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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Atlas of albedo and absorbed solar radiation derived from Nimbus 6 earth radiation budget data set, July 1975 to May 1978

An atlas of monthly mean global contour maps of albedo and absorbed solar radiation is presented. The atlas is based on 35 months of continuous measurements from July 1975 through May 1978. The data were retrieved from measurements made by the shortwave wide field-of-view radiometer of the first Earth Radiation Budget (ERB) instrument, which flew on the Nimbus 6 spacecraft in 1975. Profiles of zonal mean albedos and absorbed solar radiation are tabulated. These geographical distributions are provided as a resource for studying the radiation budget of the earth. This atlas of albedo and absorbed solar radiation complements the atlases of outgoing longwave radiation by Bess and Smith in NASA-RP-1185 and RP-1186, also based on the Nimbus 6 and 7 ERB data.

Smith, G. Louis↗
NASA NTRS1990

Atlas of albedo and absorbed solar radiation derived from Nimbus 7 Earth radiation budget data set, November 1978 to October 1985

An atlas of monthly mean global contour maps of albedo and absorbed solar radiation is presented. This atlas contains 7 years of continuous data from November 1978 through October 1985. The data were retrieved from measurements made by the second Earth Radiation Budget (ERB) wide field-of-view instrument, which flew on the Nimbus 7 spacecraft in 1978. The deconvolution method used to produce these data is briefly discussed here so that the user may understand their generation and limitations. These geographical distributions of albedo and absorbed solar radiation are provided as a resource for researchers studying the radiation budget of the Earth. This atlas of albedo and absorbed solar radiation complements the atlases of outgoing longwave radiation by Bess and Smith, also based on the Nimbus 6 and 7 ERB data.

Smith, G. Louis↗
NASA NTRS1992

Atlas of albedo and absorbed solar radiation derived from Nimbus 7 earth radiation budget data set, November 1985 to October 1987

An atlas of monthly mean global contour maps of albedo and absorbed solar radiation is presented for 21 months from Nov. 1985 to Oct. 1987. These data were retrieved from measurements made by the shortwave wide-field-of-view radiometer of the Earth Radiation Budget (ERB) instrument aboard the Nimbus 7 spacecraft. Profiles of zonal mean albedos and absorbed solar radiation were tabulated. These geographical distributions are provided as a resource for researchers studying the radiation budget of the Earth. The El Nino/Southern Oscillation event of 1986-1987 is included in this data set. This atlas of albedo and absorbed solar radiation extends to 12 years the period covered by two similar atlases: NASA RP-1230 (Jul. 1975 - Oct. 1978) and NASA RP-1231 (Nov. 1978 - Oct. 1985). These three compilations complement the atlases of outgoing longwave radiation by Bess and Smith in NASA RP-1185, RP-1186, and RP-1261, which were also based on the Nimbus 6 and 7 ERB data.

Smith, G. Louis↗
DOE OSTI2022

Investigating capacity credit sensitivity to reliability metrics and computational methodologies

Assigning capacity value to renewable energy sources (RES) is a challenge faced in planning their integration with the grid. The difficulties stem from the natural characteristics of variability and intermittency of wind and solar sources. The capacity credit (CC) analysis evaluates the system’s actual power output compared with a constant capacity generator, i.e., conventional generator and determines an effective capacity to use for planning and operation. Herein this paper presents different factors that could affect the CC of a system. Two methods are proposed to determine the CC, namely equivalent firm capacity (EFC) and effective load carrying capability (ELCC). Since these methods are based on satisfying reliability criteria, daily loss of load expectation (LOLE), hourly loss of load (LOLH), and expected energy not served (EENS) have been employed as indices. To obtain the CC value, both methods apply two techniques: traditional and optimization. Genetic algorithm (GA) is the optimization approach used in this paper. Then, this work compares the two techniques and shows the superior performance of the optimization approach. Two hybrid systems, stand-alone (SA) and grid-connected (GC) modes, are proposed and used as case studies. The hybrid systems consist of photovoltaic (PV), wind turbine (WT), and battery energy storage system (BESS). In this work, three different scenarios are used to compare capacity credit: system as a whole, only wind, and no batteries. Finally, sensitivity analysis is carried out to examine the impact of varying the wind speed, solar irradiation, and load. It is demonstrated that the choice of reliability index plays an important role in determining the capacity credit and it is shown that EENS is a more comprehensive and consistent index of reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A scalable planning framework of energy storage systems under frequency dynamics constraints

As the penetration of renewables increases in power systems, the declining system inertia can cause frequency stability issues. Battery energy storage systems (BESSs) respond fast and therefore can relieve the low inertia difficulty but need to be appropriately sized considering the associated cost. This paper presents a novel stochastic optimization model for economically planning BESS capacity while considering the spatial–temporal correlation of wind generation and generator outages under frequency stability constraints, which include the rate-of-change of frequency (RoCoF), frequency nadir (FN), and quasi-steady-state (QSS) frequency. A set of new FN constraints that can be easily linearized is developed. To account for renewable uncertainties, a realistic uncertainty modeling approach, Random Field, is adopted to generate wind generation scenarios by considering both spatial and temporal evolutions of wind speed profiles. The ESS sizing is formulated as a mixed-integer linear programming problem and solved by using a scalable decomposition-and-coordination approach, Surrogate Absolute Value Lagrangian Relaxation (SAVLR). To further improve the scalability and reduce computational burdens, a rolling-horizon-based update is developed and incorporated into SAVLR for providing a practical solution to the long-term planning of very large-scale power systems. Finally, a modified IEEE 118-bus system and the Polish system are used to validate the effectiveness and scalability of the model and solution methodology.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Demonstrating the data center as a flexible grid asset using a C-HIL setup

Increasing data center demand is outpacing grid infrastructure development. Artificial intelligence workloads and hyperscale cloud growth are creating unprecedented demand for power, while traditional grid expansion faces multiyear development timelines. Verrus is developing an innovative datacenter solution for this challenge, data centers that act as active grid-supportive assets rather than passive loads. Our approach integrates a novel grid-aware power flow management system with battery energy storage systems(BESS) into a microgrid-controlled, medium-voltage power distribution architecture that delivers critical capabilities, such as: * Fast response to grid disturbances such over/ under voltage or over/ under frequency * Demand flexibility that can service requests from the utility within 10 s * Uninterrupted transition to islanded operation during grid outages * Continuous uptime assurance for compute loads while maintaining all customer service level agreements. Through Verrus' strategic partnership with the National Renewable Energy Laboratory (NREL), these capabilities were validated using NREL's Advanced Research on Integrated Energy Systems (ARIES) virtual emulation environment to model a 70-MW grid-interactive data center. This paper outlines the design, methodology, and results of this emulated deployment, demonstrating that data centers can provide both critical load resilience and ancillary grid support without compromising uptime requirements. Specifically, we present a digital real time simulation of a 70 MW data center integrated with a physical microgrid controller, and demonstrate the data center response in the event of a grid voltage and frequency event, utility demand response request and utility outage.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A Frequency Control Method for Islanded Microgrids Using Energy Storage Systems

Islanded microgrids are vulnerable to frequency fluctuations due to the presence of low-inertia distributed energy resources (DERs). Moreover, implementation of both synchronous-based and inverter-based DERs with a significant difference in inertia leads to a power imbalance between generation and consumption during transients. This results in frequency variations which might have severe consequences such as blackouts. This paper develops a control scheme for battery energy storage systems (BESSs) to enhance the dynamic response of islanded microgrids by mitigating the frequency fluctuations. A piecewise linear-elliptic (PLE) droop characteristic is proposed and employed in BESS to achieve a faster power balance between generation and consumption during transients, resulting in enhanced frequency responses. Different case studies are carried out to validate the viability of the proposed approach in improving the dynamics of islanded microgrids.

Pilehvar, Mohsen S.↗
DOE OSTI2022

Optimal Sizing and Operation of a Hybrid Clean Energy Center

In this paper, we consider the deployment of battery energy storage systems (BESSs) paired with photovoltaics (PV) to form a hybrid clean energy center (HCEC), where the BESS is equipped for two main purposes: i) reducing the volatility of PV output and ii) shifting energy to meet an export limit. We develop a linear dynamical model to characterize the output of an HCEC and express the volatility and export power as functions of the battery's dispatch operations. We also propose an optimal sizing method via second-order cone programming (SOCP) to maximize the net benefits of the HCEC. Numerical studies are performed to illustrate and validate the proposed method.

Battery energy storage systems, photovoltaics, sec↗
DOE OSTI2024

High-Penetration Microgrids Providing Grid Stability Using Frequency Watt Control

The U.S. grid is rapidly transitioning towards utilizing inverter-based renewable energy resources such as solar, wind, and batteries, reducing the carbon emission footprint. Inverter-based microgrid control architectures remain a critical focus to address power system stability issues in future high penetration markets lacking spinning generation assets. Idaho National Laboratory (INL) is researching an active layered inverter based frequency-Watt control scheme that provides distribution level stability in high-penetration markets where grid inertia is lacking. Hardware in the loop case study was implemented using INL’s Microgrid Testbed to combat scalable frequency deviations ranging from 60 Hz down to 50 Hz initialized by a hydropower model implementing step loads using a 540-kW grid emulator. Our research findings demonstrate the importance of distribution level, inverter-based active frequency-Watt controls utilizing a battery energy storage system (BESS) to provide adequate frequency support at the point of common coupling without major power infrastructure upgrades.

14 SOLAR ENERGY↗
DOE OSTI2024

Real-Time Inertia Estimation Tool Implementation Based on Probing Signals

As renewable energy penetration increases and the traditional generators retire in power grids, system inertia decreases and exhibits significant daily fluctuations. Furthermore, fast frequency responses (FFRs) provided by the inverter-based resources (IBRs) begin to playa very critical role and bring new challenges to real-time system inertia monitoring due to the difficulties of quantifying its artificial inertia contribution. Thus, necessitating an accurate real-time inertia estimation tool will not only benefit the secure power grid operations, but also provide insights on assessing the artificial inertia contribution from the IBRs. This paper presents a probing-based real-time inertia estimation tool that has been validated through a power-hardware-in-the-Ioop (PHIL) test system using identical hardware battery energy storage system (BESS) and control in an actual power grid. Preliminary results indicate high estimation accuracy of the developed tool and pave the way for the field test and deployment.

inverter-based resources↗
DOE OSTI2022

Sizing Considerations for EV Dynamic Wireless Charging Systems with Integrated Energy Storage

Roadways with dynamic wireless charging systems (DWCS) enable charge-sustaining in-motion EV charging, which can reduce charging idle time while increasing range capabilities. Spatially distributed transmitter coils are controlled in response to traffic load that varies significantly minute to minute with high power levels, very short charging time, and low system utilization like wind turbine power. Traffic load estimation and localized analysis may guide effective sizing and topology adoption for feasible and scalable DWCS deployment. DWCS traffic load approximation is reviewed with measured Automated Traffic Recorder (ATR) data and statistical distributions being used to create a synthetic load analyzed using proposed metrics quantifying system utilization over time. Lumped coil section segmentation is compared between second-based distance and spatial density analysis methods, offering 17-27% greater system utilization. A peak load shifting method is proposed for traffic redirection across two tracks with optional BESS integration increasing system utilization by 50-60% depending on time-based and power reserve-based sizing and control.

Lewis, Donovin D.↗
DOE OSTI2021

Cyber-Physical Event Emulation-Based Transmission-and-Distribution Co-Simulation for Situational Awareness of Grid Anomalies (SAGA)

Energy management of transmission and distribution networks (T&D) is becoming more challenging with the accelerated adoption of distributed energy resources (DERs)-such as distributed photovoltaic generation and battery energy storage systems (BESS)-on the electric grid. To better analyze the impacts of DERs on both transmission and distribution systems, a comprehensive T&D co-simulation platform is developed. Further, with DERs more actively participating in system operation-e.g., by providing real-time grid services-their cyber vulnerability needs to be better understood to maintain system reliability. This paper discusses a cyber-physical events emulation-based T&D co-simulation platform to perform comprehensive cyber events emulations, physical simulation, and analysis of interdependent impacts. Results from the case studies-which show how cyber events on a synthetic distribution network can impact operations on the transmission and distribution network-validate that the proposed T&D cosimulation platform can perform cyber-physical events emulation and produce response in near realtime; therefore, with extensive simulation using the proposed co-simulation platform, the system operators can accumulate adequate training data for system situational awareness of grid anomalies.

anomalies detection↗
DOE OSTI2022

Novel Real- Time EMT- TS Modeling Architecture for Feeder Blackstart Simulations

This paper presents the development and benchmarking of a novel real-time electromagnetic-transient and transient-stability (EMT-TS) modeling architecture for distribution feeder restoration studies. The work presents for the first time in the literature a real-time EMT-TS testbed in which the grid-forming unit is simulated in EMT domain, operating as the slack bus of the phasor domain while including unbalanced voltage conditions. To evaluate the performance and limitations of the proposed model, an equivalent EMT testbed is developed to serve as a benchmark. First, the co-simulation framework and the domain coupling methodology are introduced. Next, the steady state operation of the EMT-TS and EMT models are matched. Then, tests are conducted to analyze the transient performance of the proposed EMT-TS model when compared to its EMT benchmark. Results reveal that when utilizing a battery energy storage system (BESS) as the grid-forming unit, the EMT-TS testbed can maintain high accuracy for typical load steps.

Paduani, Victor↗
DOE OSTI2020

Soft-Switching Solid-State Transformer With Reduced Conduction Loss

Solid-state transformers (SSTs) are a promising solution photovoltaic (PV), wind, traction, data center, battery energy storage system (BESS), and fast charging electric vehicle (EV) applications. The traditional SSTs are typically three-stage, i.e., hard-switching cascaded multilevel rectifiers and inverters with dual active bridge (DAB) converters, which leads to bulky passives, low efficiency, and high electromagnetic interference (EMI). This article proposes a new soft-switching solid-state transformer (S4T). The S4T has full-range zero-voltage switching (ZVS), electrolytic capacitor-less dc link, and controlled dv/dt, which reduces EMI. The S4T comprises two reverse-blocking current-source inverter (CSI) bridges, auxiliary branches for ZVS, and transformer magnetizing inductor as a reduced dc link with 60% ripple. Compared with the prior S4T, an effective change on the leakage inductance diode is made to reduce the number of the devices on the main power path by 20% for significant conduction loss saving and retain the same functionality of damping the resonance between the leakage and resonant capacitors and recycling trapped leakage energy. The conduction loss saving is crucial, being the dominating loss mechanism in SSTs. Importantly, the proposed single-stage SST not only holds the potential for high power density and high efficiency but also has full functionality, e.g., multiport dc loads integration, voltage regulation, and reactive power compensation, unlike the traditional single-stage matrix SST. The S4T can achieve single-stage isolated bidirectional dc–dc, ac–dc, dc–ac, or ac–ac conversion. It can also be configured input-series output-parallel (ISOP) in a modular way for medium-voltage (MV) grids. Hence, the S4T is a promising candidate for the SST. The full functionality, e.g., voltage buck–boost, multiport, etc., and the universality of the S4T for the dc–dc, dc–ac, and ac–ac conversion are verified through the simulations and experiments of two-port and three-port MV prototypes based on 3.3 kV SiC MOSFETs in dc–dc, dc–ac, and ac–ac modes at 2 kV.

14 SOLAR ENERGY↗
DOE OSTI2022

A Data-Driven Algorithm for Enabling Delay Tolerance in Resilient Microgrid Controls Using Dynamic Mode Decomposition

The increased implementation of smart grid technologies in the power distribution grid presents unique opportunities that enable resiliency, but also brings challenges motivating needs for novel solutions and mitigation techniques. The bi-directional power and data flow allow for the grid to operate with increased resiliency, which is the ability to avoid discontinuity of service to end-use loads during extreme events. However, in applications where control of the distribution grid or microgrid relies on communication networks, the degradation of communication systems in the form of loss or high latency can cause maloperation and result in loss of end-use loads. Here this paper presents a novel framework to enable delay tolerance of centralized microgrid control schemes to mitigate communication system latency impacts and guarantee successful control action. We demonstrate the delay tolerance on a control scheme that operates a battery energy storage system (BESS) to offset the sudden loss of generation and maintain system frequency. During periods of severely degraded communication system performance, the proposed delay-tolerant algorithm compensates for the latency by utilizing a data-driven model generated at the device level using dynamic mode decomposition (DMD) to determine the performance of the communications. The DMD technique predicts the system’s frequency using device-level terminal measurements and provides updated control signals. The HELICS cosimulation platform evaluates the cyber-physical interaction of the power system model in GridLAB-D, the centralized control agent in Python, and the discrete network model in NS-3. The framework is tested and validated on the IEEE-123 node system modified to represent a networked remote microgrid model, and the results show an improvement in the dynamic performance

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Real-Time Dispatcher for a Distributed Energy Resource Power Plant to Provide Grid Services [SWR-25-17]

This software dispatches the aggregated power of a distributed energy resource (DER) plant located on an electrical distribution network. It is designed to provide the following services to the grid in real-time: (i) voltage support of the distribution network, (ii) virtual power plant at the substation with power factor support, and (iii) operating reserves for automatic generator control for the transmission system. This dispatcher integrates with the local power plant controller and utilizes the battery energy storage system (BESS) to smooth the volatile net power output from the DERs. It can also integrate with a day-ahead scheduler to strategically charge and discharge.

Comden, Joshua [National Renewable Energy Laborato↗
DOE OSTI2025

Data-Driven Energy Resilience Assessment and Enhancement in Urban Communities: A Case Study in Detroit

This paper presents a data-driven framework for assessing and enhancing energy resilience in urban communities. The resilience assessment is based on two datasets: 1) annual aggregated power outage data and 2) 15-minute interval outage data. High-impact, low-probability (HILP) events are identified within these datasets to evaluate community resilience under extreme conditions. To enhance resilience, an optimization framework utilizing mixed integer linear programming is developed to determine the optimal sizing and placement of solar photovoltaic (PV) systems and battery energy storage systems (BESS). This method offers a cost-effective and practical solution for improving energy resilience in vulnerable communities. Furthermore, a case study of the City of Detroit in Michigan demonstrates the effectiveness of the framework through simulation and validation.

Energy resilience assessment↗
DOE OSTI2021

Energy Storage in South Asia: Understanding the Role of Grid-Connected Energy Storage in South Asia’s Power Sector Transformation

During the last decade, the cost of energy storage technologies, primarily lithium-ion battery energy storage systems (BESS), has declined rapidly and is projected to decline further over the next decade. This study provides a first-of-its-kind assessment of cost-effective opportunities for grid-scale energy storage deployment in South Asia both in the near term and the long term, including a detailed analysis of energy storage drivers, potential barriers, and the role of energy storage in system operations. We conduct scenarios-based capacity expansion modeling to assess when, where and how much energy storage can be cost-effectively deployed in India through 2050. The analysis relies on state-of-the-art modeling approaches to uncover and compare the value streams of battery storage with different durations as well as pumped storage hydropower. We also run hourly simulations of system operations in 2030 and 2050 to understand how energy storage will be utilized by system operators to help integrate RE and reduce operating costs. For Bangladesh, Bhutan, and Nepal, we use operational simulations to explore how increasing deployment of energy storage can help optimize the use of domestic resources and cross-border electricity trade.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗