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At least 145 records · Page 8

Valued peaks: Sustainable water allocation for small hydropower plants in an era of explicit ecological needs

Optimizing hydropower operations to balance economic profitability and support functioning ecosystem services is integral to river management policy. In this article, we propose a dynamic, constrained optimization framework for small hydropower plants (SHPs) to evaluate trade-offs between economic profitability and socio-ecological requirements. Specifically, we examine the balance between short-term losses in hydropower generation and the potential for compensatory benefits in the form of revenue from recreational ecosystem services, irrespective of the direct beneficiary. Our framework integrates a fish habitat model, a hydropower optimization model, and a recreational ecosystem service estimate to evaluate different environmental flow scenarios. The optimization process gives three outflow release scenarios, informed by previous streamflow realisations (dam inflow), and designed environmental flow constraints. The framework is applied and tested for the river Kuusinkijoki in North-eastern Finland, which is a habitat for migratory brown trout and grayling populations. We show that the revenue loss due to the environmental flow constraints arises through a reduction in revenue per generated energy unit and through a reduction in turbine efficiency. Additionally, the simulation results reveal that all the designed environmental flow constraints cannot be met simultaneously. Under the environmental flow scenario with both minimum flow and flow ramping rate constraints, the annual hydropower revenue decreases by 16.5 %. An annual increase of 8 % in recreational fishing visits offsets the revenue loss. In conclusion, the developed framework provides knowledge of the costs and benefits of hydropower environmental flow constraints and guides the prioritizing process of environmental measures.

13 HYDRO ENERGY↗

Duluth Transit Authority Battery-Electric Bus Evaluation

Duluth Transit Authority (DTA) collaborated with the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) to evaluate a fleet of seven battery-electric buses (BEBs) in revenue service in Duluth, Minnesota. The focus of the evaluation was to compare performance and cost of the BEBs to that of conventional technology buses in similar service and track progress over time. DTA enlisted the help of the Center for Transportation and the Environment (CTE) to manage the project and provide technical services with the BEB fleet and infrastructure. This report summarizes the results of the BEB evaluation and contains a combination of analyses performed by NREL and by CTE during the overall data collection period of December 2018 through February 2022.

33 ADVANCED PROPULSION SYSTEMS↗

Development of an Energy Services Interface for the EGoT

The Energy Services Interface (ESI) is a set of rules that ensure private, secure, and trustworthy information exchange between Grid Service Providers (GSPs) and utility customers. Large-scale adoption of Distributed Energy Resources (DERs) will be necessary for GSPs to dispatch effective grid services, and to stimulate technological innovations in DER and DERMS (DER Management Systems) technologies, as well as novel grid service programs. The ESI promotes these objectives by advancing a set of rules and interoperability requirements that define bi-directional, service-oriented, logical interfaces between GSPs and customers’ DERs, with expectations for privacy, security, and trust. The ESI rules and interoperability requirements establish boundaries between customers and GSPs that delineate the functions and responsibilities that must be implemented by the developers of Energy Grid of Things (EGoT) ecosystem products. These rules impose constraints on the implementation of a DERMS. The ESI interoperability requirements are based on the Interoperability Maturity Model (IMM), developed by the Grid Modernization Laboratory Consortium. By emphasizing private, secure, and trustworthy information exchange, and by mandating a service-oriented and interoperable architecture, the ESI promotes the development of an EGoT ecosystem that motivates customer participation and technological innovation. Interoperability will encourage innovation by reducing barriers to entry and increasing confidence of stakeholders. Customers will be willing to participate in DER service programs that establish trust and emphasize customer choice. Large-scale customer participation ensures GSPs have ample DER resources to provide grid services that have significant impact on grid reliability and reduce electricity cost for consumers. This in turn signals economic opportunities that encourage innovation, resulting in the development of a robust EGoT ecosystem.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Driving Next-Generation Workflows from the Data Plane

We observe the emergence of a new generation of scientific workflows that process data produced at a sustained rate by scientific instruments and large scale numerical simulations. This data is consumed by multiple analysis, visualization, or Machine Learning components not only to enable inference and justify the scientific program, but also to monitor and steer the evolution of these experiments. In such workflows, moving intermediate data efficiently is key to performance, more than efficiently scheduling computational tasks. However, most traditional workflow management systems focus on optimizing task scheduling and then deal with data management, assuming a “move little, compute for long” model, which makes them unfit to the efficient management of this new generation of workflows. Therefore, we advocate for a new way to manage scientific workflows. We propose to consider an efficiently and independently managed data plane that can store and stream data. Workflows compute components, in the application plane can then interact with the data plane, abstracted from complexities of data management. Then, the role of a workflow management system would become that of a control plane that allows users to connect services together to execute the workflow and manages connections between the application and data planes. In this position paper, we characterize several next-generation workflow motifs and describe how their interaction with the data plane is a challenge to traditional workflow management systems. Then, we express a set of requirements that a workflow management system should meet to efficiently manage next-generation workflows at different scales. Based on these requirements, we expose our vision of driving next-generation workflows from the data plane and list remaining open challenges.

Suter, Fred↗

Converting from NIS to Redhat Identity Management

The Jefferson Lab (Jlab) accelerator controls network has transitioned to a new authentication and network service interface. The new system uses the Redhat Identity Manager (IdM) as a single integrating front end to the Lightweight Directory Access Protocol (LDAP) and a replacement for NIS and the Kerberos authentication service. This system allows for integration of access and authentication across Unix and Windows environments and across different Jlab computing environments, including across firewalls. The decision making process, conversion steps, issues and solutions will be discussed.

McGuckin, T. S.↗

Greenhouse gas mitigation strategies and opportunities for agriculture

To cope with increasing demands for food, feed, and energy along with environmental challenges due to climate change, the agricultural sector has a unique opportunity to meet sustainable development goals set by the United Nations through innovative and regenerative agriculture practices that enhance agricultural productivity, ecosystem services, and human well-being simultaneously. Among many sustainability metrics to measure agriculture's impacts on sustainability and contribution to its improvements, we focus on the greenhouse gas (GHG) emissions from the agricultural sector as a key environmental indicator to assess several GHG mitigation practices from the perspective of life-cycle analysis applied to agriculture. In this work, we first analyze the key factors contributing to farming GHG emissions and then identify a range of GHG mitigation strategies, such as optimizing farm fertilizer/chemical inputs, manufacturing low-carbon fertilizer/chemical, reducing on-farm energy/fuel consumption, and increasing soil carbon stocks. Furthermore, we elaborate on how these strategies can be successfully implemented to different scales of farming through policies and incentives and better quantification and verification schemes for effective policies and incentives. Finally, we present the holistic evaluation of agricultural GHG emissions in terms of landscape management approaches and provide ecosystem services to address social and economic issues.

54 ENVIRONMENTAL SCIENCES↗

Intensification differentially affects the delivery of multiple ecosystem services in subtropical and temperate grasslands

Intensification, the process of intensifying land management to enhance agricultural goods, results in “intensive” pastures that are planted with productive grasses and fertilized. These intensive pastures provide essential ecosystem services, including forage production for livestock. Understanding the synergies and tradeoffs of pasture intensification on the delivery of services across climatic regions is crucial to shape policies and incentives for better management of natural resources. Here, we investigated how grassland intensification affects key components of provisioning (forage productivity and quality), supporting (plant diversity) and regulating services (CO 2 and CH 4 fluxes) by comparing these services between intensive versus extensive pastures in subtropical and temperate pastures in the USDA Long-term Agroecosystem Research (LTAR) Network sites in Florida and Oklahoma, USA over multiple years. Our results suggest that grassland intensification led to a decrease in measured supporting and regulating services, but increased forage productivity in temperate pastures and forage digestibility in subtropical pastures. Intensification decreased the net CO 2 sink of subtropical pastures while it did not affect the sink capacity of temperate pastures; and it also increased environmental CH 4 emissions from subtropical pastures and reduced CH 4 uptake in temperate pastures. Intensification enhanced the global warming potential associated with C fluxes of pastures in both ecoregions. Our study demonstrates that comparisons of agroecosystems in contrasting ecoregions can reveal important drivers of ecosystem services and general or region-specific opportunities and solutions to maintaining agricultural production and reducing environmental footprints. Further LTAR network-scale comparisons of multiple ecosystem services across croplands and grazinglands intensively vs extensively managed are warranted to inform the sustainable intensification of agriculture within US and beyond. Our results highlight that achieving both food security and environmental stewardship will involve the conservation of less intensively managed pastures while adopting sustainable strategies in intensively managed pastures.

60 APPLIED LIFE SCIENCES↗

A Distributed Trust Model Simulator for Energy Grid of Things Distributed Energy Resource Management System

The evolution of networks into more distributed, self-reliant nodes has mitigated single-point failures that plagued traditional centralized networks. Applied to power grids, distributed systems can increase the integrity and availability of grid services while also offering a power management solution. However, while distributed networks provide scalability, security, and sustainability compared to centralized networks, their distributed nature makes them harder for anomaly detection and prevention. Incorporating a Distributed Trust Model (DTM) System into an Energy Grid of Things Distributed Energy Resource Management System (EGOT DERMS) allows grid participants to be characterized and their communication to be analyzed for possible attacks. A Trust Model simulator is needed to evaluate and improve the DTM System.Trustworthiness is calculated using a Trust Model. While many trust models exist, most only consider 2-3 matrices to evaluate trust. The TM proposed in this thesis uses a Metric Vector of Trust (MVoT) monitoring 17 parameters when assessing trust. Moreover, unlike standard trust models, the proposed trust model establishes a method to test the trust between various actors within the network and probe the trust model itself. Using a Trust Model Simulator, MVoT calaculations, initial values, and parameters are fine-tuned to achieve high-confidence message classifications and minimize false positives. The DTM System and Trust Mode Simulation Suite allow for distributed trust evaluation with a real-time classification of EGOT DERMS actors, providing additional security for distributed systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

AQDrop Quantum Service (AQDrop) v1.0

AQDrop is a job management system designed to streamline access to the Advanced Quantum Testbed (AQT) at NERSC (National Energy Research Scientific Computing Center). It serves as a centralized middleware layer between researchers and quantum processing hardware. Key Features: AQDrop provides a FastAPI-based server backed by PostgreSQL for job submission, queue management, and role-based access control (members, operators, and administrators). Users submit Qiskit circuits via JSON payloads, which are queued, dispatched to the QPU through the Qubic API, and returned as measurement counts. A Python client library and web dashboard round out the interface options. Primary Use: Researchers submit quantum circuit jobs from a laptop or login node; an operator client executes those jobs on the AQT's physical QPU and returns results — all coordinated through the central API. Advantages: Compared to ad-hoc or direct hardware access, AQDrop adds structured queue management, auditable job-status tracking and OAuth2 authentication — reducing scheduling conflicts and unauthorized access. Its containerized deployment also improves reproducibility and scalability. Overall, AQDrop functions as a purpose-built quantum job broker tailored to NERSC's specific hardware and institutional access requirements.

Caplinger, Evan [Lawrence Berkeley National Labora↗

Distribution System Congestion Management - A Survey of Reliable Integration for Aggregated Resources and Microgrids

Rising penetration of consumer-owned Distribution Grid Resources (DGRs), increasingly managed by third party aggregators and enrolled in grid services and wholesale market programs, can create localized congestion in distribution networks. Managing these constraints is challenging due to a persistent coordination and information gap: utilities are accountable for reliability and have network topology and state visibility, while aggregators control the DGR capability needed to relieve congestion. This survey synthesizes congestion management solutions for distribution systems with high DGR penetration, covering both market-based mechanisms (distribution level markets, locational pricing, flexibility auctions) and non-market-based solutions (network reconfiguration, direct DGR control, demand response, curtailment, etc.). The literature is organized across three decision horizons: long term planning, operational planning, and real-time operation. Special attention is devoted to emerging distribution system operator architectures and coordination frameworks spanning transmission system operators, aggregators, and microgrids. Drawing on recent case studies and implementations, we distill best practices, identify key technical and economic barriers, and outline research directions. The evidence points to a shift toward integrated congestion management that combines market signals with technical controls, enabled by improved monitoring, forecasting, and closed loop control capabilities.

Active Distribution Networks (ADN)↗

Data-Driven Linear Parameter-Varying Modeling and Control of Flexible Loads for Grid Services

Flexible loads have great potential to improve the electric grid's flexibility and stability. To effectively control large ensembles of heterogeneous loads, reliable models thereof are required. This paper presents a data-driven modeling and control approach to manage flexible loads for providing grid services. We leverage a linear parameter-varying autoregressive moving average (LPV-ARMA) model to describe the aggregate load response, where the parameters in the model are used to capture external environmental impacts (e.g., weather). A gain-scheduling feedback controller is then developed to adapt to environmental variations. This data-driven approach can be easily applied to different types of loads in various environmental conditions. In addition to the ensemble controller, distributed load controllers are designed to deliver grid services, while maintaining the quality of service of inherent load tasks. We demonstrate the work on the IEEE 37-node distribution system for real-time power regulation services through control of thermostatically controlled loads.

61 RADIATION PROTECTION AND DOSIMETRY↗

Defining a Use Case for the ADMS Test Bed: Fault Location, Isolation, and Service Restoration with Distributed Energy Resources: Preprint

Advanced distribution management systems (ADMS) integrate multiple enterprise-level functions into a single platform and offer advanced applications such as fault location, isolation, and service restoration (FLISR), to utilities to meet their operational needs for a modernized grid. These applications need to operate reliably even as distributed energy resource (DER) penetration increases on distribution systems. The ADMS test bed at the National Renewable Energy Laboratory offers utilities and vendors the opportunity to evaluate the performance of such advanced applications on distribution feeders of the future and to understand their potential benefits for a specific utility. This is done through defining use cases that address specific questions. This paper presents the definition of a use case on the performance of a commercially-available FLISR application on a feeder of an electric cooperative with DERs. Results from this use case will be disseminated to the electric utility and research community to improve understanding of the challenges and benefits that DERs present to ADMS applications and the operation of a modernized grid.

61 RADIATION PROTECTION AND DOSIMETRY↗

Compliance of NNSS Activities with P322-4 Issues Management and NNSSWAC Requirements

The Institutional Quality and Performance Assurance Division's Quality Support Services Group conducted a surveillance of the compliance of Waste Management Program activities to Issues Management/Corrective Action requirements communicated in P322-4 and the Nevada National Security Site Waste Acceptance criteria (NNSSWAC). All corrective actions reviewed and records examined were found to be compliant with appropriate and relevant procedures. There were no Findings or Opportunities for Improvement noted.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Data-Driven Linear Parameter-Varying Modeling and Control of Flexible Loads for Grid Services: Preprint

Flexible loads have great potential to improve the power grid's flexibility and stability. To effectively control large ensembles of heterogeneous loads, reliable models thereof are required. The paper presents a data-driven modeling and control approach to manage flexible loads for providing grid services. We leverage a linear parameter-varying autoregressive moving average (LPV-ARMA) model to describe the aggregate load response, where the parameters in the model are used to capture external environment impacts (e.g., weather). A gain-scheduling feedback controller is then developed to adapt to environmental variations. This data-driven approach can be easily applied to different types of loads in various environmental conditions. In addition to the ensemble controller, distributed load controllers are designed to deliver grid services, while maintaining the quality of service of inherent load tasks. We demonstrate the work on the IEEE 37-node distribution system for real-time power regulation services through control of thermostatically controlled loads.

control↗

Congestion Management Solutions for Enhanced Distribution System Operations with Aggregated Distribution Grid Resources Providing Grid Services and Market Participation

Microgrids and other aggregations of distribution grid resources (DGRs) are poised to actively participate in electricity markets and provide essential grid services in the coming years. In fact, DGRs already play such a role through behind-the-meter (BTM) demand response programs and small-scale BTM dispatchable generation initiatives. At the same time, the rapid growth of artificial intelligence (AI) and cryptocurrency datacenters imposes significant, often unpredictable, demands on the power distribution system. Aggregated DGRs can serve as flexible resources that help mitigate these pressures by using available transmission and distribution capacity more efficiently, supporting resource adequacy and other reliability services, and providing bridge strategies while long-term transmission infrastructure is being developed. The impacts this activity will have on distribution networks are not fully understood and could present significant challenges for distribution utilities due to capacity constraints and the need for congestion management. Technical issues include reverse power flow, variability and possible degradation of equipment integrity, voltage violations, and customer power quality concerns. These issues will likely intensify as electricity market operators across the United States implement Federal Energy Regulatory Commission Order 2222 over the next few years.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Smart Energy Storage Integration and Management Platform for Buildings (SESIMP-B)

This project involved the design, development, and testing of a commercial smart service panel. It includes an innovative AI-driven control method to manage smart functions of the panel and a technical-economic feasibility assessment for enhancing building energy resilience and grid-edge technology integration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Multi-service battery energy storage system optimization and control

Battery energy storage systems (BESS) have become fundamental part of modern power systems due to their capability to provide multiple grid services. As the renewable penetration increases, BESS procurement is also expected to increase where it is envisioned to play a systematic and strategical role in power systems planning and operation. Hence, in this paper we present a multiple grid service procurement and operation for BESS - ranging from energy arbitrage, reserve/regulation services, power factor correction, and demand management. The proposed framework considers an optimal multi-temporal dimension, designed to be operable for both planning and real-time operation. Moreover, non-linearity inherent to BESS services and uncertainty associated to market forecasts variables are addressed using techniques such as polyhedral norms and robust optimization approaches. Here, the developed model is tested using a utility-scaled BESS and the obtained results show the effectiveness of the systematic BESS multi-service planning and operation approach.

25 ENERGY STORAGE↗

Next generation experimental data access at NSLS-II

The NSLS-II network and computing infrastructure has been significantly updated recently. The re-IP process in 2020-2021 enabled the NSLS-II network to be routable to the rest of the BNL campus. Then, standardization of the operating systems and deployment procedures helped to deliver a consistent environment to workstations and servers used by all NSLS-II beamlines. In particular, the RedHat Enterprise Linux 8 was deployed to 700+ machines using the RedHat Satellite infrastructure management product, and all critical services (IOCs, databases, etc.) were migrated to the new OS. NFS users’ home directories are consistent across all of the machines, which eliminates the need for the individual configuration of the user environment on each host. The standard suite of software packages is available to the beamline staff and users, which includes the system packages (deployed via RPM) as well as the conda environments for data acquisition and analysis. Security measures were implemented to comply with the industry standards, which include multi-factor authentication (using Duo), secure screen lock for the beamline machines, and advanced access control to the experimental data that is stored in shared central storage available on all hosts. These major enhancements facilitated sharing the experimental data (currently for a number of selected beamlines, with a plan to extend it to the whole facility in the nearest future) with the users via an externally facing JupyterHub instance. The beamlines keep using the Bluesky data acquisition framework to orchestrate their experiments, and the new infrastructure enabled them to use a next-generation data access library called tiled.

36 MATERIALS SCIENCE↗