# Smart Grid Fault Mitigation and Cybersecurity with Wide-Area Measurement Systems: A Review
## 3 WAMS Operation and Dynamic Fault Detection  
WAMS are integral to modern power system management, particularly in enhancing grid observability, supporting network expansion, and aligning with the SGAM [31]. The ability of WAMS to perform real-time dynamic fault detection sets it apart from conventional protection technologies, including SCADA-based state estimation. While traditional systems rely on periodic measurements and interpolation techniques to estimate system states, WAMS leverages phasor measurement units (PMUs) to provide high-resolution, time-synchronized data, enabling more precise and timely fault identification (Figure 5). This capability significantly enhances grid resilience by facilitating faster fault detection, reduced fault-clearing times, and improved system stability [1; 3; 7]. Extensive research has explored the integration of WAMS into advanced smart grid architectures, with a particular emphasis on enhancing the incorporation of renewable energy sources [52; 53; 54]. WAMS enhances the adaptability of power networks to accommodate DERs such as wind and solar power by providing real-time insights into voltage stability, frequency variations, and power flow dynamics [38; 43]. This integration is particularly crucial for the development of renewable, smart microgrids, which utilize WAMS for intelligent energy management, adaptive load balancing, and improved operational resilience [54]. Figure 4: SGAM layers, zones, and domains [17]. Despite significant advancements in smart grid research, limited attention has been paid to the deployment of WAMS in aging power system networks, which are prevalent in developing economies. The lack of comprehensive research on the type of data that traditional power grids can provide for informed expansion remains a critical gap in the literature, potentially hindering the progress of renewable energy development. One key challenge in these regions is the frequent collapse of grid infrastructure. This issue, particularly prevalent in Nigeria and South Africa, has led to recurrent power outages, negatively impacting economic growth and deterring private investment in both the energy and industrial sectors. [PERSON] et al. conducted a comprehensive analysis of blackouts in developed economies, outlining the operational states of a wide-area power system network--Normal, Alert, Emergency, In-Extremis, and Restorative--to examine the mechanisms through which blackouts occur and propagate within WAMS-integrated grids. Their study identified the preconditions, initiating events, cascading failures, and restoration processes that characterize blackout events [31]. While these insights have primarily been applied to modern smart grids, they are equally relevant to traditional power networks. Understanding how WAMS can be leveraged to mitigate systemic vulnerabilities in aging power infrastructures presents a crucial research avenue that warrants further investigation. The effects of weather conditions, along with the varying oscillations within power systems, can collectively be classified as dynamic faults that impact grid stability. Through WAMS, these faults can be accurately characterized, predicted, and mitigated, enabling more efficient fault detection and facilitating the restoration of wide-area power systems (WAPS) in the event of disruptions. WAMS can enhance grid observability and enable proactive fault management by leveraging high-resolution, time-synchronized data from the power system network. Additionally, WAMS can collect and analyze critical data on the impact of lightning strikes, governor responses, frequency instability (e.g., rate of change in frequency), oscillation issues, and interoperability challenges. These insights are particularly valuable for increasing the observability and operational efficiency of traditional power system  
Figure 5: Operationalization of PMU-based WAMS in infinite-bus grid model with communication system.