Deep Learning-Based Secure Transmission Strategy with Sensor-Transmission-Computing Linkage for Power Internet of Things

The automatic collection of power grid situation information, along with real-time multimedia interaction between the front and back ends during the accident handling process, has generated a massive amount of power grid data. While wireless communication offers a convenient channel for grid terminal access and data transmission, it is important to note that the bandwidth of wireless communication is limited. Additionally, the broadcast nature of wireless transmission raises concerns about the potential for unauthorized eavesdropping during data transmission. To address these challenges and achieve reliable, secure, and real-time transmission of power grid data, an intelligent security transmission strategy with sensor-transmission-computing linkage is proposed in this paper. The primary objective of this strategy is to maximize the confidentiality capacity of the system. To tackle this, an optimization problem is formulated, taking into consideration interruption probability and interception probability as constraints. To efficiently solve this optimization problem, a low-complexity algorithm rooted in deep reinforcement learning is designed, which aims to derive a suboptimal solution for the problem at hand. Ultimately, through simulation results, the validity of the proposed strategy in guaranteed communication security, stability, and timeliness is substantiated. The results confirm that the proposed intelligent security transmission strategy significantly contributes to the safeguarding of communication integrity, system stability, and timely data delivery.

Multi-source heterogeneous data access management framework and key technologies for electric power Internet of Things

The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.

RL and AHP-Based Multi-Timescale Multi-Clock Source Time Synchronization for Distribution Power Internet of Things

Time synchronization(TS)is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things(IoT).Multi-clock source time synchronization(MTS)has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales,and the coupling of synchronization latency jitter and pulse phase difference.In this paper,the multi-timescale MTS model is conducted,and the reinforcement learning(RL)and analytic hierarchy process(AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of synchronization latency jitter standard deviation and average pulse phase difference.Specifically,the multi-clock source selection is optimized based on Softmax in the large timescale,and the clock source weight calculation is optimized based on lower confidence bound-assisted AHP in the small timescale.Simulation shows that the proposed algorithm can effectively reduce time synchronization delay standard deviation and average pulse phase difference.

Architecture design and demand analysis on application layer of standard system for ubiquitous power Internet of Things

The ubiquitous power Internet of Things(UPIoT)is an intelligent service system with comprehensive state perception,efficient processing,and flexible application of information.It focuses on each link of the power system and makes full use of the mobile internet,artificial intelligence,and other advanced information and communication technologies in order to realize the inter-human interaction of all things in all links of the power system.This article systematically presents to the national and international organizations and agencies in charge of UPIoT layer standardization the status quo of the research on the Internet of Things(IoT)-related industry standards system.It briefly describes the generic standard classification methods,layered architecture,conceptual model,and system tables in the UPIoT application layer.Based on the principles of inheritance,innovation,and practicability,this study divides the application layer into customer service,power grid operation,integrated energy,and enterprise operation,emerging business and analyzes the standard requirements of these five fields.This study also proposes a standard plan.Finally,it summarizes the research report and provides suggestions for a follow-up work.

Advanced Sensors Towards Ubiquitous Power Internet of Things

The ubiquitous power Internet of Things(UPIoT)uses modern information technology and advanced communication technologies to realize interconnection and human-computer interaction in all aspects of the power system.UPIoT has the characteristics of comprehensive state perception and efficient information processing,and has broad application prospects for transformation of the energy industry.The fundamental facility of the UPIoT is the sensor-based information network.By using advanced sensors,Wireless Sensor Networks(WSNs),and advanced data processing technologies,Internet of Things can be realized in the power system.In this paper,a framework of WSNs based on advanced sensors towards UPIoT is proposed.In addition,the most advanced sensors for UPIoT purposes are reviewed,along with an explanation of how the sensor data obtained in UPIoT is utilized in various scenarios.

Distributed sensing and cooperative estimation/detection of ubiquitous power internet of things

The rapid development of Internet Plus Smart Energy requires further strengthening of three kinds of interconnections based on traditional power systems: physical interconnection, information interconnection, and commercial interconnection. Due to the integration of renewable energy, the reform of the electricity market, and the deployment of the Smart Grid, a large amount of data will be generated. Thus, it is necessary to establish a Ubiquitous Power Internet of Things (UPIoT) to realize connections among people and things, things and things, and people and people in power systems. This paper studies the concept and architecture of the UPIoT and indicates the deployment of the perception layer and network layer as the key to building UPIoT in the initial stage. As UPIoT tends to cover a wide area and produce massive and distributed data, signal processing and data analytics theories and techniques are needed to handle the data and observe the state of the large-scale system. Further studies on distributed sensing and cooperative estimation theories and techniques of UPIoT are also required. Finally, the application prospects of UPIoT and the directions for future research are discussed.

EdgeKeeper: a trusted edge computing framework for ubiquitous power Internet of Things

Ubiquitous power Internet of Things(IoT)is a smart service system oriented to all aspects of the power system,and has the characteristics of universal interconnection,human-computer interaction,comprehensive state perception,efficient information processing,and other convenient and flexible applications.It has become a hot topic in the field of IoT.We summarize some existing research work on the IoT and edge computing framework.Because it is difficult to meet the requirements of ubiquitous power IoT for edge computing in terms of real time,security,reliability,and business function adaptation using the general edge computing framework software,we propose a trusted edge computing framework,named“EdgeKeeper,”adapting to the ubiquitous power IoT.Several key technologies such as security and trust,quality of service guarantee,application management,and cloud-edge collaboration are desired to meet the needs of the edge computing framework.Experiments comprehensively evaluate EdgeKeeper from the aspects of function,performance,and security.Comparison results show that EdgeKeeper is the most suitable edge computing framework for the electricity IoT.Finally,future directions for research are proposed.

A power resource dispatching framework with a privacy protection function in the Power Internet of Things

Smart meters in the Power Internet of Things generate a large amount of power data.However,data privacy in the process of calculation,storage,and transmission is an urgent problem to be solved.Therefore,in this paper we propose a power resource dispatching framework(PRDF)with a privacy protection function,which uses a certificateless aggregate signcryption scheme based on cloud-fog cooperation.Using pseudonyms and aggregating users’power data,PRDF not only protects users’privacy,but also reduces the computing cost and communication overhead under traditional cloud computing.In addition,if the control center finds that a user has submitted abnormal data,it can send a request to the user management center to track the real identity of the user.Our scheme satisfies security requirements based on the random oracle model,including confidentiality and unforgeability.Furthermore,we compare our scheme with other certificateless aggregate signcryption schemes by simulations.Simulation results show that compared with traditional methods,our method performs better in terms of the computation cost.

Directed Acyclic Graph Blockchain for Secure Spectrum Sharing and Energy Trading in Power IoT

Peer-to-peer(P2P)spectrum sharing and energy trading are promising solutions to locally satisfy spectrum and energy demands in power Internet of Things(IoT).However,implementation of largescale P2P spectrum sharing and energy trading confronts security and privacy challenges.In this paper,we exploit consortium blockchain and Directed Acyclic Graph(DAG)to propose a new secure and distributed spectrum sharing and energy trading framework in power IoT,named spectrum-energy chain,where a set of local aggregators(LAGs)cooperatively confirm the identity of the power devices by utilizing consortium blockchain,so as to form a main chain.Then,the local power devices verify spectrum and energy micro-transactions simultaneously but asynchronously to form local spectrum tangle and local energy tangle,respectively.Moreover,an iterative double auction based micro transactions scheme is designed to solve the spectrum and energy pricing and the amount of shared spectrum and energy among power devices.Security analysis and numerical results illustrate that the developed spectrum-energy chain and the designed iterative double auction based microtransactions scheme are secure and efficient for spectrum sharing and energy trading in power IoT.

Progress and prospects of innovative coal-fired power plants within the energy internet

The development of electrical engineering and electronic, communications, smart power grid, and ultra-high voltage transmission technologies have driven the energy system revolution to the next generation: the energy internet. Progressive penetration of intermittent renewable energy sources into the energy system has led to unprecedented challenges to the currently wide use of coal-fired power generation technologies. Here, the applications and prospects of advanced coal-fired power generation technologies are analyzed. These technologies can be summarized into three categories:(1) large-scale and higher parameters coal-fired power generation technologies, including 620/650/700 oC ultra-supercritical thermal power and double reheat ultra-supercritical coal-fired power generation technologies;(2) system innovation and specific, highefficiency thermal cycles, which consist of renewable energy-aided coal-fired power generation technologies, a supercritical CO_2 Brayton cycle for coal-fired power plants, large-scale air-cooling coal-fired power plant technologies, and innovative layouts for waste heat utilization and enhanced energy cascade utilization;(3) coal-fired power generation combined with poly-generation technologies, which are represented by integrated gasification combined cycle(IGCC) and integrated gasification fuel cell(IGFC) technologies. Concerning the existing coal-fired power units, which are responsible for peak shaving, possible strategies for enhancing flexibility and operational stability are discussed. Furthermore, future trends for coal-fired power plants coupled with cyber-physical system(CPS) technologies are introduced. The development of advanced, coal-fired power generation technologies demonstrates the progress of science and is suitable for the sustainable development of human society.

用Power Builder建立基于Plugins方式的Internet应用

主要讨论用PowerBuilder6.x/7.x实现Internet应用的原理和方法 ,并以基于Plugins(插入件)的方式为例 ,说明了开发一个Internet应用的过程。

新型电力系统专用传感与边缘智能关键技术及其展望

电力物联网在电力系统的实时传感、透明感知与全局调控中发挥着重要作用。随着新型电力系统的不断演化,传统的设备传感与静态独立的智能系统难以应对多样化业务需求激增、多元化数据爆发式增长、传感器通信可靠性差与能效低下和算法模型迭代成本高等难题。因此,高度多元集成、绿色持续可靠、云边端深度协同的新型电力系统专用传感与边缘智能有望成为新范式。该文首先以新型电力系统专用传感与边缘智能的基本内涵为基础,构建了专用传感与边缘智能融合贯通的体系架构。然后重点阐述了国产化高频新型传感技术、绿色供能的高性能嵌入式芯片技术、高可靠性灵活组网技术、轻量化模型推理技术、云边协同资源共享技术和在线学习持续迭代技术。并进一步展望了专用传感与边缘智能在数据治理、隐私保护、软件定义硬件、业务-算力微服务、多层分布式泛在智能和电力大模型等发展方向,以期为新型电力系统建设提供参考。

一种基于NB-IoT的智能井盖监测系统设计

针对城市井盖保有量大、安全事故频发、人工巡检困难、管理组织混乱等问题,提出一种基于窄带物联网(NB-IoT)技术的窨井盖自动监测系统。该系统以STM32作为主控模块,包含倾角、水位等传感器,实现对井盖状态以及井内重点数据的采集,配合云端服务器和客户端完成井盖数据远程可视化显示。结果表明,所提系统可以实现故障井盖自动报警、精确定位,降低人工巡检的难度,让城市井盖管理更加智能化,让故障检修更加便捷化,提高城市管理的智能化水平。

高校思政教育网络话语权的构建研究

大学生的学习生活与网络密不可分,历经多年逐渐成为各种社会思潮和利益诉求的集散地,构建高校思想政治教育网络话语权是建设网络文化工作体系的需要,是发挥网络思政育人功能的需要。党和政府意识到提升高校思想政治教育网络话语权重要意义,构建高校思想政治教育网络话语权迫在眉睫。借助蒂姆·乔丹的网络权力理论,分析大学生思想政治教育网络话语权四个构建要素,需要从提高话语能力、改进话语方式、创新话语内容方面构建高校思想政治教育网络话语权。

改进PBFT算法的配电物联网接入认证方法

随着物联网与配电网深度融合,海量终端设备接入系统给配电物联网安全稳定运行带来巨大挑战。针对传统身份认证方式过于中心化且无法承载大规模终端等现状,设计一种基于区块链共识机制的配电物联网终端接入认证方法。由配电物联网网关负责对待接入终端节点登记注册,采用共识算法进行分布式认证,将合法终端上链存储。在传统PBFT算法的基础上,设计了配电物联网终端共识算法。该算法引入权重机制,根据终端节点权重选取认证节点,缩小共识规模;引入可验证随机函数增强主节点安全,避免启动视图切换协议,提高共识效率;结合实际应用场景优化一致性协议,降低通信开销。实验分析表明该方法可有效规避多种网络攻击,通信开销和吞吐量优于其他方法,系统抗攻击性较强,满足配电物联网对认证效率和系统可靠性等要求。

电能路由器电气安全风险解析与关键试验研究

电能路由器是未来能源互联网的核心装备,但尚无对于其电气安全方面的测试标准。本文对于电能路由器风险源可能存在的情况进行了详尽的分类解析;重点针对电气安全列出了安全检测项目和指标,给出了电能路由器的测试系统,并根据应用场景制订了测试工况。

互联网背景下电力电子技术教学创新之路研究

互联网背景下,电力电子技术教学呈现出了智能化、多元化和多媒体化。首先,根据实际情况分析可得,电力电子技术的教学创新应进一步贴合课堂服务,进一步抓好情境服务,进一步应用新资源,完善新技术服务课堂、新情境服务教学和新资源服务发展。其次,通过创新化、制度化和效益化逐步解决学校教育教学模式中所存在的一些不足和问题。教学方面存在的问题包括教学观念的滞后、人才建设的落后和软硬件的落后。最后,希望通过以下方法的改进能更好地为课程服务,即多元化教学管理,塑品牌形象;多面化队伍建设,强教学质效;多方位软硬件提升,增教学内涵等方法的改进能更好的为课程服务,不断增强学生群体对电力电子实践的理解和操作能力,更好地培养满足社会和企业要求的复合型人才。

高校思政教育的网络话语权研究——基于问题诊断

互联网的不断普及对人们产生了重大影响。网络能够让大学生轻易获取很多信息,也改变了他们的生活、学习和交往方式。正因如此,高校要充分利用好网络平台对大学生进行思想政治教育,发挥出积极重要作用。构建高校思想政治教育网络话语权是顺应时代之变,对接时代之需,有重大意义和深远作用。高校需要聚焦主要任务,直面突出问题,深刻全面剖析现实之问,坚持守正创新,强化思想观念,完善工作举措,主动积极作好实践之答。

影响大学生思想政治教育网络话语权的因素分析

普及的网络已经成为新形势下高校思想政治教育的重要场域,要切实加强大学生思想政治工作,就得充分利用好网络,发挥出网络思政重要作用,传播马克思主义科学理论,弘扬中国特色社会主义建设的主旋律,打赢思想政治教育网络话语权主动仗,引导大学生牢固树立社会主义核心价值观。高校要因势而谋,梳理网络话语权的发展,阐释网络话语权的内涵和意义,分析影响大学生思想政治教育网络话语权的因素,统筹联动相互促进,引领网络意识形态发展的正确方向。

数字时代的“表达”:算法推荐的信息干预及其法治化因应

算法正位于生活的中心,算法推荐服务所带来的隐性信息干预隐含着侵蚀表达自由的风险。数字时代“表达”的结构已发生更迭,保护“表达”所依赖的信息基础尤为重要。算法推荐领域保护“表达”的二阶规范渊源分别为契约与立法,契约责任面临有限的意思自治与公法属性权利让渡的悖论,走向“算法治理”的立法规制则面临执行的困境。宪法基本权利第三人效力及我国社会主义性质宪法“合作的基本权利”结构为宪法基本权利条款的介入提供了法理依据。宪法为划定政府、平台责任边界提供根本依据,宪法基本权利条款的新内涵能够指导规则体系的生成及运行,有利于形成统一的法秩序。将算法推荐规则纳入合宪性审查、备案审查的制度体系内,能够实现平台权力与国家权力的衔接统合。