Research on Volt/Var Control of Distribution Networks Based on PPO Algorithm

In this paper,a model free volt/var control(VVC)algorithm is developed by using deep reinforcement learning(DRL).We transform the VVC problem of distribution networks into the network framework of PPO algorithm,in order to avoid directly solving a large-scale nonlinear optimization problem.We select photovoltaic inverters as agents to adjust system voltage in a distribution network,taking the reactive power output of inverters as action variables.An appropriate reward function is designed to guide the interaction between photovoltaic inverters and the distribution network environment.OPENDSS is used to output system node voltage and network loss.This method realizes the goal of optimal VVC in distribution network.The IEEE 13-bus three phase unbalanced distribution system is used to verify the effectiveness of the proposed algorithm.Simulation results demonstrate that the proposed method has excellent performance in voltage and reactive power regulation of a distribution network.

Effects of T-Factor on Quantum Annealing Algorithms for Integer Factoring Problem

The hardness of the integer factoring problem(IFP)plays a core role in the security of RSA-like cryptosystems that are widely used today.Besides Shor’s quantum algorithm that can solve IFP within polynomial time,quantum annealing algorithms(QAA)also manifest certain advantages in factoring integers.In experimental aspects,the reported integers that were successfully factored by using the D-wave QAA platform are much larger than those being factored by using Shor-like quantum algorithms.In this paper,we report some interesting observations about the effects of QAA for solving IFP.More specifically,we introduce a metric,called T-factor that measures the density of occupied qubits to some extent when conducting IFP tasks by using D-wave.We find that T-factor has obvious effects on annealing times for IFP:The larger of T-factor,the quicker of annealing speed.The explanation of this phenomenon is also given.

Effects of different nozzle materials on atomization results via CFD simulation

Spray drying,as a crucial operation in industrial production,converts solution to fine particle.The spray moiety directly affects the final particle morphology,size and distribution.Compared with the experimental method,computational fluid dynamics(CFD)modeling is a powerful and convenient tool for simulating the spray process.Based on the verified CFD model,different materials of atomizer were simulated to investigate the effect on droplet size and distribution in this work.The modeling result proved that the droplet size and distribution were influenced by the resistance coefficient of materials,wherein the Reynolds number could change the effect of roughness along with the change of mass flow rate on spray process.The results in this work have implication for controlling droplet size through developing new spray nozzle with different materials or surface coating.

The Late Cretaceous source-to-sink system at the eastern margin of the Tibetan Plateau:Insights from the provenance of the Lanping Basin

The surface uplift of the Tibetan Plateau(TP)and its geomorphology evolution has triggered aridification of Asia's interior and drainage development at the eastern margin of the plateau.However,how the pre-Cenozoic early growth histories of the TP impact the drainage system and climate is poorly constrained.The Late Mesozoic Lacustrine evaporite-bearing basins on the eastern margin of the TP record significant information on the uplift of the source terranes,source-to-sink system development and climate change.In this study,we presented detrital zircon U-Pb ages from the Upper Cretaceous Yunlong Formation in the Lanping Basin,as well as Hf isotopic,petrographic,direct statistical,and multidimensional scaling analyses,and use them to characterize the provenance and reconstruct the drainage system.All of the samples have five major age peaks at 200-290 Ma,400-490 Ma,750-1000 Ma,1750-1950 Ma,and 2400-2600 Ma with mostly negativeε_(Hf)(t)values(81%).We infer the sediments are primarily derived from recycled sediments of the Songpan-Garze terrane,and partly from the Sichuan Basin and the Southern Qiangtang terrane,as well as the exposed magmatic rocks of the Yidun Arc and SongpanGarze terrane.The provenance features of the contemporaneous sediments from the Sichuan,Xichang,Chuxiong,and Simao basins indicate a complex hierarchical drainage pattern on the eastern margin of the TP during the Late Cretaceous.The hierarchical drainage system exhibits a complete gradational cycle of lake-basin types from overfilled freshwater Sichuan Basin through balanced fill saline Xichang Basin and underfilled hypersaline Chuxiong,Lanping,Simao,and Khorat Plateau basins from proximal to distal.The early growth of the TP primarily controlled the drainage and lake-basin evolution by not only causing the uplift and exhumation of the source areas and providing large amounts of clastic material to the proximal sub-drainage areas but also intensifying the aridity and deposition of evaporites.

Naive Echo-State-Network Based Services Awareness Algorithm of Software Defined Optical Networks

As internet services newly emerge with diversity and complexity, great challenges and demands are presented to the Open Flow controlled software defined optical networks(SDON) to achieve better match between services and SDON. With this aim, this paper proposes a naive Echo-State-Network(Naive-ESN) based services awareness algorithm of the software defined optical network, where the naive ESN model adopts the ring topology structure and generates the probability output result to determine the Qo S policy of SDON. Moreover, the Naive-ESN engine is also designed in controller node of SDON to perform services awareness by obtaining service traffic features from data plan, together with some necessary extension of the Open Flow protocol. Test results show that the proposed approach is able to improved services-oriented supporting ability of SDON.

Seismic Behaviour of Beam-Column Joints of Precast and Partial Steel Reinforced Concrete

A beam-column joint of precast and partial steel reinforced concrete( PPSRC) is proposed for precast reinforced concrete frames. The PPSRC consists of partial steel and reinforced concrete. The partial steel is located in the core joint region and the connections between concrete members. This paper presents an experimental study of a series of PPSRC specimens. These specimens are tested under low cyclic loading.Experimental results demonstrate that the bearing capacity of the PPSRC specimens is 3 times that of the ordinary reinforced concrete( RC) beam-column joints. The strength and stiffness degradation rates are slower compared with that of the RC beam-column joints. In addition,the strength of the core joint region and the connections is higher than other parts of the PPSRC specimens. Beam failure occurs firstly for the PPSRC specimens,followed by column failure and connections failure. The failure of the core joint region occurs finally.Test results show that the seismic performance of the PPSRC is better than that of the ordinary RC beam-column joints.

Encoding-Decoding-Based Control and Filtering of Networked Systems： Insights, Developments and Opportunities

In order to make the information transmission more efficient and reliable in a digital communication channel with limited capacity, various encoding-decoding techniques have been proposed and widely applied in many branches of the signal processing including digital communications, data compression,information encryption, etc. Recently, due to its promising application potentials in the networked systems(NSs), the analysis and synthesis issues of the NSs under various encoding-decoding schemes have stirred some research attention. However, because of the network-enhanced complexity caused by the limited network resources, it poses new challenges to the design of suitable encoding-decoding procedures to meet certain control or filtering performance for the NSs. In this survey paper, our aim is to present a comprehensive review of the encoding-decodingbased control and filtering problems for different types of NSs.First, some basic introduction with respect to the coding-decoding mechanism is presented in terms of its engineering insights,specific properties and theoretical formulations. Then, the recent representative research progress in the design of the encodingdecoding protocols for various control and filtering problems is discussed. Some possible further research topics are finally outlined for the encoding-decoding-based NSs.

HB-Protocol Based Advance Security System for PKES Using Multiple Antennas

Modern cars are mostly computerized and equipped with passive keyless entry and start(PKES) system. PKES is based on Radio Frequency Identification(RFID) technology for authentication of the authorized drivers. RFID technology has replaced the conventional ways of identification and authorization in order to facilitate users while introducing new security challenges. In this article, we focused on verifying the presence of authorized key in the physical proximity of car by employing multiple antennas. Application of multiple antennas to the currently developed cryptographic algorithms opens a new approach for researchers to improve security of RFID based systems. We propose an advanced security system for PKES using multiple antennas wherein an authorized key passes through multiple vicinities to allow driver to access and start the car. Furthermore, we modified a light-weight cryptographic protocol named as HB(Hopper and Blum) protocol to integrate it with the proposed design based on multiple antennas. Simulation results show improvement in security functionality while keeping in view the efficiency constraints.

Prediction of Health Level of Multiform Lithium Sulfur Batteries Based on Incremental Capacity Analysis and an Improved LSTM

Capacity estimation plays a crucial role in battery management systems,and is essential for ensuring the safety and reliability of lithium-sulfur(Li-S)batteries.This paper proposes a method that uses a long short-term memory(LSTM)neural network to estimate the state of health(SOH)of Li-S batteries.The method uses health features extracted from the charging curve and incre-mental capacity analysis(ICA)as input for the LSTM network.To enhance the robustness and accuracy of the network,the Adam algorithm is employed to optimize specific hyperparameters.Experimental data from three different groups of batteries with varying nominal capac-ities are used to validate the proposed method.The results demonstrate the effectiveness of the method in accurately estimating the capacity degradation of all three batteries.Also,the study examines the impact of different lengths of network training sets on capacity estimation.The results reveal that the ICA-LSTM model achieves a prediction accuracy of mean absolute error 4.6%and mean squared error 0.21%with three different training set lengths of 20%,40%,and 60%.The analysis demonstrates that the lightweight model maintains high SOH estimation accu-racy even with a small training set,and exhibits strong adaptive and generalization capabilities when applied to different Li-S batteries.Overall,the proposed method,supported by experimental validation and analysis,demonstrates its efficacy in ensuring accurate and reliable SOH estimation,thereby enhancing the safety and per-formance of Li-S batteries.Index Terms—Adam algorithm,incremental capacity analysis,Li-S battery,long short-term memory,state of health.

Event-triggered distributed optimization for model-free multi-agent systems

In this paper,the distributed optimization problem is investigated for a class of general nonlinear model-free multi-agent systems.The dynamical model of each agent is unknown and only the input/output data are available.A model-free adaptive control method is employed,by which the original unknown nonlinear system is equivalently converted into a dynamic linearized model.An event-triggered consensus scheme is developed to guarantee that the consensus error of the outputs of all agents is convergent.Then,by means of the distributed gradient descent method,a novel event-triggered model-free adaptive distributed optimization algorithm is put forward.Sufficient conditions are established to ensure the consensus and optimality of the addressed system.Finally,simulation results are provided to validate the effectiveness of the proposed approach.

Sensing as the key to the safety and sustainability of new energy storage devices

New energy storage devices such as batteries and supercapacitors are widely used in various fields because of their irreplaceable excellent characteristics.Because there are relatively few monitoring parameters and limited under-standing of their operation,they present problems in accurately predicting their state and controlling operation,such as state of charge,state of health,and early failure indicators.Poor monitoring can seriously affect the performance of energy storage devices.Therefore,to maximize the efficiency of new energy storage devices without damaging the equipment,it is important to make full use of sensing systems to accurately monitor important parameters such as voltage,current,temperature,and strain.These are highly related to their states.Hence,this paper reviews the sensing methods and divides them into two categories:embedded and non-embedded sensors.A variety of measurement methods used to measure the above parameters of various new energy storage devices such as batteries and super-capacitors are systematically summarized.The methods with different innovative points are listed,their advantages and disadvantages are summarized,and the application of optical fiber sensors is emphasized.Finally,the challenges and prospects for these studies are described.The intent is to encourage researchers in relevant fields to study the early warning of safety accidents from the root causes.

Stabilization of high-voltage layered oxide cathode by utilizing residual lithium to form NASICON-type nanoscale functional coating

High-voltage medium-nickel low-cobalt lithium layered oxide cathode materials are becoming a popular development route for high-energy lithium-ion batteries due to their relatively high capacity,low cost,and improved safety.Unfortunately,capacity fading derived from surface lithium residue,electrode-electrolyte interfacial side reactions,and bulk structure degradation severely limits large-scale commercial utilization.In this work,an ultrathin and uniform NASICON-type Li_(3)V_(2)(PO_(4))_(3)(LVP)nanoscale functional coating is formed in situ by utilizing residual lithium to enhance the lithium storage performance of LiNi_(0.6)Co0.05Mn_(0.35)O_(2)(NCM)cathode.The GITT and ex-situ EIS and XPS demonstrate exceptional Li+diffusion and conductivity and attenuated interfacial side reactions,improving the electrode-electrolyte interface stability.The variable temperature in-situ XRD demonstrates delayed phase transition temperature to improve thermal stability.The battery in-situ XRD displays the singlephase H1-H2 reaction and weakened harmful H3 phase transition,minimizing the bulk mechanical degradation.These improvements are attributed to the removal of surface residual lithium and the formation of NASICON-type Li_(3)V_(2)(PO_(4))_(3)functional coatings with stable structure and high ionic and electronic conductivity.Consequently,the obtained NCM@LVP delivers a higher capacity retention rate(97.1%vs.79.6%)after 150 cycles and a superior rate capacity(87 mAh·g^(-1)vs.58 mAh·g^(-1))at a 5 C current density than the pristine NCM under a high cut-off voltage of 4.5 V.This work suggests a clever way to utilize residual lithium to form functional coatings in situ to improve the lithium storage performance of high-voltage medium-nickel low-cobalt cathode materials.

State-of-health estimation of lithium-ion batteries based on electrochemical impedance spectroscopy: a review

Lithium-ion batteries(LIBs)are crucial for the large-scale utilization of clean energy.However,because of the com-plexity and real-time nature of internal reactions,the mechanism of capacity decline in LIBs is still unclear.This has become a bottleneck restricting their promotion and application.Electrochemical impedance spectroscopy(EIS)contains rich electrochemical connotations and significant application prospects,and has attracted widespread atten-tion and research on efficient energy storage systems.Compared to traditional voltage and current data,the state-of-health(SOH)estimation model based on EIS has higher accuracy.This paper categorizes EIS measurement methods based on different principles,introduces the relationship between LIBs aging mechanism and SOH,and compares the advantages of different SOH estimation methods.After a detailed analysis of the latest technologies,a review is given.The insights of this review can deepen the understanding of the relationship between EIS and the aging effect mechanism of LIBs,and promote the development of new energy storage devices and evaluation methods.

Triboelectric nanogenerators:the beginning of blue dream

Wave energy is inexhaustible renewable energy.Making full use of the huge ocean wave energy resources is the dream of mankind for hundreds of years.Nowadays,the utilization of water wave energy is mainly absorbed and transformed by electromagnetic generators(EMGs)in the form of mechanical energy.However,waves usually have low frequency and uncertainty,which means low power generation efficiency for EMGs.Fortunately,in this slow current and random direction wave case,the triboelectric nanogenerator(TENG)has a relatively stable output power,which is suitable for collecting blue energy.This article summarizes the main research results of TENG in harvesting blue energy.Firstly,based on Maxwell’s displacement current,the basic principle of the nanogenerator is expounded.Then,four working modes and three applications of TENG are introduced,especially the application of TENG in blue energy.TENG currently used in blue energy harvesting is divided into four categories and discussed in detail.After TENG harvests water wave energy,it is meaningless if it cannot be used.Therefore,the modular storage of TENG energy is discussed.The output power of a single TENG unit is relatively low,which cannot meet the demand for high power.Thus,the networking strategy of large-scale TENG is further introduced.TENG’s energy comes from water waves,and each TENG’s output has great randomness,which is very unfavorable for the energy storage after large-scale TENG integration.On this basis,this paper discusses the power management methods of TENG.In addition,in order to further prove its economic and environmental advantages,the economic benefits of TENG are also evaluated.Finally,the development potential of TENG in the field of blue energy and some problems that need to be solved urgently are briefly summarized.

Nonlinearity-induced localization enhancement in Fibonacci-like waveguide arrays[Invited]

Based on the one-dimensional periodic and Fibonacci-like waveguide arrays,we experimentally investigate localized quantum walks(QWs),both in the linear and nonlinear regimes.Unlike the ballistic transport behavior in conventional random QWs,localization of QWs is obtained in the Fibonacci-like waveguide arrays both theoretically and experimentally.Moreover,we verify the enhancement of the localization through nonlinearity-induced effect.Our work provides a valid way to study localization enhancement in QWs,which might broaden the understanding of nonlinearity-induced behaviors in quasiperiodic systems.

Integrated energy storage system based on triboelectric nanogenerator in electronic devices

The emergence of electronic devices has brought earth-shaking changes to people's life.However,an extemal power source may become indispensable to the electronie devices due to the limited capacity of batteries.As one of the possible solutions for the extermal power sources,the triboelectric nanogenerator(TENG)provides a novel idea to the increasing mumber of personal electronic devices.TENG is a new type of energy ollector,which has become a hot spot in the field of nanotechnology.It is widely used at the acquisition and conversion of mechan-ical enegy to electrice energy through the principle of electrostatic induction.On this basis,the TENG could be integrated with the energy stonage system into a self-powered system,W hich can supply power to the electronic devices and make them work continuously.In this review,TENG's basic structure as well as its working process and working mode are firstly discussed.The integration method of TENGs with enegy storage systems and the related research status are then introduced in detail.At the end of this paper,we put forward some problems and discuss the prospect in the future.

A thermally flexible and multi-site tactile sensor for remote 3D dynamic sensing imaging

A flexible,multi-site tactile and thermal sensor(MTTS)based on polyvinylidene fluoride(resolution 50×50)is reported.It can be used to implement spatial mapping caused by tactile and thermal events and record the two-dimensional motion trajectory of a tracked target object.The output voltage and current signal are recorded as amapping by sensing the external pressure and thermal radiation stimulus,and the response distribution is dynamically observed on the three-dimensional interface.Through the mapping relationship between the established piezoelectric and pyroelectric signals,the piezoelectric component and the pyroelectric component are effectively extracted from the composite signals.The MTTS has a good sensitivity for tactile and thermal detection,and the electrodes have good synchronism.In addition,the signal interference is less than 9.5%and decreases as the pressure decreases after the distance between adjacent sites exceeds 200μm.The integration of MTTS and signal processing units has potential applications in human-machine interaction systems,health status detection and smart assistive devices.

A lattice-based signcryption scheme without random oracles

In order to achieve secure signcryption schemes in the quantum era, Li Fagen et al. [Concurrency and Computation： Practice and Experience, 2012, 25（4）： 2112-2122] and Wang Fenghe et al. [Applied Mathematics ＆ Information Sciences, 2012, 6（1）： 23-28] have independently extended the concept of signcryption to lattice-based cryptography. However, their schemes are only secure under the random or- acle model. In this paper, we present a lattice-based signcryp- tion scheme which is secure under the standard model. We prove that our scheme achieves indistinguishability against adaptive chosen-ciphertext attacks （IND-CCA2） under the learning with errors （LWE） assumption and existential unforgeability against adaptive chosen-message attacks （EUF- CMA） under the small integer solution （SIS） assumption.

Linkages Between Tropical Cyclones and Extreme Precipitation over China and the Role of ENSO

This research investigated the linkages between tropical cyclones(TCs)and extreme precipitation,and their associations with El Nino-Southern Oscillation(ENSO)over China.The contribution of TC-induced to total extreme precipitation events along the southeast coast of China was higher than 50%,and the values gradually decreased as TCs moved inland.However,the precipitation extremes(magnitude and frequency)related to TCs did not show statistically significant changes over the most recent 57 years.The impacts of TCs on precipitation extremes are evidently modulated by the ENSO phases.We found less extreme precipitation linked with TCs in southeastern China during El Nino phase,because of the fewer TC tracks over this region and less TC genesis in the western North Pacific(WNP).The small TC track density over southeastern China is due to the prevalent westerly steering flow and abnormal integrated vapor transport from northern to southern China during El Nino years.Additionally,warmer sea surface temperature,more vigorous westerlies,larger vorticity in 250 hPa,and higher divergence in 850 hPa in an El Nino phase jointly displaced the mean genesis of the WNP TCs eastward and this led to fewer TCs passing through southeastern China.

Online estimation of SOH for lithium-ion battery based on SSA-Elman neural network

The estimation of state of health(SOH)of a lithium-ion battery(LIB)is of great significance to system safety and economic development.This paper proposes a SOH estimation method based on the SSA-Elman model for the first time.To improve the correlation rates between features and battery capacity,a method combining median absolute deviation filtering and Savitzky-Golay filtering is proposed to process the data.Based on the aging characteristics of the LIB,five features with correlation rates above 0.99 after data processing are then proposed.Addressing the defects of the Elman model,the sparrow search algorithm(SSA)is used to optimize the network parameters.In addition,a data incremental update mechanism is added to improve the generalization of the SSA-Elman model.Finally,the performance of the proposed model is verified based on NASA dataset,and the outputs of the Elman,LSTM and SSA-Elman models are compared.The results show that the proposed method can accurately estimate the SOH,with the root mean square error(RMSE)being as low as 0.0024 and the mean absolute percentage error(MAPE)being as low as 0.25%.In addition,RMSE does not exceed 0.0224 and MAPE does not exceed 2.21%in high temperature and low temperature verifications.