Higher-order expansions of powered extremes of logarithmic general error distribution

In this paper,Let M_(n)denote the maximum of logarithmic general error distribution with parameter v≥1.Higher-order expansions for distributions of powered extremes M_(n)^(p)are derived under an optimal choice of normalizing constants.It is shown that M_(n)^(p),when v=1,converges to the Frechet extreme value distribution at the rate of 1/n,and if v>1 then M_(n)^(p)converges to the Gumbel extreme value distribution at the rate of(loglogn)^(2)=(log n)^(1-1/v).

Stackelberg Game for Wireless Powered and Backscattering Enabled Sensor Networks

This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.

Resource Allocation for IRS Assistedmm Wave Wireless Powered Sensor Networks with User Cooperation

In this paper,we investigate IRS-aided user cooperation(UC)scheme in millimeter wave(mmWave)wirelesspowered sensor networks(WPSN),where two single-antenna users are wireless powered in the wireless energy transfer(WET)phase first and then cooperatively transmit information to a hybrid access point(AP)in the wireless information transmission(WIT)phase,following which the IRS is deployed to enhance the system performance of theWET andWIT.We maximized the weighted sum-rate problem by jointly optimizing the transmit time slots,power allocations,and the phase shifts of the IRS.Due to the non-convexity of the original problem,a semidefinite programming relaxation-based approach is proposed to convert the formulated problem to a convex optimization framework,which can obtain the optimal global solution.Simulation results demonstrate that the weighted sum throughput of the proposed UC scheme outperforms the non-UC scheme whether equipped with IRS or not.

Intelligent UAV Based Energy Supply for 6G Wireless Powered IoT Networks

In this paper,we develop a 6G wireless powered Internet of Things(IoT)system assisted by unmanned aerial vehicles(UAVs)to intelligently supply energy and collect data at the same time.In our dual-UAV scheme,UAV-E,with a constant power supply,transmits energy to charge the IoT devices on the ground,whereas UAV-B serves the IoT devices by data collection as a base station.In this framework,the system's energy efficiency is maximized,which we define as a ratio of the sum rate of IoT devices to the energy consumption of two UAVs during a fixed working duration.With the constraints of duration,transmit power,energy,and mobility,a difficult non-convex issue is presented by optimizing the trajectory,time duration allocation,and uplink transmit power of concurrently.To tackle the non-convex fractional optimization issue,we deconstruct it into three subproblems and we solve each of them iteratively using the descent method in conjunction with sequential convex approximation(SCA)approaches and the Dinkelbach algorithm.The simulation findings indicate that the suggested cooperative design has the potential to greatly increase the energy efficiency of the 6G intelligent UAV-assisted wireless powered IoT system when compared to previous benchmark systems.

Solvent-Resistant Wearable Triboelectric Nanogenerator for Energy-Harvesting and Self-Powered Sensors

Wearable triboelectric nanogenerators(TENGs)have attracted attention owing to their ability to harvest energy from the surrounding environment without maintenance.Herein,polyetherimide-Al_(2)O_(3)(PAl)and polyvinylidene fluoride-co-hexafluoropropylene(PVDF-HFP,PH)nanofiber membranes were used as tribo-positive and tribo-negative materials,respectively.Phytic acid-doped polyaniline(PANI)/cotton fabric(PPCF)and ethylenediamine(EDA)-crosslinked PAl(EPAl)nanofiber membranes were used as triboelectrode and triboencapsulation materials,respectively.The result showed that when the PAl-PH-based TENG was shaped as a circle with a radius of 1 cm,under the pressure of 50 N,and the frequency of 0.5 Hz,the open-circuit voltage(V_(oc))and short-circuit current(I_(sc))reached the highest value of 66.6 V and-93.4 to 110.1 nA,respectively.Moreover,the PH-based TENG could be used as a fabric sensor to detect fabric composition and as a sensor-inductive switch for light bulbs or beeping warning devices.When the PAl-PH-based TENG was shaped as a 5×5 cm^(2)rectangle,a 33 pF capacitor could be charged to 15 V in 28 s.Interestingly,compared to PAl nanofiber membranes,EPAl nanofiber membranes exhibited good dyeing properties and excellent solvent resistance.The PPCF exhibited<5%resistance change after washing,bending,and stretching.

Design and high-power testing of offline conditioning cavity for CiADS RFQ high-power coupler

To validate the design rationality of the power coupler for the RFQ cavity and minimize cavity contamination,we designed a low-loss offline conditioning cavity and conducted high-power testing.This offline cavity features two coupling ports and two tuners,operating at a frequency of 162.5 MHz with a tuning range of 3.2 MHz.Adjusting the installation angle of the coupling ring and the insertion depth of the tuner helps minimize cavity losses.We performed electromagnetic structural and multiphysics simulations,revealing a minimal theoretical power loss of 4.3%.However,when the cavity frequency varied by110 kHz,theoretical power losses increased to10%,necessitating constant tuner adjustments during conditioning.Multiphysics simulations indicated that increased cavity temperature did not affect frequency variation.Upon completion of the offline high-power conditioning platform,we measured the transmission performance,revealing a power loss of 6.3%,exceeding the theoretical calculation.Conditioning utilized efficient automatic range scanning and standing wave resonant methods.To fully condition the power coupler,a 15°phase difference between two standing wave points in the condition-ing system was necessary.Notably,the maximum continuous wave power surpassed 20 kW,exceeding the expected target.

Security-Reliability Tradeoff Analysis for Jamming Aided Decode-and-Forward Relay Networks

In this paper,we explore a cooperative decode-and-forward(DF)relay network comprised of a source,a relay,and a destination in the presence of an eavesdropper.To improve physical-layer security of the relay system,we propose a jamming aided decodeand-forward relay(JDFR)scheme combining the use of artificial noise and DF relaying which requires two stages to transmit a packet.Specifically,in stage one,the source sends confidential message to the relay while the destination acts as a friendly jammer and transmits artificial noise to confound the eavesdropper.In stage two,the relay forwards its re-encoded message to the destination while the source emits artificial noise to confuse the eavesdropper.In addition,we analyze the security-reliability tradeoff(SRT)performance of the proposed JDFR scheme,where security and reliability are evaluated by deriving intercept probability(IP)and outage probability(OP),respectively.For the purpose of comparison,SRT of the traditional decode-and-forward relay(TDFR)scheme is also analyzed.Numerical results show that the SRT performance of the proposed JDFR scheme is better than that of the TDFR scheme.Also,it is shown that for the JDFR scheme,a better SRT performance can be obtained by the optimal power allocation(OPA)between the friendly jammer and user.

Efficient Digital Twin Placement for Blockchain-Empowered Wireless Computing Power Network

As an open network architecture,Wireless Computing PowerNetworks(WCPN)pose newchallenges for achieving efficient and secure resource management in networks,because of issues such as insecure communication channels and untrusted device terminals.Blockchain,as a shared,immutable distributed ledger,provides a secure resource management solution for WCPN.However,integrating blockchain into WCPN faces challenges like device heterogeneity,monitoring communication states,and dynamic network nature.Whereas Digital Twins(DT)can accurately maintain digital models of physical entities through real-time data updates and self-learning,enabling continuous optimization of WCPN,improving synchronization performance,ensuring real-time accuracy,and supporting smooth operation of WCPN services.In this paper,we propose a DT for blockchain-empowered WCPN architecture that guarantees real-time data transmission between physical entities and digital models.We adopt an enumeration-based optimal placement algorithm(EOPA)and an improved simulated annealing-based near-optimal placement algorithm(ISAPA)to achieve minimum average DT synchronization latency under the constraint of DT error.Numerical results show that the proposed solution in this paper outperforms benchmarks in terms of average synchronization latency.

Primary frequency control considering communication delay for grid-connected offshore wind power systems

Offshore wind farms are becoming increasingly distant from onshore centralized control centers,and the communication delays between them inevitably introduce time delays in the measurement signal of the primary frequency control.This causes a deterioration in the performance of the primary frequency control and,in some cases,may even result in frequency instability within the power system.Therefore,a frequency response model that incorporates communication delays was established for power systems that integrate offshore wind power.The Padéapproximation was used to model the time delays,and a linearized frequency response model of the power system was derived to investigate the frequency stability under different time delays.The influences of the wind power proportion and frequency control parameters on the system frequency stability were explored.In addition,a Smith delay compensation control strategy was devised to mitigate the effects of communication delays on the system frequency dynamics.Finally,a power system incorporating offshore wind power was constructed using the MATLAB/Simulink platform.The simulation results demonstrate the effectiveness and robustness of the proposed delay compensation control strategy.

Mitigating Carbon Emissions:A Comprehensive Analysis of Transitioning to Hydrogen-Powered Plants in Japan’s Energy Landscape Post-Fukushima

One of the impacts of the Fukushima disaster was the shutdown of all nuclear power plants in Japan,reaching zero production in 2015.In response,the country started importing more fossil energy including coal,oil,and natural gas to fill the energy gap.However,this led to a significant increase in carbon emissions,hindering the efforts to reduce its carbon footprint.In the current situation,Japan is actively working to balance its energy requirements with environmental considerations,including the utilization of hydrogen fuel.Therefore,this paper aims to explore the feasibility and implications of using hydrogen power plants as a means to reduce emissions,and this analysis will be conducted using the energy modeling of the MARKAL-TIMES Japan framework.The hydrogen scenario(HS)is assumed with the extensive integration of hydrogen into the power generation sector,supported by a hydrogen import scheme.Additionally,this scenario will be compared with the Business as Usual(BAU)scenario.The results showed that the generation capacities of the BAU and HS scenarios have significantly different primary energy supplies.The BAU scenario is highly dependent on fossil fuels,while the HS scenario integrates hydrogen contribution along with an increase in renewable energy,reaching a peak contribution of 2,160 PJ in 2050.In the HS scenario,the target of reducing CO_(2) emissions by 80%is achieved through significant hydrogen penetration.By 2050,the total CO_(2) emissions are estimated to be 939 million tons for the BAU scenario and 261 million tons for the Hydrogen scenario.In addition,the contribution of hydrogen to electricity generation is expected to be 153 TWh,smaller than PV and wind power.

Hover performance estimation and validation of battery powered vertical takeoff and landing aircraft

Battery powered vertical takeoff and landing(VTOL) aircraft attracts more and more interests from public, while limited hover endurance hinders many prospective applications. Based on the weight models of battery, motor and electronic speed controller, the power consumption model of propeller and the constant power discharge model of battery, an efficient method to estimate the hover endurance of battery powered VTOL aircraft was presented. In order to understand the mechanism of performance improvement, the impacts of propulsion system parameters on hover endurance were analyzed by simulations, including the motor power density, the battery capacity, specific energy and Peukert coefficient. Ground experiment platform was established and validation experiments were carried out, the results of which showed a well agreement with the simulations. The estimation method and the analysis results could be used for optimization design and hover performance evaluation of battery powered VTOL aircraft.

Online Computation Offloading and Trajectory Scheduling for UAV-Enabled Wireless Powered Mobile Edge Computing

The unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) architecture is expected to be a powerful technique to facilitate 5 G and beyond ubiquitous wireless connectivity and diverse vertical applications and services, anytime and anywhere. Wireless power transfer(WPT) is another promising technology to prolong the operation time of low-power wireless devices in the era of Internet of Things(IoT). However, the integration of WPT and UAV-enabled MEC systems is far from being well studied, especially in dynamic environments. In order to tackle this issue, this paper aims to investigate the stochastic computation offloading and trajectory scheduling for the UAV-enabled wireless powered MEC system. A UAV offers both RF wireless power transmission and computation services for IoT devices. Considering the stochastic task arrivals and random channel conditions, a long-term average energyefficiency(EE) minimization problem is formulated.Due to non-convexity and the time domain coupling of the variables in the formulated problem, a lowcomplexity online computation offloading and trajectory scheduling algorithm(OCOTSA) is proposed by exploiting Lyapunov optimization. Simulation results verify that there exists a balance between EE and the service delay, and demonstrate that the system EE performance obtained by the proposed scheme outperforms other benchmark schemes.

Twin model-based fault detection and tolerance approach for in-core self-powered neutron detectors

The in-core self-powered neutron detector(SPND)acts as a key measuring device for the monitoring of parameters and evaluation of the operating conditions of nuclear reactors.Prompt detection and tolerance of faulty SPNDs are indispensable for reliable reactor management.To completely extract the correlated state information of SPNDs,we constructed a twin model based on a generalized regression neural network(GRNN)that represents the common relationships among overall signals.Faulty SPNDs were determined because of the functional concordance of the twin model and real monitoring sys-tems,which calculated the error probability distribution between the model outputs and real values.Fault detection follows a tolerance phase to reinforce the stability of the twin model in the case of massive failures.A weighted K-nearest neighbor model was employed to reasonably reconstruct the values of the faulty signals and guarantee data purity.The experimental evaluation of the proposed method showed promising results,with excellent output consistency and high detection accuracy for both single-and multiple-point faulty SPNDs.For unexpected excessive failures,the proposed tolerance approach can efficiently repair fault behaviors and enhance the prediction performance of the twin model.

Computation Rate Maximization in Multi-User Cooperation-Assisted Wireless-Powered Mobile Edge Computing with OFDMA

In the era of Internet of Things(Io T),mobile edge computing(MEC)and wireless power transfer(WPT)provide a prominent solution for computation-intensive applications to enhance computation capability and achieve sustainable energy supply.A wireless-powered mobile edge computing(WPMEC)system consisting of a hybrid access point(HAP)combined with MEC servers and many users is considered in this paper.In particular,a novel multiuser cooperation scheme based on orthogonal frequency division multiple access(OFDMA)is provided to improve the computation performance,where users can split the computation tasks into various parts for local computing,offloading to corresponding helper,and HAP for remote execution respectively with the aid of helper.Specifically,we aim at maximizing the weighted sum computation rate(WSCR)by optimizing time assignment,computation-task allocation,and transmission power at the same time while keeping energy neutrality in mind.We transform the original non-convex optimization problem to a convex optimization problem and then obtain a semi-closed form expression of the optimal solution by considering the convex optimization techniques.Simulation results demonstrate that the proposed multi-user cooperationassisted WPMEC scheme greatly improves the WSCR of all users than the existing schemes.In addition,OFDMA protocol increases the fairness and decreases delay among the users when compared to TDMA protocol.

An Improvement in Power Quality and By-Product of the Run-Off River Micro Hydro Power Plant

Utilization of Micro Hydro Power Plant at the Gunung Halu case study type run-off the river is a household use only in the afternoon,around 5 pm until bedtime at about 10 pm.Therefore,more than 75%of the energy is lost.This case study lost power which can be used as a by-product,such as for drying coffee beans.In this case study,a design was carried out to obtain by-products and improve power quality in the electrical system.In addition,they complain about the poor quality of power controlled by frequency using Triac-Based Electronic Dummy Load Control.The heat from the dummy load in the case study is used as a by-product.MHP with a minimum power of 20 kW,and the usage time of customer service is about 6 h.The energy for the by-products is about 360 kWh/day,and the power quality improved by using Triac-Based Electronic Load Control and Hysteresis Current Control for the active filter.As a result,the power factor is close to one,the generator current harmonics is less than 2%,and the voltage harmonics is less than 5%.

Energy-Delay Tradeoff for Online Offloading Based on Deep Reinforcement Learning in Wireless Powered Mobile-Edge Computing Networks

Benefited from wireless power transfer(WPT)and mobile-edge computing(MEC),wireless powered MEC systems have attracted widespread attention.Specifically,we design an online offloading scheme based on deep reinforcement learning that maximizes the computation rate and minimizes the energy consumption of all wireless devices(WDs).Extensive results validate that the proposed scheme can achieve better tradeoff between energy consumption and computation delay.

A Multi-mode Electronic Load Sensing Control Scheme with Power Limitation and Pressure Cut-off for Mobile Machinery

In mobile machinery,hydro-mechanical pumps are increasingly replaced by electronically controlled pumps to improve the automation level,but diversified control functions(e.g.,power limitation and pressure cut-off)are integrated into the electronic controller only from the pump level,leading to the potential instability of the overall system.To solve this problem,a multi-mode electrohydraulic load sensing(MELS)control scheme is proposed especially considering the switching stability from the system level,which includes four working modes of flow control,load sensing,power limitation,and pressure control.Depending on the actual working requirements,the switching rules for the different modes and the switching direction(i.e.,the modes can be switched bilaterally or unilaterally)are defined.The priority of different modes is also defined,from high to low:pressure control,power limitation,load sensing,and flow control.When multiple switching rules are satisfied at the same time,the system switches to the control mode with the highest priority.In addition,the switching stability between flow control and pressure control modes is analyzed,and the controller parameters that guarantee the switching stability are obtained.A comparative study is carried out based on a test rig with a 2-ton hydraulic excavator.The results show that the MELS controller can achieve the control functions of proper flow supplement,power limitation,and pressure cut-off,which has good stability performance when switching between different control modes.This research proposes the MELS control method that realizes the stability of multi-mode switching of the hydraulic system of mobile machinery under different working conditions.

Research on the Critical Buckling Pressure of Bucket Foundations with Inner Compartments for Offshore Wind Turbines

In the process of suction penetration of bucket foundations with inner compartments for offshore wind turbines,most researches focus on soil seepage failure and soil plugs,while the buckling of foundations is rarely investigated.Therefore,theoretical calculation methods for critical buckling pressures of the skirt and bulkheads of the bucket foundation are first presented according to the stability theory of a cylindrical shell and the small deflection theory of a thin plate,respectively.Furthermore,two types of models with and without considering the skirt-soil interaction are developed for the calculation of critical buckling pressure of the bucket foundation.Taking a practical project as an example,theoretical and numerical methods are used to obtain the critical buckling pressures of a bucket foundation.In this work,the theoretical method and the finite element model considering the skirt-soil interaction for calculating the critical buckling pressure of bucket foundations are firstly proposed.The results can help to optimize the design process of offshore wind turbine foundations and improve the safety of offshore wind power systems.

Energy Management System with Power Offering Strategy for a Microgrid Integrated VPP

In the context of both the Virtual Power Plant (VPP) and microgrid(MG), the Energy Management System (EMS) is a key decision-maker forintegrating Distributed renewable Energy Resources (DERs) efficiently. TheEMS is regarded as a strong enabler of providing the optimized schedulingcontrol in operation and management of usage of disperse DERs and RenewableEnergy reSources (RES) such as a small-size wind-turbine (WT) andphotovoltaic (PV) energies. The main objective to be pursued by the EMSis the minimization of the overall operating cost of the MG integrated VPPnetwork. However, the minimization of the power peaks is a new objective andopen issue to a well-functional EMS, along with the maximization of profitin the energy market. Thus, both objectives have to be taken into accountat the same time. Thus, this paper proposes the EMS application incorporatingpower offering strategy applying a nature-inspired algorithm such asParticle Swarm Optimization (PSO) algorithm, in order to find the optimalsolution of the objective function in the context of the overall operating cost,the coordination of DERs, and the energy losses in a MG integrated VPPnetwork. For a fair DERs coordination with minimized power fluctuationsin the power flow, the power offering strategies with an active power controland re-distribution are proposed. Simulation results show that the proposedMG integrated VPP model with PSO-based EMS employing EgalitarianreDistribution (ED) power offering strategy is most feasible option for theoverall operating cost of VPP revenue. The total operating cost of the proposedEMS with ED strategy is 40.98$ compared to 432.8$ of MGs only withoutEMS. It is concluded that each MGs in the proposed VPP model intelligentlyparticipates in energy trading market compliant with the objective function,to minimize the overall cost and the power fluctuation.

NOMA Empowered Energy Efficient Data Collection and Wireless Power Transfer in Space-Air-Ground Integrated Networks

As the sixth generation network(6G)emerges,the Internet of remote things(IoRT)has become a critical issue.However,conventional terrestrial networks cannot meet the delay-sensitive data collection needs of IoRT networks,and the Space-Air-Ground integrated network(SAGIN)holds promise.We propose a novel setup that integrates non-orthogonal multiple access(NOMA)and wireless power transfer(WPT)to collect latency-sensitive data from IoRT networks.To extend the lifetime of devices,we aim to minimize the maximum energy consumption among all IoRT devices.Due to the coupling between variables,the resulting problem is non-convex.We first decouple the variables and split the original problem into four subproblems.Then,we propose an iterative algorithm to solve the corresponding subproblems based on successive convex approximation(SCA)techniques and slack variables.Finally,simulation results show that the NOMA strategy has a tremendous advantage over the OMA scheme in terms of network lifetime and energy efficiency,providing valuable insights.