Enhancing Energy Efficiency with a Dynamic Trust Measurement Scheme in Power Distribution Network

The application of Intelligent Internet of Things(IIoT)in constructing distribution station areas strongly supports platform transformation,upgrade,and intelligent integration.The sensing layer of IIoT comprises the edge convergence layer and the end sensing layer,with the former using intelligent fusion terminals for real-time data collection and processing.However,the influx of multiple low-voltage in the smart grid raises higher demands for the performance,energy efficiency,and response speed of the substation fusion terminals.Simultaneously,it brings significant security risks to the entire distribution substation,posing a major challenge to the smart grid.In response to these challenges,a proposed dynamic and energy-efficient trust measurement scheme for smart grids aims to address these issues.The scheme begins by establishing a hierarchical trust measurement model,elucidating the trust relationships among smart IoT terminals.It then incorporates multidimensional measurement factors,encompassing static environmental factors,dynamic behaviors,and energy states.This comprehensive approach reduces the impact of subjective factors on trust measurements.Additionally,the scheme incorporates a detection process designed for identifying malicious low-voltage end sensing units,ensuring the prompt identification and elimination of any malicious terminals.This,in turn,enhances the security and reliability of the smart grid environment.The effectiveness of the proposed scheme in pinpointing malicious nodes has been demonstrated through simulation experiments.Notably,the scheme outperforms established trust metric models in terms of energy efficiency,showcasing its significant contribution to the field.

A Moored Underwater Energy Conservation System for Profiling Measurement

There is a need to obtain the hydrologic data including ocean current, wave, temperature and so on in the South China Sea. A new profiling instrument which does not suffer from the damage due to nature forces or incidents caused by passing ships, is under development to acquire data from this area. This device is based on a taut single point mid-water mooring system. It incorporates a small, instrumented vertically profiling float attached via an electromechanical cable to a winch integral with the main subsurface flotation. On a pre-set schedule, the instrument float with sensors is winched up to the surface if there is no ship passing by, which is defined by an on-board miniature sonar. And it can be. inunediately winched down to a certain depth if the sonar sensor finds something is coming. Since, because of logistics, the area can only be visited once for a long time and a minimum of 10 times per day profiles are desired, energy demands are severe. To respond to these concerns, the system has been designed to conserve a substantial portion of the potential energy lost during the ascent phase of each profile and subsequently use this energy to pull the instrument down. Compared with the previous single-point layered measuring mode, it is advanced and economical. At last the paper introduces the test in the South China Sea.

Reinforcement Learning-Based Energy Management for Hybrid Power Systems:State-of-the-Art Survey,Review,and Perspectives

The new energy vehicle plays a crucial role in green transportation,and the energy management strategy of hybrid power systems is essential for ensuring energy-efficient driving.This paper presents a state-of-the-art survey and review of reinforcement learning-based energy management strategies for hybrid power systems.Additionally,it envisions the outlook for autonomous intelligent hybrid electric vehicles,with reinforcement learning as the foundational technology.First of all,to provide a macro view of historical development,the brief history of deep learning,reinforcement learning,and deep reinforcement learning is presented in the form of a timeline.Then,the comprehensive survey and review are conducted by collecting papers from mainstream academic databases.Enumerating most of the contributions based on three main directions—algorithm innovation,powertrain innovation,and environment innovation—provides an objective review of the research status.Finally,to advance the application of reinforcement learning in autonomous intelligent hybrid electric vehicles,future research plans positioned as“Alpha HEV”are envisioned,integrating Autopilot and energy-saving control.

Regenerative Braking Energy Recovery System of Metro Train Based on Dual-Mode Power Management

In order to fully utilize the regenerative braking energy of metro trains and stabilize the metro DC traction busbar voltage,a hybrid regenerative braking energy recovery system with a dual-mode power management strategy is proposed.Firstly,the construction of the hybrid regenerative braking energy recovery system is explained.Then,based on the power demand of low-voltage load in metro stations,a dual-mode power management strategy is proposed to allocate the reference power of each system according to the different working conditions,and the control methods of each system are set.Finally,the correctness and effectiveness of the dual-mode strategy are verified through simulation,and the proposed braking energy utilization scheme is compared with other singleform utilization schemes.The results illustrate that the hybrid system with the dual-mode strategy can effectively recycle the regenerative braking energy of metro train and inhibit the busbar voltage fluctuation;the proposed braking energy utilization scheme has certain advantages on energy recovery and DC bus voltage stabilization compared with other single-form schemes;the proposed power management strategy can correctly allocate the reference power of each system with a lower construction cost.

Topological Structure-Modulated Collagen Carbon as Two-in-One Energy Storage Configuration toward Ultrahigh Power and Energy Density

Efficient energy storage devices with suitable electrode materials,that integrate high power and high energy,are the crucial requisites of the renewable power source,which have unwrapped new possibilities in the sustainable development of energy and the environment.Herein,a facile collagen microstructure modulation strategy is proposed to construct a nitrogen/oxygen dual-doped hierarchically porous carbon fiber with ultrahigh specific surface area(2788 m^(2)g^(-1))and large pore volume(4.56 cm^(3)g^(-1))via local microfibrous breakage/disassembly of natural structured proteins.Combining operando spectroscopy and density functional theory unveil that the dual-heteroatom doping could effectively regulate the electronic structure of carbon atom framework with enhanced electric conductivity and electronegativity as well as decreased diffusion resistance in favor of rapid pseudocapacitive-dominated Li^(+)-storage(353 mAh g^(-1)at 10 A g^(-1)).Theoretical calculations reveal that the tailored micro-/mesoporous structures favor the rapid charge transfer and ion storage,synergistically realizing high capacity and superior rate performance for NPCF-H cathode(75.0 mAh g^(-1)at 30 A g^(-1)).The assembled device with NPCF-H as both anode and cathode achieves extremely high energy density(200 Wh kg^(-1))with maximum power density(42600 W kg^(-1))and ultralong lifespan(80%capacity retention over 10000 cycles).

Rough law energy and measurement of ■-decomposition rough law

By employing function one-direction S-rough sets and rough law generation method based on function S-rough sets, ^-f-decomposition law and ^-F-decomposition rough law are proposed, and the measurement of rough law variation in the process of rough law ^-F-decomposition is researched. The concepts of law energy and attdbute ^-f-interference degree are presented, which make the variation of rough law become measurable. ^-f-decomposition law energy characteristic theorem, ^-f- decomposition law energy inequality theorem, ^-F-decomposition rough law energy characteristic theorem, and ^-f-decomposition law energy mean value theorem are presented.

Source-Load Coordinated Optimal Scheduling Considering the High Energy Load of Electrofused Magnesium and Wind Power Uncertainty

In fossil energy pollution is serious and the“double carbon”goal is being promoted,as a symbol of fresh energy in the electrical system,solar and wind power have an increasing installed capacity,only conventional units obviously can not solve the new energy as the main body of the scheduling problem.To enhance the systemscheduling ability,based on the participation of thermal power units,incorporate the high energy-carrying load of electro-melting magnesiuminto the regulation object,and consider the effects on the wind unpredictability of the power.Firstly,the operating characteristics of high energy load and wind power are analyzed,and the principle of the participation of electrofusedmagnesiumhigh energy-carrying loads in the elimination of obstructedwind power is studied.Second,a two-layer optimization model is suggested,with the objective function being the largest amount of wind power consumed and the lowest possible cost of system operation.In the upper model,the high energy-carrying load regulates the blocked wind power,and in the lower model,the second-order cone approximation algorithm is used to solve the optimizationmodelwithwind power uncertainty,so that a two-layer optimizationmodel that takes into account the regulation of the high energy-carrying load of the electrofused magnesium and the uncertainty of the wind power is established.Finally,the model is solved using Gurobi,and the results of the simulation demonstrate that the suggested model may successfully lower wind abandonment,lower system operation costs,increase the accuracy of day-ahead scheduling,and lower the final product error of the thermal electricity unit.

The Correlation between the Power Quality Indicators and Entropy Production Characteristics of Wind Power+Energy Storage Systems

Power quality improvements help guide and solve the problems of inefficient energy production and unstable power output in wind power systems.The purpose of this paper is mainly to explore the influence of different energy storage batteries on various power quality indicators by adding different energy storage devices to the simulated wind power system,and to explore the correlation between systementropy generation and various indicators,so as to provide a theoretical basis for directly improving power quality by reducing loss.A steady-state experiment was performed by replacing the wind wheel with an electric motor,and the output power qualities of the wind power systemwith andwithout energy storagewere compared and analyzed.Moreover,the improvement effect of different energy storage devices on various indicatorswas obtained.Then,based on the entropy theory,the loss of the internal components of the wind power system generator is simulated and explored by Ansys software.Through the analysis of power quality evaluation indicators,such as current harmonic distortion rate,frequency deviation rate,and voltage fluctuation,the correlation between entropy production and each evaluation indicator was explored to investigate effective methods to improve power quality by reducing entropy production.The results showed that the current harmonic distortion rate,voltage fluctuation,voltage deviation,and system entropy production are positively correlated in the tests and that the power factor is negatively correlated with system entropy production.In the frequency range,the frequency deviationwas not significantly correlated with the systementropy production.

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

Analysis and measurement of acoustic power in plastics ultrasonic welding process

A measuring principle for acoustic power in plastics ultrasonic welding process is introduced in this paper. Signal detection circuits of current, voltage, frequency, power for ultrasonic transducer of plastic ultrasonic welder are developed. A computer controlled measuring system is designed to sample the signals of welding process parameters. By using the designed system, the acoustic power curve during welding is calculated, saved, and displayed. And the relation between fusion state of plastics workpieces and input energy of joint is analyzed.

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.

A Two-Layer Active Power Optimization and Coordinated Control for Regional Power Grid Partitioning to Promote Distributed Renewable Energy Consumption

With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.

Energy efficiency aware dynamic rate and power adaptation in carrier sensing based WLANs under Rayleigh fading and shadowing

We consider the problem of energy efficiency aware dynamic adaptation of data transmission rate and transmission power of the users in carrier sensing based Wireless Local Area Networks(WLANs)in the presence of path loss,Rayleigh fading and log-normal shadowing.For a data packet transmission,we formulate an optimization problem,solve the problem,and propose a rate and transmission power adaptation scheme with a restriction methodology of data packet transmission for achieving the optimal energy efficiency.In the restriction methodology of data packet transmission,a user does not transmit a data packet if the instantaneous channel gain of the user is lower than a threshold.To evaluate the performance of the proposed scheme,we develop analytical models for computing the throughput and energy efficiency of WLANs under the proposed scheme considering a saturation traffic condition.We then validate the analytical models via simulation.We find that the proposed scheme provides better throughput and energy efficiency with acceptable throughput fairness if the restriction methodology of data packet transmission is included.By means of the analytical models and simulations,we demonstrate that the proposed scheme provides significantly higher throughput,energy efficiency and fairness index than a traditional non-adaptive scheme and an existing most relevant adaptive scheme.Throughput and energy efficiency gains obtained by the proposed scheme with respect to the existing adapting scheme are about 75%and 103%,respectively,for a fairness index of 0.8.We also study the effect of various system parameters on throughput and energy efficiency and provide various engineering insights.

A Home Appliance Recognition System Using the Approach of Measuring Power Consumption and Power Factor on the Electrical Panel, Based on Energy Meter ICs

Currently a large effort is being done with the intention to educate people about how much energy each electrical appliance uses in their houses, since this knowledge is the fundamental basis of energy efficiency programs that can be managed by the household owners. This paper presents a simple yet functional non-intrusive method for electric power measurement that can be applied in energy efficiency programs, in order to provide a better knowledge of the energy consumption of the appliances in a home.

A Novel Bidirectional Interaction Model and Electric Energy Measuring Scheme of EVs for V2G with Distorted Power Loads

With the increasing demand for petroleum resources and environmental issues,new energy electric vehicles are increasingly being used.However,the large number of electric vehicles connected to the grid has brought new challenges to the operation of the grid.Firstly,A novel bidirectional interaction model is established based on modulation theory with nonlinear loads.Then,the electric energy measuring scheme of EVs for V2G is derived under the conditions of distorted power loads.The scheme is composed of fundamental electric energy,fundamental-distorted electric energy,distorted-fundamental electric energy and distorted electric energy.And the characteristics of each electric energy are analyzed.Finally,the correctness of the model and energy measurement method is verified by three simulation cases:the impact signals,the fluctuating signals,and the harmonic signals.

Calorimetric power measurements in the EAST ECRH system

In this paper, the measurement method of calorimetric power for an electron cyclotron resonance heating（ECRH） system for EAST is presented. This method requires measurements of the water flow through the cooling circuits and the input and output water temperatures in each cooling circuit. Usually, the inlet water temperature stability is controlled to obtain more accurate results.The influence of the inlet water temperature change on the measurement results is analyzed for the first time in this paper. Also, a novel temperature calibration method is proposed. This kind of calibration method is accurate and effective, and can be easily implemented.

Instantaneous frequency measurement using two parallel I/Q modulators based on optical power monitoring

A scheme for instantaneous frequency measurement(IFM)using two parallel I/Q modulators based on optical power monitoring is proposed.The amplitude comparison function(ACF)can be constructed to establish the relationship between the frequency of radio frequency(RF)signal and the power ratio of two optical signals output by two I/Q modulators.The frequency of RF signal can be derived by measuring the optical power of the optical signals output by two I/Q modulators.The measurement range and measurement error can be adjusted by controlling the delay amount of the electrical delay line.The feasibility of the scheme is verified,and the corresponding measurement range and measurement error of the system under different delay amounts of the electrical delay line are given.Compared with previous IFM schemes,the structure of this scheme is simple.Polarization devices,a photodetector and an electrical power meter are not used,which reduces the impact of the environmental disturbance on the system and the cost of the system.In simulation,the measurement range can reach 0 GHz-24.5 GHz by adjusting the delay amount of the electrical delay lineτ=20 ps.The measurement error of the scheme is better at low frequency,and the measurement error of low frequency 0 GHz-9.6 GHz can reach-0.1 GHz to+0.05 GHz.

Placido disk-based topography versus high-resolution rotating Scheimpflug camera for corneal power measurements in keratoconic and post-LASIK eyes：reliability and agreement

AIM：To compare the repeatability/reproducibility of measurement by high-resolution Placido disk-based topography with that of a high-resolution rotating Scheimpflug camera and assess the agreement between the two instruments in measuring corneal power in eyes with keratoconus and post-laser in situ keratomileusis（LASIK）. METHODS：One eye each of 36 keratoconic patients and 20 subjects who had undergone LASIK was included in this prospective observational study. Two independent examiners worked in a random order to take three measurements of each eye with both instruments. Four parameters were measured on the anterior cornea：steep keratometry（Ks）,flat keratometry（Kf）,mean keratometry（Km）,and astigmatism（Ks-Kf）. Intra-examiner repeatability and inter-examiner reproducibility were evaluated by calculating the within-subject standard deviation（Sw）the coefficient of repeatability（R）,the coefficient of variation（Co V）,and the intraclass correlation coefficient（ICC）. Agreement between instruments was tested with the BlandAltman method by calculating the 95% limits of agreement（95% Lo A）.RESULTS：In keratoconic eyes,the intra-examiner and inter-examiner ICC were 〉0.95. As compared with measurement by high-resolution Placido disk-based topography,the intra-examiner R of the high-resolution rotating Scheimpflug camera was lower for Kf（0.32 vs 0.88）,Ks（0.61 vs 0.88）,and Km（0.32 vs 0.84）but higher for Ks-Kf（0.70 vs 0.57）. Inter-examiner R values were lower for all parameters measured using the high-resolution rotating Scheimpflug camera. The 95% Lo A were-1.28 to ＋0.55 for Kf,-1.36 to ＋0.99 for Ks,-1.08 to ＋0.50 for Km,and-1.11 to ＋1.48 for Ks-Kf. In the post-LASIK eyes,the intra-examiner andinter-examiner ICC were 〉0.87 for all parameters. The intra-examiner and inter-examiner R were lower for all parameters measured using the high-resolution rotating Scheimpflug camera. The intra-examiner R was 0.17 vs 0.88 for Kf,0.21 vs 0.88 for Ks,0.17 vs 0.86 for Km,and 0.28 vs 0.33 for Ks-Kf. The inter-examiner R was 0.09 vs 0.64 for Kf,0.15 vs 0.56 for Ks,0.09 vs 0.59 for Km,and 0.18 vs 0.23 for Ks-Kf. The 95% Lo A were-0.54 to ＋0.58 for Kf,-0.51 to ＋0.53 for Ks and Km,and-0.28 to ＋0.27 for Ks-Kf. CONCLUSION：As compared with Placido disk-based topography,the high-resolution rotating Scheimpflug camera provides more repeatable and reproducible measurements of Ks,Kf and Ks in keratoconic and post-LASIK eyes. Agreement between instruments is fair in keratoconus and very good in post-LASIK eyes.

Measurement of Secondary Electron Energy Spectra of Polymethyl Methacrylate

We report on a novel and convenient method of measuring secondary electron spectra for insulators in a secondary electron yield measurement system with a planar grid analyzer configuration and a metal mesh probe. In this measurement, the planar grid is negatively biased to force some emitted secondary electrons to return to the sample surface and to neutralize charges accumulated on the sample during the previous beam irradiation. The surface potential of the sample is then measured by use of a metal mesh probe. The grid bias for neutralization corresponding to the zero surface potential is determined based on the linear relationship between the surface potential and the grid bias. Once the surface potential equals zero, the secondary electron spectra of polymethyl methacrylate（PMMA） are studied experimentally by measuring the -curve and then fitting it to Everhart＇s formula. The measurement results show that the peak energy and the full width at half maximum of the spectra are 4.26 eV and 14.06 eV, respectively.

Simultaneous Measurements of Rainfall Intensity, Low Energy Neutrons and Gamma Radiation in Sao Jose Dos Campos, SP, Brazil

The article aims to study the possible correlation between the presence and intensity of rainfall X- and T-radiation and low energy neutrons at one specific location in S[io Jos6 dos Campos, SP, Brazil. Monitoring of these parameters was carried out from end February to half of June 2013 just in Physics Department of ITA （Technological Institute of Aeronautics）. By correlating the data of measurements of intensity of X and ）,-radiations with the rainfall it has been found that this meteorological parameter had a significant influence on the background of these radiation profile. A possible reason for this fact is associated with the presence of radon gas in the environment that is dragged to the surface during the occurrences of local rainfall. In relation neutrons, it was possible to note that the rainfall has small influence on this parameter measures.