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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Cost Recovery for Standby and Ancillary Services for Distributed Generation: Considerations for New Mexico

A New Mexico statute allows investor-owned utilities to recover costs of “standby and ancillary services” resulting from distributed generation (DG). In attempting to do so, it is important to recognize both the physical and economic impacts, positive and negative, that distributed generation creates. Distributed generation has different impacts on ancillary and standby services depending on the location, capacity, and production patterns of the systems. Low penetrations of small distributed generation systems will not create significant contingencies for utilities. System impact of fluctuations in DG production may be no larger than normal fluctuations caused by customer demand, such as an air conditioner cycling. Higher penetrations and large DG system may produce noticeable impacts; so magnitude is critical when determining potential additional recoverable utility costs. Understanding DG impact on ancillary services is a relatively new and emerging area of study and as such there are not well-established formulas or protocols. Discretion is required. A hosting capacity analysis can help determine how much DG can be implemented before the impacts become substantive. Standby rates are traditionally used for large industrial generators or combined heat and power systems and threshold system size levels are often used in determining applicability of standby rates. System size thresholds may also be appropriate for standby rates and DG. Relatively small, geographically diverse DG systems are unlikely to create a noticeable coincident outage, so developing a standby charge based on assumed coincidence may not be appropriate. Individual lines and feeders may have considerable excess capacity during coincident outages, or they may be fully utilized and facing upgrades in the near future, which could vary over time. Understanding specific events that create concern for utilities is critical to developing an appropriate rate mechanism (e.g., single residential or community system outage, cascading event, clouds, eclipse). Any modeling or studies of the grid should also recognize the unique situation created when DG is coupled with a smart inverter or storage. These devices change the value proposition and can help mitigate some of the voltage and ramping issues DG can pose for a utility. Utilities can recover their fixed costs in a variety of ways, and some are better suited for DG than others. Beyond charging for standby and ancillary services, other options include fixed customer charges, demand charges, minimum bills, time-of-use rates and updated net energy-metering policies. Studies and analyses of the specific impacts that DG has on the grid should inform utilities’ decision-making process because distributed generation creates both costs and benefits for the grid. Any charge specific to DG customers should be backed up with analysis. At the heart of this conversation is utilities attempting to recover fixed costs. Allowing utilities to indiscriminately recover all stranded fixed costs can negatively affect long-term market efficiency by blunting utility incentives to lower costs and acting as a barrier to entry and exit. The current status of New Mexico’s grid, impending infrastructure updates, and likely customer adoption patterns for DG (backed up by transparent analysis) should remain at the forefront when considering charges for standby and ancillary services. Recognizing that utility regulation is largely a reactive process, it is recommended that applications for DG related standby or ancillary services cost recovery mechanisms be thoroughly reviewed by an experienced economist. If the commission has no such skill set on staff, one might be hired.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Time Dependence of Methane Generation Rates from Saltstone

This report documents the tests performed to address the requirements listed in the Technical Request, which resulted in a Task Technical & Quality Assurance Plan (TTQAP) and a Run Plan to obtain the required information. The research expands previous scoping work to better understand methane generation in the Saltstone Disposal Facility (SDF). That scoping work demonstrated that methane is produced when sulfide-containing material is added to methylmercury (MeHg), which is found in the SDF Tank 50 feed waste. When Tank 50 waste is combined with grout premix solids dry feed ingredients of cement, slag cement, and fly ash, sulfides are released from the slag cement component of the premix. The prior testing results showed that while the concentration of total mercury was not affected in the pH 14 waste, the MeHg likely reacted with the sulfide contained in the slag. The scoping tests were performed in sealed reactors and thus, methane generation was not measured continuously; rather, it was measured after one hour and after 24 hours. After 24 hours, a large percentage of the MeHg was converted to methane, but after 1 hour only a small percentage of methane was released. It is noteworthy that the methane generation rate (MGR) was greater at the one-hour measurement. The data compiled from the scoping work needed to be expanded to better understand the generation of methane released from grout mixed with Tank 50 waste. This expanded study developed a more extensive knowledge of how and when methane is generated to inform the Documented Safety Analysis (DSA) of the SDF. As such, employing 8 sealed reactors, the methane generation time periods were extended to 2, 4, 6, 18, 30, 48, 72, and 96 hours (4 days). Results are documented herein to determine the capacity for MeHg, contained within Tank 50 salt solution (T50SS) simulant, to produce methane when mixed with saltstone dry feed ingredients, i.e., individual components (cement, slag, and fly ash) or a combination of those components.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Wind Turbine Generator Reliability Analysis to Reduce Operations and Maintenance (O&M) Costs

Wind turbine major systems (blades, pitch, main bearing, gearbox, and generator) are integrated into a composite system. Specifications for these systems and components are developed to achieve symmetry of operation, avoiding negative interaction. For instance, the main bearing, gearbox, and generator (drivetrain) components are interdependent, functioning in unison for efficient energy production. Hence, wind resource and grid interactions affecting the drivetrain impact the performance and reliability of the turbine generator. This paper discusses generator reliability covering the technology evolution over the last 20 years. EPRI's Wind Network for Enhanced Reliability (WinNER) web-based tool and Shermco Industries databases are presented, and conclusions are drawn regarding failures specific to generator design, manufacturing, and operating conditions. Additionally, this paper compares the life expectancy of stator-fed configurations and doubly fed generator systems.

17 WIND ENERGY↗
DOE OSTI2024

Generating Electricity with Hydraulically Amplified Self-Healing Electrostatic (HASEL) Transducers

This study identifies hydraulically amplified self-healing electrostatic (HASEL) transducers as electricity generators, contrary to their conventional role as actuators. HASELs are soft, variable-capacitance transducers inspired by biological muscles which were developed to mimic the flexibility and functionality of natural muscle tissues. This research characterizes HASELs as generators by reversing their energy conversion mechanism—generating electricity through mechanical deformation. The study assesses the practical laboratory performance of HASELs by analytic modeling and experimental evaluation. Outcomes of the study include the following: (i) up to 2.5 mJ per cycle per 50 mm wide HASEL pouch of positive net energy generation in experimental testing—corresponding to an energy density of 2.0 mJ cm−3; (ii) a maximum theoretical energy density of 4.2 mJ cm−3; (iii) the electromechanical characteristics governing efficient conversion; and (iv) design considerations to enhance HASEL generator performance in future applications. This study broadens HASEL’s applicability and utility as a multi-functional transducer for renewable energy and general adaptive electricity generation.

13 HYDRO ENERGY↗
DOE OSTI2026

Applying Particle Swarm Optimization and Extended Kalman Filtering to Model Kaplan Generation Dynamics for Hydropower Systems

Variable renewable generation is increasing the need for hydropower plants to provide fast and flexible grid support, which places new demands on plant-level dynamic models used for monitoring, control, and operational decision-making. This need is especially important for hydroelectric systems, where turbine and generator dynamics are strongly coupled, nonlinear, and time-varying, making accurate real-time representation difficult. To address this problem, this paper develops a digital twin (DT) framework for a synchronous generator–Kaplan turbine system using an explicit separation of slow turbine dynamics and fast generator dynamics. The turbine subsystem is represented by a six-coefficient model, whose parameters are identified offline using particle swarm optimization, while the generator subsystem is updated online through an extended Kalman filter for real-time state and parameter estimation. These models are integrated within a closed-loop simulation that includes a proportional–integral–derivative–double-derivative governor and excitation system, allowing the DT to track plant behavior under realistic operating conditions. Unlike prior studies that treat turbine and generator modeling separately or rely mainly on simulated inputs, the proposed framework is validated using real operational data from a hydropower plant. Results show that the DT reproduces terminal voltage, active power, and reactive power with a normalized root mean square error of approximately 5%. This hybrid offline–online formulation constitutes the main contribution of the work, providing an adaptive and practically deployable DT for hydropower systems with direct relevance to control improvement, performance monitoring, and grid-support applications under high renewable penetration.

13 HYDRO ENERGY↗
DOE OSTI2018

Projected Growth in Small-Scale, Fossil-Fueled Distributed Generation: Potential Implications for the U.S. Greenhouse Gas Inventory

The generation capacity of small-scale (less than one megawatt) fossil-fueled electricity in the United States is anticipated to grow by threefold to twenty-fold from 2015 to 2040. However, in adherence with internationally agreed upon carbon accounting methods, the Environmental Protection Agency's (EPA's) U.S. Greenhouse Inventory (GHGI) does not currently attribute greenhouse gases (GHGs) from these small-scale distributed generation sources to the electric power sector and instead accounts for these emissions in the sector that uses the distributed generation (e.g., the commercial sector). In addition, no other federal electric-sector GHG emission data product produced by the EPA or the U.S. Energy Information Administration (EIA) can attribute these emissions to electricity. We reviewed the technical documentation for eight federal electric-sector GHG emission data products, interviewed the data product owners, collected their GHG emission estimates, and analyzed projections for growth in fossil-fueled distributed generation. We show that, by 2040, these small-scale generators could account for at least about 1%- 5% of total CO2 emissions from the U.S. electric power sector. If these emissions fall outside the electric power sector, the United States may not be able to completely and accurately track changes in electricity-related CO2 emissions, which could impact how the country sets GHG reduction targets and allocates mitigation resources. Because small-scale, fossil-fueled distributed generation is expected to grow in other countries as well, the results of this work also have implications for global carbon accounting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Providing Ancillary Services with Photovoltaic Generation in Multi-Timescale Grid Operation: Preprint

With photovoltaic (PV) generation substantially increases, electric power systems need more flexible resources that can provide ancillary services to mitigate the variability and uncertainty of the PV generation. On the one hand, the increase of PV generation necessitates the needs of more flexible resources. On the other hand, PV generation, because of its low operation cost, has been replacing the conventional generation in the system which is the main flexible resources in the current system. Consequently, there is a trend to require the renewable generation including PV to provide flexible ancillary services to further accommodate more PV integration. This paper proposes a multi-timescale grid operation model considering the various control strategies of PV providing different ancillary services. Numerical case studies demonstrate that with PV providing both regulation reserve and primary frequency reserve, the system operating costs and PV curtailment will be reduced significantly. It shows that not only the system reliability but also PV's profitability can be improved with PV providing more ancillary services.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2022

System Resilience Benefits of Dual-Fuel Capable Generators

The growing dependency on natural gas (NG) for power generation raises challenges for ensuring the resilience of power systems during extreme cold weather. Dual-fuel capable generators that can switch from burning NG to distillate fuel oil during an NG shortage over one way to alleviate these challenges. In this study, the impacts of gas unavailability on the IEEE 73-bus reliability test system (RTS) with 2019 updated generation mixture are explored. An extension to the standard production cost model formulation of unit commitment and economic dispatch is proposed to allow the representation of dual-fuel capable generators that can switch fuels between NG and distillate oil with a specified oil tank capacity and tank refueling capability. The operation of the system under gas unavailability with 0%, 25%, 50%, 75%, and 100% of combined cycle and combustion turbine generators as dual-fuel capable with a one-day supply of fuel oil are simulated using PLEXOS, a production cost model. The dual-fuel generator performance, unserved energy, and system costs are fully assessed.

dual-fuel capable generator↗
DOE OSTI2016

Thermal Flux Maximization from a DD Neutron Generator

The University of Sharjah recently acquired a model DD-109.4M neutron generator from Adelphi Technology. The generator is moderated and has three neutron ports which are capable of providing fast and thermal neutrons. The neutron ports are plugged with polyethylene layers of different thickness in order to control the neutron flux at different regions in the port. Neutron Activation Analysis (NAA) is an important analysis technique to determine the amounts of isotopes in a sample at different concentrations. For many isotopes the ability to precisely determine their concentrations is enhanced by utilizing thermal neutrons in the activation process; where the capture cross section is greatest. It is thus important to subject the sample to the maximum thermal flux in order to minimize the time required to activate the sample and consequently extend the lifetime of the neutron generator. A detailed MCNP model of the neutron generator has been developed for the purpose of determining the moderator thickness required to maximize the thermal neutron flux in the neutron port. The maximization of the neutron flux must therefore take into account both the forward and backscattered neutrons reaching the sample. Also provided in this work is a mapping of the thermal flux at different moderator thicknesses in order to study the variation of the flux over the area of the sample. The developed model will be used as the basis for optimizing experiments and predicting their results. A study was performed to determine the moderator thickness needed to maximize the thermal neutron flux that can be obtained from a DD neutron generator. This has a significant role in the efficient utilization of the neutron generator. The maximum thermal neutron flux was found at approximately a 3.2 cm moderator thickness. The thermal neutron flux is resulting from both the directly moderated neutrons and the backscattered neutrons from the surrounding polyethylene. The results obtained in this work will be verified experimentally by irradiating samples at different moderator thickness and performing a neutron activation analysis for these samples. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

The Economic and Societal Impact of Baseload Power Generation on Local Communities

In the United States (US), energy from coal, natural gas, and nuclear power plants produced approximately 3,500 TWh of electricity and accounted for 85% of total net generation in 2015. In 2015, coal and natural gas power plants each contributed about 33% of all generation in the US. generation II nuclear power plants represents about 20% of all electricity produced in the US and 62.4% of emission-free electricity in 2015. As a byproduct of electricity, combustion fossil fuel plants release hazardous emissions such as CO{sub 2}, N{sub 2}O, NOx and SO{sub 2}. CO{sub 2}, CH{sub 4}, and N{sub 2}O. Many of these emissions are major greenhouse gases (GHG) that have been linked to contributing to global climate change. The release of NOx and SO{sub 2} have a negative impact on human health and contribute to smog and acid rain. As a result, communities are often subjected to negative externalities such as pollution, noise, undesirable visuals, and safety concerns when sited near power plants. Though nuclear power plants do not produce any air emissions, there are concerns of nuclear waste, radiation leaks into the environment, and Fukushima-level accidents. With electricity generation, there are economic, safety, and environmental tradeoffs between the three technologies. These factors can contribute to negative and positive externalities for communities that are sited near baseload power plants. Davis (2010) using the hedonic price method found that communities living within 2 miles of power plants experience a 3-7% decrease in housing values. There is further evidence that those that live even closer experience larger decreases. While several studies focus on hedonic price methods and health effects, none have investigated and compared the socioeconomic indicators of communities near baseload power plants. The goal of this work is to investigate and examine relationship between societal and economic community indicators with respect to distance and generation technology. From a cost benefit standpoint an argument can be made based on the externalities from these power plants. Positive externalities that improve median incomes and home values could mean added tax revenue for local municipalities and governments. Typically, comparisons between generating technologies are made using the levelized cost of electricity (LCOE) and life cycle GHG emissions, however the impacts on local communities can also be used as a metric when comparing technologies. (authors)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Dose Mapping from a DD Neutron Generator at the University of Sharjah

The University of Sharjah recently acquired a model DD109.4M neutron generator from Adelphi Technology. The generator is moderated and has three neutron ports which are capable of providing fast and thermal neutrons. This neutron generator is intended to be used for various studies like neutron activation analysis, neutron imaging, and profiling and irradiation effects. It is imperative that appropriate measures are taken in order to minimize the radiation dose to the operators, students, and the public. The resulting dose must not exceed the limits set by the UAE Federal Authority for Nuclear Regulations (FANR) and the International Atomic Energy Agency (IAEA). The objective of this study is to generate a neutron and photon dose map of the generator room and its surrounding using simulations, experimentally verify this dose mapping, and set the operating and safety procedures for the neutron generator. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Distributed Automatic Generation Control Considering DPV Using T&D Dynamic Co-Simulation

The increasing adoption of distributed energy resources (DERs) over the last decade warrants a reconsideration of control of generation resources. This paper proposes a distributed Automatic Generation Control (AGC) using transmission-and-distribution (T&D) dynamic co-simulation framework for the efficient DPV frequency regulation services. The co-simulation framework allows AGC units to exchange the information for distributed AGC, based on their adopted communication network topology. As a result, a cost-effective automatic generation control is achieved with DPV and conventional generators. The proposed distributed AGC is based on the gossip algorithm in which the neighboring AGC units share the relevant local information with each other and updates their share of AGC regulation signal. Distributed photovoltaics (DPV) unit contribute to AGC response based on their headroom capacity via DER aggregators. The algorithm is tested on IEEE-14 bus transmission system under conditions of generation failure and random load variation to observe effective frequency regulations service offered by DPVs and other AGC units. The study shows that DPV can effectively participate in AGC with the proposed distributed control framework.

automatic generation control↗
DOE OSTI2025

Synthetic Scientific Image Generation with VAE, GAN, and Diffusion Model Architectures

Generative AI (genAI) has emerged as a powerful tool for synthesizing diverse and complex image data, offering new possibilities for scientific imaging applications. This review presents a comprehensive comparative analysis of leading generative architectures, ranging from Variational Autoencoders (VAEs) to Generative Adversarial Networks (GANs) on through to Diffusion Models, in the context of scientific image synthesis. We examine each model's foundational principles, recent architectural advancements, and practical trade-offs. Our evaluation, conducted on domain-specific datasets including microCT scans of rocks and composite fibers, as well as high-resolution images of plant roots, integrates both quantitative metrics (SSIM, LPIPS, FID, CLIPScore) and expert-driven qualitative assessments. Results show that GANs, particularly StyleGAN, produce images with high perceptual quality and structural coherence. Diffusion-based models for inpainting and image variation, such as DALL-E 2, delivered high realism and semantic alignment but generally struggled in balancing visual fidelity with scientific accuracy. Importantly, our findings reveal limitations of standard quantitative metrics in capturing scientific relevance, underscoring the need for domain-expert validation. We conclude by discussing key challenges such as model interpretability, computational cost, and verification protocols, and discuss future directions where generative AI can drive innovation in data augmentation, simulation, and hypothesis generation in scientific research.

Generative Adversarial Networks↗
DOE OSTI2026

Generative Models for Crystalline Materials

Understanding structure-property relationships in materials is fundamental in condensed matter physics and materials science. Over the past few years, machine learning (ML) has emerged as a powerful tool for advancing this understanding and accelerating materials discovery. Early ML approaches primarily focused on constructing and screening large material spaces to identify promising candidates for various applications. More recently, research efforts have increasingly shifted toward generating crystal structures using end-to-end generative models. This review analyzes the current state of generative modeling for crystal structure prediction and de novo generation. It examines crystal representations, outlines the generative models used to design crystal structures, and evaluates their respective strengths and limitations. Furthermore, the review highlights experimental considerations for evaluating generated structures and provides recommendations for suitable existing software tools. Emerging topics, such as modeling disorder and defects, integration in advanced characterization, incorporating synthetic feasibility constraints, and model explainability are explored. Ultimately, this work aims to inform both experimental scientists looking to adapt suitable ML models to their specific circumstances and ML specialists seeking to understand the unique challenges related to inverse materials design and discovery.

Metni, Houssam [Karlsruhe Inst. of Technology (KIT↗
DOE OSTI2015

Statistical scaling of geometric characteristics in stochastically generated pore microstructures

In this study, we analyze the statistical scaling of structural attributes of virtual porous microstructures that are stochastically generated by thresholding Gaussian random fields. Characterization of the extent at which randomly generated pore spaces can be considered as representative of a particular rock sample depends on the metrics employed to compare the virtual sample against its physical counterpart. Typically, comparisons against features and/patterns of geometric observables, e.g., porosity and specific surface area, flow-related macroscopic parameters, e.g., permeability, or autocorrelation functions are used to assess the representativeness of a virtual sample, and thereby the quality of the generation method. Here, we rely on manifestations of statistical scaling of geometric observables which were recently observed in real millimeter scale rock samples [13] as additional relevant metrics by which to characterize a virtual sample. We explore the statistical scaling of two geometric observables, namely porosity (Φ) and specific surface area (SSA), of porous microstructures generated using the method of Smolarkiewicz and Winter [42] and Hyman and Winter [22]. Our results suggest that the method can produce virtual pore space samples displaying the symptoms of statistical scaling observed in real rock samples. Order q sample structure functions (statistical moments of absolute increments) of Φ and SSA scale as a power of the separation distance (lag) over a range of lags, and extended self-similarity (linear relationship between log structure functions of successive orders) appears to be an intrinsic property of the generated media. The width of the range of lags where power-law scaling is observed and the Hurst coefficient associated with the variables we consider can be controlled by the generation parameters of the method.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Effects of the Spin Heat Accumulation on the Heat Generation in a Quantum Dot Coupled to Leads

Heat generation by a spin-polarized current in a single-level quantum dot (QD) subjected to spin heat accumulation (SHA), which denotes the spin-dependent electron temperature, is studied by using the nonequilibrium Green’s function technique. The heat generation originates from the energy exchange between the conduction electrons and the phonon reservoir coupled to the QD. Due to the SHA, the spin-up and spin-down heat generations are opposite in sign, and each has a maximum when the QD level is aligned to the chemical potentials of the leads, where the electric current is zero. Under a magnetic field, the maxima of the spin-up and spin-down heat generations are shifted to different dot level regimes. Now total negative heat generation emerges, indicating that the electron absorbs heat from the phonon reservoir to the dot. By tuning the dot levels and the system temperature, the magnitude of the negative heat generation can be enhanced accompanied by weakened electric current, an ideal condition for the realization of nanorefrigerator.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Factorization of generalized γ-generating matrices

The class of γ-generating matrices and its subclasses of regular and singular γ-generating matrices were introduced by D. Z. Arov in [8], where it was shown that every γ-generating matrix admits an essentially unique regular–singular factorization. The class of generalized γ-generating matrices was introduced in [14, 20]. In the present paper, subclasses of singular and regular generalized –generating matrices are introduced and studied. As the main result, a theorem of existence of the regular–singular factorization for a rational generalized γ-generating matrix is proved.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Metabolites of 2,3-diketogulonate delay peroxidase action and induce non-enzymic H 2 O 2 generation: Potential roles in the plant cell wall

A proportion of the plant's l-ascorbate (vitamin C) occurs in the apoplast, where it and its metabolites may act as pro-oxidants and anti-oxidants. One ascorbate metabolite is 2,3-diketogulonate (DKG), preparations of which can non-enzymically generate H 2 O 2 and delay peroxidase action on aromatic substrates. As DKG itself generates several by-products, we characterised these and their ability to generate H 2 O 2 and delay peroxidase action. DKG preparations rapidly produced a by-product, compound ( 1 ), with λ max 271 and 251 nm at neutral and acidic pH respectively. On HPLC, ( 1 ) co-eluted with the major H 2 O 2 -generating and peroxidase-delaying principle. Compound ( 1 ) was slowly destroyed by ascorbate oxidase, and was less stable at pH 6 than at pH 1. Electrophoresis of an HPLC-enriched preparation of ( 1 ) suggested a strongly acidic (p K a ≈ 2.3) compound. Mass spectrometry suggested that un-ionised ( 1 ) has the formula C 6 H 6 O 5 , i.e. it is a reduction product of DKG (C 6 H 8 O 7 ). In conclusion, compound ( 1 ) is the major H 2 O 2 -generating, peroxidase-delaying principle formed non-enzymically from DKG in the pathway ascorbate → dehydroascorbic acid → DKG → ( 1 ). We hypothesise that ( 1 ) generates apoplastic H 2 O 2 (and consequently hydroxyl radicals) and delays cell-wall crosslinking - both these effects favouring wall loosening, and possibly playing a role in pathogen defence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗