximation (QA) technique. The QASHO is used to track the GMPP under different weather conditions such as partial shading. The simulation results are compared with Perturb and Observe (P&O) algorithm and Cuckoo Search optimization (CSO) algorithm and promised for better performance in tracking GMPP. The experimental results are provided to validate the proposed MPPT methodology.

Effect of the Conduction Resistance of SiC MOSFET on the Harmonics of Inverter Voltage in Wireless Power-Transfer Systems for Electric Vehicles

Effect of the Conduction Resistance of SiC MOSFET on the Harmonics of Inverter Voltage in Wireless Power-Transfer Systems for Electric Vehicles

Power system transfer learning to identify event types with or without event labels

To enable fast and accurate analysis for modern power systems, Machine Learning (ML) models have achieved great success with the emerging synchrophasor measurements. However, it is hard to train an ML model directly for data-limited scenarios like a newly constructed power system. Thus, we propose a transfer learning framework to transfer knowledge from a source grid to a target grid. We focus on event identification and study how knowledge can be efficiently transferred with or without event labels. While existing work mainly focuses on regular data like image datasets, knowledge transfer for power systems is challenging since the size and distribution of the two systems are different. Thus, we propose methods to align the dimensionality and maintain close data distributions in the latent space. For generality, we propose transfer learning to both supervised and unsupervised approaches. For supervised learning methods, we develop efficient data processing and common knowledge voting scheme to enable efficient transfer. For unsupervised learning methods, we introduce dimensionality-reduction and clustering algorithms to find common features with small distribution distances. Finally, we introduce proper theorems to validate our model and conduct both supervised and unsupervised transfer learning over diversified power system datasets.

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

High-Efficiency Sine-Wave Current Pulses Charging Method in Wireless Power-Transfer System Applications

There has been extensive discourse surrounding energy storage equipment and technologies for sustainable energy solutions. To address the need for prolonging the operational lifespan of energy storage equipment, this research introduces a high-efficiency charging method that integrates wireless power-transfer (WPT) technology. In the proposed LLC-S charger, the diodes of the receiver side rectify the incoming power while generating interleaved sinusoidal wave current pulses for charging two lead-acid battery energy storage systems (BESSs). This approach offers the advantage of providing rest intervals for BESSs and mitigating the impact of electrochemical reactions, thus promoting their overall durability. To validate the proposed charger, two 60 V/14 Ah BESSs as storage equipment within the solar power system are utilized for the charging tests. The results revealed that the utilization of sine-wave current pulses for charging enabled soft switching at both the transmitter and receiver sides, resulting in an overall average efficiency exceeding 80%. Experimental data derived from a prototype with a maximum output power of 1391 W during charging demonstrated that BESSs could be fully charged in a mere 1.61 h, achieving an impressive efficiency of 98%. These findings substantiate the feasibility and effectiveness of utilizing sine-wave current pulses for charging.

Optimizing power transfer in selective wireless charging systems: A genetic algorithm-based approach

This paper presents a novel approach to optimize selective wireless power transmission to multiple receivers utilizing a single transmitter. The primary focus is on achieving target power levels at specific resonant frequencies on each receiver while ensuring maximum transmission efficiency. To address this, an analytical model based on magnetic coupling between coils is employed to explore different solutions, and a Genetic Algorithm (GA) is applied to identify the optimal configuration. The application of a GA for system design optimization is introduced, which proves highly effective, especially when dealing with multiple receivers where analytical models become difficult to manage. The GA-based approach facilitates the discovery of numerical solutions that might be challenging to deduce analytically. The validity of the proposed approach is confirmed through simulation and experimental measurements.

Experimentally verified numerical model for asymmetric ferrite core wireless power transfer with on-chip interfacing circuits

This paper presents a novel numerical model for asymmetric ferrite core wireless power transfer, which has been experimentally verified. The research focuses on addressing the challenge of reducing the resonance frequency in wireless power transfer technology, particularly for cost reduction in power transfer systems. To achieve this, a toroidal ferrite core is utilized to decrease the self-resonant frequency, and the transmission parameter is measured using a vector network analyzer. Inductive wireless power transfer designs operating at MHz frequencies often suffer from low current efficiency due to the quality factor of the resonant coils. To overcome this limitation, finite element analysis is employed to optimize the cross-sectional area of the inductors, specifically for high-frequency wireless power transfer. The results demonstrate the effectiveness of the optimized coils, achieving an impressive transfer efficiency of nearly 98% at 5 cm, with an operating frequency of 21.6 MHz. Furthermore, the system is enhanced with a CMOS-based interfacing circuit, designed to enable system-on-chip power transfer for Internet of Things (IoT) applications. This integrated system design contributes to the advancement of wireless power transfer technology by not only addressing resonance frequency reduction but also proposing a cost-effective and efficient solution for power transfer in IoT applications.

An Enhanced Tuna Swarm Algorithm for Optimizing FACTS and Wind Turbine Allocation in Power Systems

The significance of FACTS devices has been increasing as they have the ability to donate compensation for power systems, making a significant impact on power system stability and power transfer issues. However, to optimize the performance of these devices, it is important to carefully select their sizes and locations. This article aims to determine the optimal size and location of several FACTS devices to achieve two objectives: minimizing fuel costs and minimizing power losses. These objectives are solved one by one, then combined into a multi-objective function to minimize gross cost. An Enhanced Tuna Swarm Optimization is proposed to improve the performance of the original version of Tuna Swarm Optimization. The traditional Tuna swarm optimization is improved relying on “high and low-velocity ratios” included in the Marine Predator Algorithm. The main advantage of this approach is to avoid the risk of the optimal value being trapped in local minima. The IEEE 30-bus standard system is used as a case study, with SVC, TCSC, and TCPS installed as FACTS devices, and two wind turbines as renewable resources penetration. Different optimization algorithms are used, and a comparison is made to prove the superiority of the proposed algorithm compared to the other tested algorithms.

Unified Power Flow Controller: A Brief Review on Tuning and Allocation for Power System Stability

The Power System can become unstable due to disturbances. To enhance system stability the Unified Power Flow Controller (UPFC) is tuned and allocated in the System. In this paper, a brief review of UPFC tuning and allocation studies for power systems stability is presented. The databases consulted for literature are the IEEE Xplore, ScienceDirect, Google Scholar and IOP Publications. The search terms used are Allocation, Tuning, UPFC, Power System and Stability to find the literature used in this review. A total of 26 Journal articles and conference papers were found and reviewed based on tuning and allocation studies. The Researchers applied Fuzzy coordination, Genetic Algorithm (GA), Particles Swarm Optimization (PSO), Grey Wolf Optimization (GWO) and Linear Quadratic Tracker (LQT) to tune the UPFC for enhancing power system stability. For studies on UPFC allocation in power systems, the Researchers applied frequency response of power system transfer function, power flow, Tabu Search (TS), PSO and GA. For allocation based on optimization, the Researchers minimized power losses, voltage index and investment costs considering equality and inequality constraints.

Different DC-Link Control Methods with Multilevel Inverter for Low Harmonic and Efficient Power Transfer in Grid-Tied Hydrogen Fuel Cell Systems

In grid-connected power generation systems, dc-link voltage control is needed to prevent energy losses, reduce voltage fluctuations and provide a stable energy flow. In addition, control of the power factor via the voltage source inverter is a process that supports the efficient use of the energy produced. Moreover, keeping the total harmonic distortion (THD) of the current injected into the grid in accordance with IEEE-519 harmonic standards (

Rectifier Design Challenges for Wireless Energy Harvesting/Wireless Power Transfer Systems: Broadening Bandwidth and Extended Input Power Range

RF-based wireless energy harvesting (WEH) and wireless power transfer (WPT) are gaining attention due to their capability of powering various sensors and devices. A low-power device can be fed wirelessly by capturing ambient RF energy through a WEH system. In the case of a high-power device, a WPT system can provide the required amount of power using intentional RF sources.