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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Corrosion testing needs and considerations for additively manufactured materials in nuclear reactors

Additive manufacturing (AM) technologies have developed rapidly in recent years, creating new opportunities and challenges for the nuclear industry; however, adoption requires that their corrosion performance be evaluated. Here, we discuss known reactor-specific corrosion issues for multiple reactor types and engineering concerns such as regulations and standards. A review of corrosion studies conducted on select AM alloys informs a discussion on key bulk and surface factors likely to impact corrosion behaviors. Recommendations to assess corrosion performance for AM materials are provided, including management of the unique nature of as-built AM surfaces and the inherent process variability that occurs for AM components.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Electrical Load Forecasting Over Multihop Smart Metering Networks With Federated Learning

Electric load forecasting is essential for power management and stability in smart grids. This is mainly achieved via advanced metering infrastructure, where smart meters (SMs) record household energy data. Traditional machine learning (ML) methods are often employed for load forecasting, but require data sharing, which raises data privacy concerns. Federated learning (FL) can address this issue by running distributed ML models at local SMs without data exchange. However, current FL-based approaches struggle to achieve efficient load forecasting due to imbalanced data distribution across heterogeneous SMs. Here, this article presents a novel personalized FL (PFL) method for high-quality load forecasting in metering networks. A meta-learning-based strategy is developed to address data heterogeneity at local SMs in the collaborative training of local load forecasting models. Moreover, to minimize the load forecasting delays in our PFL model, we study a new latency optimization problem based on optimal resource allocation at SMs. A theoretical convergence analysis is also conducted to provide insights into FL design for federated load forecasting. Extensive simulations from real-world datasets show that our method outperforms existing approaches regarding better load forecasting and reduced operational latency costs.

Rahman, Ratun [Univ. of Alabama, Huntsville, AL (U↗
DOE OSTI2023

Standard experimental paradigm designs and data exclusion practices in cognitive psychology can inadvertently introduce systematic “shadow” biases in participant samples

Abstract Standard cognitive psychology research practices can introduce inadvertent sampling biases that reduce the reliability and generalizability of the findings. Researchers commonly acknowledge and understand that any given study sample is not perfectly generalizable, especially when implementing typical experimental constraints (e.g., limiting recruitment to specific age ranges or to individuals with normal color vision). However, less obvious systematic sampling constraints, referred to here as “shadow” biases, can be unintentionally introduced and can easily go unnoticed. For example, many standard cognitive psychology study designs involve lengthy and tedious experiments with simple, repetitive stimuli. Such testing environments may 1) be aversive to some would-be participants (e.g., those high in certain neurodivergent symptoms) who may self-select not to enroll in such studies, or 2) contribute to participant attrition, both of which reduce the sample’s representativeness. Likewise, standard performance-based data exclusion efforts (e.g., minimum accuracy or response time) or attention checks can systematically remove data from participants from subsets of the population (e.g., those low in conscientiousness). This commentary focuses on the theoretical and practical issues behind these non-obvious and often unacknowledged “shadow” biases, offers a simple illustration with real data as a proof of concept of how applying attention checks can systematically skew latent/hidden variables in the included population, and then discusses the broader implications with suggestions for how to manage and reduce, or at a minimum acknowledge, the problem.

Siritzky, Emma M.↗
DOE OSTI2024

LAW Glass Formulation to Support Melter Runs with Simulants

The major objective of this work was to prepare and characterize glass formulations in order to develop and select formulations that are compliant with contractual and processing requirements to support melter tests with each of the LAW Sub-Envelopes. Glasses that cover composition ranges of interest were prepared and characterized to ensure that selected glass compositions can tolerate expected composition variations resulting from process errors without adversely affecting processing characteristics or product quality. Glass compositions that are expected to result during transitions from one waste stream to another were also prepared and characterized. Other objectives of the work included preparation and characterization of glasses with respect to the properties of interest, optimization of sulfate loading in the glasses, evaluation of ability to achieve waste loading limits, testing to demonstrate compatibility of glass melts with melter materials of construction, and identification of glass formulation issues with respect to contract specifications and processing requirements.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

EMP - Environmental Radiological Air Monitoring Plan: PNNL Operations in Washington

The Environmental Radiological Air Monitoring Plan (EMP) for Pacific Northwest National Laboratory (PNNL) describes systems/processes/practices related to radiological operations in Richland and Sequim, Washington, that are associated with environmental radiological air monitoring and surveillance activities. The activities described support the lab’s responsibility to maintain safe operations and minimize negative impacts to both onsite and offsite persons and environment. Dose assessments required by regulations and DOE Orders for the public and biota are described. PNNL conducts environmental air surveillance monitoring as part of the PNNL Site Radioactive Air Emissions License (RAEL)-005 for Richland Campus, issued in 2010 with its most recent renewal effective in January 2021. The radioactive air emissions license for the PNNL-Sequim campus (RAEL-014) was issued to the U.S. Department of Energy in 2012 with its most recent renewal effective in January 2023. The EMP is a compilation of the following four documents: - Environmental Radiological Air Monitoring Plan (this main document) (PNNL-20919) - Sampling and Analysis Plan (Attachment 1) (PNNL-20919-1) - Data Management Plan (Attachment 2) (PNNL-20919-2) - Dose Assessment Guidance (Attachment 3) (PNNL-20919-3).

40 CFR 61 Subpart H↗
DOE OSTI2024

ExaWorks software development kit: a robust and scalable collection of interoperable workflows technologies

Scientific discovery increasingly requires executing heterogeneous scientific workflows on high-performance computing (HPC) platforms. Heterogeneous workflows contain different types of tasks (e.g., simulation, analysis, and learning) that need to be mapped, scheduled, and launched on different computing. That requires a software stack that enables users to code their workflows and automate resource management and workflow execution. Currently, there are many workflow technologies with diverse levels of robustness and capabilities, and users face difficult choices of software that can effectively and efficiently support their use cases on HPC machines, especially when considering the latest exascale platforms. We contributed to addressing this issue by developing the ExaWorks Software Development Kit (SDK). The SDK is a curated collection of workflow technologies engineered following current best practices and specifically designed to work on HPC platforms. We present our experience with (1) curating those technologies, (2) integrating them to provide users with new capabilities, (3) developing a continuous integration platform to test the SDK on DOE HPC platforms, (4) designing a dashboard to publish the results of those tests, and (5) devising an innovative documentation platform to help users to use those technologies. Our experience details the requirements and the best practices needed to curate workflow technologies, and it also serves as a blueprint for the capabilities and services that DOE will have to offer to support a variety of scientific heterogeneous workflows on the newly available exascale HPC platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Smart Planning for Radioactive Source Transport Advanced Tools for Increased Safety and Efficiency

End-of-life (EOL) management of high-activity radioactive sources is made uniquely challenging by the inherent risks associated with storage and transportation of these sources, the complex logistics involved, and the strict requirements for regulatory compliance. Traditional methods lack comprehensive tools for accurate site assessments and precision planning for the transportation of radioactive sources. They also frequently fail to provide the adaptability required to consider diverse operational environments, resulting in inefficiencies and potential safety concerns. This paper introduces a novel software solution developed to address these issues by integrating advanced technologies such as light detection and ranging (LiDAR)-based 3D environment modeling, smart dynamic route planning, and customizable measurement functionalities. This software enables detailed terrain visualizations, facilitating thorough environmental assessments and enabling users to virtually navigate, analyze, and plan site-specific operations. Among the key features are a user-centric interface for virtual navigation, precise site measurement tools for site evaluations, interactive visualizations that highlight potential operational hazards, dynamic route planning capabilities, and real-time collision detection to promote safe workflows. By demonstrating the effectiveness of this tool through real-world application, the present work underscores the tool’s potential to revolutionize radioactive source EOL management by improving operational efficiencies, minimizing risk, and advancing the state of practice to achieve suitable and secure radioactive material handling.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Experiences with Mobile Units for Liquid RAW Management in Slovak and Czech Nuclear Power Plants - 20089

In Nuclear Power Plants VVER 440, Russian type of reactor there was designed auxiliary building where according to basic design all operational liquid radioactive waste (RAW) should be stored in large capacity tanks during the whole operational period. That's why there are in the auxiliary building several types of large storage tanks with different internal volume from 110 m{sup 3}, 460 m{sup 3} to 550 m{sup 3}. Storage tanks are usually situated in rooms with limited access and minimal handling space. Operational waste was here transported by the system of pipes from the reactor building. There is possibility to handle with the waste and set the pipeline in to the chosen storage tanks. Nobody takes care about the quality of waste in the storage tanks and waste waits for the period of decommissioning when it should be treated. The storage capacity was designed for the whole lifetime of nuclear power plant. Currently the life time of Nuclear Power Plant's (NPP) is extended and there is necessity to retrieve and treat the RAW in advance. Another reason why the stakeholder, who operates the NPPs, decides to treat the operational RAW during the operational period of NPP, is that there are still new requirements from safety point of view which need to have free available space for example because of potential accident. So treating the operational RAW during the life time of NPP is present issue. Because in basic design nobody cares how the RAW will be retrieved and treated in the future, there is usually no technology for that in existing NPP. Some of the NPPs build an additional building with suitable technologies for treatment or hire the company which offer mobile technology for retrieving the waste from the storage tanks. Wood Nuclear Slovakia PLC provides all activities within liquid RAW management projects by its own staff including management, design, construction and deployment of equipment, engineering support, as well as all RAW retrieval and solidification activities. We offer RAW management as a service without any significant changes in existing NPP's buildings and technology. It is always a technical challenge to conduct successful retrieval, pumping and treatment of RAW. The complex RAW retrieval system can be designed as tailored solution for any RAW storage according to known boundary conditions and specific needs. These systems are based on years of experience with RAW manipulation, processing and treatment and the whole RAW management knowledge by Wood Nuclear Slovakia LTD. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Application of Cable Condition Monitoring Technologies to Assess Age-Related Degradation of Industrial Cables Installed in Harsh Environments

The aging of electrical cables has been the subject of substantial research and development (R&D) projects performed by national and international laboratories, universities, and private organizations for many years. This R&D was conducted to develop guidance, equipment, and techniques to support aging management of in-service cables in industrial facilities such as nuclear power plants, research reactors, waste facilities, and fuel fabrication plants. Through these research efforts, condition monitoring technologies have been developed that can determine the severity of age-related degradation that occurs in industrial cables and insulation polymers during service. This paper summarizes the results of aging assessments that were performed for cables installed in two U.S. nuclear power plants, one a pressurized water reactor and one a boiling water reactor. These cables had been in service for over 40 years and during plant operation were exposed to harsh environmental conditions including elevated temperatures and radiation. For these assessments, a comprehensive series of measurements was performed to assess the aged condition of the cables. These cables came from different manufacturers, were manufactured in different years, and were constructed with a variety of jacket and insulation polymers including chloro-sulfonated polyethylene (CSPE), cross-linked polyethylene (XLPE)/cross-linked polyolefin (XLPO), neoprene, and ethylene propylene rubber (EPR). The goal of these assessments was to determine the current aged condition of the cable polymers and provide an estimate of how long the cable insulation materials could remain exposed to their in-service environmental conditions before reaching their end-of-life condition. Both nuclear power plants have received license renewals to extend their operation from 40 to 60 years, and the utilities need objective evidence to show that critical components such as cables will be able to function safely and reliably during the extended operating period. Furthermore, the results of these assessments showed that the cables exhibited different aged conditions depending on the type of polymers they were constructed with and the environment they were exposed to during service. Some of the cables and insulation polymers showed signs of significant age-related degradation and were estimated to have approximately 5 years of remaining service life. Other cables exhibited no signs of significant age-related degradation and were estimated to have 50 years or more of remaining service life. Using the results of these cable aging assessments, plant personnel were able to (1) determine the overall aged condition of cables and insulation polymers using objective test results, (2) identify aged or degraded cables before they caused operability issues, and (3) avoid unnecessary and costly replacement of cables that can continue to operate safely and reliably.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A neural-network-enhanced parameter-varying framework for multi-objective model predictive control applied to buildings

Management of the electrical grid is becoming more complex due to the increased penetration of alternative energy generation technologies and a broadening diversity of electric loads. This complexity creates challenges in balancing demand and generation that can increase the potential for grid instabilities. One effective way to address this issue is to leverage previously unexploited demand flexibility through advanced control strategies. In this work, we propose an advanced control method, called adaptive neural parameter-varying model predictive control (ANPV-MPC), to control the temperature and energy consumption of a building via its Heating, Ventilation, and Air Conditioning system. ANPV-MPC combines key ideas in parameter-varying control, adaptive control, and online learning strategies to bridge the gap between computationally efficient linear model predictive control and more accurate nonlinear model predictive control. The novelty in ANPV-MPC is the use of a physics-inspired Bayesian neural network to estimate the coefficients of the parameter-varying linear control model. The Bayesian neural network additionally provides uncertainty estimates, triggering online training to capture evolving building system conditions. We show that ANPV-MPC can approximate the building system dynamics with a 28.39% higher accuracy than traditional linear model predictive control, resulting in 36.23% better control performance without increasing complexity of the optimal control problem. ANPV-MPC also adapts in real time to previously unseen conditions using online learning, further improving its performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Cardinality-Regularized Hawkes-Granger Model

We propose a new sparse Granger-causal learning framework for temporal event data. We focus on a specific class of point processes called the Hawkes process. We begin by pointing out that most of the existing sparse causal learning algorithms for the Hawkes process suffer from a singularity in maximum likelihood estimation. As a result, their sparse solutions can appear only as numerical artifacts. In this paper, we propose a mathematically well-defined sparse causal learning framework based on a cardinality-regularized Hawkes process, which remedies the pathological issues of existing approaches. We leverage the proposed algorithm for the task of instance-wise causal event analysis, where sparsity plays a critical role. We validate the proposed framework with two real use-cases, one from the power grid and the other from the cloud data center management domain.

Ide, Tsuyoshi↗
DOE OSTI2020

Use of an Alternative Conceptual Model of Vadose Zone Heterogeneity to Evaluate Past Tank Leaks and Other Unplanned Releases within a Tank Farm at the Hanford Site - 20061

Washington State Department of Ecology (Ecology) requested that U.S. Department of Energy (DOE)-Office of River Protection (ORP) consider an evaluation of effects of fine-grained thin sediment layers on transport with a separate alternative conceptual model in its evaluation of the potential impact of tank leaks and other unplanned releases within the tank farm at the Hanford Site. For this alternative model, Ecology recommended that the model be developed based on the general framework of fine-grained units identified by a stakeholder group in their interpretations of variability in moisture content data collected in the vicinity of Waste Management Area (WMA) C. In discussions with DOE-ORP, Ecology acknowledged that the underlying data and interpretations of the occurrence and lateral continuity of the fine-grained thin layers identified by a stakeholder group are uncertain. However, DOE-ORP agreed to Ecology's recommendation and has provided support for the requested evaluation that involved development of an alternative model based on the general framework of the unpublished report by the stakeholder. DOE-ORP considered this evaluation to be a hypothetical evaluation of vadose zone heterogeneities at WMA C. General observations from the range of simulation cases examined in the evaluation of the effects of hypothetical vadose zone heterogeneities at WMA C are as follows. - The movement of the center of mass of the simulated plumes was generally vertically downward below the source for all simulations, including those that incorporated the hypothetical fine-grained units. - All simulations that incorporated hypothetical heterogeneity produced additional plume spreading over what was produced in simulations using Equivalent Homogeneous Media (EHM) model(s)a. The spreading resulted in a broadening of the fringes of the plume, resulting in a wider region of low concentration, but lower peak concentrations associated with the center of mass of the plume. - Simulations that used the silty-sand hydraulic properties, suggested by Ecology for the hypothetical fine-grained units, generally produced similar spreading and slightly lower peak mass flux at the water table when compared to the EHM modeling results. a The EHM-based models used at WMA C do not explicitly include small-scale fine-grained heterogeneities used in the model advocated by Ecology. - Simulations that used the silty-sand hydraulic properties, suggested by Ecology for the hypothetical fine-grained units, generally produced less spreading and an earlier arrival of mass flux at the water table when compared to the use of another set of hydraulic properties from a silty-sand sample collected at a nearby disposal facility. - The EHM representation of the vadose zone generally produced higher peak mass flux and an earlier occurrence of peak fluxes at the water table compared to all analyses incorporating additional hypothetical heterogeneity. Results of this alternative model evaluation of past leaks provided some insight into the transport effects of vadose zone heterogeneities at WMA C that helped resolve Ecology's comments and issues related to the effects of vadose zone heterogeneities on past leaks and losses from the WMA C tank farms area. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Albedo of crops as a nature-based climate solution to global warming

Abstract Surface albedo can affect the energy budget and subsequently cause localized warming or cooling of the climate. When we convert a substantial portion of lands to agriculture, land surface properties are consequently altered, including albedo. Through crop selection and management, one can increase crop albedo to obtain higher levels of localized cooling effects to mitigate global warming. Still, there is little understanding about how distinctive features of a cropping system may be responsible for elevated albedo and consequently for the cooling potential of cultivated lands. To address this pressing issue, we conducted seasonal measurements of surface reflectivity during five growing seasons on annual crops of corn-soybean–winter wheat ( Zea mays L.- Glycine max L. Merrill - Triticum aestivum L. ; CSW) rotations at three agronomic intensities, a monoculture of perennial switchgrass ( Panicum virgatum L. ), and perennial polycultures of early successional and restored prairie grasslands. 
We found that crop-species, agronomic intensity, seasonality, and plant phenology had significant effects on albedo. The mean±SD albedo was highest in perennial crops of switchgrass (0.179±0.04), intermediate in early successional crops (0.170±0.04), and lowest in a reduced input corn systems with cover crops (0.154±0.02). The strongest cooling potentials were found in soybean (-0.450 kg CO 2 e m -2 yr -1 ) and switchgrass (-0.367 kg CO 2 e m -2 yr -1 ), with up to -0.265 kg CO 2 e m -2 yr -1 of localized climate cooling annually provided by different agroecosystems. We also demonstrated how diverse ecosystems, leaf canopy, and agronomic practices can affect surface reflectivity and provide another potential nature-based solution for reducing global warming at localized scales.

Lei, Cheyenne (ORCID:0000000272746309)↗
DOE OSTI2021

Optimal Demand Response Incorporating Distribution LMP with PV Generation Uncertainty

The utilization of aggregated demand-side flexibility via demand response (DR) has become a promising pathway for the integration of renewable energy resources in power systems. Nowadays, there are several management strategies for DR such as the price-based transactive control strategies. However, many of such existing price-based control strategies neglect the physics and operational constraints of the underlying distribution networks when computing the price, raising concerns regarding their theoretical and practical values. This paper studies this issue and investigates optimal DR (ODR) by incorporating the distribution locational marginal price (DLMP). In particular, we discuss DR in connection with DLMPs and propose a multiperiod bilevel optimization problem to find the ODR strategy. Here, the objective is to minimize the peak load, load fluctuation, and payments of load aggregators. In addition, a robust bilevel ODR model is formulated to provide a robust ODR strategy while minimizing operating costs under the worst-case realization of uncertainties; this mitigates the impact of forecasting errors on renewable energy resources. Then, we propose an efficient solution approach by employing the Karush-Kuhn-Tucker conditions and strong duality. Simulation results are presented to illustrate the mutual impacts of the interaction between DR and DLMP and the benefits of the robust ODR strategy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Demystifying asynchronous I/O Interference in HPC applications

With increasing complexity of HPC workflows, data management services need to perform expensive I/O operations asynchronously in the background, aiming to overlap the I/O with the application runtime. However, this may cause interference due to competition for resources: CPU, memory/network bandwidth. The advent of multi-core architectures has exacerbated this problem, as many I/O operations are issued concurrently, thereby competing not only with the application but also among themselves. Furthermore, the interference patterns can dynamically change as a response to variations in application behavior and I/O subsystems (e.g. multiple users sharing a parallel file system). Without a thorough understanding, I/O operations may perform suboptimally, potentially even worse than in the blocking case. To fill this gap, here we investigate the causes and consequences of interference due to asynchronous I/O on HPC systems. Specifically, we focus on multi-core CPUs and memory bandwidth, isolating the interference due to each resource. Then, we perform an in-depth study to explain the interplay and contention in a variety of resource sharing scenarios such as varying priority and number of background I/O threads and different I/O strategies: sendfile, read/write, mmap/write underlining trade-offs. The insights from this study are important both to enable guided optimizations of existing background I/O, as well as to open new opportunities to design advanced asynchronous I/O strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

IDAES-PSE 2.6.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.6.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New Intersphinx extension automatically linking Jupyter notebook examples to project documentation New end-to-end diagnostics example demonstrated on a real problem New complementarity formulation for VLE with cubic equations of state, backward compatibility for old formulation New solver interface with presolve (ipopt_v2) in support of upcoming changes to the initialization and APIs methods, with default set to ipopt to maintain backwards compatibility; this will deprecate once all examples have been updated New forecaster and parameterized bidder methods within grid integration library Updated surrogates API and examples to support Keras 3, with backwards compatibility for older formats such as TensorFlow SavedModel (TFSM) Updated costing base dictionary to include the 2023 cost year index value Updated ProcessBlock to include information on the constructing block class Updated Flowsheet Visualizer to allow visualize() method to return value and functions Bug Fixes Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Fixed typos flagged by June update to crate-ci/typos and removed DMF-related exceptions Minor corrections of units of measurement handling in power plant waste/transport costing expressions, control volume material holdup expressions, and BTX property package parameters Fixed throwing >7500 numpy deprecation warnings by replacing scalar value assignment with element extraction and item iteration calls Testing and Robustness Migrated slow tests (>10s) to integration, impacting test coverage but also yielding a nearly 30% decrease in local test runtime Pinned pint to avoid issues with older supported Python versions Pinned codecov versions to avoid tokenless upload behavior with latest version Bumped extensions to version 3.4.2 to allow pointing to non-standard install location Deprecations and Removals Python 3.8 is no longer supported. The supported Python versions are 3.9 through 3.12 The Data Management Framework (DMF) is no longer supported. Importing idaes.core.dmf will cause a deprecation warning to be displayed until the next release The SOFC Keras surrogates have been removed. The current version of the SOFC surrogate model in the examples repository is a PySMO Kriging model.

AS↗
DOE OSTI2025

Thermomechanical Separation of Biogenic and Non-biogenic Carbon from Non-Recyclable MSW

The effective separation of biogenic and non-biogenic carbon from non-recyclable municipal solid waste (n-MSW) presents a significant challenge in the United States. Currently, there are no efficient methods available to address this issue, hindering the potential for maximizing waste utilization and reducing landfilling rates. This project aims to develop and implement a combine thermomechanical separation techniques to separate biogenic and non-biogenic carbon within n-MSW, ultimately facilitating greater resource recovery and enhancing the efficiency and environmental impact of waste management practices.

09 - BIOMASS FUELS↗
DOE OSTI2023

Energy management systems for forecasted demand error compensation using hybrid energy storage system in nanogrid

This paper proposes an energy management system (EMS) for nanogrids to balance the power supply and forecasted demand in consideration of forecasting errors arising from high instantaneous demand. The proposed EMS employs a power-balancing optimization process for forecasted demand and a reference power modulation strategy for forecasting errors. This power-balancing optimization utilizes nanogrid sources, such as photovoltaics, fuel cells, and batteries, to meet forecasted demand and a supercapacitor charging process to overcome issues with a low energy density. The proposed reference power modulation strategy is utilized to allocate power from a hybrid energy storage system consisting of a battery and supercapacitor in order to compensate for forecasting errors. In addition, this proposed strategy considers battery and supercapacitor constraints such as the power changing rate and total power limitations. Further, the power-balancing optimization process also operates at faster sampling rate than the reference power modulation process in order to improve the computational efficiency. The performance of the proposed EMS is evaluated using real data obtained from the Korea Electric Power Exchange.

25 ENERGY STORAGE↗