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A Blockchain-Based Access Control Scheme for Reputation Value Attributes of the Internet of Things

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Computers, Materials & Continua 2024年第1期78卷 1297-1310页

作者： Hongliang Tian Junyuan Tian college of electrical engineering Northeast Electric Power UniversityJilin132012China

The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access control scheme is proposed.Firstly,writing the reputation value as an attribute into the access control policy,and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control;Secondly,storing a large amount of resources fromthe Internet of Things in Inter Planetary File System(IPFS)to improve system throughput;Finally,map resource access operations to qualification tokens to improve the performance of the access control system.Complete simulation experiments based on the Hyperledger Fabric platform.Fromthe simulation experimental results,it can be seen that the access control system can achieve more fine-grained and dynamic access control while maintaining high throughput and low time delay,providing sufficient reliability and security for access control of IoT devices.

关键词： Blockchain IoT access control Hyperledger Fabric

An Energy Trading Method Based on Alliance Blockchain and Multi-Signature

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Computers, Materials & Continua 2024年第2期78卷 1611-1629页

作者： Hongliang Tian Jiaming Wang college of electrical engineering Northeast Electric Power UniversityJilin132012China

Blockchain,known for its secure encrypted ledger,has garnered attention in financial and data transfer realms,including the field of energy trading.However,the decentralized nature and identity anonymity of user nodes raise uncertainties in energy transactions.The broadcast consensus authentication slows transaction speeds,and frequent single-point transactions in multi-node settings pose key exposure risks without protective measures during user signing.To address these,an alliance blockchain scheme is proposed,reducing the resource-intensive identity verification among nodes.It integrates multi-signature functionality to fortify user resources and transac-tion security.A novel multi-signature process within this framework involves neutral nodes established through central nodes.These neutral nodes participate in multi-signature’s signing and verification,ensuring user identity and transaction content privacy.Reducing interactions among user nodes enhances transaction efficiency by minimizing communication overhead during verification and consensus stages.Rigorous assessments on reliability and operational speed highlight superior security performance,resilient against conventional attack vectors.Simulation shows that compared to traditional solutions,this scheme has advantages in terms of running speed.In conclusion,the alliance blockchain framework introduces a novel approach to tackle blockchain’s limitations in energy transactions.The integrated multi-signature process,involving neutral nodes,significantly enhances security and privacy.The scheme’s efficiency,validated through analytical assessments and simulations,indicates robustness against security threats and improved transactional speeds.This research underscores the potential for improved security and efficiency in blockchain-enabled energy trading systems.

关键词： Alliance blockchain multi-signature energy trading security performance transaction efficiency

COF-based membranes for liquid phase separation:Preparation,mechanism and perspective

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Journal of Environmental Sciences 2024年第7期141卷 63-89页

作者： Yujie Zhao He Gu Yilun Zhou CaimeiWen Xiaolu Liu Suhua Wang Zhongshan Chen Hui Yang Xiangke Wang college of Environmental Science and engineering North China Electric Power UniversityBeijing 102206China School of Environmental Science and engineering Guangdong University of Petrochemical TechnologyMaoming 525000China

Covalent organic frameworks(COFs)are a new kind of crystalline porous materials composed of organic molecules connected by covalent bonds,processes the characteristics of low density,large specific surface area,adjustable pore size and structure,and easy to functionalize,which have been widely used in the field of membrane separation technology.Recently,there are more and more researches focusing on the preparation methods,separation application,and mechanism of COF membranes,which need to be further summarized and compared.In this review,we primarily summarized several conventional preparation methods,such as two-phase interfacial polymerization,in-situ growth on substrate,unidirectional diffusion method,layer-by-layer assembly method,mixed matrix membranes,and so on.The advantages and disadvantages of each method are briefly summarized.The application potential of COF membrane in liquid separation are introduced from four aspects:dyeing wastewater treatment,heavy metal removal,seawater desalination and oil-water separation.Then,the mechanisms including pore structure,hydrophilic/hydrophobic,electrostatic repulsion/attraction and Donnan effect are introduced.For the efficient removal of different kind of pollutions,researchers can select different ligands to construct membranes with specific pore size,hydrophily,salt or organic rejection ability and functional group.The ideas for the design and preparation of COF membranes are introduced.Finally,the future direction and challenges of the next generation of COF membranes in the field of separation are prospected.

关键词： Covalent organic frameworks Membrane materials Liquid phase separation Separation mechanism

Sparse Adversarial Learning for FDIA Attack Sample Generation in Distributed Smart

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Computer Modeling in engineering & Sciences 2024年第5期139卷 2095-2115页

作者： Fengyong Li Weicheng Shen Zhongqin Bi Xiangjing Su college of Computer Science and Technology Shanghai University of Electric PowerShanghai201306China college of electrical engineering Shanghai University of Electric PowerShanghai201306China

False data injection attack(FDIA)is an attack that affects the stability of grid cyber-physical system(GCPS)by evading the detecting mechanism of bad data.Existing FDIA detection methods usually employ complex neural networkmodels to detect FDIA attacks.However,they overlook the fact that FDIA attack samples at public-private network edges are extremely sparse,making it difficult for neural network models to obtain sufficient samples to construct a robust detection model.To address this problem,this paper designs an efficient sample generative adversarial model of FDIA attack in public-private network edge,which can effectively bypass the detectionmodel to threaten the power grid system.A generative adversarial network(GAN)framework is first constructed by combining residual networks(ResNet)with fully connected networks(FCN).Then,a sparse adversarial learning model is built by integrating the time-aligned data and normal data,which is used to learn the distribution characteristics between normal data and attack data through iterative confrontation.Furthermore,we introduce a Gaussian hybrid distributionmatrix by aggregating the network structure of attack data characteristics and normal data characteristics,which can connect and calculate FDIA data with normal characteristics.Finally,efficient FDIA attack samples can be sequentially generated through interactive adversarial learning.Extensive simulation experiments are conducted with IEEE 14-bus and IEEE 118-bus system data,and the results demonstrate that the generated attack samples of the proposed model can present superior performance compared to state-of-the-art models in terms of attack strength,robustness,and covert capability.

关键词： Distributed smart grid FDIA adversarial learning power public-private network edge

A Projection and Decomposition Approach for Multi-agent Coordinated Scheduling in Power Systems

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 991-996页

作者： Haifeng Qiu Zhigang Li Hongjun Gao Hung Dinh Nguyen Veerapandiyan Veerasamy Hoay Beng Gooi IEEE the School of electrical and Electronic engineering Nanyang Technological University School of electric Power engineering South China University of Technology the college of electrical engineering Sichuan University

Aiming at multi-agent coordinated scheduling problems in power systems under uncertainty, a generic projection and decomposition(P&D) approach is proposed in this letter. The canonical min-max-min two-stage robust optimization(TSRO) model with coupling constraints is equivalent to a concise robust optimization(RO) model in the version of mixed-integer linear programming(MILP) via feasible region projection. The decentralized decoupling of the non-convex MILP problem is realized through a dual decomposition algorithm, which ensures the fast convergence to a high-quality solution in the distributed optimization. Numerical tests verify the superior performance of the proposed P&D approach over the existing distributed TSRO method.

关键词： Uncertainty Couplings Power systems Optimization Computational modeling Convergence Processor scheduling

Non-intrusive Load Monitoring Based on Graph Total Variation for Residential Appliances

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 947-957页

作者： Xiaoyang Ma Diwen Zheng Xiaoyong Deng Ying Wang Dawei Deng Wei Li the college of electrical engineering Sichuan University State Grid Chongqing electric Power Company State Grid Sichuan electric Power Company State Grid Hubei electric Power Company Limited Research Institute

Non-intrusive load monitoring is a technique for monitoring the operating conditions of electrical appliances by collecting the aggregated electrical information at the household power inlet. Despite several studies on the mining of unique load characteristics, few studies have extensively considered the high computational burden and sample training. Based on lowfrequency sampling data, a non-intrusive load monitoring algorithm utilizing the graph total variation(GTV) is proposed in this study. The algorithm can effectively depict the load state without the need for prior training. First, the combined Kmeans clustering algorithm and graph signals are used to build concise and accurate graph structures as load models. The GTV representing the internal structure of the graph signal is introduced as the optimization model and solved using the augmented Lagrangian iterative algorithm. The introduction of the difference operator reduces the computing cost and addresses the inaccurate reconstruction of the graph signal. With low-frequency sampling data, the algorithm only requires a little prior data and no training, thereby reducing the computing cost. Experiments conducted using the reference energy disaggregation dataset and almanac of minutely power dataset demonstrated the stable superiority of the algorithm and its low computational burden.

关键词： Load monitoring Costs Home appliances Hidden Markov models Training Kernel Clustering algorithms

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

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Frontiers of Information Technology & Electronic engineering 2024年第2期25卷 214-224页

作者： Shanshan ZHENG Shuai LIU Licheng WANG college of Science University of Shanghai for Science and TechnologyShanghai200093China college of Automation engineering Shanghai University of Electric PowerShanghai200090China

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.

关键词： Distributed optimization Multi-agent systems Model-free adaptive control Event-triggered mechanism

Bi-level Multi-leader Multi-follower Stackelberg Game Model for Multi-energy Retail Package Optimization

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 225-237页

作者： Hongjun Gao Hongjin Pan Rui An Hao Xiao Yanhong Yang Shuaijia He Junyong Liu the college of electrical engineering Sichuan UniversityChengdu 610065China the electric Power Research Institute State Grid Jiangsu Electric Power CompanyNanjing 211100China the Institute of electrical engineering Chinese Academy of SciencesBeijing 100190China

In the competitive energy market,energy retailers are facing the uncertainties of both energy price and demand,which requires them to formulate reasonable energy purchasing and selling strategies for improving their competitiveness in this market.Particularly,the attractive multi-energy retail packages are the key for retailers to increase their benefit.Therefore,combined with incentive means and price signals,five types of multi-energy retail packages such as peak-valley time-of-use(TOU)price package and day-night bundled price package are designed in this paper for retailers.The iterative interactions between retailers and end-users are modeled using a bi-level model of stochastic optimization based on multi-leader multi-follower(MLMF)Stackelberg game,in which retailers are leaders and end-users are followers.Retailers make decisions to maximize the profit considering the conditional value at risk(CVaR)while end-users optimize the satisfaction of both energy comfort and economy.Besides,a distributed algorithm is proposed to obtain the Nash equilibrium of above MLMF Stackelberg game model while the particle swarm optimization(PSO)algorithm and CPLEX solver are applied to solve the optimization model for each participant(retailer or end-user).Numeral results show that the designed retail packages can increase the overall profit of retailers,and the overall satisfaction of industrial users is the highest while that of residential users is the lowest after game interaction.

关键词： Conditional value at risk(CVaR) energy retailer multi-energy retail package design multi-leader multi-follower(MLMF)Stackelberg game satisfaction

Double-ring high-frequency common-mode switching oscillation current sensor for inverter-fed machine winding insulation monitoring

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Global Energy Interconnection 2024年第1期7卷 106-116页

作者： Lingqing Pan Xizhou Du Xing Lei Ting Ye Dawei Xiang Hao Li college of electrical Power engineering Shanghai University of Electric PowerShanghai 200090P.R.China State Grid Shanghai Municipal electric Power Company Shanghai 200122P.R.China college of Electronics and Information engineering Tongji UniversityShanghai 201804P.R.China

Insulation failure significantly contributes to the unpredictable shutdown of power equipment.Compared to the partial discharge and high-frequency(HF)injection methods,the HF common-mode(CM)leakage current method offers a non-intrusive and highly sensitive alternative.However,the detection of HF CM currents is susceptible to interference from differential-mode(DM)currents,which exhibit high-amplitude and multifrequency components during normal operation.To address this challenge,this paper proposes a double-ring current sensor based on the principle of magnetic shielding for inverter-fed machine winding insulation monitoring.The inner ring harnesses the magnetic aggregation effect to isolate the DM current magnetic field,whereas the outer ring serves as the magnetic core of the Rogowski current sensor,enabling HF CM current monitoring.First,the magnetic field distributions of the CM and DM currents were analyzed.Then,a correlation between the sensor parameters and signal-to-noise ratio of the target HF CM current was established.Finally,an experimental study was conducted on a 3-kW PMSM for verification.The results indicate that the proposed double-ring HF CM sensor can effectively mitigate DM current interference.Compared to a single-ring sensor,a reduction of approximately 40%in the DM component was achieved,which significantly enhanced the precision of online insulation monitoring.

关键词： Magnetic shielding Double-ring Common-mode current Maxwell simulation