Optimization of Stealthwatch Network Security System for the Detection and Mitigation of Distributed Denial of Service (DDoS) Attack: Application to Smart Grid System

The Smart Grid is an enhancement of the traditional grid system and employs new technologies and sophisticated communication techniques for electrical power transmission and distribution. The Smart Grid’s communication network shares information about status of its several integrated IEDs (Intelligent Electronic Devices). However, the IEDs connected throughout the Smart Grid, open opportunities for attackers to interfere with the communications and utilities resources or take clients’ private data. This development has introduced new cyber-security challenges for the Smart Grid and is a very concerning issue because of emerging cyber-threats and security incidents that have occurred recently all over the world. The purpose of this research is to detect and mitigate Distributed Denial of Service [DDoS] with application to the Electrical Smart Grid System by deploying an optimized Stealthwatch Secure Network analytics tool. In this paper, the DDoS attack in the Smart Grid communication networks was modeled using Stealthwatch tool. The simulated network consisted of Secure Network Analytic tools virtual machines (VMs), electrical Grid network communication topology, attackers and Target VMs. Finally, the experiments and simulations were performed, and the research results showed that Stealthwatch analytic tool is very effective in detecting and mitigating DDoS attacks in the Smart Grid System without causing any blackout or shutdown of any internal systems as compared to other tools such as GNS3, NeSSi2, NISST Framework, OMNeT++, INET Framework, ReaSE, NS2, NS3, M5 Simulator, OPNET, PLC & TIA Portal management Software which do not have the capability to do so. Also, using Stealthwatch tool to create a security baseline for Smart Grid environment, contributes to risk mitigation and sound security hygiene.

Sparse Adversarial Learning for FDIA Attack Sample Generation in Distributed Smart

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.

A Distributed Power Trading Scheme Based on Blockchain and Artificial Intelligence in Smart Grids

As an emerging hot technology,smart grids(SGs)are being employed in many fields,such as smart homes and smart cities.Moreover,the application of artificial intelligence(AI)in SGs has promoted the development of the power industry.However,as users’demands for electricity increase,traditional centralized power trading is unable to well meet the user demands and an increasing number of small distributed generators are being employed in trading activities.This not only leads to numerous security risks for the trading data but also has a negative impact on the cost of power generation,electrical security,and other aspects.Accordingly,this study proposes a distributed power trading scheme based on blockchain and AI.To protect the legitimate rights and interests of consumers and producers,credibility is used as an indicator to restrict untrustworthy behavior.Simultaneously,the reliability and communication capabilities of nodes are considered in block verification to improve the transaction confirmation efficiency,and a weighted communication tree construction algorithm is designed to achieve superior data forwarding.Finally,AI sensors are set up in power equipment to detect electricity generation and transmission,which alert users when security hazards occur,such as thunderstorms or typhoons.The experimental results show that the proposed scheme can not only improve the trading security but also reduce system communication delays.

Load distribution model and voltage static profile of Smart Grid

Voltage profiles of feeders with the connection of distributed generations(DGs) were investigated.A unified typical load distribution model was established.Based on this model,exact expressions of feeder voltage profile with single and double DGs were derived and used to analyze the impact of DG's location and capacity on the voltage profile quantitatively.Then,a general formula of the voltage profile was derived.The limitation of single DG and necessity of multiple DGs for voltage regulation were also discussed.Through the simulation,voltage profiles of feeders with single and double DGs were compared.The voltage excursion rate is 7.40% for only one DG,while 2.48% and 2.36% for double DGs.It is shown that the feeder voltage can be retained in a more appropriate range with multiple DGs than with only one DG.Distributing the total capacity of DGs is better than concentrating it at one point.

Grid tie inverter energy stabilizing in smart distribution grid with energy storage

With the growing deployment of smart distribution grid,it has become urgent to investigate the smart distribution grid behavior during transient faults and improve the system stability.The feasibility of segmenting large power grids and multiple smart distribution grids interconnections using energy storage technology for improving the system dynamic stability was studied.The segmentation validity of the large power grids and smart distribution grid inverter output interconnections power system using energy storage technology was proved in terms of theoretical analysis.Then,the influences of the energy storage device location and capacity on the proposed method were discussed in detail.The conclusion is obtained that the ESD optimal locations are allocated at the tie line terminal buses in the interconnected grid,respectively.The effectiveness of the proposed method was verified by simulations in an actual power system.

A Perspective on the Future of Distribution: Smart Grids, State of the Art, Benefits and Research Plans

Currently, the design and operation criteria for electrical distribution networks are fastly changing due to some factors;among these, the progressive penetration of Distributed Generation (DG) is destined to cause deep changes in the existing networks, no longer considered as passive terminations of the whole electrical system. Moreover, the increasing application of Information Communication Technologies (ICT) will allow the implementation of the so called “smart grids”, determining new interesting scenarios. In the paper the problems and the potential benefits of DG, the possible new electrical distribution system models and the major research projects on smart grids are faced and reported.

Distribution System Reliability Analysis for Smart Grid Applications

Reliability of power systems is a key aspect in modern power system planning, design, and operation. The ascendance of the smart grid concept has provided high hopes of developing an intelligent network that is capable of being a self-healing grid, offering the ability to overcome the interruption problems that face the utility and cost it tens of millions in repair and loss. In this work, we will examine the effect of the smart grid applications in improving the reliability of the power distribution networks. The test system used in this paper is the IEEE 34 node test feeder, released in 2003 by the Distribution System Analysis Subcommittee of the IEEE Power Engineering Society. The objective is to analyze the feeder for the optimal placement of the automatic switching devices and quantify their proper installation based on the performance of the distribution system. The measures will be the changes in the reliability system indices including SAIDI, SAIFI, and EUE. In addition, the goal is to design and simulate the effect of the installation of the Distributed Generators (DGs) on the utility’s distribution system and measure the potential improvement of its reliability.

Research on IPv6 Transition Evolvement and Security Architecture of Smart Distribution Grid Data Communication System

Smart distribution grid needs data communication systems as a support to complete their important functions. The smart distribution grid of the data and information are increasingly adopting internet protocol and Ethernet technology. The IP addresses are more and more important for the smart distribution grid equipment. The current IPv4 protocol occupies a dominant position; therefore, the challenges of the evolution to IPv6 and network security are faced by data communication systems of the smart distribution grid. The importance of data communications network and its main bearer of business were described. The data communications network from IPv4 to IPv6 evolution of the five processes and four stages of the transition were analyzed. The smart distribution grid data communications network security and types of their offensive and defensive were discussed. And the data communications network security architecture was established. It covers three dimensions, the security level, the communications network security engineering and the communications network security management. The security architecture safeguards the evolution to IPv6 for the smart distribution grid data communication systems.

Analysis of Distributed Generation Systems, Smart Grid Technologies and Future Motivators Influencing Change in the Electricity Sector

The global Electricity Sector and its customers are faced with a number of challenges that are unparalleled since the advent of widespread electrification. Challenges including climate change, escalating energy prices, energy security and energy efficiency are converging to drive fundamental change in the way energy is produced, delivered and utilized. The electricity system of the future must produce and distribute electricity that is reliable, affordable and clean. To accomplish these goals, both the electricity grid and the existing regulatory system must be smarter. This paper explores smart grid technologies, distributed generation systems, R & D efforts across Europe and the United States, and technical, economical and regulatory barriers facing modern utilities.

Serverless distributed learning for smart grid analytics

The digitization,informatization,and intelligentization of physical systems require strong support from big data analysis.However,due to restrictions on data security and privacy and concerns about the cost of big data collection,transmission,and storage,it is difficult to do data aggregation in real-world power systems,which directly retards the effective implementation of smart grid analytics.Federated learning,an advanced distributed learning method proposed by Google,seems a promising solution to the above issues.Nevertheless,it relies on a server node to complete model aggregation and the framework is limited to scenarios where data are independent and identically distributed.Thus,we here propose a serverless distributed learning platform based on blockchain to solve the above two issues.In the proposed platform,the task of machine learning is performed according to smart contracts,and encrypted models are aggregated via a mechanism of knowledge distillation.Through this proposed method,a server node is no longer required and the learning ability is no longer limited to independent and identically distributed scenarios.Experiments on a public electrical grid dataset will verify the effectiveness of the proposed approach.

Optimal Partitioning of Distribution Networks for Micro-Grid Operation

A great concern for the modern distribution grid is how well it can withstand and respond to adverse conditions. One way that utilities are addressing this issue is by adding redundancy to their systems. Likewise, distributed generation (DG) is becoming an increasingly popular asset at the distribution level and the idea of microgrids operating as standalone systems apart from the bulk electric grid is quickly becoming a reality. This allows for greater flexibility as systems can now take on exponentially more configurations than the radial, one-way distribution systems of the past. These added capabilities, however, make the system reconfiguration with a much more complex problem causing utilities to question if they are operating their distribution systems optimally. In addition, tools like Supervisory Control and Data Acquisition (SCADA) and Distribution Automation (DA) allow for systems to be reconfigured faster than humans can make decisions on how to reconfigure them. As a result, this paper seeks to develop an automated partitioning scheme for distribution systems that can respond to varying system conditions while ensuring a variety of operational constraints on the final configuration. It uses linear programming and graph theory. Power flow is calculated externally to the LP and a feedback loop is used to recalculate the solution if a violation is found. Application to test systems shows that it can reconfigure systems containing any number of loops resulting in a radial configuration. It can connect multiple sources to a single microgrid if more capacity is needed to supply the microgrid’s load.

Matlab Code to Assess the Reliability of the Smart Power Distribution System Using Monte Carlo Simulation

Reliability of power systems is a key aspect in modern power system planning, design, and operation. The ascendance of the smart grid concept has provided high hopes of developing an intelligent network that is capable of being a self-healing grid, offering the ability to overcome the interruption problems that face the utility and cost it tens of millions in repair and loss. In this work, we develop a MATLAB code to examine the effect of the smart grid applications in improving the reliability of the power distribution networks via Monte Carlo Simulation approach. The system used in this paper is the IEEE 34 test feeder. The objective is to measure the installations of the Automatic Reclosers (ARs) as well as the Distributed Generators (DGs) on the reliability indices, SAIDI, SAIFI, CAIDI and EUE, and make comparisons with results from a previous study done by the authors using another approach. The MATLAB code should provide close results to the output of the previous research to verify its effectiveness.

Optimal Power Flow Approach for Cognitive and Reliable Operation of Distributed Generation as Smart Grid

Smart grid expertise emphasises on the compound connections of the electricity to the grid, along with computing, control and communication interface. It will bring together in future smart infrastructure for power system. Investigating these complex dynamic interactions is crucial for the efficiency and robustness of the emerging smart grid. In particular, it is one of the key elements for smart-grids to establish the dynamics among sources of grid. This paper proposes the vital operation of renewable energy sources (RES) like Solar Photovoltaic (PV), wind energy with existing grid of a. c. network of power system in view of cognitive reliable operation of RES as add-on source of power. The research presents sequence of operation of these sources by optimal power flow based on power flow chart for demand side management as a smart grid of power system. The system fulfils realistic operation for power system, based on fundamentals of power system, therefore a necessary research topology is developed, for well-regarded schemes of RES for setting up a pilot model so that demand side load should not be hampered and same is verified for linear and non-linear loads of electrical networks.

Impact of Distributed Generation on Smart Grid Transient Stability

In the 21st century Smart Grid and Renewable Energy technologies are an important issue with regards to global climate change problem and energy security. The evolution of current conventional or centralized generation in form of distributed generation and Smart Power Grid (SPG) has great opportunity and potentially can eradicate several issues associated with energy efficiency, energy security and the drawback of aging power system infrastructures. In order to meet the rising electrical power demand and increasing service quality as well as reducing pollution, the existing power grid infrastructure should be developed into Smart Grid (SG) that is flexible for interconnectivity with the distributed generation. However, integrating distributed generation to power system causes several technical issues especially system stability. To make the power grid become “smarter”, particularly in terms of stability, Flexible AC Transmission System (FACTS) device especially Static VAR Compensator (SVC) is used. This paper explores Smart Grid technologies and distributed generation systems. Furthermore, it discusses the impact of distributed generation on Smart Grid, particularly its system stability after installing distributed generation in the Smart Grid. This was done by examining the system stability during interconnection and faults on the system and validated with Dig-SILENT Power Factory Software V 13.2.

Requirements and Proposed Solutions for Future Smart Distribution Substations

This paper proposes a novel solution for the secondary system of a primary distribution substation. First an evaluation is made of the changes that are to be expected for distribution substations in the future. Distributed generation, electric vehicles and other active resources will change the behavior of the distribution network in a manner that will have a great deal of implications for distribution substations. The question is how the role of the distribution substations will change when the visions of smart grids become reality. The proposed solution consists of bay level protection and control IEDs forming the backbone of the secondar？, system. The functionality is complemented with a substation level Station Computer, providing value added and advanced functionality. In addition required communication and time synchronization methods are presented. A life cycle cost evaluation is also performed on the proposed solution, and it is compared with the current dominant concept based exclusively on bay level devices.

Smart Grids with Intelligent Periphery:An Architecture for the Energy Internet

A future smart grid must fulfill the vision of the Energy Internet in which millions of people produce their own energy from renewables in their homes, offices, and factories and share it with each other. Electric vehicles and local energy storage will be widely deployed. Internet technology will be utilized to transform the power grid into an energysharing inter-grid. To prepare for the future, a smart grid with intelligent periphery, or smart GRIP, is proposed. The building blocks of GRIP architecture are called clusters and include an energy-management system （EMS）-controlled transmission grid in the core and distribution grids, micro-grids, and smart buildings and homes on the periphery; all of which are hierarchically structured. The layered architecture of GRIP allows a seamless transition from the present to the future and plug-and-play interoperability. The basic functions of a cluster consist of （1） dispatch, （2） smoothing, and （3） mitigation. A risk-limiting dispatch methodology is presented; a new device, called the electric spring, is developed for smoothing out fluctuations in periphery clusters; and means to mitigate failures are discussed.

Effect of electromagnetic disturbance on the practical QKD system in the smart grid

To improve the security of the smart grid, quantum key distribution（QKD） is an excellent choice. The rapid fluctuations on the power aerial optical cable and electromagnetic disturbance in substations are two main challenges for implementation of QKD. Due to insensitivity to birefringence of the channel, the stable phase-coding Faraday–Michelson QKD system is very practical in the smart grid. However, the electromagnetic disturbance in substations on this practical QKD system should be considered. The disturbance might change the rotation angle of the Faraday mirror, and would introduce an additional quantum bit error rate（QBER）. We derive the new fringe visibility of the system and the additional QBER from the electromagnetic disturbance. In the worst case, the average additional QBER only increases about 0.17% due to the disturbance, which is relatively small to normal QBER values. We also find the way to degrade the electromagnetic disturbance on the QKD system.

Integrating Smart Building Energy Data into Smart Grid Applications in the Intelligent Secondary Substations

Automation has arrived in the low voltage grid domain. In the next few years, the secondary substation—at the barriers of medium and low voltage grids—will thus be upgraded to enable novel functions. In this paper, we present various smart grid applications running on such intelligent secondary substations(iSSN) including their interaction with each other. We integrate energy consumption and production data, as well as forecasts, sensed from the smart buildings’ energy management systems(BEMSs) into the operation of the low voltage grid. A suitable framework for those modular applications includes features to initiate their installation, update, removal, the remote operator site, and not requiring staff on-site for such typical reappearing maintenance tasks.

On the Communication Requirements for the Smart Grid

The current power grid is facing many challenges that it was not designed or engineered to handle which range from congestions and major blackouts to the overwhelming increase in demand and security concerns. The current electric grid was established before the 1960’s. It is believed that the electric grid is the most complex and gigantic machine ever made in human history;it consists of wires, cables, towers, transformers and circuit breakers installed together in outdated manner. During the 60’s, computers and sensors were used to monitor and slightly control the grid;however, fifty years later these sensors are considered less than ideal. Presented here is a review of the smart grid communication network in terms of configuration, bandwidth and latency requirements as well as the technology used. We simulate the access layer of the smart grid net-work and show that no single available communication technology can be used for all layers of the smart grid;thus, different technologies for different layers are needed. A new protocol for optimizing the smart grid is recommended.

Aggregator Based RPL for an IoT-Fog Based Power Distribution System with 6LoWPAN

Advanced Metering Infrastructure(AMI)forms an important part in Smart Grids.Routing the data effectively from smart meters to the Edge/Fog node requires an efficient routing protocol.Routing Protocol for Low Power Lossy Area Network(RPL)is a standard routing protocol for IPv6 over Low Power Personal Area Network(6LoWPAN).In a Power Distribution system all the smart meters together form 6LoWPAN network.They communicate with the fog router,which acts as the 6LoWPAN gateway.ContikiRPL was evaluated using Cooja Network simulator for a power distribution network topology.The nodes which were far away from the fog node gave low Packet Delivery Ratio(PDR)and large End to End delay.This paper proposes an aggregation RPL scheme by modifying the existing Contiki RPL.The smart meter nodes communicate to the aggregator,which communicates to the fog node.The results show that the aggregation scheme has 35.6%increase in PDR,lesser hop count and 13.24%decrease in End to End delay on an average compared to existing RPL.