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.

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.

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.

A CPK-Based Identity Authentication Scheme for IoT

As the power Internet of Things(IoT)enters the security construction stage,the massive use of perception layer devices urgently requires an identity authentication scheme that considers both security and practicality.The existing public key infrastructure(PKI)-based security authentication scheme is currently difficult to apply in many terminals in IoT.Its key distribution and management costs are high,which hinders the development of power IoT security construction.Combined Public Key(CPK)technology uses a small number of seeds to generate unlimited public keys.It is very suitable for identity authentication in the power Internet of Things.In this paper,we propose a novel identity authentication scheme for power IoT.The scheme combines the physical unclonable function(PUF)with improved CPK technology to achieve mutual identity authentication between power IoT terminals and servers.The proposed scheme does not require third-party authentication and improves the security of identity authentication for power IoT.Moreover,the scheme reduces the resource consumption of power IoT devices.The improved CPK algorithm solves the key collision problem,and the third party only needs to save the private key and the public key matrix.Experimental results show that the amount of storage resources occupied in our scheme is small.The proposed scheme is more suitable for the power IoT.