A Comprehensive Survey on the Cyber-Security of Smart Grids: Cyber-Attacks, Detection, Countermeasure Techniques, and Future Directions

One of the significant challenges that smart grid networks face is cyber-security. Several studies have been conducted to highlight those security challenges. However, the majority of these surveys classify attacks based on the security requirements, confidentiality, integrity, and availability, without taking into consideration the accountability requirement. In addition, some of these surveys focused on the Transmission Control Protocol/Internet Protocol (TCP/IP) model, which does not differentiate between the application, session, and presentation and the data link and physical layers of the Open System Interconnection (OSI) model. In this survey paper, we provide a classification of attacks based on the OSI model and discuss in more detail the cyber-attacks that can target the different layers of smart grid networks communication. We also propose new classifications for the detection and countermeasure techniques and describe existing techniques under each category. Finally, we discuss challenges and future research directions

Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

Resilience assessment and planning in power distribution systems:Past and future considerations

Over the past decade, extreme weather events have significantly increased worldwide, leading to widespread power outages and blackouts. As these threats continue to challenge power distribution systems, the importance of mitigating the impacts of extreme weather events has become paramount. Consequently, resilience has become crucial for designing and operating power distribution systems. This work comprehensively explores the current landscape of resilience evaluation and metrics within the power distribution system domain, reviewing existing methods and identifying key attributes that define effective resilience metrics. The challenges encountered during the formulation, development, and calculation of these metrics are also addressed. Additionally, this review acknowledges the intricate interdependencies between power distribution systems and critical infrastructures, including information and communication technology, transportation, water distribution, and natural gas networks. It is important to understand these interdependencies and their impact on power distribution system resilience. Moreover, this work provides an in-depth analysis of existing research on planning solutions to enhance distribution system resilience and support power distribution system operators and planners in developing effective mitigation strategies. These strategies are crucial for minimizing the adverse impacts of extreme weather events and fostering overall resilience within power distribution systems.Comment: 27 pages, 7 figures, submitted for review to Renewable and Sustainable Energy Review

Exploring market designs for local energy markets : core functionalities and value proposition in the context of blockchain, IoT and prosumers

This dissertation aimed to assess the impact of innovative smart market solutions and Blockchain technology on achieving efficient localized energy markets. Trends suggest the future of renewable energy generation will involve a move away from centralized power plants, and towards a large number of smaller generation units, such as PV cells. There are clear synergies between the market dynamics of photovoltaic systems and Blockchain-enabled smart markets, which can be harnessed towards integrating new consumption patterns and energy sources, as well as connecting consumers. Successful business strategy to integrate these technologies can lead to market leadership in this new industry. Captivating consumers is a key determinant of success, and offering lower electricity prices a necessary condition. For such offering to be feasible, markets need to be more efficient, as smart microgrids are proving to be. Consequently, there came the interest to see how new local electricity markets could be set up, while taking advantage of decentralization. A peer-to-peer, auction-based, local energy market was idealized and various simulations of were ran with differing levels of participants and structure, to understand the impact on the price of electricity achieved by the market. Market size and structure were both shown to affect price at different magnitudes, suggesting an ideal setup of 25-40 participants with generation capabilities over 60% of demand. Further analysis was undertaken to understand the impact of smart meters and Blockchain integration in such a market. Afterwards, conclusions were compiled and recommendations provided for how to approach new practical implementations.Esta dissertação teve como objetivo avaliar o impacto de inovadoras soluções de mercados inteligentes e tecnologia Blockchain em mercados locais de energia. Tendencias apontam para que o futuro das energias renovaveis passe por uma maior prevalencia de paineis fotovoltaicos domesticos. As sinergias entre as atuais dinamicas em mercados eletricos e o uso da Blockchain em mercados inteligentes parecem claras, podendo ser aproveitaveis para integrar novos perfis de consumo e conectar consumidores. Sendo um novo segmento, estratégias de mercado bem conseguidas serão essencias para ganhar posição, e a capacidade de angariar consumidores será um indicador crucial de sucesso. Para tal, os mercados têm que ser mais eficientes, algo que se tem revelado factual em casos de micro sistemas. Assim, criou-se o interesse de perceber como desenhar e implementar mercados localizados de energia que beneficiem desta tendencia de desintermediação. Para tal, um mercado interativo à base de leilões de eletricidade entre consumidores foi idealizado. Posteriormente, este foi simulado repetidamente, com diferentes dimensões e estruturas, a fim de perceber o seu impacto nos preços médios alcançados. Foi mostrado que tamanho e composição afetam os preços em magnitudes diferentes, sugerindo uma dimensão ideal de 25-40 participantes, com capacidades de autogeração superiores a 60%. Análises posteriors foram desenvolvidas de modo substantive, para avaliar o impacto de contadores eletricos inteligentes e integração da Blockchain neste tipo de mercado. Finalmente, conclusões foram reunidas e transformadas em recomendações para futuras implementações práticas

Why High-Performance Modelling and Simulation for Big Data Applications Matters

Modelling and Simulation (M&S) offer adequate abstractions to manage the complexity of analysing big data in scientific and engineering domains. Unfortunately, big data problems are often not easily amenable to efficient and effective use of High Performance Computing (HPC) facilities and technologies. Furthermore, M&S communities typically lack the detailed expertise required to exploit the full potential of HPC solutions while HPC specialists may not be fully aware of specific modelling and simulation requirements and applications. The COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications has created a strategic framework to foster interaction between M&S experts from various application domains on the one hand and HPC experts on the other hand to develop effective solutions for big data applications. One of the tangible outcomes of the COST Action is a collection of case studies from various computing domains. Each case study brought together both HPC and M&S experts, giving witness of the effective cross-pollination facilitated by the COST Action. In this introductory article we argue why joining forces between M&S and HPC communities is both timely in the big data era and crucial for success in many application domains. Moreover, we provide an overview on the state of the art in the various research areas concerned

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea