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At least 685 records · Page 38

URBAN-NET-TOOLKIT

Strengthening and maintaining secure, functioning, and resilient Critical Infrastructure Systems (CISs) is one of our nation's primary goals, and it requires proactive and coo0rdinated efforts among federal, state, local, public and private owners and operators of CISs. Recent worldwide extreme events have shown how interdependencies across CISs (electric grid, telecommunications, transportation, water networks, etc.) can drastically increase system vulnerability. To understand these complex interdependencies, ORNL has instantiated Urban-NET, a novel decision support system for CIS operators who need to identify vulnerabilities for minimizing the cascading impacts - saving utilities, the federal and state government, and private sector companies potentially billions by avoiding a complete CI failure and/or shutdown. The developed system includes a stack of software tools for preprocessing, modeling, interconnecting multiple CIS datasets as an integrated heterogeneous graph (i.e. network), identifying vulnerabilities through topological analysis, and predicting consequences based on simulations along with visualization.

Chinthavali, Supriya↗

Is Clean Hydrogen Production a Good Fit for Questa? Intermediate Feasibility Study Results

NREL conducted a feasibility study for a clean hydrogen production facility that would be located in Questa, New Mexico. This slide deck presents the history of the coalition of stakeholders that received NREL technical assistance through the Department of Energy's Communities Leading Energy Action Program. It describes how hydrogen is generated and its end uses. It describes two conceptual applications explored in the feasibility analysis, a grid-tied power generation and long-term storage application and a heavy-duty vehicle fueling application. The presentation details the configuration of these to applications in the Questa pilot facility, including system components, required inputs (water, electricity, and land for pv generation), and outputs in kilograms of hydrogen, megawatt hours of power delivered, and hours of vehicle hours of operation. The presentation addresses key concerns raised by groups engaged through a public outreach process, including safety, health, and environmental issues; water use; visual impacts; and costs and alternatives.

heavy-duty vehicle fueling↗

Observation and Simulation of Methane Plumes During the Morning Boundary Layer Transition

Abstract Methane (CH 4 ) contributes significantly to global warming. However, accurate identification of CH 4 sources for reducing CH 4 emissions is often hampered by inadequate accuracy and spatiotemporal coverage of CH 4 detection, and lack of accurate CH 4 forward modeling used in top‐down inversion systems. In this study, a field experiment was conducted in Pampa, Texas using two CH 4 sensors (LI‐COR and OGI camera) to detect CH 4 releases. We investigated whether high‐resolution simulations using the Weather Research and Forecasting (WRF) model with greenhouse gases (WRF‐GHG) could accurately simulate the CH 4 plumes in the presence of evolving atmospheric boundary layer from sunrise to noon. CH 4 plumes showed substantial variation in time. At a release rate of ∼17.5 kg hr −1 , the maximum enhancement of CH 4 measured by LI‐COR was 2.6 ppm at sunrise (7:36 a.m.), 250 m from the release location. Within half an hour after sunrise, this enhancement decreased to 0.3–0.4 ppm. The enhancement was 0.2 ppm by 10:00 a.m. and further dropped to less than 0.1 ppm after 11:30 a.m. Due to the low temperature at sunrise, the OGI camera failed to detect the CH 4 plume. The WRF‐GHG large‐eddy simulation (LES) with 32 m grid spacing successfully reproduced these CH 4 enhancements. In situ measurements together with numerical simulations illustrate the impact of the transition from a stable boundary layer in the early morning to a convective boundary layer at noon on the dispersion of CH 4 plumes. Additionally, CH 4 plumes from a cattle farm in Oklahoma are briefly examined using the same modeling approach.

Hu, Xiao‐Ming [Center for Analysis and Prediction ↗

Characterizing How Meteorological Forcing Selection and Parameter Uncertainty Influence Community Land Model Version 5 Hydrological Applications in the United States

Despite the increasing use of large-scale Land Surface Models (LSMs) in predicting hydrological responses in extreme conditions, there's a critical gap in understanding the uncertainties in these predictions. This study addresses this gap through a detailed diagnostic evaluation of the uncertainties arising from meteorological forcing selection and model parametrization in hydrological simulations of the Community Land Model version 5 (CLM5). CLM5 is configured at a spatial scale of about 12-km to simulate runoff processes for 464 headwater watersheds, selected from the Catchment Attributes for Large-Sample Studies (CAMELS) dataset to be representative of physiographic and climatic gradients across the conterminous United States. For each watershed, CLM5 is driven by five commonly used gridded forcing datasets in combination with a large ensemble (> 1200) of key CLM5 hydrologic parameters. Our results suggest that uncertainty in CLM5 runoff simulations resulting from both forcing and parametric sources is markedly higher in arid regions, e.g., Great Plains and Midwest regions. Uncertainty in low flow is dominated by parametric uncertainty, while the selection of meteorological forcing contributes more dominantly to high flow and seasonal flows during fall and spring. Our analysis also demonstrates that the selection of forcing datasets and the metrics used to calibrate CLM5 significantly impact the model’s predictive accuracy in extreme event severity for both floods and droughts. Overall, the results from this study highlight the need to understand and account for forcing and parametric uncertainties in CLM5 simulations, particularly for hazard and risk assessments addressing hydrologic extremes.

54 ENVIRONMENTAL SCIENCES↗

Enhancing Short-Term Flexibility through Characterization of HVDC Transmission Systems

Efficient power grid operation hinges on maintaining safety and reliability through adaptable system flexibility standards. However, in a future power grid characterized by extensive renewable energy integration, conventional system flexibility and predetermined requirements may falter under extreme conditions. This paper addresses the formidable challenge of sustaining secure and dependable power grid operations under these circumstances, emphasizing the role of controllable high voltage direct current (HVdc) transmission systems in amplifying overall system flexibility and tackling operational complexities. To quantitatively assess short-term flexibility and its associated economic benefits from HVdc within specific regions, we propose a Power Flow Distribution Factors (PTDFs) based approach. This methodology takes into account both dispatchable generators and HVdc systems, pinpointing their contributions. Through an analysis of the Western Electricity Coordinating Council (WECC) system, we demonstrate the practical application of this approach to scrutinize the impacts of existing and future HVdc lines.

Operational Flexibility, Multi-terminal HVdc, tran↗

Cybersecurity of Networked Microgrids: Challenges Potential Solutions and Future Directions

Networked microgrids are clusters of geographically-close, islanded microgrids that can function as a single, aggregate island. This flexibility enables customer-level resilience and reliability improvements during extreme event outages and also reduces utility costs during normal grid operations. To achieve this cohesive operation, microgrid controllers and external connections (including advanced communication protocols, protocol translators, and/or internet connection) are needed. However, these advancements also increase the vulnerability landscape of networked microgrids, and significant consequences could arise during networked operation, increasing cascading impact. To address these issues, this report seeks to understand the unique components, functions, and communications within networked microgrids and what cybersecurity solutions can be implemented and what solutions need to be developed. A literature review of microgrid cybersecurity research is provided and a gap analysis of what is additionally needed for securing networked microgrids is performed. Relevant cyber hygiene and best practices to implement are provided, as well as ideas on how cybersecurity can be integrated into networked microgrid design. Lastly, future directions of networked microgrid cybersecurity R&D are provided to inform next steps.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Backup Power Performance of Solar-plus-Storage Systems during Routine Power Interruptions: A Case Study Application of Berkeley Lab’s PRESTO Model

This technical brief estimates the expected performance of a solar photovoltaic and energy storage system (PVESS) for providing backup power during short-duration power interruption events, accounting for the unpredictable nature of those events. The analysis relies on the Power Reliability Event Simulation TOol (PRESTO), a publicly available model developed by Berkeley Lab to simulate the occurrence of short-duration power interruption events at the county-level. A separate storage dispatch model is then used to simulate PVESS operation and backup performance for each of the large number of interruption events produced by PRESTO. In performing this simulation, the analysis accounts for how the customer operates its battery on a day-to-day basis—in this case, we assume the battery is cycled each day in response to time-of-use rates—and how that, in turn, impacts the battery’s state of charge at the beginning of each interruption event. The analysis presented here is intended to demonstrate an application of the PRESTO model as well as to illustrate some of the key determinants of PVESS backup power performance during short-duration power interruption events. The analysis focuses initially on a typical single-family home in Maricopa County, Arizona, and includes a limited set of scenarios related to system sizing, backup power configuration, and whether the customer charges its battery storage system from the grid during normal operating conditions. The analysis also presents comparative results for two other counties, in Massachusetts (Middlesex) and California (Los Angeles), illustrating how regional differences in climate, interruption patterns, and retail rate structures can affect PVESS performance as a backup power source. In the conclusions, we highlight a number of other important considerations for evaluating PVESS backup power capabilities.

14 SOLAR ENERGY↗

Air Dispersion Modeling for the INL Application for a Synthetic Minor Sitewide Air Quality Permit to Construct with a Facility Emission Cap Component

The Department of Energy Idaho Operations Office (DOE-ID) is applying for a synthetic minor, Sitewide, air quality permit to construct (PTC) with a facility emission cap (FEC) component from the Idaho Department of Environmental Quality (DEQ) for Idaho National Laboratory (INL) to limit its potential to emit to less than major facility limits for criteria air pollutants (CAPs) and hazardous air pollutants (HAPs) regulated under the Clean Air Act. This document is supplied as an appendix to the application, Idaho National Laboratory Application for a Synthetic Minor Sitewide Air Quality Permit to Construct with a Facility Emissions Cap Component, hereafter referred to as “permit application” (DOE-ID 2015). Air dispersion modeling was performed as part of the permit application process to demonstrate pollutant emissions from the INL will not cause a violation of any ambient air quality standards. This report documents the modeling methodology and results for the air dispersion impact analysis. All CAPs regulated under Section 109 of the Clean Air Act were modeled with the exception of lead (Pb) and ozone, which are not required to be modeled by DEQ. Modeling was not performed for toxic air pollutants (TAPs) as uncontrolled emissions did not exceed screening emission levels for carcinogenic and non-carcinogenic TAPs. Modeling for CAPs was performed with the EPA approved AERMOD dispersion modeling system (Version 14134) (EPA 2004a) and five years (2000-2004) of meteorological data. The meteorological data set was produced with the companion AERMET model (Version 14134) (EPA 2004b) using surface data from the Idaho Falls airport, and upper-air data from Boise International Airport supplied by DEQ. Onsite meteorological data from the Grid 3 Mesonet tower located near the center of the INL (north of INTEC) and supplied by the local National Oceanic and Atmospheric Administration (NOAA) office was used for surface wind directions and wind speeds. Surface data (i.e., land use data that defines roughness, albedo, Bowen ratio, and other parameters) were processed using the AERSURFACE utility (Version 13016) (EPA 2013). Emission sources were modeled as point sources using actual stack locations and dimensions. Emissions, flow rates and exit temperatures were based on the design operating capacity of each source. All structures close enough to produce an area of wake effect were included for all sources. For multi-tiered structures, the heights of the tiers were included or the entire building height was assumed to be equal to the height of the tallest tier. Concentrations were calculated at 1,352 receptor locations provided by DEQ. All receptors were considered for each pollutant and averaging period. Maximum modeled CAP concentrations summed with average background concentration values were presented and compared to National Ambient Air Quality Standards (NAAQS). The background concentration values used were obtained using the Washington State University’s Laboratory for Atmospheric Research North West Airquest web-based retrieval tool (http://lar.wsu.edu/nw airquest/lookup.html). The air dispersion modeling results show the maximum impacts for CAPs are less than applicable standards and demonstrate the INL will not cause a violation of any ambient air quality standards.

54 ENVIRONMENTAL SCIENCES↗

CMIP7 data request: land and land ice priorities and opportunities

The Land and Land Ice Theme in the Coupled Model Intercomparison Project Phase 7 (CMIP7) represents the current understanding of physical processes in land surface ecosystems, hydrology, cryosphere, and their physical interactions with other Earth system components. Simulations from Earth system models (ESMs) could provide crucial information for assessing planetary safety, such as critical tipping elements, and be used to inform climate risks for improving climate impact assessments and policy decisions. This paper presents a collaborative effort to identify scientific opportunities in the Land and Land Ice Theme of the CMIP7 Data Request. The proposed opportunities build upon advances in ESMs, including new freshwater system and land ice processes being included in CMIP7, as well as the scientific community's demand for high-frequency and sub-grid-scale land surface outputs. In total, 25 variable groups that contain 716 variables have been identified to be potentially available to the broad scientific audience for performing analysis in land–atmosphere coupling, hydrological processes and freshwater systems, glacier and ice sheet mass balance and their influence on the sea levels, land use, and plant phenology. Key reflections from this data request effort include advocacy for closer engagement between the user community and modeling groups, reduction in the technical barriers to tracking existing parameters and defining new variables, and more streamlined variable management. These will be essential to enhance the usability and reliability of CMIP7 outputs for climate and Earth system research and applications to a broad audience that relies on the CMIP7 endeavor.

Li, Yue [Univ. of California, Los Angeles, CA (Uni↗

Assessment of Economic Impact of Permitting Timelines on Produced Geothermal Power in Imperial County, California

Despite having a large geothermal power potential in the United States, only a small fraction has been developed for power generation. Various barriers, including technical, financial, and regulatory permit delays, are attributed to lower contribution of geothermal energy in the national grid. Unpredictable environmental reviews and permitting timelines are some of the non-technical barriers that can cause delays in geothermal exploration and utilization plans. Our study shows that the geothermal permitting timelines can vary from six months to several years, depending on the presence or absence of biological resources, cultural resources, and sensitive environmental issues at the project site. The potential impacts of these permit barriers can range from investors abandoning geothermal development to making the product (i.e., electricity) more expensive and uncompetitive. In this study, we conducted economic analysis to assess the impact of permitting timelines on cost of produced electricity from geothermal resources using data from existing geothermal plants as well as prospective sites. In this paper, we present collected timelines data, approach, and results of economic impact of permitting timelines on geothermal power. We evaluated the various environmental management and permit review processes by considering a hypothetical geothermal project in the Salton Sea Known Geothermal Resource Area. Because of the variety of the biological and environmental issues and the involvement of local, state, and federal agencies with overlapping jurisdictions, this project could go through one of the many California Environmental Quality Act (CEQA) and National Environmental Policy Act (NEPA) review scenarios that range from the least to the most complex in its circumstances. The fastest CEQA/NEPA review timelines would have the project completed in six years. In contrast, the project would substantially need longer time to complete if it were located in an area with significant environmental resources or cultural issues that required permitting from various agencies. With increasing project completion timelines, the simplified levelized cost of electricity (sLCOE) can be 4 to 11% higher with longer CEQA/NEPA review timelines than the sLCOE value with the fastest CEQA/NEPA review timeline. Lengthier CEQA/NEPA review timelines could also result in loss of $64 million to $227 million in potential revenue. Such significant economic impacts could determine the success of a geothermal project.

15 GEOTHERMAL ENERGY↗

Updraft dynamics and microphysics: on the added value of the cumulus thermal reference frame in simulations of aerosol–deep convection interactions

One fundamental question about atmospheric moist convection processes that remains debated is whether, or under which conditions, a relevant variability in background aerosol concentrations may have a significant dynamical impact on convective clouds and their associated precipitation. Furthermore, current climate models must parameterize both the microphysical and the cumulus convection processes, but this is usually implemented separately, whereas in nature there is a strong coupling between them. As a first step to improve our understanding of these two problems, we investigate how aerosol concentrations modify key properties of updrafts in eight large-eddy-permitting regional simulations of a case study of scattered convection over Houston, Texas, in which convection is explicitly simulated and microphysical processes are parameterized. Dynamical and liquid-phase microphysical responses are investigated using the following two different reference frames: static cloudy updraft grid cells versus tracked cumulus thermals. In both frameworks, we observe the expected microphysical responses to higher aerosol concentrations, such as higher cloud number concentrations and lower rain number concentrations. In terms of the dynamical responses, both frameworks indicate weak impacts of varying aerosol concentrations relative to the noise between simulations over the observationally derived range of aerosol variability for this case study. On the other hand, results suggest that thermals are more selective than cloudy updraft grid cells in terms of sampling the most active convective air masses. For instance, vertical velocity from thermals is significantly higher at upper levels than when sampled from cloudy updraft grid points, and several microphysical variables have higher average values in the cumulus thermal framework than in the cloudy updraft framework. In addition, the thermal analysis is seen to add rich quantitative information about the rates and covariability of microphysical processes spatially and throughout tracked thermal lifecycles, which can serve as a stronger foundation for improving subgrid-scale parameterizations.

54 ENVIRONMENTAL SCIENCES↗

Updraft Dynamics and Microphysics: On the Added Value of The Cumulus Thermal Reference Frame in Simulations of Aerosol–Deep Convection Interactions

One fundamental question about atmospheric moist convection processes that remains debated is whether, or under which conditions, a relevant variability in background aerosol concentrations may have a significant dynamical impact on convective clouds and their associated precipitation. Furthermore, current climate models must parameterize both the microphysical and the cumulus convection processes, but this is usually implemented separately, whereas in nature there is a strong coupling between them. As a first step to improve our understanding of these two problems, we investigate how aerosol concentrations modify key properties of updrafts in eight large-eddy-permitting regional simulations of a case study of scattered convection over Houston, Texas, in which convection is explicitly simulated and microphysical processes are parameterized. Dynamical and liquid-phase microphysical responses are investigated using the following two different reference frames: static cloudy updraft grid cells versus tracked cumulus thermals. In both frameworks, we observe the expected microphysical responses to higher aerosol concentrations, such as higher cloud number concentrations and lower rain number concentrations. In terms of the dynamical responses, both frameworks indicate weak impacts of varying aerosol concentrations relative to the noise between simulations over the observationally derived range of aerosol variability for this case study. On the other hand, results suggest that thermals are more selective than cloudy updraft grid cells in terms of sampling the most active convective air masses. For instance, vertical velocity from thermals is significantly higher at upper levels than when sampled from cloudy updraft grid points, and several microphysical variables have higher average values in the cumulus thermal framework than in the cloudy updraft framework. In addition, the thermal analysis is seen to add rich quantitative information about the rates and covariability of microphysical processes spatially and throughout tracked thermal lifecycles, which can serve as a stronger foundation for improving subgrid-scale parameterizations.

aerosols↗

Identification of Worst Impact Zones for Power Grids During Extreme Weather Events Using Q-Learning: Preprint

Both the frequency and intensity of extreme weather events have been trending higher in recent years, leading to significant infrastructure loss in the electric grid. The impact of these extreme weather events is desired to be analyzed and quantified in order to help transmission and distribution system operators to prepare and prevent significant losses. In this paper, we developed an approach that models the impact of extreme weather on the power grid and identifies the worst impact zone using Q-learning (a reinforcement learning approach). The identification results reveal grid vulnerability to weather events and provide insights for system operators to help achieve optimal resource allocation and crew dispatch in order to minimize the adverse impact of extreme weather. Simulation studies are conducted on the IEEE 123-node system to demonstrate the performance of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Rewarding Grid-Friendly Behavior: Estimating the Potential Bill Reduction and Load Shifting Benefits of Dynamic Prices

Shifting electric load from times of peak demand can be a key strategy to slow price growth as reducing peak demand avoids the cost of upgrading generation, transmission and distribution infrastructure. Utilities are releasing time-varying prices, such as time of use rates or dynamic prices, to incentivize grid-friendly load shifting. New dynamic price programs provide insight into the true cost of operating electricity grids and the potential economic benefits of load shifting. Program developers and device manufacturers need to understand the economic opportunities in terms of 1) the variation in prices across hours, days, and seasons; 2) the change in utility bills for customers who don’t shift load; and 3) the potential load shifted and economic value of different technologies if manufacturers or aggregators deploy price-responsive controls. This paper estimates possible impacts of dynamic price adoption and load shifting controls if customers paid the dynamic rate from one pilot program. Statistical analysis of historical prices identified annual and seasonal metrics as well as representative price curves for each circuit in the pilot. Simulations for residential technologies with price-responsive controls including unitary heat pump water heaters, central multifamily heat pump water heaters, heating & cooling + storage systems, and pool pumps estimated the potential impacts of highly dynamic prices both with and without load shifting controls. Results showed the potential to reduce electricity costs on representative days by 42-94% and reduce consumption during times of high electricity prices by 63-100% compared to baseline operation for those flex-friendly devices.

Grant, Peter↗

Simulating Impacts of Extreme Events on Grids with High Penetrations of Wind Power Resources

As extreme weather events become more frequent and intense, the demand for connecting grid operation and infrastructure planning with extreme event models will increase as well. We present a methodology for creating damage contingencies and scenarios for electric transmission grids during a hurricane strike. Included is an example case study: Hurricane Dolly damaging a synthetic 2000 bus test system during its landing in Southern Texas. Using WIND Toolkit meteorological data in conjunction with fragility curves for various electric grid elements, we generate stochastic damage scenarios that can be used for short- and long-term planning problems including emergency asset management. We perform statistical analysis of damages and quantify topological effects on example synthetic grid. Also, we investigate loss-of-load events during two-day economic dispatch experiment. Finally, we point out various shortcomings of our method and suggest how it can be improved.

data-driven forecasting↗

Co-Simulation of PSS/E, OpenDSS, and PSCAD for Power Systems Stability Analysis With Inverter-Based Resources: Preprint

The increasing penetration of inverter-based resources (IBRs) is reshaping the dynamic behavior of power systems. IEEE standard 1547-2018 suggests that distributed energy resources (DERs) should provide grid services such as voltage and frequency supports. On the other hand, dynamic events caused by IBRs such as sub-synchronous oscillation have been reported. These developments necessitate improvement in the current modeling capabilities to better understand the interdependencies within power systems. These include interactions between transmission and distribution systems, among IBRs themselves, and between IBRs and conventional resources. In this paper, we present a co-simulation model integrating PSS/E, OpenDSS, and PSCAD to analyze IBR impacts on the stability of transmission and distribution systems. A key challenge in developing a co-simulation model is ensuring interoperability among different simulators (interfacing and data flow) while maintaining accurate results. Using the developed model, we simulate the impact of IBRs on power systems in two test cases: 1) fault ride through (FRT) capability during a generation trip contingency; 2) IBR-induced sub-synchronous oscillation. The results show the effectiveness of the co-simulation model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Insights into Methodologies and Stochastic Optimization of Thermal Energy Storage-Coupled Advanced Reactor Systems: A Comparison of Methods for Accessing Long-Term Sub-System Sizing Adequacy

This paper investigates the potential of coupling Thermal Energy Storage (TES) with Advanced Reactors (ARs) to address uncertainties posed by climate change in deep decarbonized power systems. The TES Use-case Team at Idaho National Laboratory (INL) has examined the potential of storing thermal energy from ARs during low demand periods and optimizing discharge during peak-priced hours, in both steady-state and transient conditions. Building on this groundwork, this study bridges the gaps in optimal sizing of the sub-system of TES-coupled AR systems using Risk Analysis Virtual Environment (RAVEN) and Holistic Energy Resource Optimization Network (HERON), INL?s framework for grid optimization. By applying this framework, we present statistically-robust optimal charge, discharge including balance of plant (BOP), and storage sizing for the High-Temperature Gas-Cooled Reactor (HTGR) with 203 MWth output. To this end, we generated synthetic price samples for 30 years using 2018 ? 2021 real-time market data from ERCOT, PJM and MISO. Our results reveals that the TES-coupled HTGR system is highly effective in maximizing revenue from electricity sales. We observed a substantial increase of 40 % in ERCOT and a noteworthy 15 % increase in PJM and MISO when compared to the conventional BOP without TES. This improvement is achieved through regionally-tailored sub-system sizing, which ranges from 398 to 416 MWth for the discharge system and 610 to 1029 MWth for the TES. We find that the average electricity price directly impacts the overall economics, while price volatility influences storage size. Additional sensitivity analyses were performed to access the impact of key assumptions on system economics and sizing, differentiating the optimization window (i.e., 24 ? 219 hours of chronological observations) and by imposing storage continuity condition in tracking TES cycles. We observed that at the 120-hour of the optimization window, a reasonable balance between computation time and accuracy was achieved. Our analysis also highlights the significance of conducting multi-day cycle analysis (> 120-hour) for TES to capture interaction between electricity prices and storage dynamics, providing a comprehensive understanding of TES behavior that AR developers should integrate into their plant designs.

25 ENERGY STORAGE↗