Impact Assessment of Hypothesized Cyberattacks on Interconnected Bulk Power Systems

The first-ever Ukraine cyberattack on power grid has proven its devastation by hacking into their critical cyber assets. With administrative privileges accessing substation networks/local control centers, one intelligent way of coordinated cyberattacks is to execute a series of disruptive switching executions on multiple substations using compromised supervisory control and data acquisition (SCADA) systems. These actions can cause significant impacts to an interconnected power grid. Unlike the previous power blackouts, such high-impact initiating events can aggravate operating conditions, initiating instability that may lead to system-wide cascading failure. A systemic evaluation of "nightmare" scenarios is highly desirable for asset owners to manage and prioritize the maintenance and investment in protecting their cyberinfrastructure. This survey paper is a conceptual expansion of real-time monitoring, anomaly detection, impact analyses, and mitigation (RAIM) framework that emphasizes on the resulting impacts, both on steady-state and dynamic aspects of power system stability. Hypothetically, we associate the combinatorial analyses of steady state on substations/components outages and dynamics of the sequential switching orders as part of the permutation. The expanded framework includes (1) critical/noncritical combination verification, (2) cascade confirmation, and (3) combination re-evaluation. This paper ends with a discussion of the open issues for metrics and future design pertaining the impact quantification of cyber-related contingencies

A Review of Fault Diagnosing Methods in Power Transmission Systems

Transient stability is important in power systems. Disturbances like faults need to be segregated to restore transient stability. A comprehensive review of fault diagnosing methods in the power transmission system is presented in this paper. Typically, voltage and current samples are deployed for analysis. Three tasks/topics; fault detection, classification, and location are presented separately to convey a more logical and comprehensive understanding of the concepts. Feature extractions, transformations with dimensionality reduction methods are discussed. Fault classification and location techniques largely use artificial intelligence (AI) and signal processing methods. After the discussion of overall methods and concepts, advancements and future aspects are discussed. Generalized strengths and weaknesses of different AI and machine learning-based algorithms are assessed. A comparison of different fault detection, classification, and location methods is also presented considering features, inputs, complexity, system used and results. This paper may serve as a guideline for the researchers to understand different methods and techniques in this field

Quantitative modeling of reliability and survivability for cyber-physical power systems

Critical infrastructure systems are increasingly reliant on cyber infrastructure that enables intelligent real-time control of physical components. This cyber infrastructure utilizes environmental and operational data to provide decision support intended to increase the efficacy and reliability of the system and facilitate mitigation of failure. Realistic imperfections, such as corrupt sensor data, software errors, or failed communication links can cause failure in a functional physical infrastructure, defying the purpose of intelligent control. As such, justifiable reliance on cyber-physical critical infrastructure is contingent on rigorous investigation of the effect of intelligent control, including modeling and simulation of failure propagation within the cyber-physical infrastructure. To this end, this thesis investigates the reliability and survivability of a cyber-physical power grid based on the IEEE 9-bus test system. The research contributions include quantitative modeling of both non-functional attributes, based on data from N-1 contingency analysis that considers failures in physical and cyber components of the system. The resulting survivability model is utilized in determining the importance of each transmission line. The final research contribution is identification of optimal recovery strategies for the system, where the objective is to maintain the highest possible survivability in the course of recovery. --Abstract, page iii

Cooperative Hierarchical Deep Reinforcement Learning based Joint Sleep, Power, and RIS Control for Energy-Efficient HetNet

Energy efficiency (EE) is one of the most important metrics for 5G and future 6G networks to reduce energy costs and control carbon footprint. Sleep control, as a cost-efficient approach, can significantly lower power consumption by switching off network devices selectively. Meanwhile, reconfigurable intelligent surface (RIS) has emerged as a promising technique to enhance the EE of 5G beyond and 6G networks. In this work, we jointly consider sleep and transmission power control for reconfigurable intelligent surface (RIS)-aided energy-efficient heterogeneous networks (Hetnets). In particular, we first propose a fractional programming (FP) method for RIS phase-shift control, which aims to maximize the sum-rate under given transmission power levels. Then, considering the timescale difference between sleep control and power control, we introduce a cooperative hierarchical deep reinforcement learning (Co-HDRL) algorithm, including a cross-entropy enabled meta-controller for sleep control, and correlated equilibrium-based sub-controllers for power control. Moreover, we proposed a surrogate optimization method as one baseline for RIS control, and conventional HDRL as another baseline for sleep and power control. Finally, simulations show that the RIS-assisted sleep control can achieve more than 16% lower energy consumption and 30% higher energy efficiency than baseline algorithms

Reliability Analysis of Secondary Distribution System in Nigeria: A Case Study of Ayetoro 1 Substation, Lagos State.

A power system is set up basically to meet the demands of the customers. However, interruptions which are largely unavoidable contribute to the unavailability of power and thus prevent power system from achieving this. In most cases, it is the sustained interruptions that greatly affect both the utility company and its customers. Hence, it is necessary to find means of determining which component failure contributes most to the unavailability of the distribution system, and how this unavailability actually affects the customers. This is to enable system planners and designers to seek better ways of improving the reliability of a typical secondary distribution substation system having a single-end fed radial configuration. By using analytical method and network reduction technique, the substation reliability was analyzed based on the outage data gotten from the utility company. The conclusion from this work shows that transformer failure followed by fuse failure contributes most to the substation’s unavailability. The overall system availability shows that the system’s performance is poor

Reliability Modeling for the Advanced Electric Power Grid

The advanced electric power grid promises a self-healing infrastructure using distributed, coordinated, power electronics control. One promising power electronics device, the Flexible AC Transmission System (FACTS), can modify power flow locally within a grid. Embedded computers within the FACTS devices, along with the links connecting them, form a communication and control network that can dynamically change the power grid to achieve higher dependability. The goal is to reroute power in the event of transmission line failure. Such a system, over a widespread area, is a cyber-physical system. The overall reliability of the grid is a function of the respective reliabilities of its two major subsystems, namely, the FACTS network and the physical components that comprise the infrastructure. This paper presents a mathematical model, based on the Markov chain imbeddable structure, for the overall reliability of the grid. The model utilizes a priori knowledge of reliability estimates for the FACTS devices and the communications links among them to predict the overall reliability of the power grid

Dynamic Security Assessment For Power System Using Attribute Selection Technique

The evaluation of the dynamic security of the electrical power system after the occurrence of disturbances in the network is one of the most important tools that the control center uses to maintain the system in a safe operating mode, as well as prevent cases of system out of control and cases of complete shutdown. With the annual increase in the size of the electrical system and its distribution over a very wide geographical area, this led to a new challenge to assess dynamic security assessment (DSA), which is dealing with a huge and varied amount of data that requires processing in a very short time. To address these challenges, this study presented a new technique of artificial intelligence, which is the attribute selection technique, to reduce the size of this data and thus improve the accuracy and speed of results. This method relied on the combination of decision tree algorithms and a technique (Attribute selection) in the data obtained from the test system (IEEE-30Bus). The results of this method showed a significant reduction in the number of data used, which amounted to (45.55%) of the total data, Which led to an improvement in the classification accuracy, as the classification accuracy reached (97.27%). This reduction is very important when dealing in the online operating environment, as it saves the time necessary to reach the most accurate evaluation decision and thus issue gives a greater opportunity to take the appropriate decision in the event of disturbances and keep the electrical system in a secure state

Smart operation of transformers for sustainable electric vehicles integration and model predictive control for energy monitoring and management

The energy transmission and distribution systems existing today are stillsignificantly dependent on transformers,despite beingmore efficient and sustainable than those of decadesago. However, a large numberof power transformers alongwith other infrastructures have been in service for decades and are considered to be in their final ageing stage. Anymalfunction in the transformerscouldaffect the reliability of the entire electric network and alsohave greateconomic impact on the system.Concernsregardingurban air pollution, climate change, and the dependence on unstable and expensive supplies of fossil fuels have lead policy makers and researchers to explore alternatives to conventional fossil-fuelled internal combustion engine vehicles. One such alternative is the introduction of electric vehicles. A broad implementation of such mean of transportation could signify a drastic reduction in greenhouse gases emissions and could consequently form a compelling argument for the global efforts of meeting the emission reduction targets. In this thesis the topic of a high penetration of electric vehicles and their possible integration in insular networksis discussed. Subsequently, smart grid solutions with enabling technologies such as energy management systems and smart meters promote the vision of smart households, which also allows for active demand side in the residential sector.However, shifting loads simultaneously to lower price periods is likely to put extra stress on distribution system assets such as distribution transformers. Especially, additional new types of loads/appliances such as electric vehicles can introduce even more uncertaintyon the operation of these assets, which is an issue that needs special attention. Additionally, in order to improve the energy consumption efficiencyin a household, home energy management systems are alsoaddressed. A considerable number ofmethodologies developed are tested in severalcasestudies in order to answer the risen questions.Os sistemas de transmissão e distribuição de energia existentes hoje em dia sãosignificativamente dependentes dos transformadores, pese embora sejammais eficientes e sustentáveis do que os das décadas passadas. No entanto, uma grande parte dos transformadores ao nível dadistribuição, juntamente com outras infraestruturassubjacentes, estão em serviço há décadas e encontram-se nafasefinal do ciclo devida. Qualquer defeito no funcionamento dos transformadorespode afetara fiabilidadede toda a redeelétrica, para além de terum grande impactoeconómico no sistema.Os efeitos nefastos associadosàpoluição do arem centro urbanos, asmudançasclimáticasea dependência de fontes de energiafósseis têm levado os decisores políticos e os investigadores aexplorar alternativas para os veículos convencionais de combustão interna. Uma alternativa é a introdução de veículos elétricos. Umaampla implementação de tal meio de transporte poderia significar uma redução drástica dos gases de efeito de estufa e poderiareforçar os esforços globais para ocumprimento das metas de redução de emissõesde poluentes na atmosfera.Nesta tese é abordado o tema da elevada penetração dos veículos elétricose a sua eventual integração numarede elétricainsular. Posteriormente, são abordadas soluções de redeselétricasinteligentes com tecnologias específicas, tais como sistemas de gestão de energia e contadores inteligentes que promovamo paradigmadas casas inteligentes, que também permitem a gestão da procura ativano sector residencial.No entanto, deslastrando significativamente as cargaspara beneficiar de preçosmais reduzidosé suscetíveldecolocarconstrangimentosadicionaissobre os sistemas de distribuição, especialmentesobre ostransformadores.Osnovos tipos de cargas tais como os veículos elétricospodem introduzir ainda mais incertezassobre a operação desses ativos, sendo uma questão que suscitaespecial importância. Além disso, com ointuitode melhorar a eficiência do consumo de energia numa habitação, a gestão inteligente daenergia é um assunto que também éabordadonesta tese. Uma pletora de metodologias é desenvolvida e testadaemvários casos de estudos, a fim de responder às questões anteriormente levantadas