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.

Research on Equivalent Modeling Method of AC-DC Power Networks Integrating with Renewable Energy Generation

Along with the increasing integration of renewable energy generation in AC-DC power networks,investigating the dynamic behaviors of this complex system with a proper equivalent model is significant.This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator(DFIG)based wind farms to decrease the simulation scale and computational burden.For the AC-DC power networks,the equivalent modeling strategy in accordance with the physical structure simplification is stated.Regarding the DFIG-based wind farms,the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo search algorithm(ICCSA)is conducted.In light of the MATLAB simulation platform,a two-zone four-DC interconnected power grid with wind farms is built to check the efficacy of the proposed equivalentmodelingmethod.Fromthe simulation analyses and comparative validation in different algorithms and cases,the proposed method can precisely reflect the steady and dynamic performance of the demonstrated system under N-1 and N-2 fault scenarios,and it can efficiently achieve the parameter identification of the wind farms and fulfill the equivalent modeling.Consequently,the proposed approach’s effectiveness and suitability are confirmed.

Computing Power Network:The Architecture of Convergence of Computing and Networking towards 6G Requirement

In 6G era,service forms in which computing power acts as the core will be ubiquitous in the network.At the same time,the collaboration among edge computing,cloud computing and network is needed to support edge computing service with strong demand for computing power,so as to realize the optimization of resource utilization.Based on this,the article discusses the research background,key techniques and main application scenarios of computing power network.Through the demonstration,it can be concluded that the technical solution of computing power network can effectively meet the multi-level deployment and flexible scheduling needs of the future 6G business for computing,storage and network,and adapt to the integration needs of computing power and network in various scenarios,such as user oriented,government enterprise oriented,computing power open and so on.

Application of Interval Algorithm in Rural Power Network Planning

Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization results of rural power network planning. To solve the problems, the interval algorithm was used to modify the initial search method of uncertainty load mathematics model in rural network planning. Meanwhile, the genetic/tabu search combination algorithm was adopted to optimize the initialized network. The sample analysis results showed that compared with the certainty planning, the improved method was suitable for urban medium-voltage distribution network planning with consideration of uncertainty load and the planning results conformed to the reality.

Research of Rural Power Network Reactive Power Optimization Based on Improved ACOA

In view of the serious reactive power loss in the rural network, improved ant colony optimization algorithm （ACOA） was used to optimize the reactive power compensation for the rural distribution system. In this study, the traditional ACOA was improved in two aspects： one was the local search strategy, and the other was pheromone mutation and re-initialization strategies. The reactive power optimization for a county＇s distribution network showed that the improved ACOA was practicable.

Improved fault location method for AT traction power network based on EMU load test

The autotransformer(AT)neutral current ratio method is widely used for fault location in the AT traction power network.With the development of high-speed electrified railways,a large number of data show that the relation between the AT neutral current ratio and the distance from the beginning of the fault AT section to the fault point(Q-L relation)is mostly nonlinear.Therefore,the linear Q-L relation in the traditional fault location method always leads to large errors.To solve this problem,a large number of load-related current data that can be used to describe the Q-L relation are obtained through the load test of the electric multiple unit(EMU).Thus,an improved fault location method based on the back propagation(BP)neural network is proposed in this paper.On this basis,a comparison between the improved method and the traditional method shows that the maximum absolute error and the average absolute error of the improved method are 0.651 km and 0.334 km lower than those of the traditional method,respectively,which demonstrates that the improved method can effectively eliminate the influence of nonlinear factors and greatly improve the accuracy of fault location for the AT traction power network.Finally,combined with a shortcircuit test,the accuracy of the improved method is verified.

Power Network Lightning Accident Quick Inquiry with the Lightning Location System

目前，闪电是 10 自然灾难之一，并且它也是力量打断的最高的环境因素。它经常引起巨大的损失到电的系统。自从 1980 年代末，中国和科技的 Huazhong 大学的州的格子公司的武汉高电压研究所一直在研究并且发展中闪电地点系统(LLS ) 。在 mid-1990s，一个闪电察觉网络在中国在 29 个省和城市被创造。很快发现闪电事故首先被使用，还原剂它极大地驱动打断。另外，它保证高效率和电系统的安全操作。显著利益被完成。中国的 LLS 通过了一“放的取向 - 放的时差 - 综合的放”开发过程。放的精确，察觉效率，自动化的学位，有实行可能和应用范围被改进。另外，国家网络的一个闪电信息系统计划被实现了，它满足整个协会。

Comparison of Three Modes of AT-fed Traction Power Networks

The features of three modes of AT-fed traction power networks (TPNs) have been briefly described in the existing literature, which is not adequate yet. In this paper, these three modes of TPNs are compared mainly on TPN capacity, transformer capacity, rail potential and voltage level, etc., and conclusions are drawn.

Fault Diagnosis Based on Graph Theory and Linear Discriminant Principle in Electric Power Network

In this paper, we adopt a novel topological approach to fault diagnosis. In our researches, global information will be introduced into electric power network, we are using mainly BFS of graph theory algorithms and linear discriminant principle to resolve fast and exact analysis of faulty components and faulty sections, and finally accomplish fault diagnosis. The results of BFS and linear discriminant are identical. The main technical contributions and innovations in this paper include, introducing global information into electric power network, developing a novel topological analysis to fault diagnosis. Graph theory algorithms can be used to model many different physical and abstract systems such as transportation and communication networks, models for business administration, political science, and psychology and so on. And the linear discriminant is a procedure used to classify an object into one of several a priori groupings dependent on the individual characteristics of the object. In the study of fault diagnosis in electric power network, graph theory algorithms and linear discriminant technology must also have a good prospect of application.