Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “distributed storage”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Alpine permafrost could account for a quarter of thawed carbon based on Plio-Pleistocene paleoclimate analogue

Estimates of the permafrost-climate feedback vary in magnitude and sign, partly because permafrost carbon stability in warmer-than-present conditions is not well constrained. Here we use a Plio-Pleistocene lacustrine reconstruction of mean annual air temperature (MAAT) from the Tibetan Plateau, the largest alpine permafrost region on the Earth, to constrain past and future changes in permafrost carbon storage. Clumped isotope-temperatures (Δ 47 -T) indicate warmer MAAT (~1.2 °C) prior to 2.7 Ma, and support a permafrost-free environment on the northern Tibetan Plateau in a warmer-than-present climate. Δ 47 -T indicate ~8.1 °C cooling from 2.7 Ma, coincident with Northern Hemisphere glacial intensification. Combined with climate models and global permafrost distribution, these results indicate, under conditions similar to mid-Pliocene Warm period (3.3–3.0 Ma), ~60% of alpine permafrost containing ~85 petagrams of carbon may be vulnerable to thawing compared to ~20% of circumarctic permafrost. This estimate highlights ~25% of permafrost carbon and the permafrost-climate feedback could originate in alpine areas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CityLearn v2: energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities

As more distributed energy resources become part of the demand-side infrastructure, quantifying their energy flexibility on a community scale is crucial. CityLearn v1 provided an environment for benchmarking control algorithms. However, there is no standardized environment utilizing realistic building-stock datasets for distributed energy resource control benchmarking without co-simulation or third-party frameworks. CityLearn v2 extends CityLearn v1 by providing a stand-alone simulation environment that leverages the End-Use Load Profiles for the U.S. Building Stock dataset to create grid-interactive communities for resilient, multi-agent, and objective control of distributed energy resources with dynamic occupant feedback. While the v1 environment used pre-simulated building thermal loads, the v2 environment uses data-driven thermal dynamics and eliminates the need for co-simulation with building energy performance software. This work details the v2 environment and provides application examples that use reinforcement learning control to manage battery energy storage system, vehicle-to-grid control, and thermal comfort during heat pump power modulation.

Nweye, Kingsley↗
DOE OSTI2022

Advanced Distributed Wind Turbine Controls Series: Part 2-Wind Energy in Isolated Grids – Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL)

In an isolated grid, wind turbines are typically deployed to provide energy to maximize energy production, reduce diesel-fuel consumption, reduce carbon emissions, and reduce costs for energy and fuel transportation. However, in addition to solely providing energy to the power system, wind turbines contain rotating masses and inverter-based controls that can enable various reliability and resilience services through advance controls. As part of the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) this paper demonstrates, through desktop simulations, advanced wind turbine controls that can be employed to support higher contributions of wind in isolated grids, and to demonstrate ways that wind can play a role in supporting stability of an isolated grid. This isolated grid used in these desktop simulations is comprised of a wind turbine (600 kW), solar PV (430 kW), battery energy storage system (1 MW/1MWh), a simulated diesel generator (2 MW) and various types of loads (critical, dynamic). We developed a model of the subsystems in MATLAB/Simulink and validated them with available data from real-world components on NREL's Flatirons Campus. These validated models are then configured for various case studies. We compare the output of the desktop simulation with a baseline case with the diesel generator. Active and reactive power control of the wind turbine can help improve frequency and voltage responses in the isolated grid, respectively. By utilizing a small integrated battery energy storage system in the DC-link of the wind turbine, we also demonstrate that wind turbines can help blackstart a critical load comparable to its rated power and support other renewables (e.g. solar PV) come online and pick up an additional load. This report illustrates some of these reliability and resilience services a wind turbine can provide in an isolated grid.

17 WIND ENERGY↗
DOE OSTI2021

Raman Microscopy Analysis of Wyoming CarbonSAFE Pilot Well Thin Sections for Mineralogy and Organic Matter Characterization

Scanning confocal Raman microspectroscopy (RMS) was used to analyze thin sections for inorganic mineral content and for evaluation of organic material (OM). Thin sections were selected from a stratigraphic test well core in the Powder River Basin, Wyoming under the Wyoming CarbonSAFE project. The well was analyzed with a variety of rock and fluid characterization techniques to determine the feasibility of a commercial-scale CO2 storage site. RMS complements other analyses, including traditional petrography, SEM, porosity and permeability, and XRD For this aspect of the study, RMS is especially important in the evaluation of OM in sealing lithologies. At prospective geologic CO2 storage sites, it is imperative to assess the unconventional oil and gas potential of seals to ensure that any future development would not compromise the integrity of the seals. Whole-slide mineralogical surveys were performed on thin sections from various shale and sandstone formations. Surveys were analyzed with Direct Classical Least Squares to identify and quantify minerals. The location and concentration of minerals was color-coded and overlaid on optical images for visualization of the distribution of minerals. Dense hyperspectral Raman mapping of OM was performed on five thin sections. Eleven spectral parameters diagnostic of organic type and thermal maturity were used to train a Partial Least Squares (PLS) calibration against a set of artificially matured samples spanning the pre- to mid-oil window. The PLS was applied to the study set and a post-mature set. Additionally, the PLS was applied to each point in hyperspectral maps for visualization of trends in maturity across sample sets and discrimination of organic matter types within a given map. In inorganic surveys on thin sections, a total of 14 unique inorganic minerals were identified in Raman spectra including quartz, dolomite, calcite, hematite and anhydrite. Shale thin sections tended to be dominated by organic material. OM was often observed mixed with inorganic minerals. Sand- and mudstones were dominated by inorganic minerals. The PLS extrapolated the post-mature set to reflectances >1.2%. The study set ranged from very immature to postmature in the median of map fit-peak parameters. However, point maturity maps indicate that matrix OM in all study samples is immature and that discreet organic particles selected for mapping, which may be inertinites, bias medians towards more-mature. The work demonstrates the capabilities of RMS to perform both whole-slide mineralogy and OM analysis with applications to formation evaluation in oil & gas, carbon sequestration and mining. Here, analysis of sealing formations in the well indicates high levels of immature organic matter that would not be a viable target for future oil production that could compromise the CO2 storage site. The work brings together diverse disciplines from geology and petrography to analytical chemistry, big data and microscopy.

Myers, Grant↗
DOE OSTI2023

Improving Frequency Stability and Minimizing Load Shedding Events by Adopting Grid-Scale Energy Storage with Grid Forming Inverters

The upward adoption trend of renewable generation not only means cleaner energy integrated into modern power grids, but also that most new generation sources are based on front-end inverter bridges, used as interfaces to most wind generation and all the solar PV. It is well known that due to their power electronics-based construction rather than rotational shafts, these sources do not provide inertia inherently, nor substantial amounts of short-circuit currents. However, stable energy such as what can be stored in energy storage systems, although interfaced via inverters, can be controlled to respond to system disturbances in a manner that emulates inertial behavior. This paper focuses on the application of such energy storage systems to augment inertia in the island of Puerto Rico. To do so, a user defined inverter model that contains grid forming capabilities and fast frequency response is modeled and integrated into the real transmission system in power flow and dynamics software. Energy storage is then connected to two selected areas so that it not only provides frequency regulation to avoid widespread load shedding events, but also other tangible benefits. The simulated cases suggest that even relatively small energy storage systems can avert load shedding events if adequately placed in the transmission network.

Grid-forming inverters, IBR, Inertia↗
DOE OSTI2023

Onsite Energy Techno-Economic Analysis Using REopt

Since 2019, the National Renewable Energy Laboratory (NREL) has collaborated with IEDO's Combined Heat and Power (CHP) Deployment Program and the CHP Technical Assistance Partnerships (TAPs) to expand the capabilities of NREL's publicly available REopt® tool for techno-economic analysis of on-site energy. As a result, capabilities to analyze heating and cooling loads and serve those loads with CHP were added to the REopt tool in 2021. Currently, NREL is using REopt to evaluate the economics and feasibility of deploying distributed energy resources at sites of 3-5 manufacturers. The analysis is based on location, site-specific load data, customized utility bill analysis, and other criteria such as resilience needs and decarbonization targets. The objectives of the current effort are to (1) assist manufacturers with analyzing on-site energy options, including CHP, solar photovoltaics (PV), wind, and battery storage, (2) validate the capabilities and use of REopt to provide technical assistance to manufacturers, and (3) publish case studies showcasing the engagement, key takeaways, and lessons learned. Future work is expected to include additional REopt capabilities for evaluating other technologies to reduce scope 1 emissions, such as electrifying process heating loads, using carbon-free fuels, and other clean heat strategies.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Can Wholesale Electricity Markets Achieve Resource Adequacy and High Clean Energy Generation Targets in the Presence of Self-Interested Actors?

Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.

capacity expansion↗
DOE OSTI2024

Mechanical Milling – Induced Microstructure Changes in Argyrodite LPSCl Solid-State Electrolyte Critically Affect Electrochemical Stability

Microstructure of argyrodite solid-state electrolyte (SSE) critically affects lithium metal electrodeposition/dissolution. While the stability of unmodified SSE is mediocre, once optimized state-of-the-art electrochemical performance is achieved (symmetric cells, full cells with NMC811) without secondary interlayers or functionalized current collectors. Planetary mechanical milling in wet media (m-xylene) is employed to alter commercial Li 6 PS 5 Cl (LPSCl) powder. Quantitative stereology demonstrates how milling progressively refines grain and pore size/distribution in the SSE compact, increases its density, and geometrically smoothens the SSE-Li interface. Mechanical indentation demonstrates that these changes lead to reduced site-to-site variation in the compact's hardness. Milled microstructures promote uniform early-stage electrodeposition on foil collectors and stabilize solid electrolyte interphase (SEI) reactivity. Analysis of half-cells with bilayer electrolytes demonstrates the importance of microstructure directly contacting current collector, with interface roughness due to pore and grain size distribution being key. For the first time, short-circuiting Li metal dendrite is directly identified, employing 1.5 mm diameter “mini” symmetrical cell and cryogenic focused ion beam (cryo-FIB) electron microscopy. The branching sheet-like dendrite traverses intergranularly, filling the interparticle voids and forming an SEI around it. Importantly, mesoscale modeling reveals the relationship between Li-SSE interface morphology and the onset of electrochemical instability, based on underlying reaction current distribution.

25 ENERGY STORAGE↗
DOE OSTI2023

In situ probing the origin of interfacial instability of Na metal anode

The unstable and fragile solid electrolyte interphase (SEI) has restricted the application of Na metal anodes. Despite numerous research efforts being put into understanding its chemical composition and physical properties, direct observation of its formation remains a challenge due to the lack of temporal and spatial resolution. Here, through combined in situ probing techniques, we exhibit two pivotal stages associated with SEI instability during the often -neglected formation process. It is revealed that Na metal that is not uniformly passivated at the initial (passivating) stage will trigger unrestricted electrolyte decomposition and homogeneous components distribution during the subsequent (growing) stage. SEI with homogenously distributed components is found to have higher solubility than that with a layered structure evolved from a compact passivation layer. Furthermore, through demonstrating an SEI dissolution model that is closely related to its formation process and compositional distribution, this work sheds light on an uncharted territory of Na metal batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Evaluating the Capabilities of Behind-the-Meter Solar-plus-Storage for Providing Backup Power during Long-Duration Power Interruptions [Slides]

The study estimates the performance of behind-the-meter solar PV-plus-energy-storage-systems (PVESS) in providing critical-load or whole-building backup across a wide range of geographies, building types, and power interruption conditions. The study also considers a set of 10 historical long-duration power outage events and evaluates how PVESS could have performed in providing backup power during those specific events. The analysis is the first in what will be a series of studies by Berkeley Lab, in collaboration with the National Renewable Energy Laboratory, on the use of PVESS for backup power. This initial study, which relies on simulated end-use level building loads, solar generation, and storage dispatch, is intended to provide a baseline set of performance estimates and to illustrate key performance drivers.

14 SOLAR ENERGY↗
DOE OSTI2023

Assessing the Resource Adequacy and Community Impacts of an Evolving Grid: Considerations for State Regulators

As U.S. power systems continue to decarbonize, state regulators must be able to broadly assess the cost and reliability implications of proposed fossil retirements and the corresponding resources that are coming online to replace them. Specifically, regulators must evaluate whether proposed infrastructure investments are sufficient to ensure the long-term reliability of the system, while also protecting rate payers by ensuring that such investments are necessary and not excessive. Broadly speaking, this objective is typically framed in terms of maintaining long-term resource adequacy at the lowest cost, while also ensuring that other social and/or environmental objectives are satisfied. System planners currently have a host of sophisticated analytical tools at their disposal to evaluate the cost-benefit trade-offs of different approaches to ensuring resource adequacy. However, most of these tools and associated metrics were designed with traditional power systems in mind. Over the past decade, it has become increasingly clear that the metrics and models that have reliably assessed resource adequacy in systems dominated by large thermal and hydropower resources will be insufficient for systems with significant contributions from emerging technologies such as wind, solar and storage. Therefore, in recent years many new metrics and modeling approaches have been developed, and are increasingly being implemented, to meet the needs of the clean energy transition.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Multiscale petrophysical characterization and flow unit classification of the Minnelusa eolian sandstones

Integration of petrophysical and geological information is critical to simulation of subsurface carbon storage (GCS). In this sense, two depositional facies were identified from the core description and well-log interpretation, namely massive (MS) and cross-bedded (CB) facies groups. Additionally, pore-scale characteristics were studied by a combination of techniques, e.g. Nuclear Magnetic Resonance (NMR) and mercury intrusion capillary pressure (MICP). Scanning electron microscope (SEM) and petrographic analyses show that the pore structure is dominantly controlled by the depositional environment and dolomite cementation. NMR-T 2 distributions of MS and CB facies show triple and quadruple modes, respectively. In addition, MICP of high- and low-permeability MS facies samples, and their CB facies group mixtures were collected. The MS sample pore-throat size distribution is uni-modal, while the triple-modal characteristic of the mixtures indicates heterogeneous pore structures at the sub-core scale for CB facies. The reliably estimates of porosity and permeability for both facies groups via NMR techniques and the MLR (Multiple Linear Regression) approach demonstrate the applicability of these techniques to eolian sandstone. Moreover, irreducible water saturation via the T 2 -cutoff method correlates strongly with T 2LM instead of porosity. Finally, the rock quality index and flow zone indicator were calculated based on Combinable Magnetic Resonance (CMR) log interpretations. This provides direct connection to properties measured in the well. Four flow units were classified for both facies groups. Finally, results show that better reservoir quality with significant heterogeneities is observed in the CB facies. This study highlights the importance integrating multiscale petrophysical properties including facies, pore architecture and diagenesis analysis with core- to log-scale property characterization. The results herein validate our reservoir characterization and flow unit classification in eolian reservoirs.

58 GEOSCIENCES↗
DOE OSTI2023

Visualizing interfacial collective reaction behaviour of Li–S batteries

Benefiting from high energy density (2,600 Wh kg -1 )) and low cost, lithium-sulfur (Li-S) batteries are considered promising candidates for advanced energy-storage systems. Despite tremendous efforts in suppressing the long-standing shuttle effect of lithium polysulfides, understanding of the interfacial reactions of lithium polysulfides at the nanoscale remains elusive. This is mainly because of the limitations of in situ characterization tools in tracing the liquid-solid conversion of unstable lithium polysulfides at high temporal-spatial resolution. There is an urgent need to understand the coupled phenomena inside Li-S batteries, specifically, the dynamic distribution, aggregation, deposition and dissolution of lithium polysulfides. Here, by using in situ liquid-cell electrochemical transmission electron microscopy, we directly visualized the transformation of lithium polysulfides over electrode surfaces at the atomic scale. Notably, an unexpected gathering-induced collective charge transfer of lithium polysulfides was captured on the nanocluster active-centre-immobilized surface. It further induced an instantaneous deposition of nonequilibrium Li2S nanocrystals from the dense liquid phase of lithium polysulfides. Without mediation of active centres, the reactions followed a classical single-molecule pathway, lithium polysulfides transforming into Li 2 S 2 and Li 2 S step by step. Molecular dynamics simulations indicated that the long-range electrostatic interaction between active centres and lithium polysulfides promoted the formation of a dense phase consisting of Li + and S n 2- (2 < n ≤ 6), and the collective charge transfer in the dense phase was further verified by ab initio molecular dynamics simulations. Finally, the collective interfacial reaction pathway unveils a new transformation mechanism and deepens the fundamental understanding of Li-S batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Role of silicon-graphite homogeneity as promoted by low molecular weight dispersants

This study explores low molecular weight polymers with the same chemical repeat structure as high molecular weight poly acrylic acid (PAA) and lithium poly acrylic acid (LiPAA) binders which act as a dispersant to improve the silicon-graphite electrode performance. The electrodes which utilize LiPAA as a dispersant perform, on average, the best with respect to the maximum capacity (compared to theoretical), rate performance, and capacity retention with time. These electrodes also have the poorest dispersion of binder, indicating that the poor binder dispersion is essential to electrode performance. In contrast, this study shows that electrodes formulated using PAA had good dispersion and performs the worst in cycling. Finally, this work demonstrates that the binder is not uniformly distributed in the electrode, but rather resides in local regions. Overall, the results indicate these regions accommodate volume expansion during cycling.

25 ENERGY STORAGE↗
DOE OSTI2021

A Massively Parallel Implementation of the CCSD(T) Method Using the Resolution-of-the-Identity Approximation and a Hybrid Distributed/Shared Memory Parallelization Model

In this work, a parallel algorithm is described for the coupled-cluster singles and doubles method augmented with a perturbative correction for triple excitations [CCSD(T)] using the resolution-of-the-identity (RI) approximation for two-electron repulsion integrals (ERIs). The algorithm bypasses the storage of four-center ERIs by adopting an integral-direct strategy. The CCSD amplitude equations are given in a compact quasi-linear form by factorizing them in terms of amplitude-dressed three-center intermediates. A hybrid MPI/OpenMP parallelization scheme is employed, which uses the OpenMP-based shared memory model for intranode parallelization and the MPI-based distributed memory model for internode parallelization. Parallel efficiency has been optimized for all terms in the CCSD amplitude equations. Two different algorithms have been implemented for the rate-limiting terms in the CCSD amplitude equations that entail and -scaling computational costs, where N O and N V denote the number of correlated occupied and virtual orbitals, respectively. One of the algorithms assembles the four-center ERIs requiring N V 4 and N O 2 N V 2 -scaling memory costs in a distributed manner on a number of MPI ranks, while the other algorithm completely bypasses the assembling of quartic memory-scaling ERIs and thus largely reduces the memory demand. It is demonstrated that the former memory-expensive algorithm is faster on a few hundred cores, while the latter memory-economic algorithm shows a better strong scaling in the limit of a few thousand cores. The program is shown to exhibit a near-linear scaling, in particular for the compute-intensive triples correction step, on up to 8000 cores. The performance of the program is demonstrated via calculations involving molecules with 24–51 atoms and up to 1624 atomic basis functions. As the first application, the complete basis set (CBS) limit for the interaction energy of the π-stacked uracil dimer from the S66 data set has been investigated. This work reports the first calculation of the interaction energy at the CCSD(T)/aug-cc-pVQZ level without local orbital approximation. The CBS limit for the CCSD correlation contribution to the interaction energy was found to be -8.01 kcal/mol, which agrees very well with the value -7.99 kcal/mol reported by Schmitz, Hättig, and Tew [ Phys. Chem. Chem. Phys. 2014 , 16 , 22167-22178]. The CBS limit for the total interaction energy was estimated to be -9.64 kcal/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The Role of Snowmelt and Subsurface Heterogeneity in Headwater Hydrology of a Mountainous Catchment in Colorado: A Model‐Data Integration Approach

Mountainous headwater streams are sustained by both snowmelt‐driven streamflow and groundwater discharge in the Upper Colorado River Basin. However, predicting headwater stream discharge magnitude and peak flow timing is challenging in mountainous terrains, where snowmelt rates vary with vegetation type and elevation, and heterogeneous subsurface physical properties influence groundwater storage and its release. We used a model‐data integration approach to investigate the roles of snowmelt and subsurface structure in stream discharge and groundwater level. We ran an ensemble of 100 integrated surface‐subsurface hydrologic models for a mountainous headwater catchment near Crested Butte, Colorado, USA. We also evaluated and calibrated these models against observed data sets, including snow depth measurements using distributed temperature probes, stream discharge, and groundwater levels. Calibration with multiple data sources using neural density estimators has further constrained uncertainty in subsurface properties and snowmelt rates. Results indicated that observed slower snowmelt rates in evergreen forests delayed the peak flow and baseflow onset. In upstream areas with lower subsurface permeability, water was stored within the subsurface but was not released as interflow or shallow groundwater flow, and thereby not contributing to downstream streamflow during recession limb periods. Double peaks in groundwater occurred in areas with spatial subsurface heterogeneity, in our case due to the contrast between granodiorite and Mancos shale. These process‐based insights into groundwater and snowmelt dynamics in mountainous headwaters will help improve predictions of headwater hydrology.

Wang, Lijing [University of Connecticut, Storrs, C↗
DOE OSTI2022

Bulk density, grain size, carbon content and isotopes, and nitrogen content of floodplain sediment along the Koyukuk River, Alaska collected in Summer 2018.

The dataset is comprised of grain size, bulk density, carbon and nitrogen content, stable carbon isotopes, and radiocarbon content of soils sampled on the floodplain of the Koyukuk River near Huslia, AK. This dataset was collected to characterize sediment properties and floodplain organic carbon stocks in the discontinuous permafrost floodplain of the Koyukuk River. The data help quantify the flux and storage of sediment and carbon between the Koyukuk River and the surrounding floodplain as the river migrates laterally. The samples were collected in June 27 - July 9, 2018. The soil samples come from a total of 24 locations and were sampled in the upper 490 cm of the river cutbanks, point bars, and floodplain. Samples were analyzed for bulk density, full particle size distribution, nitrogen content and carbon content and isotopes, though not all samples were included in each analysis. An additional 10 samples of floodplain woody debris were measured for radiocarbon content. Data, detailed methods, analyses, and interpretations were previously published at: Douglas, M. M., Lingappa, U. F., Lamb, M. P., Rowland, J. C., West, A. J., Li, G., et al. (2021). Impact of river channel lateral migration on microbial communities across a discontinuous permafrost floodplain. Applied and Environmental Microbiology, 87(20), AEM.01339-21. https://doi.org/10.1128/AEM.01339-21 Douglas, M. M., Li, G. K., Fischer, W. W., Rowland, J. C., Kemeny, P. C., West, A. J., et al. (2022). Organic carbon burial by river meandering partially offsets bank erosion carbon fluxes in a discontinuous permafrost floodplain. Earth Surface Dynamics, 10(3), 421–435. https://doi.org/10.5194/esurf-10-421-2022 The dataset is comprised of a total of three separate data files based on the sample type and analysis, including a file that lists the sample locations, permafrost presence, and geomorphic landform.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Deep reinforcement learning assisted co-optimization of Volt-VAR grid service in distribution networks

With the increasing penetration of distributed energy resources in distribution networks, Volt-VAR control and optimization (VVC/VVO) have become very important to ensure an acceptable quality of service to all customers. System operators can rely on slow-responding utility devices, including capacitor banks and on-load tap changing transformers, along with fast-responding battery and photovoltaic (PV) inverters for the VVC/VVO implementation. Because of variations in response time of these two classes of devices, and different control actions (discrete versus continuous), coordinated and optimal scheduling and operation have become of utmost importance. Here, this paper develops a look-ahead deep reinforcement learning (DRL)-based multi-objective VVO technique to improve the voltage profile of active distribution networks, decrease network and inverter power loss, and save the operational cost of the grid. It proposes a deep deterministic policy gradient (DDPG)-based approach to schedule the optimal reactive and/or active power set-points of fast-responding inverters, and a deep Q-network (DQN)-based DRL agent to schedule the discrete decisions variables of slow-responding assets. The reactive power output of PV and battery smart inverters are scheduled at 30-minute intervals and the capacitors’ commitment status is scheduled with several hour intervals. The proposed framework is validated on the modified IEEE 34-bus and 123-bus test cases with embedded PV and PV-plus-storage. To validate the efficacy of the proposed VVO, it is compared with several scenarios, including the base case without VVO, localized droop control of DERs, DDPG-only, and twin delayed DDPG (TD3) agent-based DRL techniques. The results justify the superior performance of the proposed method to improve the voltage profile, reduce network power loss, and minimize the look-ahead grid operational cost while minimizing the undesirable power losses in inverters as a result of power factor adjustments.

24 POWER TRANSMISSION AND DISTRIBUTION↗