Modeling Adequacy of Droop-Controlled Grid-Forming Converters for Transient Studies: Singular Perturbation Analysis
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Geomagnetic-induced current (GIC) flow in power grids can cause undesirable effects such as transformer overheating, harmonics, higher reactive power demand, etc. Many simulation models have been developed to study these effects, but real-world verification on modern transformer designs is rare. Here, this paper presents the first long-duration GIC field test in the U.S. performed on high-voltage, grid-connected transformers featuring winding clamps and tie rods instead of conventional tie bars. Field measurements were taken to evaluate GIC effects. These measurements also aided in developing and validating thermal and electromagnetic transient (EMT) models of the transformers. During the test, significant current and voltage distortions were observed along with considerable transformer reactive power losses. Analysis of the field measurements showed that the transformers’ hottest spot was at the inner windings, and their k-factors were close to factory test and software default values. Thermal simulations indicated that the transformers would not violate their thermal limits even for a GIC waveform that peaks at about 200 A/phase. EMT simulations revealed that increased transformer loading may reduce GIC-induced reactive power demand and harmonics in certain scenarios. The study also highlighted potential inaccuracies in using the k-factor method to calculate transformer reactive power losses.
Momentary cessation (MC) and response to rate-of-change-of-frequency (ROCOF) are inverter responses that can have serious impact on the stability of the grid during abnormal conditions. Though IEEE Std 1547-2018 provides fairly well defined expected responses from inverter-based DERs during abnormal grid conditions, a significant portion of currently installed DERs in the distribution network do not have a well defined response to abnormal grid conditions. Any analysis of the grid involving inverter MC and ROCOF response must consider the specific characteristics of these responses for the installed DERs to have better confidence in the analysis results, especially for grids with high levels of DERs. However, there is lack of information on MC and ROCOF response for the inverters already installed in the field. In this paper, we examine a large data set of installed inverters to map the dominant population of installed inverters. This information is then used to characterize the most dominant MC and ROCOF responses of installed inverters using experimental data.
Smart grids are envisioned to accommodate high penetration of distributed photovoltaic (PV) generation, which may cause adverse grid impacts in terms of voltage violations. Therefore, PV Hosting capacity is being used as a planning tool to determine the maximum PV installation capacity that causes the first voltage violation and above which would require infrastructure upgrades. Additionally, traditional methods of Hosting capacity analysis are scenario based and computationally complex as they rely on iterative load flow algorithms that require investigating a large number of scenarios for accurate assessment of PV impacts. Therefore, this paper presents a computationally efficient analytical approach to compute the probability distribution of voltage change due to random behavior of randomly located multiple distributed PVs. The proposed approach is based on Spatio-temporal probabilistic voltage sensitivity analysis that exploits both spatial and temporal uncertainties associated with PV injections. Thereafter, the derived distribution is used to quantify voltage violations for various PV penetration levels and subsequently determine the hosting capacity of the system without the need to examine large number of scenarios. Results of the proposed framework are validated via conventional load flow based simulation approach on the IEEE 37 and IEEE 123 node test systems.
An interface with the OpenDSS distribution grid simulator, facilitating users in calibrating and validating models. Additionally, three distinct tools have been developed: PV Hosting Capacity: This tool allows users to determine the additional amount of photovoltaic (PV) generation that can be integrated into the system without breaching operational constraints. EV Hosting Capacity: This tool focuses on identifying the capacity for incorporating extra electric vehicle (EV) load into the system without surpassing operational limitations. Project Impact Analysis Tool: This tool is designed to assess and report all potential grid violations associated with a specific project, providing valuable insights into its impact on the distribution grid.
Fast-growing freight activities over the decades have become one of the major contributors to air pollution, leading to many efforts in freight decarbonization and electrification. However, the development of freight electrification is slow due to technological uncertainty, slow charging, high capital cost, etc. This paper analyzes the potential impact and benefit of heavy-duty vehicle (HDV) electrification and automation on fleet cost, infrastructure cost, the electricity grid, and environmental outcomes. In this work, we extended the vehicle electrification benefit analysis tool: Grid-Electrified Mobility (GEM) model, which had primarily been used to study light-duty passenger vehicles (LDVs), to analyze heavy-duty vehicle electrification. The extended model is derived for freight transportation electrification, and different freight electrification and automation adoption scenarios were analyzed. We find that the increased penetration of automated electric freight fleets within other types of electrified freight fleets from 1% to 99% will result in an overall cost reduction of 18.2%, fleet size reduction of 20.4%, and lower peak load reduction of 14.3%.
Increased penetration of power electronics in the grid is happening through development of high-power drives (like in Type 3 or 4 wind turbines, industrial drives, etc.), high-voltage direct current (HVdc) systems, flexible alternating current transmission systems (FACTS), energy storage systems (ESSs), inverter-based renewables like solar and wind, electric vehicle chargers, and other technologies. Ongoing research and development in new power electronic technologies including, but not limited to, solid-state power substations (SSPS), extreme fast charging (XFC), solid-state transformers, and multi-port power electronics that integrate multiple sources/loads will further increase penetration levels. To ensure stakeholders can integrate high penetration of power electronic technologies safely and reliably requires tools and methods to assess and evaluate their impact on the grid. Objectives: This report surveys, assesses, and analyzes commercially available and open-source tools that can support the assessment and evaluation of power electronics in future grids with high penetration levels. The study includes aspects that range from power flow analysis to dynamics evaluation (including hardware-in-the-loop – HIL testing) for such systems. The challenges and gaps associated with the current generation of toolsets available to assess the technical impact of introducing high penetration of power electronics are reported. The method is summarized in Figure ES-1.
Ongoing work in air-vehicle design illustrates the potential of advanced concepts to provide significant improvements in efficiency; but with their incorporation of lightweight flexible structures, such configurations may require active control systems to ensure reliability and safety. However, many contemporary analysis methods are inefficient for aeroelastic analysis and design of such configurations. This paper describes the development of a new approach that automates the geometry setup, mesh generation, and assembly of fluid–structural coupling interfaces to enable efficient aeroelastic and aeroservoelastic analysis of advanced concepts. The core elements for this approach are a cut-cell Cartesian grid-based computational fluid dynamics solver, a nonlinear beam element structural model, a conservative fluid–structural interface treatment, and the formulation and implementation of a new deforming grid capability within the cut-cell Cartesian grid solver. In this paper, emphasis is on this latter component with detailed description given of the mesh motion strategy, evaluation of fluxes and structural loads at the surface, and computation of geometrical properties such as cell volume, directed face areas, centroids, and motion-induced fluxes for deforming Cartesian grids required to advance the flow states. Aeroelastic simulations exercising the capability show favorable agreement with data and predictions in the literature for subsonic and supersonic applications.
xCDAT (Xarray Climate Data Analysis Tools) is an open-source Python package that extends Xarray (Hoyer & Hamman, 2017) for climate data analysis on structured grids. xCDAT streamlines analysis of climate data by exposing common climate analysis operations through a set of straightforward APIs. Some of xCDAT’s key features include spatial averaging, temporal averaging, and regridding. These features are inspired by the Community Data Analysis Tools (CDAT) library (Dean N. Williams et al., 2009) (D. N. Williams, 2014) (Doutriaux et al., 2019) and leverage powerful packages in the Xarray ecosystem including xESMF (Zhuang et al., 2023), xgcm (Abernathey et al., 2022), and CF xarray (Cherian et al., 2023). To ensure general compatibility across various climate models, xCDAT operates on datasets that are compliant with the Climate and Forecast (CF) metadata conventions (Hassell et al., 2017).
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Due to the rapid development of economies, large urban cities consume an increasing amount of energy and have a higher requirement for power quality. Voltage source converter based high voltage direct current (VSC-HVDC) is a promising device to transmit clean power from remote regions to urban power systems, while also providing wide area damping control (WADC) for frequency stabilization. However, the time-delay naturally existing in the VSC-HVDC system may degrade the performance of WADC and even result in instability. To address this issue, this paper develops a time-delay correction control strategy for VSC-HVDC damping control in urban power grids. First, a small signal model of WADC is built to analyze the negative impacts of time delay. Then, a data-driven approach is proposed to compensate for the inherent time delay in VSC-HVDC damping control. The extensive training data will be generated under various disturbances. After offline training, the long short-term memory network (LSTM) can be implemented online to predict the actual frequency deviation based on real-time measurements. Finally, the proposed method is validated through MATLAB-Simulink in a two-area four-machine system. The results indicate that the data-driven compensation has a strong generalization ability for random delay time constants and can improve the performance of WADC significantly.
Amidst ongoing discussions about hydropower removals, retirements, and reduced availability due to drought and other environmental considerations, it is important to understand the long-term effects of reduced hydropower resources on the U.S. electric grid. This analysis uses the Regional Energy Deployment System (ReEDS™) grid planning model to compare several representative scenarios of retiring hydropower and pumped storage hydropower (PSH) capacity over time and explore the overall implications on the U.S. grid from present day through 2050. Reduced hydropower capacity and generation is replaced by a mix of both fossil and non-fossil resources, including natural gas, wind, solar, and battery technologies. Additional natural gas usage leads to an increase in cumulative national electric sector carbon dioxide and criteria pollutant operating emissions of less than 1% in many scenarios but up to 4-5.3% in some cases. Total electric sector costs also increase by <1% in many scenarios but up to 3.6% in the most extreme scenarios where nearly all the hydropower and PSH fleet retires, equating to $\$$340 billion in undiscounted costs. National results indicate that absent additional interventions, retiring hydropower and PSH capacity could increase electric sector emissions and direct capital and operating costs. However, more focused analysis is required to evaluate specific asset-level, local, and regional implications, and a broader scope is necessary to weigh these electric sector impacts alongside economic, ecological, water management, and other cross-sectoral effects that could be either negative or positive.
In recent years, many electric utilities have submitted grid modernization plans for review by state public utility commissions. A central objective of these plans is to demonstrate that grid modernization investments will provide net benefits to customers, be reasonable and be in the public interest. The plans typically include some form of benefit-cost analysis, but the assumptions, methodologies and frameworks vary considerably between utilities. This report: -Describes utility-facing technologies and projects for modernizing distribution systems, including interdependencies of grid components -Highlights benefit-cost considerations related to grid modernization -Summarizes recent trends in benefit-cost analysis for grid modernization based on a review of 21 plans by U.S. electric utilities -Discusses challenges state public utility commissions face in reviewing utility plans and provides options for addressing challenges
As the penetration of power-electronics based smart inverters (SIs) is increasing in distribution grids, it adds computational challenges in solving dynamic models of large-scale distribution feeders. Voltage and reactive power (Volt/VAr), and voltage and active power (Volt/Watt) dynamics have been analyzed at slower time scales akin to the control of legacy grid devices. However, smart inverters, being power-electronics based devices, can provide dynamic active/reactive power support at a faster time scale, which necessitates Volt/VAr and Volt/Watt dynamics to be analyzed at a faster time scale. The existing dynamic models are overly detailed and computationally intractable for distribution feeders with a large number of inverters. In this context, this proposed work aims towards developing a computationally tractable, scalable, and accurate phasor-based model for dynamic Volt/VAr and Volt/Watt analyses of large distribution systems with high penetration of smart inverters. Case studies demonstrate that the proposed phasor-based model sufficiently captures the Volt/VAr and Volt/Watt dynamics, and is computationally faster by one order of magnitude compared to the average model and by two orders of magnitude compared to the detailed switching model. Case studies also demonstrate the efficacy and scalability of the proposed model in analyzing Volt/VAr and Volt/Watt dynamics of large-scale power networks with hundreds of SIs.
As part of CEF Round 1 funding, Pacific Northwest National Laboratory (PNNL) was engaged by the U.S. Department of Energy (DOE) and the Washington Department of Commerce to work with Puget Sound Energy (PSE), Avista, and Snohomish Public Utility District (SnoPUD) in evaluating the economic and technical performance of each of their battery energy storage systems (BESSs). This report presents the final results of the economic assessment.
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