Alexandre B. Nassif

Large artificial intelligence (AI) training data centers are emerging as significant, highly dynamic digital loads that pose numerous challenges to power system stability. Methods to study and assess their impact are still being developed and have been the focus of numerous industry interest groups. Intended to contribute to bridging this gap, this paper develops a credible impact study for data centers, presenting a dynamic data‑center model that includes an uninterruptible power supply (UPS), co‑generator, cooling system, and a grid-forming (GFM) controlled energy storage system (ESS), with explicit converter and control dynamics. Using electromagnetic transient simulations, two stress scenarios are studied: low‑voltage faults and fast load fluctuations characteristic of AI training. The results show that an adequately tuned and controlled GFM ESS can significantly improve the large load response by reducing frequency overshoot, raising the nadir, shortening settling time, and enhancing post‑fault recovery. Under fast fluctuation AI training load profiles, the ESS also damps active‑power oscillations and reduces torsional shaft‑torque oscillations in the generator train to safe levels. These findings support ESS‑based control as an effective tool for integrating large AI data centers without compromising grid stability.

The increasing intensity and frequency of extreme events have raised significant concerns about the electrical grid’s resilience. Numerous extreme events such as hurricanes, tornadoes, earthquakes, geomagnetic storms, high-altitude electromagnetic pulses, ice storms, cyber-attacks, and physical attacks, among others, threaten the entire electrical grid and its various components. Fragility curves play a crucial role in assessing asset vulnerability having a significant impact in all studies that evaluate the power system resilience for extreme events. Real-world data for such extreme events are often significantly limited, and thus in this paper a method for calibrating fragility curves with limited real-world data is presented. This paper also introduces a methodology to generate likely temporal sequences of failures during a hurricane event leveraging the newly calibrated fragility curves and the geospatial knowledge utilizing the electric grid resilience & assessment system (EGRASS) tool. Furthermore, the methodology evaluates the sequential contingencies using the dynamic contingency analysis tool (DCAT) for power system dynamic simulations. The main contribution of this work is the development and analysis of the methodology that enables dynamic simulations of power systems under climate-related extreme events using limited real-world data. The methodologies and case studies presented in this paper focus on the hurricanes faced by Puerto Rico’s grid as an extreme event but are agnostic of the type of extreme event and can be applied to other such events.

Over the last decade there has been increased interest in using synchronized measurement technologies (SMTs) to address distribution system needs. Modern distribution systems include growing penetration levels of distributed energy resources (DERs); photovoltaic (PV) and wind distributed generation (DG), and battery energy storage systems; electric vehicles (EVs); data centers; and more active consumer participation through, for instance, time-of-use rates and demand response. Furthermore, the need for higher reliability, power quality, resilience, and greater situational awareness of the distribution system is driving the increasing utilization of georeferenced and time-synchronized data with high spatial granularity and temporal resolution. This type of data can be used for multiple applications to enhance distribution monitoring, control, and protection capabilities. These benefits have prompted growing interest in the broad-scale deployment of SMTs on the distribution grid.

The rise of inverter-based distributed energy resources (IBRs) is reshaping global power system planning and operation. Unlike traditional rotating machines, IBRs lack physical characteristics and rely on control algorithms to support the grid during abnormal conditions. This is especially evident in mass-adopted distributed sources like rooftop residential-scale Distributed Energy Resources (DER), which are controlled to behave as constant current sources. Numerous jurisdictions already experience steady-state reverse flows at substations during periods of minimum load and maximum generation. However, the aggregation of IBRs exacerbates ground fault overvoltages (GFOV) at the transmission level, as they appear as open circuits in the zero and/or negative sequence networks. This paper analyzes the issue through electromagnetic transient (EMT) simulations, yielding chart-based screening guidelines. These guidelines can assist utilities in evaluating necessary retrofits for substations as more IBRs are adopted, particularly for small-scale IBRs that are interconnected with little to no rigorous analysis.

Sustained oscillations persist without decay, impacting system stability and performance. Sustained oscillations in distribution systems exhibit unique mechanisms compared to those in transmission systems, yet research in this area of distribution systems is lacking. In distribution systems, these oscillations degrade power quality, jeopardizing stability and causing relay malfunctions and supply discontinuity. Understanding their mechanisms in modern distribution systems is crucial for their detection, classification, and localization. This paper provides a comprehensive review of sustained oscillations in modern distribution systems. Additionally, it discusses key methodologies for detecting and classifying sustained oscillations in transmission systems. Finally, it applies transmission system methodologies to real cases in Ontario's distribution system, shedding light on challenges and future directions.

Puerto Rico, an island heavily reliant on fossil fuels for primary electricity generation, faces challenges stemming from inadequate preventative maintenance, leading to an intermittently insufficient generation mix to meet overall load demand. Media coverage, exemplified by the Department of Energy PR100 study, delineates a strategic roadmap for transitioning Puerto Rico to achieve 100% renewable energy generation. This shift aims not only to mitigate dependence on fossil fuels but also to replace outdated conventional plants. Integrating inverter-interfaced renewable generation into the grid introduces a challenge, as these resources cannot match the short-circuit levels typically supplied by rotational synchronous generation. Complexity arises in determining whether existing protection schemes can maintain dependability during this transition or whether upgrades, such as adjustments to protection settings or philosophical enhancements, are imperative. This paper addresses this challenge by evaluating system strength at different stages of incorporating utility-scale renewable shares in the island system. It discerns the reduction in short-circuit currents for both three-phase faults and single-line-to-ground faults as conventional plants are phased out in favor of inverter-based resources. This research work also quantifies the impact of synchronous condensers and STATCOMs as a solution to strengthen the grid and increase short-circuit levels. This research equips the transmission operator with valuable insights into the necessary future system modifications to ensure the dependability and safety of the grid.

Electric power generation is quickly transitioning toward nontraditional inverter-based resources (IBRs). Prevalent devices today are solar PV, wind generators, and battery energy storage systems (BESS) based on electrochemical packs. These IBRs are interconnected throughout the power system via power electronics inverter bridges, which have sophisticated controls. This paper studies the impacts and benefits resulting from the integration of grid forming (GFM) inverters and energy storage on the stability of power systems via replicating real events of loss of generation units that resulted in large load shedding events. First, the authors tuned the power system dynamic model in Power System Simulator for Engineering (PSSE) to replicate the event records and, upon integrating the IBRs, analyzed the system dynamic responses of the BESS. This was conducted for both GFM and grid following (GFL) modes. Additionally, models for Grid Forming Static Synchronous Compensator (GFM STATCOM), were also created and simulated to allow for quantifying the benefits of this technology and a techno-economic analysis compared with GFM BESSs. The results presented in this paper demonstrate the need for industry standardization in the application of GFM inverters to unleash their benefits to the bulk electric grid. The results also demonstrate that the GFM STATCOM is a very capable system that can augment the bulk system inertia, effectively reducing the occurrence of load shedding events.

Extreme climate-driven events such as hurricanes, floods, and wildfires are becoming more intense in areas exposed to these threats, requiring approaches to improve the resilience of the electrical infrastructure serving these communities. Long-duration outages caused by such high impact events propagate to economic, health, and social consequences for communities. As essential service providers, electric utilities are mandated to provide safe, economical and reliable electricity to their customers. The public is becoming less tolerant to these more frequent disruptions, especially in view of technological advances that are intended to improve power quality, reliability and resilience. One promising solution is state-of-the-art microgrids and the advanced controls employed therein. This paper presents and demonstrates an approach to technoeconomic analysis that can be used to value the avoided economic consequences of grid resilience investments, as applied to the islands of Vieques and Culebra in Puerto Rico. This valuation methodology can support policies to incorporate resilience value into any investment decision-making process, especially those which serve the public interest.

Inverter-based resources are proliferating in distribution systems across the globe, along with battery energy storage systems. This in part is attributed to a descending trend observed in their costs. These inverter-based resources, however, create new problems for electrical utilities planners and engineers. One such issue is how to measure, test, and manage load rejection overvoltage. This phenomenon takes place upon sudden islanding of a power system area such that it becomes supported by grid-following inverter-based resources only. This letter presents background, practical methods to test the behavior, as well as two case studies of utility-scale generation and energy storage connected to a distribution feeder.