Fortifying Smart Grids: A Holistic Assessment Strategy against Cyber Attacks and Physical Threats for Intelligent Electronic Devices

Intelligent electronic devices(IEDs)are interconnected via communication networks and play pivotal roles in transmitting grid-related operational data and executing control instructions.In the context of the heightened security challenges within smart grids,IEDs pose significant risks due to inherent hardware and software vulner-abilities,as well as the openness and vulnerability of communication protocols.Smart grid security,distinct from traditional internet security,mainly relies on monitoring network security events at the platform layer,lacking an effective assessment mechanism for IEDs.Hence,we incorporate considerations for both cyber-attacks and physical faults,presenting security assessment indicators and methods specifically tailored for IEDs.Initially,we outline the security monitoring technology for IEDs,considering the necessary data sources for their security assessment.Subsequently,we classify IEDs and establish a comprehensive security monitoring index system,incorporating factors such as running states,network traffic,and abnormal behaviors.This index system contains 18 indicators in 3 categories.Additionally,we elucidate quantitative methods for various indicators and propose a hybrid security assessment method known as GRCW-hybrid,combining grey relational analysis(GRA),analytic hierarchy process(AHP),and entropy weight method(EWM).According to the proposed assessment method,the security risk level of IEDs can be graded into 6 levels,namely 0,1,2,3,4,and 5.The higher the level,the greater the security risk.Finally,we assess and simulate 15 scenarios in 3 categories,which are based on monitoring indicators and real-world situations encountered by IEDs.The results show that calculated security risk level based on the proposed assessment method are consistent with actual simulation.Thus,the reasonableness and effectiveness of the proposed index system and assessment method are validated.

Teaching Protective Relaying Design and Application Using New Modeling and Simulation Tools

As the smart grid concepts are emphasized lately, the need to modernize the power engineering education is also well recognized. This paper presents a set of newly developed modeling, simulation and testing tools aimed at better understanding of the design concept and related applications for protective relaying and substation automation solutions for the smart grid. Since the smart grid applications require integration of data from multiple IEDs （intelligent electronic devices）, understanding properties of each IED type in detail, as well as their responses to the power system events is needed. In addition, understanding the communication requirements to perform data integration is also important. To illustrate how the mentioned smart grid issues may be taught, the following advanced teaching approaches are presented： （1） Use of modeling and simulation means to better understand interaction between the relays and power system; （2） Use of IED test facilities to better understand performance of physical devices used for protection, monitoring and control; （3） Utilization of communication network modeling tools to simulate the communication network within SAS （substation automation system）. Examples showing the use of proposed techniques for teaching the fundamentals and applications are presented. The examples demonstrate the adequacy and efficiency of the proposed techniques.

Adaptive Fault Detection Based on Neural Networks and Multiple Sampling Points for Distribution Networks and Microgrids

Smart networks such as active distribution network(ADN)and microgrid(MG)play an important role in power system operation.The design and implementation of appropriate protection systems for MG and ADN must be addressed,which imposes new technical challenges.This paper presents the implementation and validation aspects of an adaptive fault detection strategy based on neural networks(NNs)and multiple sampling points for ADN and MG.The solution is implemented on an edge device.NNs are used to derive a data-driven model that uses only local measurements to detect fault states of the network without the need for communication infrastructure.Multiple sampling points are used to derive a data-driven model,which allows the generalization considering the implementation in physical systems.The adaptive fault detector model is implemented on a Jetson Nano system,which is a single-board computer(SBC)with a small graphic processing unit(GPU)intended to run machine learning loads at the edge.The proposed method is tested in a physical,real-life,low-voltage network located at Universidad del Norte,Colombia.This testing network is based on the IEEE 13-node test feeder scaled down to 220 V.The validation in a simulation environment shows the accuracy and dependability above 99.6%,while the real-time tests show the accuracy and dependability of 95.5%and 100%,respectively.Without hard-to-derive parameters,the easy-to-implement embedded model highlights the potential for real-life applications.

Operational Control of Low-voltage MTDC Systems in a Cyber-physical Environment

Based on the standardized cyber-physical modeling and communication system-IEC 61850,this paper establishes the operational control architecture of a low-voltage multi-terminal DC(LV-MTDC)system.The coordinated operational control strategies,including power electronic transformer(PET),and voltage source converter(VSC),are proposed.Then a cyberphysical model of the system based on IEC 61850 is built,according to the application requirements of operational control in the LV-MTDC system.On this basis,the implementation method of system operational control based on IEC 61850 is proposed,including the software/hardware design of the intelligent electronic device(IED),dispatching operations and uninterrupted power supply.The simulation environment is further built to verify the system operational control technology,and the test platform is used to carry out the actual tests.The research results show that the operational control technology for the LV-MTDC system proposed in this paper is feasible,which can guarantee the rapid and accurate information exchange of control commands and settings,and thus effectively realize the operational control of the LV-MTDC system under complex conditions.