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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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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Transmission Data-Driven User-Defined Model for Inverter-based and Conventional Power Plants

Recent events in Odessa [1], [2] have shed light on the complexities of integrating large Inverter-Based Resource (IBR) plants with the transmission system, prompting NERC to stress continuous performance monitoring by transmission operators. Challenges such as plant control updates, IBR model revisions, Phase-locked loop loss of synchronism, and protection events have been identified, underscoring the need for enhanced monitoring protocols by regulatory bodies. The recent FERC 901 order underscores the importance of accurate data exchange regarding IBRs for reliability studies. However, limited access to IBR plant-related data hampers effective decision-making for transmission operators (TOP). This paper proposes a method for constructing data-driven User-Defined dynamic Models (UDM) for power plants for validating multiple-event data using field measurements from interconnection bus locations. The problem is formulated as a power plant model identification problem and a multi-task learning approach under partial input observability assumptions is proposed in this work. This approach aims to predict aggregated responses of conventional and IBR power plants during various dynamic physical events which is useful for planning studies under diverse disturbance conditions. Ultimately, this methodology emphasizes the importance of plant visibility to operators in addressing power system challenges, facilitating improved planning and operational studies.

Mahapatra, Kaveri [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2020

Will Solar Panels Help When the Power Goes Out? Planning for PV Resilience

PV systems, like all energy systems, must chart a difficult course in order to improve resilience. They need to simultaneously withstand extreme conditions that cause grid power disruptions, be configured in a way that allows electricity to be delivered to meet the PV user's needs, and overcome disruptions arising from solar resource intermittency. Certain considerations reveal themselves as key to a PV system's resilience benefits. Choice of hardware is critical, as is site selection for the PV array. Voluminous evidence in a hurricane context demonstrates that durable hardware, properly maintained and sited, leads to PV systems surviving extreme weather with their functionality intact. Structurally weak or poorly maintained PV equipment, on the other hand, has demonstrated failures during extreme weather events. PV system stakeholders should ensure that best practices are followed for hardware procurement and siting. It is also important to understand that PV systems are not one-size-fits-all. While incorporating islanding capabilities and energy storage into the system's electrical topology will typically enhance resilience, the user's needs will determine the optimally resilient conformation of any given system. These factors - appropriate hardware, siting, maintenance, and system design - are the primary drivers of PV resilience. PV systems possess high potential for resilient energy generation due to their distributed, abundant, and free fuel supply, but the technology itself does not inherently lead to resilient outcomes. Realizing PV's potential for resilience requires consideration of these determinative factors.

14 SOLAR ENERGY↗
DOE OSTI2026

Igiugig Comprehensive Energy Plan Implementation Assistance

In 2023, the National Laboratory of the Rockies (NLR) partnered with the Renewable Energy Alaska Project (REAP) to provide technical assistance to Igiugig through the US Department of Energy's Energy Transitions Initiative Partnership Project (ETIPP). The overall objective of this ETIPP project was to provide technical support to help the community achieve their energy goal of reducing diesel fuel for electricity by 50% by 2030 through the implementation of high priority strategies defined in their 2022 Community Energy Plan. Technical support focused on evaluating additional renewables and renewable heating scenarios, identifying heat recovery system design options for high penetration renewables, investigation power quality and line loss issues, and supporting integration of battery energy storage.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Oscillatory Spreading and Inertia in Power Grids

The increase in variable renewable generators (VRGs) in power systems has altered the dynamics from a historical experience. VRGs introduce new sources of power oscillations, and the stabilizing response provided by synchronous generators (SGs, e.g., natural gas, coal, etc.), which help avoid some power fluctuations, will lessen as VRGs replace SGs. These changes have led to the need for new methods and metrics to quickly assess the likely oscillatory behavior for a particular network without performing computationally expensive simulations. This work studies the impact of a critical dynamical parameter - the inertia value - on the rest of a power system's oscillatory response to representative VRG perturbations. We use a known localization metric in a novel way to quantify the number of nodes responding to a perturbation and the magnitude of those responses. This metric allows us to relate the spread and severity of a system's power oscillations with inertia. We find that as inertia increases, the system response to node perturbations transitions from localized (only a few close nodes respond) to delocalized (many nodes across the network respond). We introduce a heuristic computed from the network Laplacian to relate this oscillatory transition to the network structure. We show that our heuristic accurately describes the spread of oscillations for a realistic power-system test case. Using a heuristic to determine the likely oscillatory behavior of a system given a set of parameters has wide applicability in power systems, and it could decrease the computational workload of planning and operation.

dynamical systems↗
DOE OSTI2024

Assessing compounding climate-related stresses and development pathways on the power sector in the central U.S.

Future configurations of the power system in the central region of the USA are dependent on relative costs of alternative power generation technologies, energy and environmental policies, and multiple climate-induced stresses. Higher demand in the summer months combined with compounding supply shocks in several power generation technologies can potentially cause a “perfect storm” leading to failure of the power system. Potential future climate stress must be incorporated in investment decisions and energy system planning and operation. We assess how projected future climate impacts on the power system would affect alternative pathways for the electricity sector considering a broad range of generation technologies and changes in demand. We calculate a “potential supply gap” metric for each pathway, system component, and sub-region of the US Heartland due to climate-induced effects on electricity demand and power generation. Potential supply gaps range from 5% in the North Central region under mild changes in climate to 21% in the Lakes-Mid Atlantic region under more severe climate change. We find increases in electricity demand to be more important in determining the size of the potential supply gap than stresses on power generation, while larger shares of renewables in the power system contribute to lower supply gaps. Our results provide a first step toward considering systemic climate impacts that may require changes in managing the grid or on potential additional capacity/reserves that may be needed.

Gurgel, Angelo Costa↗
DOE OSTI2024

Enhancing Power Grid Resilience with Causal Loops Diagram and Bayesian Networks

Enhancing power grid resilience through improved analysis and planning of Distributed Energy Resources is a key for power system planner. This paper explores the integration of Causal Loop Diagrams (CLDs) and Bayesian Networks (BNs) for enhancing resilience in power systems, focusing on Distributed Energy Resources (DER) planning. By automating CLD analysis in Python's matplotlib, we present a tool for rapid model validation and structural accuracy, crucial for power system planners. This hybrid approach utilizes BNs for inferential depth and CLDs for dynamic system modeling, offering a comprehensive framework for policy formulation and collaborative strategy development against disruptions. Here, we highlight the tool's capability to identify and analyze interconnected feedback loops, facilitating a deeper understanding of DER integration's impact on network resilience. This work aims to bridge quantitative analysis and qualitative insights, addressing the limitations of each method while providing a robust model for power system resilience assessment.

14 SOLAR ENERGY↗
DOE OSTI2022

Least-Cost Storage Mix for Low-Carbon Operations

As communities plan for high- or ultrahigh-renewable power systems, they face diverse options for energy storage. Each energy storage technology has a unique power capacity and discharge duration, and each community has a unique load, generation mix, and weather pattern. Determining the optimal storage portfolio across these parameters could save planners significant costs when building out high-renewable power systems.

analysis↗
DOE OSTI2024

Representative Period Selection for Robust Capacity Expansion Planning in Low-carbon Grids

With the increasing urgency to decarbonize power systems, while mitigating extreme events, capacity expansion models can play a vital role in reliably planning the expansion of power systems and facilitating the integration of renewable energy sources. Optimizing capacity expansion generally involves selecting surrogate representative days from forecasts of load and the generation profiles of variable renewable energy resources. To properly select those representative days, we propose a novel input-based approach in combination with the k-means clustering algorithm that utilize three unique operational inputs: load shedding, renewable curtailment, and transmission congestion. The proposed method allows for more robust and cost-effective capacity planning. The method is validated using a capacity expansion model and a production cost model based on California Independent System Operator (CAISO)'s decarbonization goals, and results in reduced costs and drastically lower load shedding.

Anderson, Osten P.↗
DOE OSTI2022

Optimal Gas-Electric Energy System Decarbonization Planning

As energy utilities implement climate change mitigation policies, system planners require strategies for achieving affordable emissions reductions. Coordinated planning of electric power and natural gas systems will allow synergistic investments to address cross-sector operational constraints, competing uses for net-zero emissions fuels, and shifts in energy demands across energy carriers. In this study, we develop a novel optimization program that finds the cost-minimizing mix of infrastructure expansion or reduction across gas and electric systems to satisfy sector-specific emissions constraints. Alongside energy supply resources, our framework allows for central-planning of end-use equipment stocks to allow switching between gas and electric appliances upon failure or premature replacement. The proposed model is used to simulate case study scenarios for a benchmark 24-pipe gas network coupled to a 24-node power system test network. We find that electrification of greater than 80% of core gas demands is a component of the least-cost solution for modeled energy systems. Despite this substitution, the gas system is maintained to service difficult-to-electrify customers and to deliver net-zero emissions gas to electricity generators in times of peak electricity demand. Restricting electrification of gas appliances increases reliance on power- to-gas technologies and increases annual costs by 15% in 2040. Neglecting constraints on pipeline blending of hydrogen can produce a misleading result that relies on hydrogen blend fractions of greater than 50%. In all cases, we find the average costs of delivered gas increase nearly 5-fold across the decarbonization transition, highlighting the importance of future work investigating cost-allocation strategies for ensuring an equitable energy transition.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Managing Solar Photovoltaic Integration in the Western United States: Resource Adequacy Considerations

This study examines the impact of reserve margin-based reliability assessment, as commonly used in capacity expansion models, on planning resource-adequate power systems under high penetrations of solar photovoltaics (PV). As a generation resource, PV is operationally different from the conventional dispatchable resources for which most capacity expansion models were designed. The question this study attempts to answer is whether large amounts of PV on a system (in this case, the Western Interconnection of North America) would bias the results of conventional reserve margin-based capacity expansion modeling towards an over- or under-provisioning of resource adequacy. This analysis used NREL’s Resource Planning Model (RPM) for capacity expansion modeling and NREL’s Probabilistic Resource Adequacy Suite (PRAS) for resource adequacy assessment. RPM uses a reserve margin requirement to enforce resource adequacy. PRAS, a collection of tools for studying the resource adequacy of power systems and the adequacy contributions of individual resources on a probabilistic basis, was used to compute multiple resource adequacy metrics across a number of simulated scenarios and system representations with differing regional detail. In all cases, including high PV penetrations (up to 33% annual generation from PV, interconnection-wide), RPM was able to produce resource-adequate systems as measured by normalized expected unserved energy and loss-of-load expectation results from PRAS. The accuracy of reserve margin approaches depends heavily on the underlying assumptions informing the capacity credit assigned to variable and energy-limited resources, particularly when such resources are abundant in the modeled system. RPM’s standard methodology for estimating variable and flexible resources’ capacity contributions, which is based on the top 100 hours of net load, did not appear to systematically undervalue or overvalue variable generation relative to a more rigorous equivalent firm capacity assessment using PRAS, although both over- and under-valuations were observed in specific scenarios. In the worst cases, the top 100 hour method underestimated the equivalent firm capacity of PV by two percentage points, and overestimated the equivalent firm capacity of PV by five percentage points. Calculating capacity contributions based on the top 10 hours of net load systematically underestimated equivalent firm capacities at more modest PV penetrations, but was often a better approximation of equivalent firm capacity than the existing 100-hour approach in scenarios with higher PV penetrations.

14 SOLAR ENERGY↗
DOE OSTI2022

Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100): Six-Month Progress Update [Slides]

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phase-out of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040, as established in Puerto Rico Energy Public Policy Act (Act 17). Since hurricanes Irma and Maria in September 2017, DOE and its national laboratories have provided Puerto Rico energy system stakeholders with tools, training, and modeling support to enable planning and operation of the electric power grid with more resilience against further disruptions. On February 2, 2022, DOE, FEMA, and six national laboratories launched the two-year Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) to conduct comprehensive analysis of stakeholder-driven pathways to Puerto Rico's energy future. The robust and objective energy analysis entails five activities, with an emphasis on power system reliability, resilience, and generation planning. This presentation provides a six-month progress update on the study, including presentation of four initial scenario frameworks defined with extensive stakeholder input.

14 SOLAR ENERGY↗
DOE OSTI2022

Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) (Six-Month Progress Update) [Slides]

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phase-out of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040, as established in Puerto Rico Energy Public Policy Act (Act 17). Since hurricanes Irma and Maria in September 2017, DOE and its national laboratories have provided Puerto Rico energy system stakeholders with tools, training, and modeling support to enable planning and operation of the electric power grid with more resilience against further disruptions. On February 2, 2022, DOE, FEMA, and six national laboratories launched the two-year Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) to conduct comprehensive analysis of stakeholder-driven pathways to Puerto Rico's energy future. The robust and objective energy analysis entails five activities, with an emphasis on power system reliability, resilience, and generation planning. This presentation was delivered in a public webinar on July 21, 2022, providing a high level summary of the progress in the first six months of the study, including presentation of four initial scenario definitions based on extensive stakeholder input.

14 SOLAR ENERGY↗
DOE OSTI2023

Open-Source Steady-State Models for Integration of Wave Energy Converter into Microgrids

This paper proposes a software framework, WEC-Grid, for integrating wave energy converters (WECs) into power flow software, such as Siemens PSS®E, to aid the integration of alternative energy sources into Microgrids. While integrating alternative sources such as WECs presents specific challenges such as cost, power quality, and power variability, wave energy is a promising renewable energy resource. Evaluating the integration of WECs into the power grid is a complex and nuanced problem that requires seamless communication between a WEC model and power flow software. The presented WEC-Grid software framework bridges and extends the functionality of WEC-Sim, an open-source WEC modeling package for MATLAB, through a wave-to-wire (W2W) electro-mechanical power conversion and processing model. WEC-Grid acts as a software wrapper, handler, and communication layer between the W2W modeler and power flow software. The software is designed to represent each grid system as a class object, allowing power system operators to perform power system duties such as contingency planning and dispatch operations. The integration of WECs with PSS®E’s power flow calculations workflow is demonstrated with an IEEE RTS case study.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Power System Modeling for the Study of High Penetration of Distributed Photovoltaic Energy

Many conventional power systems are evolving due to the growth of renewable energy and distributed energy resources (DERs). Modeling the interplay of transmission and distribution systems is critical to analyze how DERs impact a system’s conventional operation and which electric infrastructure improvements are needed to achieve a balance between centralized generation and DERs. This article describes the process, tools, and resources used to model electric power systems with a centralized infrastructure in an isolated context and limited access to actual utility data. Photovoltaic systems installed on residential rooftops were the main design option. This work broadened the typical power system modeling to include planning and social considerations. This integrative engineering-social method allows for interdisciplinary teams to work in the development of a model as part of broader design goals for a renewable-dominant energy system. The Puerto Rico electric power system was used as a case study to demonstrate the process. The integrative engineering-social perspective in developing the model and the actions to manage data limitations are aspects that could be followed in other locations with aggressive renewable energy goals and where utility data are not readily available.

Cuello-Polo, Gustavo↗
DOE OSTI2022

Potential Roles For Demand Response in More-Electrified Futures

Power systems, both supply- and demand-side, are rapidly evolving due to technological change and various policy goals. This talk will describe potential roles for demand response in future power systems serving more electrified loads (including transport) and with higher shares of variable renewable generation. Starting from a broad definition of demand response as any change imposed on demand-side end-use operations meant to support power grid functionalities, we draw on a number of past and ongoing research topics to provide insight into the value of different kinds of demand response in different kinds of power systems.

demand response↗
DOE OSTI2022

1.4.2.402 - Water Risk for the Bulk Power System: Asset to Grid Impacts

Utilities and stakeholders need a standardized mechanism for evaluating how future climate and hydrologic conditions translate to water-related risks for power grid assets and systems to support planning decisions. Yet, no such mechanism exists. To address this need, our goals are to: (1) Develop and execute a state-of-the-art multi-model framework to assess future climate-water impacts and risks to the grid, including sensitivities to varying hydrologic drivers and infrastructure scenarios. (2) Create a standardized interactive visualization platform, using data from the climate-water risk assessments, that enables stakeholders to evaluate climate-water impacts, risks, and adaptation measures for power systems.

bulk power system↗
DOE OSTI2024

Bias Correcting NOAA's High-Resolution Rapid Refresh (HRRR) Wind Resource Data for Grid Integration Applications [Slides]

Many weather years of high-quality wind data are widely accepted in the grid integration community to be important for studying wind energy technical potential, energy system operations, and grid resilience. NREL makes high-quality wind and solar resource data available. NREL's Grid-Atmosphere workshop (March 2024) identified NREL National Solar Radiation Database as widely used in grid integration modeling, but there is less agreement on commonly used wind datasets. One important factor identified by ESIG's 2023 report 'Weather Dataset Needs for Planning and Analyzing Modern Power Systems' for gold standard wind data is regular updates. To address the need for regular updates, NREL's team can now process all currently available and regularly updated High-Resolution Rapid Refresh (HRRR) outputs. HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). One barrier to NREL using HRRR is systematic bias and consistency with NREL's existing wind datasets (e.g. WIND Toolkit, 'WTK') across weather years. To address this barrier, we show that the HRRR can be interpolated and bias-corrected to be consistent with NRE's existing datasets. We call the new dataset BC-HRRR (bias-corrected HRRR). As with historical datasets like the WTK, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling). BC-HRRR's (2015-present) consistency with WTK (2007-2013) allows NREL to extend internal grid integration tooling with 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. The rest of this slide deck documents the BC-HRRR processing methods, validation, and its implications for intended use.

17 WIND ENERGY↗
DOE OSTI2022

Opportunities for Renewable Energy, Storage, Vehicle Electrification, and Demand Response in Rajasthan's Power Sector

To support the government of Rajasthan and inform state policy makers, regulators, planners, and system operators on power system trends, NREL undertook a long-term capacity expansion planning study. We used NREL's flagship capacity expansion planning tool for the power sector called the Regional Energy Deployment System India (ReEDS-India) to understand the generation and transmission needs of Rajasthan through 2050. NREL's modeling framework includes co-optimized decisions about generation, energy storage, transmission, and reserves investments needed to meet future demand while maintaining reliable electricity supply. Scenario analysis was conducted to assess a range of potential future scenarios, providing insight for planning agencies, utilities, and local stakeholders about key trends and sources of uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗