As the IEC 61850 digital substation standard becomes progressively adopted by utilities throughout the world, entirely computerized methods will completely replace traditional strategies for monitoring the power system. Although newer techniques offer enhanced efficiency and controllability, their reliability is not as established as that of conventional practices. Modern approaches require extensive validation and analysis before they can be implemented on a widespread basis. One specific area of interest is the performance of protection systems that utilize voltage and current samples digitized directly at their source. This research presents a complete test bench for evaluating sampled values-based protection schemes and measures their efficacy under several different operating conditions. It is shown that the novel system operates correctly for the situations it is expected to, with minimal latency compared to traditional practices. / Master of Science / Power system infrastrcutures are changing rapidly from analog arrangements to entirely digital methods. This offers numeous benefits such as increased efficiency, lower cost, higher accuracy, and even improved safety. However, digital implementations do not have an as proven track record as compared to conventional practices, leading to concerns about their reliaiblity. This research tests the performance an en entirely digital protection scheme by using various hardware components. The results are analyzed and show that the novel scheme operates correctly, albeit with a slight delay as compared to traditional methods.

The advent of Information and Communications Technology (ICT) in power systems has revolutionized the monitoring, operation, and control mechanisms through advanced control and communication functions. However, this integration significantly elevates the vulnerability of modern power systems to cyber intrusions, posing severe risks to the integrity and reliability of the power grid. This dissertation presents the results of a comprehensive study into the detection of cyber intrusions and restoration of cyber-power systems post-attack with a focus on IEC 61850 based substations and recovery methodologies in the cyber-physical system framework. The first step of this study is to develop a novel Intrusion Detection System (IDS) specifically designed for deployment in automated substations. The proposed IDS effectively identifies falsified measurements within Manufacturing Messaging Specification (MMS) messages by verifying the consistency of electric circuit laws. This distributed approach helps avoid the transfer of contaminated measurements from substations to the control center, ensuring the integrity of SCADA systems. Utilizing a cyber-physical system testbed and the IEEE 39-bus test system, the IDS demonstrates high detection accuracy and validates its efficacy in real-time operational environments. Building upon the intrusion detection methodology, this dissertation advances into cyber system recovery strategies, which are designed to meet the challenges of restoring a power grid as a cyber-physical system following catastrophic cyberattacks. A novel restoration strategy is proposed, emphasizing the self-recovery of a substation automation system (SAS) within the substation through dynamic network reconfiguration and collaborative efforts among Intelligent Electronic Devices (IEDs). This strategy, validated through a cyber-power system testbed incorporating SDN technology and IEC 61850 protocol, highlights the critical role of cyber recovery in maintaining grid resilience. Further, this research extends its methodology to include a cyber-physical system restoration strategy that integrates an optimization-based multi-system restoration approach with cyber-power system simulation for constraint checking. This innovative strategy developed and validated using an Software Defined Networking (SDN) network for the IEEE 39-bus system, demonstrates the capability to efficiently restore the cyber-power system and maximize restoration capability following a large-scale cyberattack. Overall, this dissertation makes original contributions to the field of power system security by developing and validating effective mechanisms for the detection of and recovery from cyber intrusions in the cyber-power system. Here are the main contributions of this dissertation: 1) This work develops a distributed IDS, specifically designed for the substation automation environment, capable of pinpointing the targets of cyberattacks, including sophisticated attacks involving multiple substations. The effectiveness of this IDS in a real-time operational context is validated to demonstrate its efficiency and potential for widespread deployment. 2) A novel recovery strategy is proposed to restore the critical functions of substations following cyberattacks. This strategy emphasizes local recovery procedures that leverage the collaboration of devices within the substation network, circumventing the need for external control during the initial recovery phase. The implementation and validation of this method through a cyber-physical system testbed—specifically, within an IEC 61850 based Substation Automation System (SAS)—underscores its practicality and effectiveness in real-world scenarios. 3) The dissertation results in a new co-restoration strategy that integrates mixed integer linear programming to sequentially optimize the restoration of generators, power components, and communication nodes. This approach ensures optimal restoration decisions within a limited time horizon, enhancing the recovery capabilities of the cyber-power system. The application of an SDN based network simulator facilitates accurate modeling of cyber-power system interactions, including communication constraints and dynamic restoration scenarios. The strategy's adaptability is further improved by real-time assessment of the feasibility of the restoration sequence incorporating power flow and communication network constraints to ensure an effective recovery process. / Doctor of Philosophy / Electricity is a critical service that supports the society and economy. Today, electric power systems are becoming smarter, using advanced Information and Communications Technology to manage and distribute electricity more efficiently. This new technology creates a smart grid, a network that not only delivers power but also uses computers and other tools to remotely monitor electricity flows and address any issues that may arise. However, these smart systems with high connectivity utilizing information and communication systems can be vulnerable to cyberattacks, which could disrupt the electricity supply. To protect against these threats, this study is focused on creating systems that can detect when an abnormal condition is taking place in the cyber-power grid. These detection systems are designed to detect and identify signs of cyberattacks at key points in the power network, particularly at substations, which play a vital role in the delivery of electricity. Substations control the power grid operating conditions to make sure that electricity service is reliable and efficient for the consumers Just like traffic lights help manage the flow of vehicles, substations manage the flow of electricity to make sure electric energy is delivered to where it needed. Once a cyberattack is detected, the next step is to stop the attack and mitigate the impact it may have made to ensure that the power grid returns to normal operations as quickly as possible. This dissertation is concerned with the development and validation of analytical and computational methods to quickly identify the cyberattacks and prevent the disruptions to the electricity service. Also, the focus of this work is also on a coordinated recovery of both the cyber system ( digital controls and monitoring) and power system (physical infrastructure including transformers and transmission and distribution lines). This co-restoration approach is key to sustain the critical electricity service and ensures that the grid is resilient against the cyber threats. By developing strategies that address both the cyber and physical aspects, the proposed methodology aims to minimize downtime and reduce the impact of large-scale cyberattacks on the electrical infrastructure. The impact of the results of this dissertation is the enhancement of security and resilience of the electric energy supply in an era where the risks of cyber threats are increasingly significantly. Overall, by developing new methodologies to detect and respond to cyberattacks, the cyber-power system's capability to withstand and recover from cyberattacks is enhanced in the increasingly technology-dependent power grid environment.

With the advancements in the Industrial Internet of Things (IIoT), new networking requirements and demands are introduced to Substation Automation Systems (SAS) within electrical power grids. The possibility of merging Information Technology (IT) and Operational Technology (OT) traffic on the same network to achieve higher productivity, however, presents new challenges in providing real-time guarantees to OT traffic. Time-Sensitive Networking (TSN) can be a promising solution that allows IT and OT traffic to coexist seamlessly while still providing real-time guarantees for critical applications. Substations act as critical nodes within power grids, and their digitalisation is a crucial element in the energy transition. A digital substation handles International Electrotechnical Commission (IEC) 61850 protocol traffic such as Generic Object Oriented Substation Event (GOOSE), Sampled Values (SV), and Manufacturing Message Specification (MMS), which all have strict timing requirements. The integration of TSN into these substations could improve the handling of this traffic and, consequently, the controllability of power grids. This thesis investigates the use of TSN in an IEC 61850 process bus, typically implemented in an SAS. A series of simulated test scenarios were developed to evaluate the impact of TSN compared to traditional networking methods. These included configurations using Ethernet, Ethernet with priority queuing, and TSN with Time-Aware Shaper (TAS) and Credit-Based Shaper (CBS). The results indicate that TSN can meet critical timing requirements, reduce jitter, and manage sporadic traffic effectively under high traffic loads. While the TAS scheduler may increase End-to-End delay for periodic traffic, CBS can reduce it for event-based traffic. Furthermore, robust timing guarantees are ensured for the TSN scenarios by providing a feasible schedule for Scheduled Traffic (ST) and a worst-case response time analysis for Audio-Video Bridging (AVB) traffic. This research highlights TSN’s potential to improve grid controllability and reliability through enhanced network performance, illustrating its role in the future of resilient grid technologies.