Detection of False Data Injection Attacks in Multi-Microgrid

In this thesis an Intrusion Detection System was developed to fight False Data Injection Attacks in Multi-Microgrids. Multi-Microgrids are a part of future power systems and they form the core part of critical infrastructure where resiliency and availability are exceedingly important. Severe consequences in the main power grid can happen if security is not taken into account. The Energy Management System has to be protected against cyber-attacks and one of the dire threats is a False Data Injection Attack. False Data Injections in Energy Management Systems are among the critical threats that need to be taken seriously as they can cause a major harm. In this thesis, the impact of a False Data Injection Attack on Multi-Microgrids and Energy Management Systems has been explored. It has also been researched how to detect these attacks by designing and developing a Multi-Microgrid model in MATLAB/Simulink for emulating the operation of Multi-Microgrid. The MATLAB/Simulink model simulates a Multi-Microgrid environment over the course of 24 hours. To detect False Data Injection Attacks from the data created in this simulation a Kalman Filter based Intrusion Detection System was developed. The Kalman Filter based Intrusion Detection System analyzes simulation data for possible False Data Injection Attacks. Further analysis was done based on the results of the Kalman Filter based Intrusion Detection System implementation. The implementation was tested with a set of attack simulations. The results analysis revealed that developed Kalman Filter based Intrusion Detection System is suitable for detecting simple attacks but it has low accuracy for complex intrusion attacks. With taking into account only the types of attacks the implementation was initially planned to detect the detection rate averaged to 87 %. The detection accuracy could be improved in future work by considering complex attack types early on in the implementation of the detection system. Securing power systems against malicious actors from causing harm or gaining financial benefits is a far-reaching research topic with plenty of future paths to explore. Kalman Filter based methods are one of the potential methods for detecting False Data Injection Attacks in Energy Management Systems. More research on Kalman Filter based protections is part of the ongoing race in protecting ourselves from cyber-attacks against critical infrastructure

Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts

The climate changes that are visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this book presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications such as hybrid and microgrid power systems based on energy internet, blockchain technology, and smart contracts, we hope that they are of interest to readers working in the related fields mentioned above

Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts-Volume II

The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications, such as hybrid and microgrid power systems based on the Energy Internet, Blockchain technology, and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

CINELDI Annual Report 2020

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