Leveraging Standards to Create an Open Platform for the Development of Advanced Distribution Applications
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With high-penetration levels of renewable generating sources being integrated into the existing electric power grid, conventional generators are being replaced and grid inertial response is deteriorating. This technical challenge is more severe with photovoltaic (PV) generation than with wind generation because PV generation systems cannot provide inertial response unless special countermeasures are adopted. To enhance the inertial response, this paper proposes to synthesize a virtual inertia emulator (VIE) by using a battery energy storage system (BESS) and a three-phase grid-tied inverter to simulate a traditional generator such that the inertial response can be appropriately enhanced without sacrificing energy efficiency. Control systems for the VIE are presented in this paper, along with simulation results from PSCAD and MATLAB to validate the effectiveness of the proposed scheme.
This paper develops a hierarchical control frame-work to aggregate and to manage behind-the-meter distributed energy resources (DERs), which will be ubiquitous in future distribution systems. In the proposed framework, firstly, each controller in the hierarchy determines the flexibility of the DERs such that the obtained flexibility is feasible with respect to its operational purview. For example, the operational purview of a home energy management system may only consider consumer comfort preferences, while that for an aggregator or a grid controller may consider network voltage management as well. Based on the feasible flexibility, optimal setpoints for the DERs is then determined by the hierarchical controllers to help the distribution power network in voltage regulation, coordination issues with existing transmission-level conventional generators, etc. Therefore, the proposed strategy, which is based on model-predictive control, can be effectively utilized by the distribution network to coordinate several DERs to provide grid regulation services. Numerical simulations performed on the IEEE 37-bus test system demonstrate the efficacy of the proposed approach.
As the coordination of distributed energy re-sources becomes more necessary to provide grid services through a distributed energy resource management system (DERMS), studying the communication requirements for suc-cessful real-world, low-cost implementation becomes increasingly important. Specifically, this paper studies the necessary communication time resolutions between the different system components for a primal-dual-based DERMS, a highly de-veloped DERMS framework. We design a metric to evaluate the functionality of a DERMS with respect to providing grid services. Using numerical simulations based on a real-world feeder in Colorado, we show that the upper bound on the time resolutions is on the order of minutes instead of the previously assumed order of seconds.
Simulation of modern distribution system powerflow increasingly requires capturing the impact of advanced PV inverter voltage regulation on powerflow. With Volt/var control, the inverter adjusts its reactive power flow as a function of the point of common coupling (PCC) voltage. Similarly, Volt/watt control curtails active power production as a function of PCC voltage. However, with larger systems and higher penetrations of PV, this active/reactive power flow itself can cause significant changes to the PCC voltage potentially introducing oscillations that slow the convergence of system simulations. Improper treatment of these advanced inverter functions could potentially lead to incorrect results. This paper explores a simple approach to speed such convergence by blending in the previous iteration's reactive power estimate to dampen these oscillations. Results with a single large (5MW) PV system and with multiple 500kW advanced inverters show dramatic improvements using this approach.
To help bridge the gap between traditional power system engineering instruction and emerging industry needs, a new set of classroom and research tools are needed. Real-time simulation tools emulating power system control room software present an opportunity to introduce students to the array of operational considerations, technical challenges, and decision-making associated with power system operations. The GridAPPS-D platform is proposed to support coursework and academic research as it provides an open-source platform for simulation, application development, and software integration. The GridAPPS-D platform, simulation capabilities, development environment, and interactive training are discussed in the context of lessons-learned from implementation for undergraduate and graduate students in the US and India. A series of potential GridAPPS-D supported academic capabilities are introduced.
One of the greatest challenges for the analysis of distribution systems is the high level of diversity across the world. For nearly 20 years the Test Feeder Working Group of the Distribution System Analysis Subcommittee has been developing distribution test feeders. The purpose of these test feeders is to provide openly-available models of distribution systems that reflect the diversity in systems and the analytic challenges they present. Because of their utility and accessibility, the test feeders have been used for a wide range of research, some of which they were not originally intended to cover. The purpose of this paper is to provide an overview of the variety of existing distribution systems, and to clarify the specific analytic challenges that each test feeder was originally designed to examine. Additionally, the paper will provide guidance on which feeders are best suited for various types of analysis. The purpose of this paper is to provide the original intent of the Working Group and to inform researchers so that they may make an informed decision on which of the test feeders are most appropriate for their work.
A generic simulation tool for power grid and general dynamic systems based on semi-analytical solutions (SAS) technology.
Test-grid-buildouts is a set of notebooks for creating buildouts of synthetic transmission grids with various levels of renewable energy. Workflows can be used to augment various test grid with varying levels of wind/solar generation. Aggregated renewable energy time series (actuals and scenarios) at grid buses can then be used for various transmission grid operation problems. Highly customizable workflow consists of parsing of synthetic grid files, setting up SAM & reV simulations, application of exclusion masks, creating of custom renewable generators on the grid, aggregating of power time series, and writing of modified grid description files.
The South America Affinity Group (SAAG) was established in early 2019 by the National Center for Atmospheric Research (NCAR) Water Systems Program as a community effort focused on improving hydroclimate science over South America. SAAG supports large research efforts such as the ANDEX Regional Hydroclimate Program as well as individual research groups. The group started with a dozen members and quickly grew to over 100 participants from more than ten countries. For the past four years, the SAAG has been meeting online every two weeks and has organized sessions at international conferences such as the American Geophysical Union Fall Meeting and the Convection-Permitting Climate Workshop. At the core of the SAAG effort are two multi-decadal convection permitting (CP) model simulations with 4-km grid spacing for historical and future climates over the South American continent. Additionally, a major observational data collection effort has been undertaken, including in-situ station data from South American meteorological and water services, gridded products, satellite-based observations, and field campaign data. In conclusion, this article discusses the research needs and scientific goals that drive this community of scientists with diverse backgrounds and interests.
This summarizes technical highlights from the DOE Early Career Project entitled “Understanding the Roles of Cloud Microphysics and Land Surface Coupling Feedbacks in Multi-Scale Predictions of Central US Summer Hydroclimate” led by PI Mike Pritchard at the University of California. The project’s original aims were to investigate trade-offs of cloud superparameterization such as the effects of microphysical assumptions on mesoscale convective systems (Section I) and the representation of land-atmosphere coupling under explicit convection (Section II). Under the same broader theme of water cycle dynamics, superparameterization, and land interaction, the project evolved to further investigate the climate dynamics of irrigation, vegetation and streamflow (Section III), the dynamics of the Madden- Julian Oscillation (Section IV), as well as the use of modern machine learning to replace traditional sub grid approaches for climate simulation (Section V). Twenty peer-reviewed journal publications were produced as a result of this project (Section VI).
The Distribution System Operator with Transactive (DSO+T) study investigates the engineering and economic performance of a transactive energy retail market coordinating a high penetration of customer-side flexible energy assets. The study seeks to answer whether such an implementation is cost effective for customers, recovers sufficient revenue for DSOs, and is equally applicable and beneficial to a range of flexible asset types, renewable generation scenarios, and market assumptions. This report volume provides a detailed set of results for the DSO+T study extending results presented in Volumes 1, 2, and 4. The engineering and economic performance of the transactive energy scheme is presented for two separate flexible asset deployments: flexible loads (HVAC units and residential water heaters) and behind-the-meter batteries. The results of each transactive case are compared to a business-as-usual case. These cases are subject to two different renewable generation scenarios, a moderate renewable generation scenario, representative of current levels of renewable generation deployment, and a future high renewables scenario, including the increased deployment of rooftop solar photovoltaic and electric vehicles. The transactive coordination scheme is shown to produce effective and stable control and decrease peak loads 9–15%. The resulting annual demand flexibility provides net economic savings of $3.3–5.0B per year for a region the size of Texas. Detailed analysis shows that net benefits were seen for a range of distribution system operator, customer, and flexible asset types. Both participating customer (with transactive flexible assets) and nonparticipating customers (with nonflexible assets) see reductions in annual utility bills and net annual energy expenses in the range of 10–16%.
Weather models typically operate on averages of 1 km or more. This averages out fine scale turbulence. This results in smooth laminar flows and rapid vertical motions are usually averaged out. In this study, those fine scaled features were simulated for a 2013 field study of transport and diffusion of a tracer gas. Parameterized subgrid turbulence was required to produce dilution representative of observations. Despite this, the simulation with the finest grid and contained parameterized subgrid turbulence produced dilution that was consistent with observations.
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We present a simple analytic procedure for generating atomic (H i) to molecular (H{sub 2}) density profiles for optically thick hydrogen gas clouds illuminated by far-ultraviolet radiation fields. Our procedure is based on the analytic theory for the structure of one-dimensional H i/H{sub 2} photon-dominated regions, presented by Sternberg et al. Depth-dependent atomic and molecular density fractions may be computed for arbitrary gas density, far-ultraviolet field intensity, and the metallicity-dependent H{sub 2} formation rate coefficient, and dust absorption cross section in the Lyman–Werner photodissociation band. We use our procedure to generate a set of H I-to-H{sub 2} transition profiles for a wide range of conditions, from the weak- to strong-field limits, and from super-solar down to low metallicities. We show that if presented as functions of dust optical depth, the H I and H{sub 2} density profiles depend primarily on the Sternberg “αG parameter” (dimensionless) that determines the dust optical depth associated with the total photodissociated H I column. We derive a universal analytic formula for the H I-to-H{sub 2} transition points as a function of just αG. Our formula will be useful for interpreting emission-line observations of H i/H{sub 2} interfaces, for estimating star formation thresholds, and for sub-grid components in hydrodynamics simulations.
We investigate the evolution of the cosmic web since z = 5 in grid-based cosmological hydrodynamical simulations, focusing on the mass and velocity fields of both baryonic and cold dark matter. The tidal tensor of density is used as the main method for web identification, with λ {sub th} = 0.2–1.2. The evolution trends in baryonic and dark matter are similar, although moderate differences are observed. Sheets appear early, and their large-scale pattern may have been set up by z = 3. In terms of mass, filaments supersede sheets as the primary collapsing structures from z ∼ 2–3. Tenuous filaments assembled with each other to form prominent ones at z < 2. In accordance with the construction of the frame of the sheets, the cosmic divergence velocity, v {sub div}, was already well-developed above 2–3 Mpc by z = 3. Afterwards, the curl velocity, v {sub curl}, grew dramatically along with the rising of filaments, becoming comparable to v {sub div}, for <2–3 Mpc at z = 0. The scaling of v {sub curl} can be described by the hierarchical turbulence model. The alignment between the vorticity and the eigenvectors of the shear tensor in the baryonic matter field resembles that in the dark matter field, and is even moderately stronger between ω and e{sub 1}, and ω and e{sub 3}. Compared with dark matter, there is slightly less baryonic matter found residing in filaments and clusters, and its vorticity developed more significantly below 2–3 Mpc. These differences may be underestimated because of the limited resolution and lack of star formation in our simulation. The impact of the change of dominant structures in overdense regions at z ∼ 2–3 on galaxy formation and evolution is shortly discussed.
We propose a new method for determining the thermal state of the intergalactic medium based on Voigt profile decomposition of the Lyα forest. The distribution of Doppler parameter and column density (b–N H i distribution) is sensitive to the temperature–density relation T = T 0 (ρ/ρ 0 ) γ-1 , and previous work has inferred T 0 and γ by fitting its low-b cutoff. This approach discards the majority of available data and is susceptible to systematics related to cutoff determination. We introduce an approach that exploits all information encoded in the b – N H i distribution by modeling its entire shape. We apply kernel density estimation to discrete absorption lines to generate model probability density functions, and then we use principal component decomposition to create an emulator that can be evaluated anywhere in thermal parameter space. We introduce a Bayesian likelihood based on these models enabling parameter inference via Markov Chain Monte Carlo. The method's robustness is tested by applying it to a large grid of thermal history simulations. By conducting 160 mock measurements, we establish that our approach delivers unbiased estimates and valid uncertainties for a 2D ( T 0 , γ) measurement. Furthermore, we conduct a pilot study applying this methodology to real observational data at z = 2. Using 200 absorbers, equivalent in path length to a single Lya forest spectrum, we measure $\mathrm{log}{T}_{0}={4.092}_{-0.055}^{+0.050}$ and $\gamma ={1.49}_{-0.074}^{+0.073}$ in excellent agreement with cutoff fitting determinations using the same data. Our method is far more sensitive than cutoff fitting, enabling measurements of log T 0 and γ with precision on $\mathrm{log}{T}_{0}$ (γ) nearly two (three) times higher for current data set sizes.
This paper systematically studies the relation between metallicity and mass loss of massive stars. We perform one-dimensional stellar evolution simulations and build a grid of ~2000 models with initial masses ranging between 11 and 60 M ⊙ and absolute metallicities Z between 0.00001 and 0.02. Steady-state winds, comprising hot main-sequence winds and cool supergiant winds, are the main drivers of the mass loss of massive stars in our models. We calculate the total mass loss over the stellar lifetime for each model. Our results reveal the existence of a critical metallicity Z c at Z ~ 10 –3 , where the mass loss exhibits a dramatic jump. If Z > Z c , massive stars tend to evolve into cool supergiants, and a robust cool wind is operational. In contrast, if Z < Z c , massive stars usually remain as blue supergiants, wherein the cool wind is not activated and the mass loss is generally weak. Moreover, we calculate the wind feedback in a 10 5 M ⊙ star cluster with the Salpeter initial mass function. The kinetic energy released by winds does not exhibit any significant transition at Z c because the wind velocity of a cool supergiant wind is low and contributes little to the kinetic energy. The effects of critical metallicity provide implications for the fates of metal-poor stars in the early universe.