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At least 361 records · Page 20

Criteria for Grid-Forming Inverters Transitioning Between Current Limiting Mode and Normal Operation

Here, this letter focuses on the fault recovery analysis of inverters using multi-loop droop based grid-forming control, taking into account different current limiting strategies. A criterion is proposed to determine when the inverter can exit the current limiting mode after fault clearance. The theoretical findings are verified through electromagnetic transient simulations using the direct (d)-axis priority-based current limiting method, circular current limiting method, and virtual impedance method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Leveraging Artificial Intelligence in Federal Projects

Artificial intelligence (AI) has the potential to transform grid operations. As energy demand rises, weather patterns shift, and foreign threats to critical infrastructure grow, it is essential to harness advanced technology to modernize the grid and increase overall resiliency. This paper examines the integration of AI in federally funded grid infrastructure projects. By analyzing project data, it evaluates the penetration and use cases of AI technologies within key funding initiatives and explores opportunities and challenges associated with their deployment. This analysis categorizes AI adoption in recent federal grid investments, establishing a baseline for measuring near-term impacts and identifying promising AI applications. The research found that 16% of recent federal energy projects included AI integration, and approximately 75% of these projects used AI for more than one primary application.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

EverGREEN 2045: An Energy Mix to Decarbonize Washington State

Washington State’s future resource mix is likely to be comprised of intermittent renewables and carbon-free generation including hydropower by 2045. Generation will likely be comprised of wind, solar photovoltaic (PV), batteries, pumped storage hydropower (PSH), existing nuclear power plants, and potentially enhanced geothermal systems and advanced nuclear reactor technologies. To assess the cost and stability of the future resource mix, we partner with X-energy (advanced reactor design) and AltaRock Energy (enhanced geothermal system) for proprietary cost data. After estimating the costs of these two new technologies, we design plausible future resource mix scenarios to meet Washington State’s Clean Energy Transformation Act which transitions the state to carbon-free generation by 2045. We assess the cost and stability of the future resource mix with power system analysis tools, finding revenues are sufficient to cover variable operating and maintenance costs for most technologies providing power in 2030 and 2045, but capacity payments or power purchase agreements will likely be necessary for flexible resources, including enhanced geothermal systems and advanced nuclear reactors, to participate in the future resource mix.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Noise and error analysis and optimization in particle-based kinetic plasma simulations

In this paper we analyze the noise in macro-particle methods used in plasma physics and fluid dynamics, leading to approaches for minimizing the total error, focusing on electrostatic models in one dimension. We begin by describing kernel density estimation for continuous values of the spatial variable x, expressing the kernel in a form in which its shape and width are represented separately. The covariance matrix of the noise in the density is computed, first for uniform true density. The bandwidth of the covariance matrix C(x,y) is related to the width of the kernel. A feature that stands out is the presence of constant negative terms in the elements of the covariance matrix both on and off-diagonal. These negative correlations are related to the fact that the total number of particles is fixed at each time step; they also lead to the property ∫C(x,y)dy = 0. We investigate the effect of these negative correlations on the electric field computed by Gauss's law, finding that the noise in the electric field is related to a process called the Ornstein-Uhlenbeck bridge, leading to a covariance matrix of the electric field with variance significantly reduced relative to that of a Brownian process. For non-constant density, p(x), still with continuous x, we analyze the total error in the density estimation and discuss it in terms of bias-variance optimization (BVO). For some characteristic length l, determined by the density and its second derivative, and kernel width h, having too few particles within h leads to too much variance; for h that is large relative to l, there is too much smoothing of the density. The optimum between these two limits is found by BVO. For kernels of the same width, it is shown that this optimum (minimum) is weakly sensitive to the kernel shape. Next, we repeat the analysis for x discretized on a grid. In this case the charge deposition rule is determined by a particle shape. An important property to be respected in the discrete system is the exact preservation of total charge on the grid; this property is necessary to ensure that the electric field is equal at both ends, consistent with periodic boundary conditions. We find that if the particle shapes satisfy a partition of unity property, the particle charge deposited on the grid is conserved exactly. Further, if the particle shape is expressed as the convolution of a kernel with another kernel that satisfies the partition of unity, then the particle shape obeys the partition of unity. This property holds for kernels of arbitrary width, including widths that are not integer multiples of the grid spacing. Furthermore, we show results relaxing the approximations used to do BVO optimization analytically, by doing numerical computations of the total error as a function of the kernel width, on a grid in x. The comparison between numerical and analytical results shows good agreement over a range of particle shapes. We discuss the practical implications of our results, including the criteria for design and implementation of computationally efficient particle shapes that take advantage of the developed theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A resource adequacy assessment of correlated wide-area outages in the power grid

As the power grid is undergoing rapid transformations, numerous questions are emerging about its vulnerability to wide-area extreme events (WAEE), which could influence its operations. Relatively few analyses have been conducted to date regarding the impact of correlated outages during WAEEs on the grid’s ability to balance resources with demand. This study addresses this gap by conducting a resource adequacy analysis for a hurricane-inspired WAEE on a 2035 synthetic power grid system for the United States. A sensitivity analysis was also conducted to characterize the relative impact of weather on unserved energy. Our results indicate that although the magnitude and duration of the shortfalls vary depending on weather conditions, persistent shortfalls are observed in some regions. Initial explorations indicate a strong correlation between transmission-constrained regions and regions with persistent shortfalls. Future work could generate empirically-grounded representations for generator outages as well as conduct causal analyses of these shortfalls to improve understanding of drivers as well as possible mitigation strategies. Continued exploration of extreme weather impacts on the grid is important to develop more robust understanding of the reliability and resilience of our power systems, especially as they undergo rapid transformations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100)

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phaseout of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040 as established in Puerto Rico Energy Public Policy Act (Act 17). To meet these goals and support widespread end-use electrification, Puerto Rico is exploring renewable energy and innovative technologies for energy storage, distributed generation, distribution control, electric vehicles, and energy efficient and responsive loads that can be deployed in each of Puerto Rico's cities and communities. Launched in February 2022, a two-year study entitled Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy (PR100) will perform a comprehensive analysis of stakeholder-driven pathways to Puerto Rico's clean energy future. This fact sheet describes the five activities this robust and objective energy analysis entails.

ENERGY PLANNING, POLICY, AND ECONOMY↗

A Study of Emerging Ancillary Service Markets in Non-Restricted Regions of the Western Power Grid (CRADA Final Report)

Rising penetrations of renewable energy generation in the Western United States pose new requirements for ancillary services, which are the services required, in addition to energy service, in order to maintain the system reliability. This project combines the research capabilities of the National Renewable Energy Laboratory (NREL) and the University of Colorado at Boulder (CU-Boulder) to provide more accurate information to market participants and regulators about the present and future size and composition of ancillary service markets in the non-restructured regions of the West. This information would provide market participants and state and federal regulators with a more transparent view of future ancillary service markets, and allow for more efficient system planning in both the private and public sectors of the electricity market.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Accelerating nuclear-integrated data center pursuits in the USA: SWOT analysis, power-thermal management strategies and demonstration plan

Here, this study explores the increasing interest in leveraging nuclear power to meet the escalating energy demands of data centers in the United States (U.S.) by focusing on key factors that contribute to accelerated deployment. The study highlights the importance of N+1/N+2 power supplies (where N is the required number of units), outlines research and innovations in nuclear-integrated data center thermal management and demonstration plan. It also provides updates about status and costing of various reactor system designs. A summarized strengths, weaknesses, opportunities, and threats (SWOT) analysis shows the potential options for grid connectivity, reactors, and site selection. Suitable site discussions consider land and water availability, grid access, and optical fiber connectivity, and the study presents graded prospects for Department of Energy (DOE) sites with a specific example. Community engagement and partnerships are emphasized, particularly the roles of local government, federal agencies, utilities, and data center industry partners, which are crucial for accelerating deployment, business outreach, and approvals. The study provides actionable insights for stakeholders to accelerate the deployment of nuclear-powered data centers.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Frequency Stability Enhancement in a Fully Solar Power Grid: A Case Study on the Saudi Model

Recently, renewable energy sources (RES) such as solar photovoltaic (PV) have been recognized for their significant potential. Several studies have explored the issue of frequency stability with high RES penetration. A significant observation related to this issue is the decline in the weighted short circuit ratio (WSCR), which has the potential to adversely affect system stability. This research uniquely focuses on the gradual transition of the Saudi Electricity Company (SEC) system to a fully integrated solar PV grid, offering insight and methodology that can be adapted for other power systems. While a variety of mitigation methods are available, synchronous condensers (SC) were used in this study to stabilize grid frequency, and their implementation has been shown to improve the overall performance of the system. In response to the observed decline in WSCR, a comprehensive short circuit analysis was applied across all regions in the Saudi power grid model to evaluate the reduction in short circuit power and highlight areas requiring enhancement. Finally, scenarios illustrating frequency response with a gradual increase in SCR were analyzed, with the objective of establishing a stable, fully solar PV power system that is resilient to sudden power grid disturbances.

14 SOLAR ENERGY↗

Sub-melt nanosecond pulsed-laser induced densification and strain-field relaxation in single-crystal diamond

Dislocations and polishing-induced defect networks in synthetic diamond introduce local strain fields and broaden Raman features, limiting performance in optical, thermal, and electronic applications. Laser annealing is emerging as a promising approach to repair surface and near-surface defects in diamond without entering the melt regime, yet surface densification, defect-state modification, and associated structural changes have not been well quantified. In this work, we show that sub-melt nanosecond pulsed-laser annealing (PLA) induces near-surface densification and defect-mediated strain relaxation in single-crystal Chemical Vapor Deposition (CVD) diamond. Single- and two-pulse PLA were applied, and structural evolution was quantified using co-registered ISO 25,178 white-light interferometry, depth-resolved Raman spectroscopy, and cross-sectional STEM with geometric phase analysis (GPA). Across a 5 × 6 grid (n = 30), responsive regions exhibit large reductions in local slope (Sdq 45–65%), developed area (Sdr 60–90%), height spread (Sp, Sz 30–65%), void volume (Vv 57–60%), and roughness amplitude (Sa, Sq 48–57%), consistent with densification of ∼4–6.5 nm. Raman profiling shows narrowing of the diamond line and improved spectral uniformity to depths of ∼2–3 μm. Given that the Raman probing depth significantly exceeds the densified layer thickness, this response is interpreted as consistent with long-range strain-field redistribution originating from the near-surface region. STEM-GPA strain maps further support this interpretation, showing smoother strain fields, suppressed hotspots, and redistribution of localized strain concentrations following PLA. These results are consistent with defect-mediated strain relaxation and densification-driven modification of the near-surface energy state. The approach provides a scalable pathway for improving near-surface structural quality in diamond relevant to electronic, photonic, and quantum applications.

Areal surface metrology (ISO 25,178)↗

Understanding Precipitation Bias Sensitivities in E3SM-Multi-Scale Modeling Framework From a Dilution Framework

We investigate a set of Energy Exascale Earth System Model Multi-scale modeling framework (MMF) (E3SM-MMF) simulations that vary the dimensionality and momentum transport configurations of the embedded cloud-resolving models (CRMs), including unusually ambitious 3D configurations. Issues endemic to all MMF simulations include too much Intertropical Convergence Zone rainfall and too little over the Amazon. Systematic MMF improvements include more on-equatorial rainfall across the Warm Pool. Interesting sensitivities to the CRM domain are found in the regional time-mean precipitation pattern over the tropics. The 2D E3SM-MMF produces an unrealistically rainy region over the northwestern tropical Pacific; this is reduced in computationally ambitious 3D configurations that use 1,024 embedded CRM grid columns per host cell. Trajectory analysis indicates that these regional improvements are associated with desirably fewer tropical cyclones and less extreme precipitation rates. To understand why and how the representation of precipitation improved in 3D, we propose a framework that dilution is stronger in 3D. This viewpoint is supported by multiple indirect lines of evidence, including a delayed moisture-precipitation pickup, smaller precipitation efficiency, and amplified convective mass flux profiles and more high clouds. We also demonstrate that the effects of varying embedded CRM dimensionality and momentum transport on precipitation can be identified during the first few simulated days, providing an opportunity for rapid model tuning without high computational cost. Meanwhile the results imply that other less computationally intensive ways to enhance dilution within MMF CRMs may also be strategic tuning targets.

54 ENVIRONMENTAL SCIENCES↗

An Analysis of Post Attack Impacts and Effects of Learning Parameters on Vulnerability Assessment of Power Grid

Due to the increasing number of heterogeneous devices connected to electric power grid, the attack surface increases the threat actors. Game theory and machine learning are being used to study the power system failures caused by external manipulation. Most of existing works in the literature focus on one-shot process of attacks and fail to show the dynamic evolution of the defense strategy. In this paper, we focus on an adversarial multistage sequential game between the adversaries of the smart electric power transmission and distribution system. We study the impact of exploration rate and convergence of the attack strategies (sequences of action that creates large scale blackout based on the system capacity) based on the reinforcement learning approach. We also illustrate how the learned attack actions disrupt the normal operation of the grid by creating transmission line outages, bus voltage violations, and generation loss. This simulation studies are conducted on IEEE 9 and 39 bus systems. The results show the improvement of the defense strategy through the learning process. The results also prove the feasibility of the learned attack actions by replicating the disturbances created in simulated power system.

attack impacts↗

Q-Learning-Based Impact Assessment of Propagating Extreme Weather on Distribution Grids

The increasing number of power outage events due to extreme weather conditions is hampering us socioeconomically. Preparing in advance for the extreme weather event is critical. It can help utility operators to reduce grid damages, restore grid service quickly, allocate energy resources and repair crews strategically, and hence dramatically increase grid resilience. In this paper, we propose a method to identify the sequence of worst impact zones in the power grid caused by extreme weather events based on Q-learning (a reinforcement learning algorithm). To quantity the weather severity and its effect on the grid, we model the impact of extreme weather on the grid as a function of intensity, vulnerability, and exposure. A modified IEEE 123-node distribution feeder is presented in a mesh grid and experimented for sequences of zones identification. Finally, simulation results present the identified sequences and their associated impacts on the grid caused by extreme weather events.

distribution system↗

Fault Detection Utilizing Convolution Neural Network on Timeseries Synchrophasor Data From Phasor Measurement Units

An end-to-end supervised learning method is proposed for fault detection in the electric grid using Big Data from multiple Phasor Measurement Units (PMUs). The approach consists of preprocessing steps aimed at reducing data noise and dimensionality, followed by utilization of six classification models considered for detecting faults. Three of the models were variants of Convolutional Neural Network (CNN) architectures that consider a single type of measurement (voltage, current or frequency) at all PMUs or all types together also at all PMUs. CNN based models were compared to traditional methods of Logistic Regression (LR), Multi-layer Perceptron (MLP) and Support Vector Machine (SVM). Evaluation was conducted on two-year data measured by PMUs at 37 locations in a large electric grid. Here, the response variable for classification were extracted from the grid-wide outage event log. Experiments show that CNN-based models outperformed traditional methods on one year out-of-sample outage detection over the entire grid.

42 ENGINEERING↗

Waiting in Queue: A Historical Evaluation of Interconnection Policy

Both states and Independent System Operators (ISO)/Regional Transmission Organizations (RTO) have struggled with long wait times in interconnection queues. As a result, numerous reforms have been proposed to expedite the connection of new resources to the grid. This paper conducts a quantitative analysis of two of these policies: one providing detail hosting capacity information in Massachusetts, the other experimenting with cost allocation in New York. We find that both policies led to a statistically significant decrease in the times projects spend pending in interconnection queues, with New York seeing a small drop in days pending, and Massachusetts seeing a much larger one. We also include an analysis of how energy storage is impacts queue time in these states. These results can help inform regulators who are weighing reforms to interconnection policies, with the goal of reducing wait times.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Q-Learning Based Impact Assessment of Propagating Extreme Weather on Distribution Grids: Preprint

Increasing number of power outage events due to extreme weather condition is hampering us socioeconomically. Preparing in advance for the extreme weather event is critical and can help utility operators to reduce grid damages, restore grid service quickly, allocate energy resources and repair crews strategically, and hence dramatically increase grid resilience. In this paper, we propose a method to identify the sequence of worst impact zones in the power grid caused by extreme weather events based on Q-learning (a reinforcement learning algorithm). To quantify weather severity and it’s effect on the grid, we model the impact of extreme weather on the grid as a function of intensity, vulnerability and exposure. A modified IEEE 123-node distribution feeder is presented in a mesh grid and experimented for sequences of zones identification. Finally, simulation results present the identified sequences and their associated impacts on the grid caused by the extreme weather events.

distribution system↗

Dynamic Phasor Modeling of Three Phase Voltage Source Inverters

With the increase in the development and implementation of distributed energy resources, application of parallel connected inverters is increasing and as a result having accurate modeling and simulation tools that can help in the design, analysis and stability assessment of the grid is of great importance. Development of fundamental methods that can achieve accurate, reliable, and computationally efficient results can be very beneficial. Application of Dynamic phasor (DP) modeling method has been limited to study of limited harmonics and small combination of interconnected converters due to the complexity associated with developing models that describe larger systems. In this paper, application of DP modeling method is expanded to model any number of parallel connected three phase voltage source inverter (VSI) with inclusion of a wider harmonic content including fundamental, subharmonics, inter-harmonics, switching frequency and their sidebands. Results achieved from this modeling method is compared with conventional average model as well as detailed switching model and the effect of inclusion of wider harmonic content on accuracy of DP modeling method is demonstrated.

Xue, Yaosuo↗

US 2023/0182605 A1 Network constraint energy management system for electric vehicle depot charging and scheduling

Network constraint energy management system for electric vehicle (EV) depot charging and scheduling. In an embodiment, a power schedule is received from an economic dispatch application for a charging depot comprising EV charging station(s) and distributed energy resource(s). The power schedule may be simulated on a distribution network model of the charging depot, according to load flow analysis, to determine whether any grid-code violations occur. In response to the detection of violation(s), a constraint may be generated for each violating node, and the economic dispatch application may be re-executed with the constraint(s) to produce a new power schedule, until no violations are detected. When not all load demand can be satisfied by the power schedule, a charging schedule may be adjusted to ensure that critical energy requirements are satisfied. The final power and charging schedules may be used to schedule and control power generation and charging in the charging depot.

Hafiz, Faeza↗