29 research outputs found

    Assessing the Cyber Threat Landscape for Virtual Power Plants

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    Virtual Power Plants (VPPs) aggregate and coordinate Distributed Energy Resources (DER) as a single entity aiding in decarbonization of the energy generation mix. The infrastructure of VPPs relies heavily on rigorous and accurate exchange of information between the DER and the VPP, as well as other grid entities. This exposes them to possible cyber threats that impede their functions and can have negative impacts on the stability and reliability of the grid. In this paper, the threat landscape is evaluated against threats that affect VPPs. A heuristic method of assessing the impact and likelihood of attacks is constructed based on a) proposed methods in literature, b) standardization bodies, and c) in relation to a VPPs security profile. Our findings indicate that False Data Injection attacks are posing the greatest risk, competing with disruption of their functions due to Denial of Service

    Machine Learning based Anomaly Detection for Cybersecurity Monitoring of Critical Infrastructures

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    openManaging critical infrastructures requires to increasingly rely on Information and Communi- cation Technologies. The last past years showed an incredible increase in the sophistication of attacks. For this reason, it is necessary to develop new algorithms for monitoring these infrastructures. In this scenario, Machine Learning can represent a very useful ally. After a brief introduction on the issue of cybersecurity in Industrial Control Systems and an overview of the state of the art regarding Machine Learning based cybersecurity monitoring, the present work proposes three approaches that target different layers of the control network architecture. The first one focuses on covert channels based on the DNS protocol, which can be used to establish a command and control channel, allowing attackers to send malicious commands. The second one focuses on the field layer of electrical power systems, proposing a physics-based anomaly detection algorithm for Distributed Energy Resources. The third one proposed a first attempt to integrate physical and cyber security systems, in order to face complex threats. All these three approaches are supported by promising results, which gives hope to practical applications in the next future.openXXXIV CICLO - SCIENZE E TECNOLOGIE PER L'INGEGNERIA ELETTRONICA E DELLE TELECOMUNICAZIONI - Elettromagnetismo, elettronica, telecomunicazioniGaggero, GIOVANNI BATTIST

    Machine Learning and Data Mining Applications in Power Systems

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    This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries

    Advanced Operation and Maintenance in Solar Plants, Wind Farms and Microgrids

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    This reprint presents advances in operation and maintenance in solar plants, wind farms and microgrids. This compendium of scientific articles will help clarify the current advances in this subject, so it is expected that it will please the reader

    Denial-of-service attack on iec 61850-based substation automation system: A crucial cyber threat towards smart substation pathways

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    The generation of the mix-based expansion of modern power grids has urged the utilization of digital infrastructures. The introduction of Substation Automation Systems (SAS), advanced networks and communication technologies have drastically increased the complexity of the power system, which could prone the entire power network to hackers. The exploitation of the cyber security vulnerabilities by an attacker may result in devastating consequences and can leave millions of people in severe power outage. To resolve this issue, this paper presents a network model developed in OPNET that has been subjected to various Denial of Service (DoS) attacks to demonstrate cyber security aspect of an international electrotechnical commission (IEC) 61850 based digital substations. The attack scenarios have exhibited significant increases in the system delay and the prevention of messages, i.e., Generic Object-Oriented Substation Events (GOOSE) and Sampled Measured Values (SMV), from being transmitted within an acceptable time frame. In addition to that, it may cause malfunction of the devices such as unresponsiveness of Intelligent Electronic Devices (IEDs), which could eventually lead to catastrophic scenarios, especially under different fault conditions. The simulation results of this work focus on the DoS attack made on SAS. A detailed set of rigorous case studies have been conducted to demonstrate the effects of these attacks.Scopu

    Recent Development of Hybrid Renewable Energy Systems

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    Abstract: The use of renewable energies continues to increase. However, the energy obtained from renewable resources is variable over time. The amount of energy produced from the renewable energy sources (RES) over time depends on the meteorological conditions of the region chosen, the season, the relief, etc. So, variable power and nonguaranteed energy produced by renewable sources implies intermittence of the grid. The key lies in supply sources integrated to a hybrid system (HS)

    WOFEX 2021 : 19th annual workshop, Ostrava, 1th September 2021 : proceedings of papers

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    The workshop WOFEX 2021 (PhD workshop of Faculty of Electrical Engineer-ing and Computer Science) was held on September 1st September 2021 at the VSB – Technical University of Ostrava. The workshop offers an opportunity for students to meet and share their research experiences, to discover commonalities in research and studentship, and to foster a collaborative environment for joint problem solving. PhD students are encouraged to attend in order to ensure a broad, unconfined discussion. In that view, this workshop is intended for students and researchers of this faculty offering opportunities to meet new colleagues.Ostrav

    Advanced Signal Processing Techniques Applied to Power Systems Control and Analysis

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    The work published in this book is related to the application of advanced signal processing in smart grids, including power quality, data management, stability and economic management in presence of renewable energy sources, energy storage systems, and electric vehicles. The distinct architecture of smart grids has prompted investigations into the use of advanced algorithms combined with signal processing methods to provide optimal results. The presented applications are focused on data management with cloud computing, power quality assessment, photovoltaic power plant control, and electrical vehicle charge stations, all supported by modern AI-based optimization methods
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