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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.

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DOE OSTI2023

Power sector impacts of the Inflation Reduction Act of 2022

Abstract The Inflation Reduction Act (IRA) is regarded as the most prominent piece of federal climate legislation in the U.S. thus far. This paper investigates potential impacts of IRA on the power sector, which is the focus of many core IRA provisions. We summarize a multi-model comparison of IRA to identify robust findings and variation in power sector investments, emissions, and costs across 11 models of the U.S. energy system and electricity sector. Our results project that IRA incentives accelerate the deployment of low-emitting capacity, increasing average annual additions by up to 3.2 times current levels through 2035. CO 2 emissions reductions from electricity generation across models range from 47%–83% below 2005 in 2030 (68% average) and 66%–87% in 2035 (78% average). Our higher clean electricity deployment and lower emissions under IRA, compared with earlier U.S. modeling, change the baseline for future policymaking and analysis. IRA helps to bring projected U.S. power sector and economy-wide emissions closer to near-term climate targets; however, no models indicate that these targets will be met with IRA alone, which suggests that additional policies, incentives, and private sector actions are needed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Advanced Performance Metrics and their Application to the Sensitivity Analysis for Model Validation and Calibration

High-quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMUs, measurement-based approach for model validation has gained significant prominence. In this approach, the quality of a model is analyzed by visually comparing measured generator response with the model-based simulated response for large system disturbances. This paper proposes a new set of performance metrics to assess the model validation results to facilitate automation of the model validation process. In the proposed methodology, first, the slow governor response and comparatively faster oscillatory response are separated, and then a separate set of performance metrics is calculated for each of these two components. These proposed metrics quantify the mismatch between the actual and model-based response in a comprehensive manner without missing any information enabling automation of the process. Furthermore, in this paper, we are also proposing that the sensitivity analysis for model calibration be performed with respect to the proposed metrics for the systematic identification of key parameters. In this work, results obtained using both simulated and real-world case-studies validate the effectiveness of the proposed performance metrics for model validation and their application to the sensitivity analysis for model calibration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Thermal & Electrochemical Power Plant Design and Cost Estimation

Public textbook for "Thermal & Electrochemical Power Plant Design and Cost Estimation: Version#1" This public textbook is an extension of class notes from Carnegie Mellon University courses: Energy System Modeling (24-722) and Fuel Cell Systems (24-262), taught by Dr. Nicholas Siefert between 2010-2021. Textbook includes some references to class notes from Dr. Shawn Litster, Department of Mechanical Engineering, Carnegie Mellon University. Textbook covers the equilibrium and nonequilibrium thermodynamics of power systems as well as an overview of system and economic modeling of these systems. There is in-depth coverage of (a) entropy generation, (b) exergy and (c) the redox state of molecules in equilibrium with the natural environment. This textbook is integrated with other materials (such as lecture slides, solved homeworks, and solved exams) that will be posted to the PowerShare: Energy Systems Modeling group on EDX. Publication Number: DOE/NETL-2023/3913

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Evaluating the Impacts of Coordination for Cascaded Hydropower Plants on the Mid-Columbia

The Mid-Columbia region in the U.S. Pacific Northwest includes seven large, cascaded hydropower plants with a combined nameplate capacity of nearly 14 GW. These plants have several different operators, and there is currently limited coordination among the operators. We develop a detailed model of the Mid-Columbia system that captures both river flow constraints and power system operations. We then place this detailed model within a production cost model of a 2030 system of the Western Interconnection to evaluate how coordination of the Mid-Columbia hydropower plants might impact operations throughout the interconnection. We find that coordination of the Mid-Columbia plants leads to more generation from the Mid-Columbia plants and increased revenues for the Mid-Columbia operators. This benefit is achieved primarily through better utilization of the storage reservoirs and decreased spill through the cascade. We also evaluate the impacts of look-ahead on production costs and find that longer look-ahead values result in lower system-wide production costs.

13 HYDRO ENERGY↗
DOE OSTI2024

Studying the Impact of IBR Modeling on the Commonly Applied Transmission Line Protective Elements

It is a well-accepted fact that detailed inverter-based resource (IBR) models are needed for electromagnetic transient (EMT) studies, especially for protection studies and protection designs. However, it is not clear which modeling aspects should be included in the EMT model to accurately represent the IBR fault responses. Therefore, this paper addresses this gap by evaluating the impact of key modeling aspects (DC source, inverter model, power control, current/voltage control, and current limiting) on the response of protective relay elements both qualitatively and quantitatively. Both grid-following (GFL) and grid-forming (GFM) IBR models are comprehensively evaluated through a simplified real-world transmission network by varying the IBR modeling aspects, fault locations, and types. The insights and findings from this paper will benefit the power system protection community because this work provides modeling requirements and guidelines for IBR modeling so that correct IBR models will be used for protection scheme settings design.

grid-following inverter↗
DOE OSTI2023

AI & Physics-Based Bad Command/Data Detection in Large Power Electronics Systems: Multi-Port Autonomous Reconfigurable Solar Power Plant (MARS)

Detection of bad data from measurement sensors and bad commands from control centers need to be carried out to avoid instabilities within large power electronics systems. Towards the same, in this paper, model and data driven methods are proposed to identify anomalies in measured data and commands received by large power electronics systems. The large power electronics system considered in this paper is a multi-port autonomous reconfigurable solar power plant (MARS), which consists of photovoltaic (PV) and energy storage systems (ESSs) that connect to high-voltage direct current (HVdc) system and transmission ac power grid. The proposed algorithms in the MARS power plant to detect bad data from measurements and bad commands from control centers are evaluated in simulations and hardware-in-the-loop (HIL) tests. Furthermore, it has been observed that the proposed algorithms are able to detect bad measurements and commands in all the use cases evaluated.

14 SOLAR ENERGY↗
DOE OSTI2023

Testing GFM and GFL Inverters Operating With Synchronous Condensers

Inverter-based resources (IBRs) are quickly evolving into a source of reliability services to the electric grid. Penetration levels of variable generation are rapidly increasing, ranging from 60% -70% in some systems. To go further, a fundamental shift is required to address challenges associated with grid stability. Synchronous condensers (SCs) are considered an important complementary technology in such transitions. This paper provides one-of-a-kind insights into real experimental results from operating a real MW-scale system consisting of a 2.2-MVA grid-forming (GFM) and grid-following (GFL) battery energy storage system, 2.5-MVA SCs, and a 3-MVA load bank operating as a small, islanded grid. Challenges that are expected in larger systems were mimicked in this small but real system to demonstrate seamless transitions from one mode to another as well as stable operation with different combinations of GFM and GFM resources, including a "loss of last synchronous generator" case. The experimental results presented in this paper are a valuable resource to everyone involved in developing and validating models or developing controls of power systems consisting of inverters and synchronous condensers.

grid-following converter↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (control-lable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2023

Multiphysics Modeling of Hydrokinetic Turbine Energy Conversion System

Hydrokinetic turbines (HKTs) hold great promise as a renewable energy source, but high maintenance costs and limited energy output hinder their widespread adoption. The lack of comprehensive research on HKT drivetrain designs creates a knowledge gap in enhancing generation efficiency and cost reduction. A model of the HKT system with a focus on electric drivetrains and power converters is required to address this knowledge gap. This paper first introduces a MATLAB-averaged model integrating electrical-mechanical-thermal domains and aging behaviors within multi-time frames. Then a PLECS model, which incorporates maximum power point tracking and dq reference framed control for AC-DC-AC power converters, is enriched by a dynamic thermal model to predict fast transients accurately. These models optimize the design at the component level, resulting in improved integrated system performance. Furthermore, the validation of the models is carried out through hardware experiments for the averaged model and hardware-in-the-loop testing for the dynamic model.

ADVANCED PROPULSION SYSTEMS,HYDRO ENERGY↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources: Preprint

Integration of a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problem requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs) including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperformed other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2025

Energy Scheduling-based Operating Envelopes including a Distribution System Branch Screening Algorithm

This paper presents an energy scheduling-based formulation for computing operating envelopes including a distribution branch screening algorithm, termed DBS-ES. The contribution of the paper is two-fold: firstly, it presents an innovative methodology for calculating operating envelopes using energy scheduling (baseline), and secondly, it enhances this methodology by incorporating a custom distribution branch screening algorithm (DBS-ES). The custom algorithm leverages power system knowledge to reduce both model build time and total processing time while maintaining the same scheduling results as the baseline. The effectiveness of the proposed approach is demonstrated through experiments on the IEEE13, IEEE123, and EPRI Secondary test feeders. Results highlight a 24.5% decrease in model build time and an 8.17% decrease in total processing time when using DBS-ES compared to the baseline, specifically for the IEEE123 test feeder. Additionally, the paper briefly discusses the influence of utility-controlled storage on computing operating envelopes, noting a general incre

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Electric Vehicle Managed Charging: Forward-Looking Estimates of Bulk Power System Value

When and where electric vehicle charging occurs has significant implications for power systems supporting widespread electric vehicle deployment with high shares of wind and solar generation. Numerous studies have estimated the value of scheduling or otherwise managing electric vehicle charging in such power systems. This study improves on those earlier works by leveraging detailed simulation models for electric vehicle adoption, electric vehicle use, electric vehicle charging, and bulk power system operations; and linking them with methods for describing charging flexibility at both the individual vehicle and aggregate levels. This study closely analyzes electric vehicle managed charging (EVMC) performance along the dimensions of flexibility type (within-charging session or within-week scheduling), dispatch mechanism (direct load control or one of several price-based mechanisms), and participation rate, under the assumptions of ubiquitous chargers and all trips completed on time. The study is located in a passenger light-duty vehicle adoption scenario with 100% electric vehicle sales by 2035, and in an envisioned 2038 New England power system for which within-region generation is 84% clean.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Modelling and analysis of nuclear reactor system coupled with a liquid metal battery

Traditionally, nuclear power plants in the U.S. provide baseload power to the power grid because they have less flexibility for ramping their output power than natural gas peaking plants. However, achieving climate goals to reduce the consumption of fossil‐based natural gas places pressure on nuclear power plants and other power generators to ramp up their power output to balance grid generation with demand. This paper presents the modelling and performance analysis of a nuclear reactor system (NRS) coupled to a liquid‐metal battery (LMB) to improve its dynamic response and enable its black start capability. The NRS and LMB thermal behaviour are modelled in Dymola, while the electrical dynamics of the LMB and power grid are modelled in RTDS‐RSCAD. Both simulation platforms are coupled and share their thermal and electrical data using a Transmission Control Protocol/Internet Protocol (TCP/IP) communication protocol. The dynamic performance of the NRS‐LMB integration is tested on the IEEE 9 bus, which demonstrates its ability to respond and provide frequency and voltage regulation. The black start capability of the NRS‐LMB is also evaluated by simulating a grid outage and using the LMB to supply the auxiliary loads required to bring the NRS back online as soon as possible. The results show that coupling an NRS to an LMB improves the system dynamic performance and enables it to black start after being disconnected from the grid for several days.

25 ENERGY STORAGE↗
DOE OSTI2025

A method for assessing economic, environmental, and reliability tradeoffs of interregional transmission connecting ERCOT (the Texas grid) to the eastern and western grids

Reliable development of the power grid is an evolving concern for humanity due to extreme weather that frequently threatens power sector infrastructure. The state of Texas is a uniquely structured testbed for grid planners to study when looking for solutions to development, innovation, and overcoming such challenges. Because of its size and islanded structure, Texas is small enough to model, but big enough to matter. Texas is a global leader in energy production, energy consumption, and maintains an unusually diverse fuel mix. In addition, the state has experienced winter freezes, heat waves, wind storms, droughts and floods that have threatened power sector infrastructure or caused recent blackouts and calls for demand side conservation. One of the most devastating of these events was the North American winter storm, dubbed “Winter Storm Uri” by the Weather Channel, that froze the region in February 2021 and led to an extended power outage event that put the majority of Texan residents in darkness for days. While preparing to avoid such outage events in the future, various tools have been proposed to improve grid reliability, including energy efficiency, demand response, and distributed energy resources. An additional option would be to develop interregional transmission that connects the Texas grid to other national grids. To assess the merits of this idea, we developed a novel, universally-applicable and internationally-relevant framework to study how the Texas grid would evolve alongside access to various interregional ties. This method allows us to stress the synthetic grid structure and analyze how it would respond to the shock of a simulated winter storm event. Our method leverages open-source modeling tools, such as PowerGenome, pyGRETA, and GenX to synthesize unique zonal grid data, construct a consolidated network of model regions, and simulate different developmental pathways of capacity expansion and operational dispatch. We demonstrate our method with an analysis connecting the Electric Reliability Council of Texas (ERCOT), the grid that serves most of Texas, the Western Electricity Coordinating Council (WECC), the grid that serves the western half of the contiguous U.S., and the Eastern Interconnect, the grid that serves the eastern half of the contiguous U.S. Our results indicate that the cost-optimal capacity of interregional transmission connecting the ERCOT grid to other grids lies between 9–13 GW assuming baseline conditions. Building this amount of connecting capacity in one or multiple directions lowers the costs and emissions of development and operation by up to $16 billion and 257 million metric tonnes (MMT) respectively. Additionally, our results show that the interregional connections between ERCOT and other national grids reduce the amount of total load shed required through mild winter storm events. However, our results also show that there is a threshold of very extreme winter storm conditions, spanning multiple service areas, above which the connections exacerbate resource adequacy problems. Therefore, the results indicate that the connections need to be carefully planned alongside the rest of the grid infrastructure to avoid over-reliance on specific resources or technology options.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Distribution System Dataset Generator for AI Applications [SWR-24-75]

This software is a simple, light-weight python package to generate pytorch compatible machine learning graph dataset representing electric power distribution system. User is able to use these graph datasets to test their graph generation artificial intelligence (AI) models, link prediction AI models, graph classification AI models and so much more. This package uses grid-data-models (https://github.com/NREL-Distribution-Suites/grid-data-models) as input data format for power distribution system. NREL-Ditto (https://github.com/NREL-Distribution-Suites/ditto) tool can be leveraged to transform popular distribution system file formats such as opendss, cyme and synergi to grid-data-models.

Duwadi, Kapil↗
DOE OSTI2023

Projecting Future Colorado River Basin Water and Hydropower Operations

Drought, variable renewable energy (VRE) resources (primarily wind and photovoltaic technologies), and power markets can all impact hydropower plant operations. We analyze how these three factors collectively may potentially change the future operation and economics of federal dams and hydropower plants located in the Colorado River Basin (CRB). Federal CRB energy and capacity resources, including 4,200 MW of hydropower capacity, are marketed by Western Area Power Administration (WAPA) and sold through long-term Firm Electric Service (FES) contracts to entities located in 15 western and central States that serve millions of electricity consumers. The parameters of FES contracts allow a wide range of scheduling flexibility for FES customers. The FES customers will adjust the timing of energy delivery according to the changing water, power market, and VRE contribution level to the power grid. We simulate and project water and hydropower operations with two models: 1) reservoir operation and 2) power system operation (production cost) with various temporal granularity. We consider two sets of grid scenarios (one representing today's infrastructure, and one representing higher VRE contributions in 2036) and two sets of water scenarios (drought and normal hydrology). We modeled scenarios to understand the power market-energy price levels and patterns, FES customer scheduling, hydropower economics, WAPA finances and hydropower operation for various hydrologic conditions, and VRE contribution level to the power grid. The detailed modeling framework includes: (1) creating ensembles of CRB hydrologic and hydropower futures, (2) selecting representative futures, (3) simulation of FES customer contracts, (4) simulating western U.S. power grid economic scheduling and dispatch under two VRE contribution levels, utilizing information from modeling steps (1)-(4), (5) assessment of reservoir water and hydropower operation, and (6) comparing scenario operations and economics. Our study team comprising WAPA, and an interdisciplinary team of national labs will gain insight into how WAPA can prepare for and adapt its practices in response to an evolving U.S. power grid.

Colorado River↗
DOE OSTI2025

Managing Increased Electric Vehicle Shares on Bulk Power Systems

The convergence of transportation electrification, other load growth, and the integration of many power sector technologies presents a complex planning problem requiring realistic, region-specific modeling and analysis to ensure the power system can support new loads quickly and affordably.

33 ADVANCED PROPULSION SYSTEMS↗