Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “distributed storage”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

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↗
DOE OSTI2025

Forecasting EV Charging Demand on the Distribution System

The U.S. transportation and electricity sectors have historically operated independently, but the growth of electric vehicles (EVs) is driving their convergence. After decades of stagnant demand, utilities must prepare for rising load growth, driven in part by transportation electrification. Utilities must anticipate when and where these new loads will materialize to effectively manage EV growth and maintain grid reliability. This presentation outlines NREL's approach to developing high-resolution EV load datasets for distribution planning, with insights from the Multi-State Transportation Electrification Impact Study on EV and load forecasting, infrastructure requirements, and managed charging strategies.

25 ENERGY STORAGE↗
DOE OSTI2025

Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures

Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. These experiments generate petabytes of data, with volumes soon expected to reach exabytes. Consequently, there is a growing need for computation, including structured data processing from raw data to consumer-ready derived data, extensive Monte Carlo simulation campaigns, and a wide range of end-user analysis. To manage these computational and storage demands, centralized workflow and data management systems are implemented. However, decisions regarding data placement and payload allocation are often made disjointly and via heuristic means. A significant obstacle in adopting more effective heuristic or AI-driven solutions is the absence of a quick and reliable introspective dynamic model to evaluate and refine alternative approaches. In this study, we aim to develop such an interactive system using real-world data. By examining job execution records from the PanDA workflow management system, we have pinpointed key performance indicators such as queuing time, error rate, and the extent of remote data access. The dataset includes five months of activity. Additionally, we are creating a generative AI model to simulate time series of payloads, which incorporate visible features like category, event count, and submitting group, as well as hidden features like the total computational load—derived from existing PanDA records and computing site capabilities. These hidden features, which are not visible to job allocators, whether heuristic or AI-driven, influence factors such as queuing times and data movement.

kilic, Ozgur Ozan [Brookhaven National Laboratory ↗
DOE OSTI2023

Neural Network Enhanced RKPM for Electrochemical-Mechanical Coupled Damage Modeling of Energy Storage Materials

Energy storage materials undergo significant charge cycling, which makes understanding their reliability and durability fundamental in predicting performance and service life. Strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking, largely along material interfaces and grain boundaries. For Li-ion batteries, for example, lithium moving between electrodes during charging and discharging process causes expansion and contraction of grains, and the strongly anisotropic and nonlinearly [Li]-dependent grain material properties can cause grains to expand into and contract away from each other, leading to chemo-mechanical cracking. In the first part of this work, a RKPM based computational framework for solving the coupled solid-phase lithium conservation with Fickian diffusion and the lithium concentration dependent anisotropic mechanical problem subjected to a highly nonlinear Butler-Volmer boundary condition is introduced. The choice of RKPM completeness conditions for lithium concentration and mechanical deformation fields, and the variational consistency condition for the domain integration of the coupled problem is first determined. In the second part of this work, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1] is leveraged to accurately capture damage and crack propagation throughout the material, by learning the location, orientation, and sharpness of discontinuity while allowing for a coarser nodal distribution than that is necessary for capturing sharp solution transitions using traditional mesh-based methods. NN-RKPM is used to inform how crack opening and closure in turn affect the coupled chemical equations and material microstructure.

damage modeling↗
DOE OSTI2020

Imaging Cycle-Induced Damage of MnO 2 Microparticles

MnO 2 has been proposed as an electrode material in electrochemical energy storage devices. However, poor cycle life, especially in aqueous electrolytes, remains a detriment to commercialization. Prior studies have suggested a number of explanations for this capacity loss; however, experiments aimed at elucidating the details of the degradation process (es) are sparse. We describe here a microtube-membrane construct that allows for electrodeposition of monodisperse MnO 2 microparticles distributed across the membrane surface, and for subsequent electrochemical cycling of these MnO 2 particles. This allowed for a detailed analysis of the effect of cycling on the MnO 2 , by simply imaging the membrane surface before and after cycling. When an aqueous electrolyte was used, gross changes in particle shape, size and morphology were observed over the course of 500 cycles. Partial dissolution occurred as well. No such changes were observed when the MnO 2 particles were cycled (up to 500 times) in a propylene carbonate electrolyte solution.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Polyhedral Relaxations for Optimal Pump Scheduling of Potable Water Distribution Networks

The classic pump scheduling or optimal water flow (OWF) problem for water distribution networks (WDNs) minimizes the cost of power consumption for a given WDN over a fixed time horizon. In its exact form, the OWF is a computationally challenging mixed-integer nonlinear program (MINLP). It is complicated by nonlinear equality constraints that model network physics, discrete variables that model operational controls, and intertemporal constraints that model changes to storage devices. To address the computational challenges of the OWF, this paper develops tight polyhedral relaxations of the original MINLP, derives novel valid inequalities (or cuts) using duality theory, and implements novel optimization-based bound tightening and cut generation procedures. The efficacy of each new method is rigorously evaluated by measuring empirical improvements in OWF primal and dual bounds over 45 literature instances. The evaluation suggests that our relaxation improvements, model strengthening techniques, and a thoughtfully selected polyhedral relaxation partitioning scheme can substantially improve OWF primal and dual bounds, especially when compared with similar relaxation-based techniques that do not leverage these new methods.

bound tightening↗
DOE OSTI2020

Adaptive shape control of wavefront-preserving X-ray mirrors with active cooling and heating

This article describes the development and testing of a novel, water cooled, active optic mirror system (called “REAL: Resistive Element Adjustable Length”) that combines cooling with applied auxiliary heating, tailored to the spatial distribution of the thermal load generated by the incident beam. This technique is theoretically capable of sub-nanometer surface figure error control even at high power density. Tests conducted in an optical metrology laboratory and at synchrotron X-ray beamlines showed the ability to maintain the mirror profile to the level needed for the next generation storage rings and FEL mirrors.

42 ENGINEERING↗
DOE OSTI2022

Local Atomic Configuration in Pristine and A-Site Doped Silver Niobate Perovskite Antiferroelectrics

Antiferroelectrics have attracted increasing research interests in recent years due to both their great potential in energy storage applications and intriguing structural characteristics. However, the links between the electrical properties and structural characteristics of distorted perovskite antiferroelectrics are yet to be fully deciphered. Here, we adopt local-structure methods to elucidate the nanoscale atomic structure of AgNbO3-based antiferroelectrics and their structural evolution upon La doping. The local structural features including interatomic distance distributions and atomic displacements have been analyzed using neutron small-box pair distribution function (PDF) refinement in conjunction with large-box Reverse Monte Carlo modelling. Our results highlight the correlation of cation displacements in AgNbO 3 and its disruption by the incorporation of La, apparently in corroboration with the observed anomalous dielectric properties. Spatial ordering of cation vacancies is observed in La-doped AgNbO 3 samples, which coordinates with oxygen octahedral tilting to relieve lattice strain. These results provide renewed insights into the atomic structure and antiferroelectric phase instabilities of AgNbO 3 and relevant perovskite materials, further lending versatile opportunities for enhancing their functionalities.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ECAR-6580 Rev 0 ASME Section III, Division 5 Analysis of the MARVEL PCS and GVS Top Corner

The purpose of this Engineering Calculations and Analysis Report (ECAR) is to document the structural evaluation for part of the Microreactor Applications Research Validation and Evaluation (MARVEL) Primary Coolant System (PCS) and Guard Vessel System (GVS). For the PCS this relates specifically to the Distribution Plenum (DP), The Intermediate Heat Exchanger (IHX), and the Upper Downcomer (UD). For the GVS, this will include only the top corner that is machined into the DP Top Plate. These components will be evaluated using the 2021 version of ASME Section III, Division 5 [1] which is a design code that governs the construction of vessels, storage tanks, piping, pumps, valves, supports, core support structures and nonmetallic core components for use in high temperature reactor systems and their supporting systems. Materials at high temperature are subject to creep and fatigue mechanisms that require additional analyses that aren’t covered in ASME Section III, Division 1 rules. Division 5 contains two approaches: elastic or inelastic, however, additional Code Cases specific to Division 5, allow for an Elastic-Perfectly Plastic (EPP) approach. The components analyzed in this ECAR will use a combination of the elastic and EPP approach. Only Design and Service Levels A and B are evaluated in this ECAR. Service Level D evaluations for the entire PCS are documented in ECAR-6564, “MARVEL Project Primary Coolant System Pressure Vessel Stress Documentation” [2] and for the entire GVS are documented in ECAR-6574, “MARVEL Guard Vessel System FEA and ASME Analysis” [3]. The Design and Service Level A and B analyses for the PCS Downcomer piping and Core Barrel are documented in ANL-24/36, "Engineering Calculations and Analysis of the Core Barrel and Downcomer Piping in the MARVEL PCS” [4], and the GVS (except for the top corner) is in ECAR-6574, “MARVEL Guard Vessel System FEA and ASME Analysis.” See Section 2.0 for more detail on the analysis boundaries.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2022

Real-time and post-hoc compression for data from Distributed Acoustic Sensing

Distributed Acoustic Sensing (DAS) is an emerging sensing technology that records the strain-rate along fiber optic cables at high spatial and temporal resolution. This technique is becoming a popular tool in seismology, hydrology, and other subsurface monitoring applications. However, due to the large coverage (10’s of km) and high density of measurements (1m spacing at 100’s of Hz), a DAS installation could produce terabytes of data records per day. Because many DAS instruments are deployed in remote locations, this large data size poses significant challenges to its transfer and storage. In this paper, we explore lossless compression methods to reduce the storage requirement in both real-time and post-hoc scenarios. Here we propose a two-stage compression method to improve the compression ratio and compression speed. This two-stage compression method could reduce the storage requirement by 40%, which is 20% more than other lossless methods, such as ZSTD. We demonstrate that the compression method could complete its operation well before the DAS instrument needs to output the next file, making it suitable for real-time DAS acquisition. We also implement a parallel compression method for a post-hoc scenario and demonstrate that our method could effectively utilize a parallel computer. With 256 CPU cores, our parallel compression method achieves the speed of 26GB/second.

58 GEOSCIENCES↗
DOE OSTI2021

Platform for Accurate Efficiency Quantification of > 35% Efficient Thermophotovoltaic Cells

Thermophotovoltaic (TPV) devices convert thermal radiation directly into electricity using semiconductor diodes and have a variety of uses from waste heat recovery to energy storage to primary power conversion. Recent results have demonstrated promising cells nearing and surpassing 30% conversion efficiency. As TPV cells continue to increase in efficiency, they become attractive for a wider range of applications. Their efficiencies must be quantified in a standardized fashion to compare results accurately across research groups. Here, we outline and quantify the most important characteristics of an accurate and precise TPV efficiency measurement. Using a custom-built measurement apparatus that takes these characteristics into account, we report 19 cells with greater than 30% conversion efficiency and 2 cells with greater than 35% conversion efficiency. This confirms that our reported cell efficiencies are not simply those of hero cells but rather of a distribution of cells that can be produced in a consistent, high-quality process.

III-V↗
DOE OSTI2022

Oak Ridge National Laboratory Pilot Demonstration of an Attestation and Anomaly Detection Framework using Distributed Ledger Technology for Power Grid Infrastructure

This report summarizes the design and pilot demonstration of a framework called Grid Guard that was created to provide increased data and device trustworthiness to electric grid devices by leveraging distributed ledger technology (DLT), specifically blockchain. Grid Guard contains a combination of core cryptographic methods such as the secure hash algorithm (SHA), and asymmetric cryptography, private permissioned blockchain, baselining configuration data, consensus algorithm (Raft) and the Hyperledger Fabric (HLF) framework. The system implements a low energy, fast, and robust enhancement to system trustworthiness within and across electric grid systems such as substations, control centers and metering infrastructures. Blockchain is a distributed database structured that provides a practically unalterable (immutable) timeline of stored transactions. By relying on hashing and the Raft consensus algorithm, if an entity tries to illegitimately alter a record at one instance of the database the other ledger nodes are not altered. They work to cross-reference each other and easily locate any incorrectly added data and remove it. The bulk raw data is stored in an off-chain storage (outside of the blockchain ledger) and a hash of this baseline data is stored in the Blockchain ledger via hashing windows of time-series and configuration data, after aggregation and filtering. The bulk off-chain data repository is then considered to be trust-anchored using the hashes stored in the blockchain. To secure the electric grid testbed devices and data, device configuration baselines were compared to those baselines that had been previously stored in the ledger. Statistical baselines for device configurations, network communication patterns, and high-speed sensor data are calculated and then stored off-chain and hashes stored in the ledger. Measurements such as three-phase voltage and current, frequency, breaker status, protection scheme settings, network configuration settings (and other device configuration artifacts) and network traffic features (packet interarrival times) are compared every minute or other selected time windows. During phase 1 of the Grid Guard DLT project different DLT technologies were studies, and an assessment was performed on DLT technology vulnerabilities, uses, and key characteristics. DLT consensus protocols were studies (e.g., RAFT, named after Reliable, Replicated, Redundant, And Fault-Tolerant). Also, cryptography, public, private and permissioned or permissionless systems were assessed. Grid Guard implements a permissioned private DLT. Consensus algorithm selection and choice of DLT implementation depended heavily on the use-case. For this use-case, parameters were selected to measure performance and existing tools for assessment. Benchmarking was performed theoretically and practically. During phase 2 hashed transactions/blocks were inserted into the ledger every second. During phase 2 of the Grid Guard DLT project, a prototype framework was developed and demonstrated for attestation of critical substation devices and data using precision timing systems that use PTP and IRIG-B protocols) on a testbed of operational devices that emulated a distribution substation, control center, and power metering infrastructure using real Operational Technology (OT). The testbed includes OT devices such as protective relays, human machine interfaces (HMI), and power meters. To determine when to collect and compare system and network baselines, an initial examination of an anomaly detection capability to identify malicious manipulation of data streams was conducted. The resulting anomaly detection was demonstrated in a set of experiments and leveraged to trigger device artifact attestation checks. Attestation checks occur against device configuration baselines when compared with the immutable blockchain-stored baselines, which provided a cryptographically supported means by which to store baselines. The electrical substation-grid testbed was created to test the Grid Guard framework. The testbed emulates the operations of a portion of a power grid and SCADA systems as closely as possible. The testbed integrates real protocols, mainly IEC 61850 standard protocols, such as the Sampled Value (SV) and the GOOSE protocols. The testbed also supports DNP3 and other layer 2 and layer 3 protocols such as Telnet, SSH, SFTP/FTP and other proprietary protocols needed to connect to industrial control system equipment. The testbed emulates real power conditions using the OpalRT hardware-in-the-loop (HIL) device which can create fault situations that cannot be easily tested on real systems. The electrical substation-grid testbed was created using real measurement, communication, and protection devices that electrical utilities commonly use.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Elucidating Drought-Tolerance Mechanisms in Plant Roots through 1H NMR Metabolomics in Parallel with MALDI-MS, and NanoSIMS Imaging Techniques

As direct mediators between plants and soil, roots play an important role in metabolic responses to environmental stresses such as drought, yet these responses are vastly uncharacterized on a plant-specific level, especially for co-occurring species. Here, we aim to examine the effects of drought on root metabolic profiles and carbon allocation pathways of three tropical rainforest species by combining cutting-edge metabolomic and imaging technologies in an in situ position-specific 13C-pyruvate root-labeling experiment. Further, washed (rhizosphere-depleted) and unwashed roots were examined to test the impact of microbial presence on root metabolic pathways. Drought had a species-specific impact on the metabolic profiles and spatial distribution in Piper sp. and Hibiscus rosa sinensis roots, signifying different defense mechanisms; Piper sp. enhanced root structural defense via recalcitrant compounds including lignin, while H. rosa sinensis enhanced biochemical defense via secretion of antioxidants and fatty acids. In contrast, Clitoria fairchildiana, a legume tree, was not influenced as much by drought but rather by rhizosphere presence where carbohydrate storage was enhanced, indicating a close association with symbiotic microbes. This study demonstrates how multiple techniques can be combined to identify how plants cope with drought through different drought-tolerance strategies and the consequences of such changes on below-ground organic matter composition.

Drought, Carbon cycle, MALDI-MSI, Metabolomics, Na↗
DOE OSTI2022

Alpine permafrost could account for a quarter of thawed carbon based on Plio-Pleistocene paleoclimate analogue

Estimates of the permafrost-climate feedback vary in magnitude and sign, partly because permafrost carbon stability in warmer-than-present conditions is not well constrained. Here we use a Plio-Pleistocene lacustrine reconstruction of mean annual air temperature (MAAT) from the Tibetan Plateau, the largest alpine permafrost region on the Earth, to constrain past and future changes in permafrost carbon storage. Clumped isotope-temperatures (Δ 47 -T) indicate warmer MAAT (~1.2 °C) prior to 2.7 Ma, and support a permafrost-free environment on the northern Tibetan Plateau in a warmer-than-present climate. Δ 47 -T indicate ~8.1 °C cooling from 2.7 Ma, coincident with Northern Hemisphere glacial intensification. Combined with climate models and global permafrost distribution, these results indicate, under conditions similar to mid-Pliocene Warm period (3.3–3.0 Ma), ~60% of alpine permafrost containing ~85 petagrams of carbon may be vulnerable to thawing compared to ~20% of circumarctic permafrost. This estimate highlights ~25% of permafrost carbon and the permafrost-climate feedback could originate in alpine areas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CityLearn v2: energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities

As more distributed energy resources become part of the demand-side infrastructure, quantifying their energy flexibility on a community scale is crucial. CityLearn v1 provided an environment for benchmarking control algorithms. However, there is no standardized environment utilizing realistic building-stock datasets for distributed energy resource control benchmarking without co-simulation or third-party frameworks. CityLearn v2 extends CityLearn v1 by providing a stand-alone simulation environment that leverages the End-Use Load Profiles for the U.S. Building Stock dataset to create grid-interactive communities for resilient, multi-agent, and objective control of distributed energy resources with dynamic occupant feedback. While the v1 environment used pre-simulated building thermal loads, the v2 environment uses data-driven thermal dynamics and eliminates the need for co-simulation with building energy performance software. This work details the v2 environment and provides application examples that use reinforcement learning control to manage battery energy storage system, vehicle-to-grid control, and thermal comfort during heat pump power modulation.

Nweye, Kingsley↗
DOE OSTI2022

Advanced Distributed Wind Turbine Controls Series: Part 2-Wind Energy in Isolated Grids – Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL)

In an isolated grid, wind turbines are typically deployed to provide energy to maximize energy production, reduce diesel-fuel consumption, reduce carbon emissions, and reduce costs for energy and fuel transportation. However, in addition to solely providing energy to the power system, wind turbines contain rotating masses and inverter-based controls that can enable various reliability and resilience services through advance controls. As part of the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) this paper demonstrates, through desktop simulations, advanced wind turbine controls that can be employed to support higher contributions of wind in isolated grids, and to demonstrate ways that wind can play a role in supporting stability of an isolated grid. This isolated grid used in these desktop simulations is comprised of a wind turbine (600 kW), solar PV (430 kW), battery energy storage system (1 MW/1MWh), a simulated diesel generator (2 MW) and various types of loads (critical, dynamic). We developed a model of the subsystems in MATLAB/Simulink and validated them with available data from real-world components on NREL's Flatirons Campus. These validated models are then configured for various case studies. We compare the output of the desktop simulation with a baseline case with the diesel generator. Active and reactive power control of the wind turbine can help improve frequency and voltage responses in the isolated grid, respectively. By utilizing a small integrated battery energy storage system in the DC-link of the wind turbine, we also demonstrate that wind turbines can help blackstart a critical load comparable to its rated power and support other renewables (e.g. solar PV) come online and pick up an additional load. This report illustrates some of these reliability and resilience services a wind turbine can provide in an isolated grid.

17 WIND ENERGY↗
DOE OSTI2021

Raman Microscopy Analysis of Wyoming CarbonSAFE Pilot Well Thin Sections for Mineralogy and Organic Matter Characterization

Scanning confocal Raman microspectroscopy (RMS) was used to analyze thin sections for inorganic mineral content and for evaluation of organic material (OM). Thin sections were selected from a stratigraphic test well core in the Powder River Basin, Wyoming under the Wyoming CarbonSAFE project. The well was analyzed with a variety of rock and fluid characterization techniques to determine the feasibility of a commercial-scale CO2 storage site. RMS complements other analyses, including traditional petrography, SEM, porosity and permeability, and XRD For this aspect of the study, RMS is especially important in the evaluation of OM in sealing lithologies. At prospective geologic CO2 storage sites, it is imperative to assess the unconventional oil and gas potential of seals to ensure that any future development would not compromise the integrity of the seals. Whole-slide mineralogical surveys were performed on thin sections from various shale and sandstone formations. Surveys were analyzed with Direct Classical Least Squares to identify and quantify minerals. The location and concentration of minerals was color-coded and overlaid on optical images for visualization of the distribution of minerals. Dense hyperspectral Raman mapping of OM was performed on five thin sections. Eleven spectral parameters diagnostic of organic type and thermal maturity were used to train a Partial Least Squares (PLS) calibration against a set of artificially matured samples spanning the pre- to mid-oil window. The PLS was applied to the study set and a post-mature set. Additionally, the PLS was applied to each point in hyperspectral maps for visualization of trends in maturity across sample sets and discrimination of organic matter types within a given map. In inorganic surveys on thin sections, a total of 14 unique inorganic minerals were identified in Raman spectra including quartz, dolomite, calcite, hematite and anhydrite. Shale thin sections tended to be dominated by organic material. OM was often observed mixed with inorganic minerals. Sand- and mudstones were dominated by inorganic minerals. The PLS extrapolated the post-mature set to reflectances >1.2%. The study set ranged from very immature to postmature in the median of map fit-peak parameters. However, point maturity maps indicate that matrix OM in all study samples is immature and that discreet organic particles selected for mapping, which may be inertinites, bias medians towards more-mature. The work demonstrates the capabilities of RMS to perform both whole-slide mineralogy and OM analysis with applications to formation evaluation in oil & gas, carbon sequestration and mining. Here, analysis of sealing formations in the well indicates high levels of immature organic matter that would not be a viable target for future oil production that could compromise the CO2 storage site. The work brings together diverse disciplines from geology and petrography to analytical chemistry, big data and microscopy.

Myers, Grant↗
DOE OSTI2023

Improving Frequency Stability and Minimizing Load Shedding Events by Adopting Grid-Scale Energy Storage with Grid Forming Inverters

The upward adoption trend of renewable generation not only means cleaner energy integrated into modern power grids, but also that most new generation sources are based on front-end inverter bridges, used as interfaces to most wind generation and all the solar PV. It is well known that due to their power electronics-based construction rather than rotational shafts, these sources do not provide inertia inherently, nor substantial amounts of short-circuit currents. However, stable energy such as what can be stored in energy storage systems, although interfaced via inverters, can be controlled to respond to system disturbances in a manner that emulates inertial behavior. This paper focuses on the application of such energy storage systems to augment inertia in the island of Puerto Rico. To do so, a user defined inverter model that contains grid forming capabilities and fast frequency response is modeled and integrated into the real transmission system in power flow and dynamics software. Energy storage is then connected to two selected areas so that it not only provides frequency regulation to avoid widespread load shedding events, but also other tangible benefits. The simulated cases suggest that even relatively small energy storage systems can avert load shedding events if adequately placed in the transmission network.

Grid-forming inverters, IBR, Inertia↗