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DOE OSTI2015

RACORO continental boundary layer cloud investigations. Part I: Case study development and ensemble large-scale forcings

Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60-hour case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in-situ measurements from the RACORO field campaign and remote-sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functions for concise representation in models. Values of the aerosol hygroscopicity parameter, κ, are derived from observations to be ~0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing datasets are derived from the ARM variational analysis, ECMWF forecasts, and a multi-scale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in 'trial' large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Deep Learning-enhanced Block-Diagram Modeling of Solar Power Systems

Data-driven models of power system inverter-based resources are desired to run simulations faster than with detailed electromagnetic transient models, to hide proprietary design details, to support control system design applications, and to aggregate the effects of distributed energy resources. This paper applies a customized Hammerstein Wiener framework to train block diagram models from thousands of electromagnetic transient simulations or experimental test records. The block diagram models integrate with larger grid simulations as voltagecontrolled current sources or current-controlled voltage sources for several simulators. Guidelines for block architecture and training are presented. Three-phase balanced, three-phase unbalanced, and single-phase examples all achieve an acceptable root mean square error of no more than 0.05 per-unit.

Mcdermott, Thomas E. [Private consulting company]↗

DOE OSTI2022

Valuation of Hydrogen Technology on the Electric Grid Using Production Cost Modeling: Cooperative Research and Development Final Report, CRADA Number CRD-18-00736

This research project will estimate the value to the United States electric grid of deploying hydrogen technology (such as electrolyzers and hydrogen-fueled generation) under projected conditions of high renewable penetration. The analysis will advance the state of the art in systems-level cost-benefit analysis of hydrogen technology for the electric grid by incorporating production cost modeling results in the analysis. Large-scale grid simulation tools will be used to evaluate total system production cost and grid operation when hydrogen technology is deployed for applications such as energy storage and demand response. Scenarios will include one or more future grid mixes in the Western Interconnect (WI) with a high proportion of intermittent renewables. Electric Power Research Institute (EPRI) will work with four utility companies to refine scenarios. Results of the analysis will include comparing the net cost of hydrogen to other technologies for long duration storage, and of power-to-gas (P2G) scenarios including merchant hydrogen sale and hydrogen-fueled generation.

08 HYDROGEN↗

DOE OSTI2012

Large-Scale Turbulent Simulations of Grid-to-rod Fretting

No abstract prepared.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

CLM5 Simulations of Soil Moisture and Gross Primary Productivity for CONUS at 0.125 degrees

This dataset provides 0.125-degree gridded simulations of soil moisture and gross primary productivity (GPP) for the Contiguous United States (CONUS), generated using the Community Land Model version 5 (CLM5) with the biogeochemistry module enabled. The data covers a historical baseline (1980-2015) and mid-century future projections (2020-2055). Future projections are organized into two sets of scenarios to distinguish the impacts of different drivers: (1) Atmospheric Only (ATM): These scenarios apply future atmospheric forcings while holding land use and land cover (LULC) at historical baseline levels. The atmospheric forcings represent moderately versus severely hotter/drier atmospheric conditions (dynamically downscaled perturbed thermodynamics simulations based on CMIP6 SSP245 and SSP585 warming signals), each with cooler versus hotter Earth System Model temperature sensitivity instantiations. These scenarios are identified in the folder names as rcp45_cooler_near, rcp45_hotter_near, rcp85_cooler_near, and rcp85_hotter_near. (2) Coupled Atmospheric and Land-Use (LAND+ATM): These scenarios apply future atmospheric forcing together with future LULC by pairing atmospheric pathways with lower versus higher population/economic growth scenarios representing Shared Socioeconomic Pathways 3 and 5 (SSP3 and SSP5). These scenarios are identified in the file names as ssp3_rcp45_cooler_near, ssp3_rcp45_hotter_near, ssp5_rcp85_cooler_near, and ssp5_rcp85_hotter_near. Please refer to the "README_first.md" file for detailed information on file structure, variables, units, and data formats.

drought↗

DOE OSTI2023

Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning

Here this article proposes a model-based deep reinforcement learning (DRL) method to design emergency control strategies for short-term voltage stability problems in power systems. Recent advances show promising results for model-free DRL-based methods in power systems control problems. But in power systems applications, these model-free methods have certain issues related to training time (clock time) and sample efficiency; both are critical for making state-of-the-art DRL algorithms practically applicable. DRL-agent learns an optimal policy via a trial-and-error method while interacting with the real-world environment. It is also desirable to minimize the direct interaction of the DRL agent with the real-world power grid due to its safety-critical nature. Additionally, the state-of-the-art DRL-based policies are mostly trained using a physics-based grid simulator where dynamic simulation is computationally intensive, lowering the training efficiency. We propose a novel model-based DRL framework where a deep neural network (DNN)-based dynamic surrogate model (SM), instead of a real-world power grid or physics-based simulation, is utilized within the policy learning framework, making the process faster and more sample efficient. However, having stable training in model-based DRL is challenging because of the complex system dynamics of large-scale power systems. We addressed these issues by incorporating imitation learning to have a warm start in policy learning, reward-shaping, and multi-step loss in surrogate model training. Finally, we achieved 97.5% reduction in samples and 87.7% reduction in training time for an application to the IEEE 300-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2013

Integrated Transmission and Distribution Control

Distributed, generation, demand response, distributed storage, smart appliances, electric vehicles and renewable energy resources are expected to play a key part in the transformation of the American power system. Control, coordination and compensation of these smart grid assets are inherently interlinked. Advanced control strategies to warrant large-scale penetration of distributed smart grid assets do not currently exist. While many of the smart grid technologies proposed involve assets being deployed at the distribution level, most of the significant benefits accrue at the transmission level. The development of advanced smart grid simulation tools, such as GridLAB-D, has led to a dramatic improvement in the models of smart grid assets available for design and evaluation of smart grid technology. However, one of the main challenges to quantifying the benefits of smart grid assets at the transmission level is the lack of tools and framework for integrating transmission and distribution technologies into a single simulation environment. Furthermore, given the size and complexity of the distribution system, it is crucial to be able to represent the behavior of distributed smart grid assets using reduced-order controllable models and to analyze their impacts on the bulk power system in terms of stability and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

New Developments and Capabilities Within WEC-Sim

WEC-Sim is an open-source software for simulating wave energy converters and has been actively developed and applied since its initial release in 2014 to simulate a wide variety of device archetypes. WEC-Sim is developed jointly by the National Renewable Energy Laboratory and Sandia National Laboratories within the MATLAB/SIMULINK environment. A general wave-to-wire model begins with a deployment site resource characterization, which is used to complete the hydrodynamic simulation of wave energy converters (WEC), with the power generation profile imported to a grid simulator to understand the influence on the local electrical network. While modeling the entire wave-to-wire is difficult and encompasses multiple time scales and physics, WEC-Sim is focused on the hydrodynamics simulation to predict, analyze, and optimize WEC dynamics and power performance. WEC-Sim simulations are performed in the time domain based on the radiation and diffraction method using hydrodynamics coefficients derived from boundary element method (BEM)-based frequency-domain potential flow solvers (e.g., WAMIT, NEMOH, Capytaine, or ANSYS-AQWA). With this level of modeling fidelity, WEC-Sim can handle floating body hydrodynamics, mechanical and electrical power generation methods, advanced control implementation, mooring systems, and other unique applications such as desalination. Additional WEC-Sim functionalities include pre-built Simulink blocks and MATLAB scripts that can simulate a wide range of floating systems and the corresponding auxiliary subsystems. The developers of WEC-Sim continue to release new versions of the software, at least annually, with the latest release in September 2022. These releases include bug fixes, updates to software documentation, as well as new features to expand WEC-Sim's capabilities to model a wide range of WEC concepts. This publication will highlight the new features added to WEC-Sim between versions 4.1.0 to 5.0.1, which spans a 2-year period from June 2020 to September 2022. New features described here include topics such as continuous integration checks, revised Morison Element and nonlinear hydro implementations, run directly from Simulink (required for hardware-in-the-loop execution), BEMIO updates to import Capytaine BEM hydrodynamics, addition of cable blocks, and new wave visualization features.

TIDAL AND WAVE POWER↗

DOE OSTI2017

Creation of System Validation Platform

The objective of this CRADA between Sandia National Laboratories (SNL) and SunSpec Alliance (SunSpec) was to create a software test platform called the System Validation Platform (SVP) that performs end-to-end certification testing of photovoltaic (PV) inverters, energy storage systems, and other distributed energy resources (DERs). The SVP automates interactions of test equipment (PV and grid simulators), data acquisition systems, and interoperable DERs to certify the devices for advanced grid-support functions and interoperability. To assist electricity grid, operators maintain voltage and frequency, new interconnection requirements in the U.S. and Europe require DERs to have grid-support functions with adjustable settings. Automating the certification process for DER devices impacts the bottom line of NRTLs because they do not need to rely on test engineers running days (or weeks) of experiments to validate the performance of the equipment. These savings can then be passed down to the DER vendors so the certification process becomes less expensive and lowers the barrier to market for PV inverters, charge controllers, and other grid-interconnected equipment. This technology can also be used as a research platform for SNL, other national labs, and universities that would like to run hardware tests with power electronics equipment.

14 SOLAR ENERGY↗

DOE OSTI2023

New Developments and Capabilities Within WEC-Sim: Preprint

WEC-Sim is an open-source software for simulating wave energy converters, which has been actively developed and applied since its initial release in 2014 to simulate a wide variety of device archetypes. WEC-Sim is developed jointly by the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories (Sandia) within the MATLAB/SIMULINK environment. A general wave-to-wire model begins with a deployment site resource characterization, which is used to complete the hydrodynamic simulation of wave energy converters (WEC), with the power generation profile imported to a grid simulator to understand the influence on the local electrical network. While modeling the entire wave-to-wire is difficult and encompasses multiple time scales and physics, WEC-Sim is focused on the hydrodynamics simulation to predict, analyze, and optimize WEC dynamics and power performance. WEC-Sim simulations are performed in the time domain based on the radiation and diffraction method using hydrodynamics coefficients derived from boundary element method (BEM)-based frequency-domain potential flow solvers (e.g., WAMIT, NEMOH, Capytaine, or ANSYS-AQWA). With this level of modeling fidelity, WEC-Sim can handle floating body hydrodynamics, mechanical and electrical power generation methods, advanced control implementation, mooring systems, and other unique applications such as desalination. Additional WEC-Sim functionalities include pre-built Simulink blocks and MATLAB scripts that can simulate a wide range of floating systems and the corresponding auxiliary subsystems. The developers of WEC-Sim continue to release new versions of the software, at least annually, with our latest release in September 2022. These releases include bug fixes, updates to software documentation, as well as new features to expand WEC-Sim's capabilities to model a wide range of WEC concepts. This publication will highlight the new features added to WEC-Sim between versions 4.1.0 to 5.0.1 which spans over a two year period from June 2020 to September 2022. New features to be described will include topics such as continuous integration checks, revised Morison Element and nonlinear hydro implementations, run directly from Simulink (required for hardware-in-the-loop execution), BEMIO updates to import Capytaine BEM hydrodynamics, addition of cable blocks, and new wave visualization features.

TIDAL AND WAVE POWER↗

DOE OSTI2016

Finite time step and spatial grid effects in δf simulation of warm plasmas

This paper introduces a technique for analyzing time integration methods used with the particle weight equations in δf method particle-in-cell (PIC) schemes. The analysis applies to the simulation of warm, uniform, periodic or infinite plasmas in the linear regime and considers the collective behavior similar to the analysis performed by Langdon for full-f PIC schemes [1,2]. We perform both a time integration analysis and spatial grid analysis for a kinetic ion, adiabatic electron model of ion acoustic waves. An implicit time integration scheme is studied in detail for δf simulations using our weight equation analysis and for full-f simulations using the method of Langdon. It is found that the δf method exhibits a CFL-like stability condition for low temperature ions, which is independent of the parameter characterizing the implicitness of the scheme. The accuracy of the real frequency and damping rate due to the discrete time and spatial schemes is also derived using a perturbative method. The theoretical analysis of numerical error presented here may be useful for the verification of simulations and for providing intuition for the design of new implicit time integration schemes for the δf method, as well as understanding differences between δf and full-f approaches to plasma simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Hardware-in-the-Loop Co-simulation of Distribution Grid for Demand Response

In modern power systems, co-simulation is proposed as an enabler for analyzing the interactions between disparate systems. This paper introduces the co-simulation platform Virtual Grid Integration Laboratory (VirGIL) including Hardware-in-the-Loop testing, and demonstrates its potential to assess demand response strategies. VirGIL is based on a modular architecture using the Functional Mock-up Interface industrial standard to integrate new simulators. VirGIL combines state-of-the-art simulators in power systems, communications, buildings, and control. In this work, VirGIL is extended with a Hardware-in-the-Loop component to control the ventilation system of a real 12-story building in Denmark. VirGIL capabilities are illustrated in three scenarios: load following, primary reserves and load following aggregation. Experimental results show that the system can track one minute changing signals and it can provide primary reserves for up-regulation. Furthermore, the potential of aggregating several ventilation systems is evaluated considering the impact at distribution grid level and the communications protocol effect.

Rotger-Griful, Sergi↗

DOE OSTI2022

Recent Developments in the WEC-Sim Open-Source Design Tool: Preprint

WEC-Sim (Wave Energy Converter SIMulator) is an open-source code for simulating wave energy converters, which has been actively developed and applied to simulate a wide variety of device archetypes and has become a popular tool since its initial release in 2014. WEC-Sim is developed jointly by the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories (SNL) within the MATLAB/SIMULINK environment. Figure 1 illustrates a general wave-to-wire model which begins with a deployment site resource characterization, which is used to complete the hydrodynamic simulation of a single WEC (or array), with the power generation profile imported to a grid simulator to understand the influence on the local electrical network. While modelling the entire wave-to-wire is difficult and encompass multiple time scales and physics, WEC-Sim is focused on the hydrodynamics simulation to predict, analyze and optimize WEC dynamics and power performance. WEC-Sim simulations are performed in the time domain based on the radiation and diffraction method using hydrodynamics coefficients derived from boundary element method (BEM) based-frequency-domain potential flow solvers (e.g., WAMIT, NEMOH, Capytaine, or ANSYS-AQWA). Within this level of modeling fidelity, WEC-Sim can handle floating body hydrodynamics, mechanical and electrical power generation methods, advanced control implementation, mooring systems, and other unique applications such as desalination. Table 1 lists additional WEC-Sim functionalities, which are created using prebuilt Simulink blocks and MATLAB scripts that can simulate a wide range of floating systems and the corresponding auxiliary subsystems.

hydrodynamics modeling↗

DOE OSTI2013

ParNCL and ParGAL: Data-parallel Tools for Postprocessing of Large-scale Earth Science Data

Earth science high-performance applications often require extensive analysis of their output in order to complete the scien- tific goals or produce a visual image or animation. Often this analysis cannot be done in situ because it requires calculating time-series statistics from state sampled over the entire length of the run or analyzing the relationship between similar time series from previous simulations or observations. Many of the tools used for this postprocessing are not themselves high- performance applications, but the new Parallel Gridded Analysis Library (ParGAL) provides high-performance data-parallel versions of several common analysis algorithms for data from a structured or unstructured grid simulation. The library builds on several scalable systems, including the Mesh Oriented DataBase (MOAB), a library for representing mesh data that sup- ports structured, unstructured finite element, and polyhedral grids; the Parallel-NetCDF (PNetCDF) library; and Intrepid, an extensible library for computing operators (such as gradient, curl, and divergence) acting on discretized fields. We have used ParGAL to implement a parallel version of the NCAR Command Language (NCL) a scripting language widely used in the climate community for analysis and visualization. The data-parallel algorithms in ParGAL/ParNCL are both higher performing and more flexible than their serial counterparts.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Hardware-in-the-Loop (HIL) Simulations for Smart Grid Impact Studies

Hardware-in-the-loop (HIL) simulations are increasingly employed in power engineering as more inverter-based generation and smart appliances are connected to the electric grid. HIL techniques allow for the co-simulation of analytical models with actual devices whose complex behavior is computationally inefficient or difficult to model. They also allow for testing the behavior of these devices under adverse conditions that rarely occur in the field but are important to evaluate. This paper provides an overview of how HIL simulations have been used to date and proposes that HIL simulations should play an important role in evaluating new control strategies, especially at the distribution level, that are being proposed to allow for continued affordable and reliable operation of the electric grid. We present a new capability that was developed to evaluate the interactions between residential loads and the smart grid: smart home hardware-in-the-loop. The paper includes results from an HIL experiment that incorporates multiple technologies and controls.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

PV Inverter Testing for Momentary Cessation and Rate-of-Change-of-Frequency Events

To understand the power system stability and develop better electromagnetic transient (EMT) models of field deployed photovoltaic (PV) inverters, it is important to characterize inverters' response to abnormal voltage and frequency scenarios. Because EMT models are not typically available for small distribution-connected PV inverters, and because inerterconnection standards historically did not specify desired ride-through behaviors, we tested two such inverters in the lab to characterize their responses to severe undervoltage events and high rate-of-change-of-frequency (ROCOF) conditions. The inverters tested were pre-IEEE 1547-2018 residential PV inverters widely used in the Hawaiian Electric territory and many other areas. The testing results for undervoltage scenarios showed that the inverter from one vendor exhibited momentary cessation while the inverter from the other vendor did not exhibit momentary cessation behavior or tripping for most of the events below the 120 ms undervoltage trip threshold duration set by IEEE 1547-2003. The testing results for ROCOF scenarios showed that the inverter from one vendor temporarily lost synchronization during ROCOF conditions while the inverter from the other vendor did not lose synchronization or cease generation for any ROCOF conditions. Both the inverters were also tested for EMT-simulated grid events with severe changes in frequency and voltage. The observed responses of the inverters were different from the simulated response of PV inverters represented the best available assumptions from pre-existing information. The results from these experiments can be used to update the inverter models used in bulk power system studies.

aggregates↗

DOE OSTI2023

PV Inverter Testing for Momentary Cessation and Rate-of-Change-of-Frequency Events: Preprint

IEEE 1547 2018↗

DOE OSTI2018

Hardware-in-the-Loop (HIL) Simulations for Smart Grid Impact Studies: Preprint

Hardware-in-the-loop (HIL) simulation is increasingly employed in power engineering as more inverter-based generation and smart appliances are connected to the electric grid. HIL techniques allow for co-simulation of analytical models with actual devices whose complex behavior is computationally inefficient or difficult to capture. It also allows for testing of the behavior of these devices under adverse conditions that only occur rarely in the field, but that are important to evaluate. An overview of how HIL simulation has been used to date is provided. This paper further proposes that HIL simulation should play an important role in evaluating new control strategies, especially at the distribution level, that are being proposed to allow for continued affordable and reliable operation of the electric grid with the introduction of these new technologies. It presents a new capability that was developed to enable evaluation of interactions between residential loads and the smart grid: smart home hardware-in-the-loop. The paper includes results from an HIL simulation that incorporates multiple technologies and controls.

24 POWER TRANSMISSION AND DISTRIBUTION↗