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At least 217 records · Page 12

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DOE OSTI2022

A Universal Controller for Grid-Forming Inverters in Microgrid during Islanding for Low Transient Current

This paper presents a universal controller to reduce the transient current during islanding of microgrid. In the proposed universal controller, two sets of semi-parallel paths are formed, where one set produces voltage and phase-angle references for the grid-following (GFL) mode, and the other set produces the voltage and phase-angle references for the grid-forming (GFM) mode of operation for the inverters. Herein, the controller enables an inverter to universally operate in GFL and GFM mode, whereas, only one set of voltage and phase-angle reference is engaged for PWM signal generation. When the microgrid is disconnected from the grid, the universal controller switches the voltage and phase-angle references from GFL to GFM mode. The proposed controller ensures lower transient current by keeping the two sets of semi-parallel paths synchronized throughout the operation of the inverter and enabling seamless transition between the modes. The proposed controller is verified through hardware experiments under different scenarios in a laboratory scale microgrid for inverters transitioning from GFL to GFM mode after islanding.

Sadeque, Fahmid↗

DOE OSTI2022

Inverter Design with High Short-Circuit Fault Current Contribution to Enable Legacy Overcurrent Protection for Islanded Microgrids

The resiliency offered by a microgrid may be lost if the microgrid is not properly protected during short-circuit faults inside its boundaries. Many studies conclude that protecting microgrids in islanded mode is very challenging due to the limited short-circuit capability of distributed energy resources (DERs). The limited short-circuit capability of DERs typically inhibits the use of reliable and affordable overcurrent protective devices in microgrids. Although extensive research on microgrid protection is available in the literature, to date this research has not led to a cost-effective, commercially available relay that effectively tackles the challenges of microgrid protection. This work proposes hardware modifications to enhance the current contribution of an energy storage inverter with the objective of enabling the use of legacy overcurrent protection for islanded microgrids. This paper demonstrates through experimental results that few modifications are required in the inverter to significantly enhance its current contribution. In this study, a three-phase energy storage inverter was modified to provide three times its rated current during three-phase faults, which proved sufficient current for enough time to enable fuse-relay, and relay-to-relay coordination. The proposed modifications effectively increase the current contribution of the inverter, which is a promising advancement to allow the adoption of overcurrent protective devices for protecting microgrids.

Ferrari Maglia, Max↗

DOE OSTI2020

Approximating Trajectory Constraints With Machine Learning – Microgrid Islanding With Frequency Constraints

Here, we introduce deep earning aided constraint encoding to tackle the frequency-constraint microgrid scheduling problem. The nonlinear function between system operating condition and frequency nadir is approximated by using a neural network, which admits an exact mixed-integer formulation (MIP). This formulation is then integrated with the scheduling problem to encode the frequency constraint. With the stronger representation power of the neural network, the resulting commands can ensure adequate frequency response in a realistic setting in addition to islanding success. The proposed method is validated on a modified 33-node system. Successful islanding with a secure response is simulated under the scheduled commands using a detailed three-phase model in Simulink. The advantages of our model are particularly remarkable when the inertia emulation functions from wind turbine generators are considered.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Safe Reinforcement Learning-Based Transient Stability Control for Islanded Microgrids With Topology Reconfiguration

This paper proposes a safe reinforcement learning (RL)-based transient stability emergency control (TSEC) method for islanded microgrids. RL requires extensive interaction with the environment to learn control strategies, hence, a data-driven approach is used as a substitute for time-consuming time-domain simulation calculations. Deep sigma point processes (DSPP), which is a Gaussian process model, is utilized to predict the normal distribution of transient stability of microgrids and to construct a transient stability chance constraint. Reward-constrained policy optimization (RCPO) can simultaneously achieve objective prediction, policy learning, and constraint cost coefficient update across multiple timescales. RCPO interacts with the DSPP-based microgrid environment through a multi-process parallel manner, greatly increasing the training speed. Case studies on a real islanded microgrid demonstrate that the proposed method can efficiently and quickly obtain the optimal emergency control strategy while adhering to all hard constraints.

14 SOLAR ENERGY↗

DOE OSTI2022

Deep Reinforcement Learning From Demonstrations to Assist Service Restoration in Islanded Microgrids

Microgrids can be operated in island mode during utility grid outages to support service restoration and improve system resilience. To schedule and dispatch distributed energy resources (DERs) in an islanded microgrid, conventional model-based methods rely on accurate distribution network models and lack generalization and adaptability. Data-driven methods are promising for DER coordination but face practical challenges such as potential hazards to microgrids during online training and insufficient online training opportunities due to low outage rates. This paper presents a novel two-stage learning framework that builds on the deep deterministic policy gradient from demonstrations to identify an optimal restoration strategy. At the pre-training stage, imitation learning is applied to equip the control agent with expert experiences to guarantee acceptable initial performance. At the online training stage, action clipping, reward shaping, and expert demonstrations are leveraged to ensure safe exploration while accelerating the training process. In conclusion, the proposed method is illustrated using the IEEE 123-node system and compared with a representative model-based method and the standard deep deterministic policy gradient method to prove solution accuracy and demonstrate increased computational efficiency.

Du, Yan↗

DOE OSTI2022

Patterns and controls on island‐wide aboveground biomass accumulation in second‐growth forests of Puerto Rico

Abstract Understanding the heterogeneity of biomass accumulation in second‐growth tropical forests following land use abandonment is important for informing ecosystem carbon models and forest restoration efforts. There is an urgent need for a broad sample of second‐growth forests to enhance our knowledge of carbon accumulation in human‐dominated landscapes, especially for older forests. Puerto Rico has predominantly second‐growth forests, ranging in age from approximately 25 to more than 80 years. We used an island‐wide sample of airborne lidar from the NASA Goddard Lidar, Hyperspectral, and Thermal (G‐LiHT) Airborne Imager collected on March 2017, forest inventory data, and data on forest age, precipitation, soils, and land use to estimate aboveground biomass stocks in moist and wet, second‐growth tropical forests. Biomass accumulation rates in Puerto Rico were lower, on average, than in other Neotropical forests. Median biomass across >16,700 ha of older second‐growth forests was 105 Mg ha −1 , and sampled biomass rarely surpassed 250 Mg ha −1 . Differences in biomass by age were large and persistent across different substrates and land uses, with a plateau in the pattern of island‐wide biomass accumulation after about 33 years. A spatial regression model showed that multiple factors were related to biomass accumulation, including time since abandonment, geologic substrate, past land use as coffee or pasture, precipitation, topographic wetness index, and slope. Our findings have important consequences for the total carbon storage and expected climate mitigation benefits of large‐scale reforestation efforts, and highlight the value of airborne lidar for quantifying biomass variability in complex tropical landscapes. Abstract in Spanish is available with online material.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

sup3ruhi (Super Resolution for Renewable Resource Data and Urban Heat Islands) [SWR-25-05]

Urban heat is a growing concern, particularly in dense metropolitan areas where high temperatures increase the risk of heat-related illness and drive energy expenses for cooling. Estimating the effects of urban heat remains a challenge due to limitations in describing the built environment, computational constraints, and the need for high-resolution data. This software presents open-source, computationally efficient machine learning methods that enhance the accuracy of urban temperature estimates compared to historical reanalysis data. Models trained using this software have been applied to urban microclimates in Los Angeles and Seattle showing greater accuracy and less bias when compared to low-resolution reanalysis datasets like ERA5 and even when compared to high-resolution mesoscale numerical weather models like WRF with an urban canopy model. Initial findings highlight how machine learning can support urban heat resilience planning by enabling improved assessments of local heat islands, mitigation strategies, and their energy implications. This software is an extension of (sup3r). This software supports the following publication: Buster, Grant, et al. Tackling Extreme Urban Heat: A Machine Learning Approach to Assess the Impacts of Climate Change and the Efficacy of Climate Adaptation Strategies in Urban Microclimates. arXiv:2411.05952, arXiv, 8 Nov. 2024. arXiv.org, https://doi.org/10.48550/arXiv.2411.05952. And has related public data records available at: Buster, Grant, Cox, Jordan, Benton, Brandon, and King, Ryan. Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI). United States: N.p., 16 Oct, 2024. Web. https://data.openei.org/submissions/6220.

Buster, Grant [National Renewable Energy Laborator↗

DOE OSTI2025

Redox potential in Typha-dominated tidal brackish marsh, PIE LTER, Plum Island Sound, MA, June–December 2022

This dataset includes soil redox potential measurements collected at multiple depths within a tidal brackish wetland in the upper estuary of the Plum Island Ecosystems Long-Term Ecological Research site (PIE LTER), Plum Island Sound, Newbury, Massachusetts. Measurements were taken to evaluate temporal variation in redox potential in relation to hydrological events at three replicate locations. Data were recorded every 5 minutes using a Campbell Scientific Volt116 connected to a CR6 datalogger with SWAP instrument redox probes (ORP-30-4-B) and reference electrodes. Measurements were made at the AmeriFlux site US-PLo at four soil depths (5, 10, 15, and 30 cm). The file redox_soiltemp_2022.csv contains temperature-corrected redox values and soil temperature following Silva-Machado et al. (2024). Metadata files redox_soiltemp_dd.csv and redox_soiltemp_flmd.csv provide detailed descriptions of variables and site locations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

AmeriFlux FLUXNET-1F US-Bi1 Bouldin Island Alfalfa

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Bi1 Bouldin Island Alfalfa. This is the FLUXNET version of the carbon flux data for the site US-Bi1 Bouldin Island Alfalfa produced by applying the standard ONEFlux (1F) software. Site Description - An agricultural field in the San Joaquin Sacramento Delta. The field is a mix of organic peat and sediments and minerals from old river channels

Rey-Sanchez, Camilo↗

DOE OSTI2022

AmeriFlux FLUXNET-1F US-Sne Sherman Island Restored Wetland

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Sne Sherman Island Restored Wetland. This is the FLUXNET version of the carbon flux data for the site US-Sne Sherman Island Restored Wetland produced by applying the standard ONEFlux (1F) software. Site Description - A new restored wetland on the old Sherman Pasture site. The new tower is about 67m northwest (300deg) of the old tower site (US-Snd). On Jan 30, 2020 a temporary tower was set up in the western portion of Sherman Wetland to capture the more vegetated areas and compare with the main tower.

Shortt, Robert↗

DOE OSTI2025

AmeriFlux US-PLo Plum Island Oligohaline Marsh

This is the AmeriFlux version of the carbon flux data for the site US-PLo Plum Island Oligohaline Marsh. Site Description - The site is a tidal oligohaline marsh located within the Plum Island Sound estuary, which is characterized by a tidal range of 2.5-3m and a vegetation cover of Typha angustifolia. Porewater salinity changes seasonally as influenced by freshwater discharge. Elevation is about 1.4m NAVD88.

Forbrich, Inke [University of Toledo]↗

DOE OSTI2026

AmeriFlux PA-Bar Barro Colorado Island

This is the AmeriFlux version of the carbon flux data for the site PA-Bar Barro Colorado Island. Site Description - Barro Colorado Island supports a humid tropical forest with high biodiversity, with 314 tree species in 50 ha. The climate has a strong four-month dry season from late December to late April. Several deciduous species drop their leaves during this period. Lianas are very abundant accounting for 20% of dry leaf biomass. This is the original location of the BCI flux tower, now replaced by PA-Bas

Wright, Joseph [Smithsonian Tropical Research Inst↗

DOE OSTI2021

Free fermion entanglement with a semitransparent interface: the effect of graybody factors on entanglement islands

We study the entanglement entropy of free fermions in 2d in the presence of a partially transmitting interface that splits Minkowski space into two half-spaces. We focus on the case of a single interval that straddles the defect, and compute its entanglement entropy in three limits: Perturbing away from the fully transmitting and fully reflecting cases, and perturbing in the amount of asymmetry of the interval about the defect. Using these results within the setup of the Poincaré patch of AdS _2 2 statically coupled to a zero temperature flat space bath, we calculate the effect of a partially transmitting AdS _2 2 boundary on the location of the entanglement island region. The partially transmitting boundary is a toy model for black hole graybody factors. Our results indicate that the entanglement island region behaves in a monotonic fashion as a function of the transmission/reflection coefficient at the interface.

Kruthoff, Jorrit↗

DOE OSTI2024

Energy Transitions Initiative Partnership Project: Bainbridge Island, Washington: Cohort 2 Technical Assistance: Improving Resilience

The City of Bainbridge Island (COBI) applied for and received technical assistance from the Energy Transitions Initiative Partnership Program (ETIPP) in part to achieve their goal of 100% renewable electricity generation by 2040, five years ahead of the Washington State goal. Their second goal of increasing energy resilience is discussed in this report. Pacific Northwest National Laboratory (PNNL) completed the technical analysis aspects of the project, supported by the community partner Spark Northwest and the program administrator, the National Renewable Energy Laboratory (NREL). PNNL worked with the Community Lead and stakeholders to ensure selection of hazards and energy infrastructure of highest priority and integration of existing expertise into the analysis. We have also worked to align analysis with current activities conducted by Puget Sound Energy (PSE), and other efforts within the Bainbridge Island community around resilience. This report, conducted under the ETIPP project in partnership with COBI, aims to build on this existing knowledge base with a specific energy focus, to identify hazards and threats to critical energy infrastructure, summarize the risk, and identify and analyze remaining resilience gaps.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Resonance Trajectories and Island Tune Spectra in the Tune Domain

Island tune spectra are introduced, beginning with curves of resonance trajectories plotted in the (Q x , Q I ) tune domain plane (where Q x is horizontal tune and Q I is island tune) for many resonance orders N. A slice in the (Q x , Q I ) plane delivers a Q I -spectrum at a fixed horizontal tune, with one spectral line for every appropriate value of N.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Resource Assessment Study of Long Island Sound Tidal Resource in New York State Waters Based on Numerical Modeling (Abstract)

To refine the understanding of the tidal energy resource in Long Island Sound (LIS), Verdant Power and PNNL will collaborate to conduct a numerical modeling campaign in accordance with a Stage 2 resource assessment according to IEC TC 62600-201. The work will develop a high resolution tidal hydrodynamic model using FVCOM in LIS, validate the model using NOAA C-MIST ADCP data, and conduct a Stage 2 array layout design study at selected hotspots within the project area. The teams will also model tidal energy extraction using the FVCOMTEC module at the hotspot sites, based on specific device technologies provided by Verdant Power. Model results from this study will inform additional resource assessment activities such as in situ water velocity measurements for further model validation and elucidate understanding of other key sites in Long Island Sound for commercial-scale tidal energy deployments.

16 TIDAL AND WAVE POWER↗

DOE OSTI2026

Block Island’s Energy Roadmap to 2040

This report documents an electricity planning study "Energy Roadmap to 240" for the community of New Shoreham, Rhode Island (aka Block Island), conducted under the U.S. Department of Energy (DOE) Energy Technology Innovation Partnership Project (ETIPP) by a national laboratory analysis team comprising staff from Lawrence Berkeley National Laboratory.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Shelter Island, New York, Energy Reliability Assessment and Local Generation Options

Shelter Island's Green Options Committee (GOC), an all-volunteer committee tasked with considering all environmental conservation issues, requested technical assistance under the U.S. Department of Energy (DOE)-funded Energy Technology Innovation Partnership Project (ETIPP). The primary goals of this technical assistance project included: 1. Informing the GOC about energy use trends within the community as well as distributed solar, wind and storage opportunities; 2. Providing additional resources and technical feasibility information for geothermal, agrivoltaics and tidal energy; 3. Supporting the development of a community engagement plan; and 4. Supporting collaboration between the GOC and PSEG in order to find mutually beneficial follow-on projects. Assistance from NLR to help the GOC meet these overall project goals was provided through the following primary tasks: 1. Collaborate with the local utility in order to collect energy use data and inform the community on energy use patterns through a baseline assessment; 2. Technical analysis of distributed renewable and resiliency opportunities (solar, wind and storage) that best align with the community's energy priorities; 3. Provide high level feasibility support for future renewable energy scenarios that include agrivoltaic solutions, tidal energy, and geothermal projects on Shelter Island, and 4. Integrate all findings into a Community Outreach presentation to help the GOC engage with community stakeholders to build support and awareness of chosen resilience strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗