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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Reliability of emergency and standby diesel generators: Impact on energy resiliency solutions

Emergency diesel generators are the most common form of backup power for critical loads when the grid fails and are most often deployed as stand-alone generators (<2000 kW) tied to individual buildings for hospitals, emergency services, military bases, ports, airports, industries, and commercial facilities. Understanding the finite reliability of emergency diesel generators during continuous operation is critical for energy planners, managers, and end-users. A new analysis of two large non-public emergency diesel generator operational data sets shows that commonly used reliability metrics are inadequate to predict the performance during a grid outage. Additional metrics addressing the likelihood of an emergency diesel generator to be available at the time an outage starts, successfully start and carry load, and constantly run for the duration of the outage are needed to predict the continuous run-time reliability of emergency diesel generators during a grid outage. This is the first analysis of the reliability of modern generators that follow standard maintenance protocols commonly used for backup power and these new metrics are shown to be dependent on the level of emergency diesel generator maintenance with values that can vary by more than an order of magnitude. Even using the new metrics for well-maintained emergency diesel generators, the analysis shows that the single emergency diesel generators configurations are only 80% likely to provide power for the duration of a two-week grid outage.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
DOE OSTI2019

Distribution System State Estimation in the Presence of High Solar Penetration

In recent years, the low-to-medium voltage distribution networks are experiencing rising levels of distributed energy resources, including renewable generation, along with improved sensing, communication and automation infrastructure. As such, state estimation methods for distribution systems are becoming increasingly relevant as a means to enable better control strategies that can both leverage the benefits and mitigate the risks associated with high penetration of variable and uncertain distributed generation resources. Primary challenges of this problem include modeling complexities (nonlinear non-convex power-flow equations), limited availability of sensor measurements, and high penetration of uncertain renewable generation. This paper formulates the distribution system state estimation as a nonlinear weighted least squares problem, based on sensor measurements as well as forecasts data (both load and generation). We investigate the sensitivity of state estimator accuracy to (load/generation) forecast uncertainties, sensor accuracy, and sensor coverage levels.

Distribution system state estimation, nonlinear op↗
DOE OSTI2023

MultiLoad-GAN: A GAN-Based Synthetic Load Group Generation Method Considering Spatial-Temporal Correlations

This paper presents a deep-learning framework, Multi-load Generative Adversarial Network (MultiLoad-GAN), for generating a group of synthetic load profiles (SLPs) simultaneously. The main contribution of MultiLoad-GAN is the capture of spatial-temporal correlations among a group of loads that are served by the same distribution transformer. This enables the generation of a large amount of correlated SLPs required for microgrid and distribution system studies. Here, the novelty and uniqueness of the MultiLoad-GAN framework are three-fold. First, to the best of our knowledge, this is the first method for generating a group of load profiles bearing realistic spatial- temporal correlations simultaneously. Second, two complementary realisticness metrics for evaluating generated load profiles are developed: computing statistics based on domain knowledge and comparing high-level features via a deep-learning classifier. Third, to tackle data scarcity, a novel iterative data augmentation mechanism is developed to generate training samples for enhancing the training of both the classifier and the MultiLoad-GAN model. Simulation results show that MultiLoad- GAN can generate more realistic load profiles than existing approaches, especially in group level characteristics. With little finetuning, MultiLoad-GAN can be readily extended to generate a group of load or PV profiles for a feeder or a service area.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Coastal Resilience for the Electric Power System: A National Overview and the Oregon Example

The U.S. electric system is undergoing transformative change. Research and investments into every level of the system – generation, transmission, and distribution – offer an opportunity to improve its resilience to external disruptions. Power system resilience is particularly important to the U.S. coasts, where utilities may be spatially limited in solutions and unique vulnerabilities are present. This paper will review the most recent federal perspective on resilience for the power system; knowledge gaps and research avenues; specific resiliency concerns on the Oregon coast and the national-state-local utility partnership under development.

Resilience, resiliency, Coast↗
DOE OSTI2021

The Impacts of Distinct Flexibility Enhancements on the Value and Dynamics of Natural Gas Power Plant Operations

The rapid increase of renewable generation and its anticipated continued growth requires greater operational flexibility in modern power systems. Previous studies explored the addition of more flexible resources to improve system flexibility, but this may also be achieved at lower cost by enhancing existing power plants via flexibility retrofits. Potential flexibility upgrades to existing thermal plants include modifications that enable faster ramp rates, increase maximum load levels, decrease minimum load levels, and provide faster and lower cost startup operations. In this paper, we focus on improvements to existing natural gas combined cycle generators, and apply a unit commitment model to analyze the impact that each specific upgrade has on their operational dynamics and profitability from both the system perspective and from the asset owner perspective. We show that the value of each type of flexibility improvement varies depending on the capacity factor and usage pattern of the generator before the upgrade, and that the relative benefit of each type of flexibility varies. We demonstrate diminishing returns to increased flexibility when upgrading multiple generators simultaneously. Sensitivity tests for several shares of renewable generation, different generation mixes and different net load realizations confirm the generality of the results shown.

03 NATURAL GAS↗
DOE OSTI2026

LuSEE-night power distribution system design

The Lunar Surface Electromagnetic Experiment at Night (LuSEE-Night) is a low-frequency, 0.5 to 50 MHz, radio experiment on the radio-quiet far side of the Moon. The instrument will be launched by NASA Commercial Lunar Payload Services in 2026. The LuSEE-Night instrument core is composed of a radio frequency spectrometer (SPT) processing signals from four antennas, the Data Controller Board (DCB), low electromagnetic interference (EMI) Picket Fence Power Supply (PFPS), and Power Distribution Unit (PDU). The battery powers the instrument during the lunar night and stores energy harvested by the solar panel array during the lunar day. The battery charging is controlled by the Power Conditioning and Distribution Unit (PCDU). The unregulated power is supplied either by the SpaceCraft (S/C) or the battery and gets distributed to the PFPS, communication radio, heaters, and deployables through the PDU. The PFPS generates all regulated low-voltage rails using switching regulation synchronized to the LuSEE-Night clock, which ensures self-generated EMI will be confined to well-defined frequency bins. Here, we discussed the unregulated power distribution system architecture and functionality. The PDU engineering and flight modules are developed and characterized to confirm compliance with LuSEE-Night requirements. At the time of writing, all power subsystem components have been integrated into the payload.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

A Model-Predictive Hierarchical-Control Framework for Aggregating Residential DERs to Provide Grid Regulation Services

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.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Robust Distribution State Estimation for Reliable Locational Marginal Pricing under Cyber-Attacks

Here this paper examines the impact of false data injection (FDI) cyber-attacks on distribution system state estimation (DSSE) and the resulting distribution locational marginal price (DLMP) in power markets. Two robust high-breakdown regression estimators, namely S- and MM- estimators, are implemented to provide resistance against FDI attacks targeting measurements and grid topology, creating leverage points. The introduced estimators are compared to the weighted least squares (WLS) with a bad data detection and rejection module (BDD) and the robust Huber M-estimator. The proposed estimators are shown to be effective and compare favorably to both existing Huber M- and the WLS with BDD in the presence of topology FDI attacks. Both the S- and MM-estimators provide good performance in the case of clean and corrupted measurements. Their performance is comparable in this case to the Huber M- and the WLS, followed by a BDD module. The simulation considered a modified distribution IEEE 13 and 34-bus systems where the impact of FDI attack scenarios is shown on the state and the DLMP pricing in the presence of distributed Generation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Analyzing the Impact of Solar Power on Multi-Hourly Thermal Generator Ramping

Solar power generation, unlike conventional forms of electricity generation, has higher variability and uncertainty in its output because solar plant output is strongly impacted by weather. As the penetration rate of solar capacity increases, grid operators are increasingly concerned about accommodating the increased variability and uncertainty that solar power provides. This paper illustrates the impacts of increasing solar power penetration on the ramping of conventional electricity generators by simulating the operation of the Independent System Operator -- New England power system. A production cost model was used to simulate the power system under five different scenarios, one without solar power and four with increasing solar power penetrations up to 18%, in terms of annual energy. The impact of solar power is analyzed on six different temporal intervals, including hourly and multi-hourly (2- to 6-hour) ramping. The results show how the integration of solar power increases the 1- to 6-hour ramping events of the net load (electric load minus solar power). The study also analyzes the impact of solar power on the distribution of multi-hourly ramping events of fossil-fueled generators and shows increasing 1- to 6-hour ramping events for all different generators. Generators with higher ramp rates such as gas and oil turbine and internal combustion engine generators increased their ramping events by 200% to 280%. For other generator types--including gas combined-cycle generators, coal steam turbine generators, and gas and oil steam turbine generators--more and higher ramping events occurred as well for higher solar power penetration levels.

14 SOLAR ENERGY↗
DOE OSTI2022

Characterization of Temperature Heterogeneity in Utility-Scale Power Plant Boilers by Spatially Distributed Ultrasonic Measurements

In extreme environments, even hardened insertion sensors fail quickly. For such environments, we have developed an ultrasonic (US) method for measuring the spatial distribution of temperatures in solid materials and, specifically, across containments of extreme processes. By deploying US sensors in multiple locations, spatial heterogeneity in temperatures inside harsh environments may be characterized. In this note, we update our progress on testing the developed approach in an industrial setting and its performance in describing the temperature distribution inside a 500 MW (electrical) coalfired utility boiler of an electrical power generation plant. We use waveguides (WG) structured to contain echogenic features that produce a train of echoes in response to an excitation pulse. The time of flight between echoes encodes the information on the temperature distribution in the corresponding segment of the WG, which we reconstruct using its parametrization. Five waveguides were welded to the boiler’s heat exchange surface (waterwall) and different locations at the same boiler elevation and produced reliable US waveforms 18 months after the installation. For several weeks during the latest trial, we performed US measurements in five locations spanning half of the boiler’s 14-meter width. The measurements were acquired during regular operation, including load cycling to adjust for demand and intermittent contributions of renewable power sources, and during boiler shutdown for emergency maintenance and the subsequent restart. The interpretation of US waveforms by signal processing resulted in an accurate estimation of temperature distribution along the waveguides. We captured daily cyclical variations in demand-following load. Measurements performed in multiple locations revealed unexpected temperature variations across the boiler. We conclude that an array of developed sensors can provide responsive and spatial temperature measurements while maintaining functionality despite prolonged exposure to an extreme environment.

Walton, Kenneth↗
NASA NTRS1995

PMAD for the Next Generation Spacecraft

The next generation spacecraft is reducing the power, mass and volume envelope for the power system. The Power Management and Distribution (PMAD) function has traditionally been the largest

Next↗
DOE OSTI2022

Grid-Forming Wind: Getting Ready for Prime Time With and Without Inverters

Variable wind power is one of the fastest-growing energy-generation technologies, harnessing the energy of wind, both on land and at sea. During the past decade, the global share of wind power has grown tremendously, and wind power is evolving into a major contributor to electricity supplies in many countries. In this journey, wind is also becoming a source of reliability services to the grid, which has required grid-supporting functions originally provided by synchronous generators, enabling very high levels of instantaneous penetration (ranging from 60 to 70% in some power systems). To get beyond this, a fundamental shift is required to address challenges associated with the transition to a grid with only a few remaining (or even without any) conventional synchronous generators while achieving a minimum acceptable level of stability.

energy consumption↗
DOE OSTI2015

Assessment of grid-friendly collective optimization framework for distributed energy resources

Distributed energy resources have the potential to provide services to facilities and buildings at lower cost and environmental impact in comparison to traditional electric-gridonly services. The reduced cost could result from a combination of higher system efficiency and exploitation of electricity tariff structures. Traditionally, electricity tariffs are designed to encourage the use of ‘off peak’ power and discourage the use of ‘onpeak’ power, although recent developments in renewable energy resources and distributed generation systems (such as their increasing levels of penetration and their increased controllability) are resulting in pressures to adopt tariffs of increasing complexity. Independently of the tariff structure, more or less sophisticated methods exist that allow distributed energy resources to take advantage of such tariffs, ranging from simple pre-planned schedules to Software-as-a-Service schedule optimization tools. However, as the penetration of distributed energy resources increases, there is an increasing chance of a ‘tragedy of the commons’ mechanism taking place, where taking advantage of tariffs for local benefit can ultimately result in degradation of service and higher energy costs for all. In this work, we use a scheduling optimization tool, in combination with a power distribution system simulator, to investigate techniques that could mitigate the deleterious effect of ‘selfish’ optimization, so that the high-penetration use of distributed energy resources to reduce operating costs remains advantageous while the quality of service and overall energy cost to the community is not affected.

Pensini, Alessandro↗
DOE OSTI2019

VOLTTRON/econ-dispatch

Work space for in development Economic Dispatch Application. Multi-purpose open-source control algorithms that will ensure real-time optimal operation, increase electric grid reliability, and lead to the goal of clean, efficient, reliable and affordable next generation building-integrated combine cooling, heating and power (CHP) system.The CHP system could include conventional heating, ventilation, air conditioning (HVAC) systems, distributed generation (DG), local storage (both thermal and electric) and local solar photovoltaic (PV) systems.

Katipamula, Srinivas↗
DOE OSTI2017

Contribution of Nonsynchronous Generation to Bulk System Frequency Response

There is general concern in the power system industry regarding the degradation of frequency response due to various factors, such as the withdrawal of primary or governor response shortly after an event, the lack of in-service governors on conventional generation, and the unknown and changing nature of load frequency characteristics. Large penetrations of nonsynchronous or inverter-based generation (e.g., wind and solar photovoltaic) further contribute to the concerns. This paper reports on frequency stability research designed to explore the impact of high penetrations of inverter-based generation on the frequency response of a large interconnected grid as well as the potential contribution of those nonsynchronous resources to maintaining frequency stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Electromagnetic Transient Simulation Algorithms for Evaluation of Large-Scale Extreme Fast Charging Systems (Distribution Grid Models)

The distribution and transmission grids are observing an increased penetration of power electronics in loads and generations. For example, there is increasing interest in integrating in extreme fast charging (XFC) systems for fast charging of electrical vehicles. As these systems are integrated, developing high-fidelity electromagnetic transient model of XFC systems in distribution grids and evaluating their interactions with the power grid would be of significant interest. This model will be utilized for design of XFC systems, to identify upgrades in distribution and/or transmission grids, for planning purposes by transmission planners or operators or owners, among others. It can also be utilized in operations for improved reliable performance of the grid and/or XFC station. The challenge with simulating these models is the high computational complexity introduced by the large number of states present in the system and the time-step needed to simulate the system. In this paper, advanced simulations algorithms are applied to reduce the computational complexity of simulating large-scale XFC systems. The algorithms include numerical stiffness-based segregation, time constant-based segregation, clustering and aggregation on differential algebraic equations (DAEs), and multi-order integration approaches. While the first three algorithms split the matrix that needs to be inverted from a large matrix to much smaller matrices, the final algorithm reduces the computational burden of applying higher-order integration approaches in the complete system. The comparison made in the previous sentence is with respect to use of homogeneous integration approaches used in conventional electromagnetic transient simulators like power systems computer aided design (PSCAD). The approaches mentioned here have resulted in speed-up of 36x in the simulation of a single distribution system with 15 XFCs.

Debnath, Suman↗
DOE OSTI2022

Wave resource spatial and temporal variability dependence on WEC size

As the wave energy sector grows and looks to the Blue Economy for commercialization opportunities, there is a distinct and pressing need to clearly understand and quantify the coupled impacts of wave energy converter (WEC) size and wave resource characteristics on the annual energy production, spatial variability and temporal variability. Utilizing generic frequency domain representations of the Oscilla Power Triton WEC and spectral wave conditions at PacWave (Oregon), Los Angeles (California) and WETS (Hawaii), a series of interesting results emerge. Firstly, the ‘optimal’ WEC size, from an energy standpoint, is fundamentally dependent on the frequency distribution of the incoming wave variance density spectrum. Secondly, and from a seasonality perspective, the seasonal WEC energy generation doesn’t necessarily follow the seasonal distribution of gross wave power. Finally, from an hourly power variability perspective, a reduction in WEC size generally decreases variability. However, for each of the locations investigated, there appears to be a WEC size threshold; a threshold where further reducing WEC size results in increased power variability.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Wave Resource Spatial and Temporal Variability Dependence on WEC Size

As the wave energy sector grows and looks to the Blue Economy for commercialization opportunities, there is a distinct and pressing need to clearly understand and quantify the coupled impacts of wave energy converter (WEC) size and wave resource characteristics on the annual energy production, spatial variability and temporal variability. Utilizing generic frequency domain representations of the Oscilla Power Triton WEC and spectral wave conditions at PacWave (Oregon), Los Angeles (California) and WETS (Hawaii), a series of interesting results emerge. Firstly, the 'optimal' WEC size, from an energy standpoint, is fundamentally dependent on the frequency distribution of the incoming wave variance density spectrum. Secondly, and from a seasonality perspective, the seasonal WEC energy generation doesn't necessarily follow the seasonal distribution of gross wave power. Finally, from an hourly power variability perspective, a reduction in WEC size generally decreases variability. However, for each of the locations investigated, there appears to be a WEC size threshold; a threshold where further reducing WEC size results in increased power variability.

blue economy↗