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DOE OSTI2022

Distribution Capacity Expansion Planning: Current Practice, Opportunities, and Decision Support

The distribution utility industry and its engineers are experiencing monumental shifts in consumer needs and expectations. Characterizing future native loads as compared to net load demand for long-term capacity planning is especially difficult, as consumers are increasingly adopting prosumer technologies. This paper is the culmination of 5 months of utility interviews coordinated by the National Renewable Energy Lab (NREL) and Kevala, Inc. (Kevala) to better understand distribution capacity planning challenges. The interviews covered all aspects of capacity planning including load and DER forecasting, criteria for assessing system constraints, solution types, and organizational and decision-making structures. Our intent is to provide insight into distribution capacity planning decision support needs for utilities and the increasing number of stakeholders involved, from state and regulatory agencies to community and solution providers with interest in increasing their understanding in the distribution capacity planning process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Distributed Wind Market Report: 2023 Edition

The annual Distributed Wind Market Report provides stakeholders with market statistics and analysis along with insights into market trends and characteristics for wind technologies used as distributed energy resources. This report presents the distributed wind market from 2003 through 2022. Installed capacity, deployment trends, customer types, incentives, policies, installed costs, performance, and the future outlook for the distributed wind market are the key topics included in the report.

17 WIND ENERGY↗

DOE OSTI2026

Scheduler Modeling of Distributed Energy Resources for Providing Ancillary Services

Distribution energy resources (DERs) have been integral components of modern power systems, and their capability to provide grid services has been widely studied. To promote the deployment of these resources in providing grid services in real-world utility operations, this paper proposes a day-ahead scheduler model for a distribution system connected DER plant. A certain amount of generation capacity of this DER plant is reserved for frequency services, and some ancillary services for the distribution system-including peak load reduction, voltage regulation, and power factor control-are integrated into the model. The model is tested on a real-world distribution system. From the simulation results, the energy and reserve schedule of the solar photovoltaic (PV) unit and battery energy storage system (BESS) can be determined, and voltage and power factor are well maintained. Additionally, in order to demonstrate the specific characteristics of the co-located and hybrid operation modes for the PV and BESS, these two modes are analyzed both theoretically and through real-time simulation. Simulation results show that most of PV's variability is transferred to the net power in the co-located mode, whereas it is transferred to the BESS in the hybrid mode. This proposed scheduler model and the comparison of co-located and hybrid modes can provide practical guidance for the applications of DER plant in the real-world utility.

14 SOLAR ENERGY↗

DOE OSTI2026

Strategies for Flood Resilience and Grid Investment Among Iowa's Electric Distribution Utilities

Flooding poses a growing threat to Iowa's electric distribution system, yet utilities face significant data and modeling challenges in planning effective resilience investments. This report provides a foundational assessment of how distribution utilities in Iowa, investor-owned, municipal, and cooperative, approach resilience planning, with a focus on flood risk. It combines hazard characterization, review of state and utility practices, and application of NLR's Energy Resilience Analysis for Distribution Systems (ERAD) and Capacity Expansion Decision Support for Distribution Networks (CADET) tools. Using FEMA floodplains, Iowa Flood Center depth grids, and utility infrastructure data, the analysis quantifies asset exposure, simulates outage risks, and evaluates resilience strategies such as pole hardening, undergrounding, and substation protection. Results indicate that while feeder-level upgrades provide incremental benefits, the most significant reductions in outage risk are achieved through targeted substation interventions. The report highlights key data gaps, such as limited elevation data and fragility functions, and underscores the need for probability-weighted investment frameworks to address both frequent and catastrophic flood events. These insights aim to support utilities, state agencies, and federal partners in prioritizing resilience investments that safeguard Iowa's electric grid against future flooding.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Network-Cognizant Time-Coupled Aggregate Flexibility of Distribution Systems Under Uncertainties

Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. To exploit this flexibility and to use the capacity potential of aggregate DERs, feasible substation power injection trajectories need to be efficiently characterized. This paper provides an ellipsoidal inner approximation of the set of feasible power injection trajectories at the substation such that for any point in the set, there exists a feasible disaggregation strategy of DERs for any load uncertainty realization. The problem is formulated as one of finding the robust maximum volume ellipsoid inside the flexibility region under uncertainty. Though the problem is NP-hard even in the deterministic case, this paper derives novel approximations of the resulting adaptive robust optimization problem based on optimal second-stage policies. The proposed approach yields less conservative flexibility characterization than existing flexibility region approximation formulations. The efficacy of the proposed method is demonstrated on a realistic distribution feeder.

aggregates↗

DOE OSTI2021

Multi-Area Distribution System State Estimation Using Decentralized Physics-Aware Neural Networks

The development of active distribution grids requires more accurate and lower computational cost state estimation. In this paper, the authors investigate a decentralized learning-based distribution system state estimation (DSSE) approach for large distribution grids. The proposed approach decomposes the feeder-level DSSE into subarea-level estimation problems that can be solved independently. The proposed method is decentralized pruned physics-aware neural network (D-P2N2). The physical grid topology is used to parsimoniously design the connections between different hidden layers of the D-P2N2. Monte Carlo simulations based on one-year of load consumption data collected from smart meters for a three-phase distribution system power flow are developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares and state-of-the-art learning-based DSSE approaches. Numerical results show that the D-P2N2 outperforms the state-of-the-art methods in terms of estimation accuracy and computational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

A Review of Distributed Secondary Control Architectures in Islanded-Inverter-Based Microgrids

The increasing energy demand, the shortage of energy resources, and the environmental challenges faced by conventional power-generation systems are some of the ongoing challenges faced by modern power systems. Therefore, many efforts have been made by the scientific community to develop comprehensive solutions to overcome these issues. For instance, current technological advances have allowed the integration of distributed generators into the power systems, promoting the use of microgrids to overcome these issues. However, the use of renewable distributed generators have introduced new challenges to the traditional control system schemes. To overcome these challenges, a hierarchical control approach has been proposed for distributed renewable sources. In other words, the control scheme have been divided into three hierarchical levels, primary, secondary, and tertiary, to overcome the new challenges present in modern power systems. Due to extensiveness of this topic, this overview is focused on secondary control systems, mainly for AC isolated microgrids. To improve the power quality of modern systems, several secondary control schemes have been proposed to overcome the well-known problem of frequency and voltage deviation. Some of these schemes have also introduced adequate active/reactive power sharing techniques to optimize the utilization of resources. Additionally, other secondary control schemes have also focused on reducing the communication load, to lower the network cost and adding robustness against communication problems. This article presents an insight of the different control techniques used to overcome power quality and communication problems. A comprehensive overview of distributed secondary control techniques for islanded microgrids is presented. In addition, the implementation of these techniques is explained in an orderly and sequential manner.

14 SOLAR ENERGY↗

DOE OSTI2023

CACTI: Best Estimate Aerosol Size Distribution by airborne measurements

These data were collected during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI; https://www.arm.gov/research/campaigns/amf2018cacti ) field campaign in the Sierras de Córdoba mountain range of north-central Argentina as part of ARM Aerial Facility (AAF) deployment. The ARM Aerial Facility Gulfstream-1 was operated from Las Higueras Airport (IATA: RCU, ICAO: SAOC), Río Cuarto, Córdoba, Argentina, for the Intensive Observation Period (IOP) from Nov. 1 through Dec. 15, 2018. The G-1 aircraft performed 22 research flights over the first ARM Mobile Facility (AMF1) location in the Sierras de Córdoba mountain range to measure atmospheric state and turbulence, cloud water content and droplet size distributions, aerosol precursor gases, aerosol chemical composition and size distributions. The current data set presents Best Estimate Aerosol Size Distribution: a merged aerosol size distribution composed of the data from 5 sensors; three aerosol spectrometers: Scanning Mobility Particle Sizer (SMPS), Ultra-High Sensitivity Aerosol Spectrometer (UHSAS), and Passive Cavity Aerosol Spectrometer (PCASP); and two cloud probes: Cloud Aerosol Spectrometer (CAS) and Fast Cloud Droplet Probe (FCDP). The SMPS data were interpolated to 1 second from “native” time resolution of about 64 second to match all other probes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers: Preprint

This paper develops a novel method to estimate the voltage magnitude on the primary side of distribution service transformers. The proposed method relies exclusively on smart meters, and therefore it is fully data-driven. This is an important feature because electric utilities have detailed models of only the primary network--that is, the network between the distribution substation and the primary side of service transformers that are installed closer to end-customer sites. The network that connects the secondary side of service transformers to end-customer sites, referred to as the secondary network, is simply represented by a lumped load. For each secondary network, the proposed method uses data acquired from only 2 smart meters: the closest and the farthest--in the sense of electrical distance--from the service transformer. As a reference to this feature, the proposed method is named SM2Vp. To our knowledge, this is the first time a method is shown to provide actionable information for real-time operation and control of power distribution grids using only two smart meters per secondary network. This is important because utilities have experienced barriers in managing and using large data sets for real-time operation and control. SM2Vp is primarily intended to provide pseudo-measurements for distribution system state estimation, but it can also be used directly for voltage control schemes. The performance of SM2Vp is demonstrated by numerical simulations carried out on three secondary network synthetic models and by using field data provided by a utility partner serving customers in southwestern California. A maximum relative error of approximately 3.9% or less is observed for the primary voltage magnitude estimates in all numerical experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Storage Futures Study - Distributed Solar and Storage Outlook: Methodology and Scenarios

This presentation discusses the fourth report in NREL’s Storage Futures Study (SFS) publications. The SFS is a multiyear research project that explores the role and impact of energy storage in the evolution and operation of the U.S. power sector. The SFS is designed to examine the potential impact of energy storage technology advancement on the deployment of utility-scale storage and the adoption of distributed storage, and the implications for future power system infrastructure investment and operations. This report describes the expanded capabilities of the Distributed Generation Market Demand (dGen) model to analyze the economics of distributed (behind-the-meter) PV paired with battery storage systems and presents projections of adoption for the contiguous United States out to 2050 under a range of scenarios. These scenarios use technology cost and performance assumptions consistent with the National Renewable Energy Laboratory’s 2020 Standard Scenarios paired with updated battery cost projections and existing policies. Additional scenarios evaluate sensitivities to the value of backup power and DER compensation mechanisms, collectively characterizing the future potential for behind-the-meter storage and identifying key drivers of adoption. Adoption projections of DER and battery storage at high spatial and temporal resolution, as presented in this report, can enable informed planning of technical infrastructure that can help planners capture the benefits and mitigate challenges to support the ongoing trend toward distributed electricity generation.

backup power↗

DOE OSTI2024

Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation: Preprint

Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.

distribution system operator↗

DOE OSTI2022

Investigating Particle Size‐Dependent Redox Kinetics and Charge Distribution in Disordered Rocksalt Cathodes

Abstract Understanding how various redox activities evolve and distribute in disordered rocksalt oxides (DRX) can advance insights into manipulating materials properties for achieving stable, high‐energy batteries. Herein, the authors present how the reaction kinetics and spatial distribution of redox activities are governed by the particle size of DRX materials. The size‐dependent electrochemical performance is attributed to the distinct cationic and anionic reaction kinetics at different sizes, which can be tailored to achieve optimal capacity and stability. Overall, the local charged domains in DRX particles display random heterogeneity caused by the isotropic delithiation pathways. Owing to the kinetic limitation, the micron‐sized particles exhibit a holistic “core‐shell” charge distribution, whereas sub‐micron particles show more uniform redox reactions throughout the particles and ensembles. Sub‐micron DRX particles exhibit increasing anionic redox activities yet inferior cycling stability. In summary, engineering particle size can effectively modulate how cationic and anionic redox activities evolve and distribute in DRX materials.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Surface and subsurface oceanographic features drive forage fish distributions and aggregations: Implications for prey availability to top predators in the US Northeast Shelf ecosystem

Abstract Forage fishes are a critical food web link in marine ecosystems, aggregating in a hierarchical patch structure over multiple spatial and temporal scales. Surface‐level forage fish aggregations (FFAs) represent a concentrated source of prey available to surface‐ and shallow‐foraging marine predators. Existing survey and analysis methods are often imperfect for studying forage fishes at scales appropriate to foraging predators, making it difficult to quantify predator–prey interactions. In many cases, general distributions of forage fish species are known; however, these may not represent surface‐level prey availability to predators. Likewise, we lack an understanding of the oceanographic drivers of spatial patterns of prey aggregation and availability or forage fish community patterns. Specifically, we applied Bayesian joint species distribution models to bottom trawl survey data to assess species‐ and community‐level forage fish distribution patterns across the US Northeast Continental Shelf (NES) ecosystem. Aerial digital surveys gathered data on surface FFAs at two project sites within the NES, which we used in a spatially explicit hierarchical Bayesian model to estimate the abundance and size of surface FFAs. We used these models to examine the oceanographic drivers of forage fish distributions and aggregations. Our results suggest that, in the NES, regions of high community species richness are spatially consistent with regions of high surface FFA abundance. Bathymetric depth drove both patterns, while subsurface features, such as mixed layer depth, primarily influenced aggregation behavior and surface features, such as sea surface temperature, sub‐mesoscale eddies, and fronts influenced forage fish diversity. In combination, these models help quantify the availability of forage fishes to marine predators and represent a novel application of spatial models to aerial digital survey data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Ruddlesden–Popper Perovskites with Narrow Phase Distribution for Air-Stable Solar Cells

2D Ruddlesden-Popper perovskites have risen to prominence as stable and efficient photovoltaic materials because of their structural diversity, rich photophysics, and low moisture ingression. However, thin films processed from stoichiometric precursor solutions possess a broad phase distribution of different number of inorganic layers with random crystal orientation, crippling device performance. The effect of methylammonium chloride (MACI) and 3-amino4-phenolsulfonic acid (APSA) on the fabrication of perpendicularly oriented (PEA) 2 MA 4 Pb 5 I 16 films with narrow phase distribution using antisolvent and hot-casting processing techniques is investigated. MACI plays a critical role in suppressing parasitic n ≤ 2 and 3D-like phases. APSA performs the dual function of trap passivation and further narrowing phase polydispersity through strong coordination with Pb 2+ . Ex situ grazing-incident wide-angle X-Ray scattering (GIWAXS) and ultrafast spectroscopic characterization reveal uniformly mixed-phase distribution with disordered orientation in antisolvent treated films, while additive-assisted hot-casting treatment results in oriented, reverse-graded phase distribution, i.e., small-n on the film surface and large-n at the bottom. Arising thin films enable efficient p-i-n solar cells with an efficiency of 14.34%, and a V oc of 1.20 V, retaining 96% initial efficiency after 1440 h under ambient conditions (RH = 50-60%) without encapsulation.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Generalized parton distributions through universal moment parameterization: non-zero skewness case

We present the first global analysis of generalized parton distributions (GPDs) combing lattice quantum chromodynamics (QCD) calculations and experiment measurements including global parton distribution functions (PDFs), form factors (FFs) and deeply virtual Compton scattering (DVCS) measurements. Following the previous work where we parameterize GPDs in terms of their moments, we extend the framework to allow for the global analysis at non-zero skewness. Together with the constraints at zero skewness, we fit GPDs to global DVCS measurements from both the recent JLab and the earlier Hadron-Electron Ring Accelerator (HERA) experiments with two active quark flavors and leading order QCD evolution. With certain choices of empirical constraints, both sea and valence quark distributions are extracted with the combined inputs, and we present the quark distributions in the proton correspondingly. We also discuss how to extend the framework to accommodate more off-forward constraints beyond the small ξ expansion, especially the lattice calculated GPDs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Metal concentration and leaf spatial distribution assessed by synchrotron µXRF in Brazilian nickel hyperaccumulators

Background and Aims: The limited number of known hyperaccumulator species in tropical regions, including Brazil, has hampered the development of nickel (Ni) agromining. In addition, the mechanisms underlying metal accumulation and distribution in these species remain poorly understood, despite their pivotal role in identifying species with economic potential. Furthermore, this study assessed the accumulation potential and foliar spatial distribution of metals in three Brazilian hyperaccumulator species (Pfaffia sarcophylla, Justicia lanstyakii, and Lippia lupulina) growing in one of the world’s largest mafic–ultramafic complexes. Methods Concentrations of Ni and other metals in leaves were determined using portable X-ray fluorescence (pXRF) and inductively coupled plasma optical emission spectroscopy (ICP-OES). Synchrotron-based X-ray microfluorescence (SR-µXRF) was employed to map the spatial distribution of metals across intact leaves. Results: The results revealed leaf Ni concentrations ranging from 320 to 1,950 mg kg⁻ 1 in P. sarcophylla, 1,640 to 6,810 mg kg⁻ 1 in L. lupulina, and 1,990 to 4,900 mg kg⁻ 1 in J. lanstyakii. Nickel, Mn, and Co exhibited similar distribution patterns, concentrating mainly in the leaf margins and veins across all species, while Ca, K, and Mg co-localization suggests regulatory mechanisms for adaptation. Conclusion: Although these plants exhibited Ni hyperaccumulation, our findings suggest limited commercial potential for agromining. Further research on genetic variability and nutrient assimilation, particularly in P. sarcophylla, is recommended to elucidate the mechanisms underlying Ni accumulation and intraspecific variability.

36 MATERIALS SCIENCE↗

DOE OSTI2023

The neutron number probability distribution in coupled lumped assemblies

Here, the validity of the gamma distribution in describing the neutron number probability distribution function for both isolated and coupled multiplying assemblies when constrained to reproduce the true mean and variance is investigated in lumped geometry by numerical comparison with kinetic Monte Carlo simulations. The mean and variance are obtained from numerical solution of moment equations constructed from the relevant forward Master equation with assembly coupling coefficients obtained from a view factor method. Numerical results for a two-group, two coupled assemblies model, with static and dynamic reactivity insertion, show that except for subcritical assemblies, the gamma distribution well-approximates the number distribution. Differences in the fast and thermal neutron population shapes are explained in terms of effective source strengths due to downscatter and coupling.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

On the role of joint probability distributions of incompatible observables in Bell and Kochen–Specker Theorems

Highlights: •Bell and Kochen–Specker theorems rule out local or noncontextual realist models. •Still, they assume a joint probability distribution for incompatible observables. •Those joint probability distributions do not exist in quantum mechanics. •Realist models without joint distributions for incompatible observables are given. •A reformulation of Bell and Kochen–Specker arguments is provided to rule them out. -- Abstract: We analyze the validity of Bell and Kochen–Specker theorems under local (or noncontextual) realism but avoiding an assumption of the existence of a joint probability distribution for incompatible observables. We formulate a realist model which complies with this requirement. This is obtained by employing divergent sequences that nevertheless have marginals which are convergent. We find that under standard reasonable assumptions this possibility does not lead to a loophole of those theorems, by deriving a short of CHSH inequality valid for any finite size ensemble. Moreover, we analyze a Hardy’s paradox setting where noncontextual realism imposes the existence of joint probabilities for incompatible observables.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗