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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A Review of Software for Designing and Operating Quantum Networks

Quantum networks development is crucial to realizing a production-grade network that can support distributed sensing, secure communication, and utility-scale quantum computation. However, the transition from laboratory demonstration to deployable networks requires software implementations of architectures and protocols tailored to the unique constraints of quantum systems. This paper reviews the current state of software implementations for quantum networks, organized around a three-plane abstraction of infrastructure, logical, and control/service planes. We cover software for both designing quantum network protocols (e.g., SeQUeNCe, QuISP, and NetSquid) and operating testbeds, with a focus on essential control/service plane functions such as entanglement, topology, and resource management, in a proposed taxonomy. Our review highlights a persistent gap between theoretical architecture and protocol proposals and their realization in simulators or testbeds, particularly in dynamic topology and network management. We conclude by outlining open challenges and proposing a roadmap for developing scalable software architectures to enable hybrid, large-scale quantum networks.

Network Design↗
DOE OSTI2020

Cyber‐physical system testbed for power system monitoring and wide‐area control verification

The electric power system is intrinsically a cyber‐physical system (CPS) with power flowing inthe physical system and information flowing in the cyber‐network. Testbeds arecrucial for understanding the cyber‐physical interactions and provideenvironments for prototyping novel applications. This study proposes afour‐layer architecture for CPS testbeds with emphases on communication networkemulation and networked physical components. A configurable software‐definednetwork is employed to bridge physical components with wide‐area applicationsfor closed‐loop control. In order to distribute physically coupled devices intomultiple software simulations, this study proposes a data broker setup based ona distributed messaging environment to achieve low‐latency data streaming. Thedecoupled design with data streaming allows for building testbed components asmodules and running them in a distributed manner. Case studies verify the databroker setup for low‐latency sensing and actuation, as well as the communicationemulation setup for the desired network latency. Also illustrated is a replayattack scenario using synchrophasors in the Western Electricity CoordinatingCouncil (WECC) 181‐bus system for demonstrating the closed‐loop cyber‐physicalsimulation capability of the testbed.

Cui, Hantao↗
DOE OSTI2021

DART-PFLOTRAN: An ensemble-based data assimilation system for estimating subsurface flow and transport model parameters

Ensemble-based Data Assimilation (EDA), based on the Monte Carlo approach, has been effectively applied to estimate model parameters through inverse modeling in subsurface flow and transport problems. However, implementation of EDA approach involves a complicated workflow that include setting up and executing ensemble forward model simulations, processing observations and model simulation results for parameter updates, and repeat for sequential or iterative EDA. To facilitate the management of such workflow and lower the barriers for adopting EDA-based parameter estimation in subsurface science, we develop a generic software frame-work linking the Data Assimilation Research Testbed (DART) with a massively parallel subsurface FLOw and TRANsport code PFLOTRAN. The new DART-PFLOTRAN leverages both the core data assimilation engines in DART and the computational power afforded by PFLOTRAN. In addition to the standard smoother and filtering options, DART-PFLOTRAN enables an iterative EDA workflow based on the Ensemble Smoother for Multiple Data Assimilation method (ES-MDA) to improve estimation accuracy for nonlinear forward problems. Here, we verify the implementation of ES-MDA in DART-PFLOTRAN using two synthetic cases designed to estimate static permeability and dynamic exchange fluxes across the riverbed, respectively, from continuous temperature measurements made across a depth profile. One-dimensional hydro-thermal simulations are performed in both cases to relate temperature responses with the parameters of interest. In the case of estimating dynamic parameters, we demonstrate the flexibility of DART-PFLOTRAN in automating sequential ES-MDA workflow, which will significantly reduce the time researchers spend on managing complex workflows in similar applications. Both studies yield accurate estimations of the parameters compared to their synthetic truth, while ES-MDA leads to more accurate estimation when a high level of nonlinearity exist between observed responses and unknown parameters. With a code base in Python and Fortran, DART-PFLOTRAN paves the way for applications in large-scale subsurface inverse modeling by automating the complex workflow of sequential ES-MDA that can be executed on various computing platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Hierarchical Model-Free Transactive Control of Building Loads to Support Grid Services

Residential buildings consume 4.4 quads of electricity annually, approximately 37% of the total electricity consumption in the United States. This represents a vast resource that can be used for demand management and other ancillary services. This project aims to develop a robust, scalable hierarchical transactional control mechanism incorporating elements of model-free control (MFC) and game theory to harness buildings to provide ancillary services to the grid. This approach is being taken to address the challenges of incorporating traditional transactional control schemes into existing buildings. The challenges include small individual building sizes requiring aggregation of many buildings, unpredictable energy usage that makes model identification difficult, and satisfying the sensitive occupant comfort constraints. In the proposed approach, by separating the control mechanism into two layers above and below the load aggregator, MFC can be used below the aggregator to modulate flexible building loads in response to pricing signals with guaranteed performance. This allows the burden of identifying an accurate model of the system to be shifted to the above-aggregator layer, where fluctuations in individual building usage have less impact on predicted building system behavior. Game theory concepts can then be used to determine pricing curves and control signals among regional aggregators. Managing this control in a game-theoretic approach will allow us to build in financial incentives that increase customer engagement. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable on small, embedded devices. In a broader sense, developing a strategy capable of effectively incorporating residential and small commercial buildings will allow greater throughput of existing and emerging grid services in addition to future transactive energy grid management methods. Using MFC within a hierarchical control architecture will allow the shifting of existing forecasting challenges to an aggregate level, where dynamics are slower and more predictable. This will enable a smooth interface between the grid services requests of utilities and the reliable control required by participating buildings. MFC, which supports distributed control architecture, permits a scalable solution that can be deployed to neighborhood-size systems as well as individual buildings. This project focuses on three objectives: (1) developing the mathematical framework, algorithm toolkit, and software toolset of the two-layer transactive control testbed; (2) developing a scalable solution for application over many residential and small-size commercial buildings with sparse distributed communication; and (3) field testing and implementation on hardware of the control strategies developed in the previous two objectives. The research and development activities are focused and designed to be impactful within the relevant 2025 targets timeframe. An open-source control framework for exploiting variability and dispatchability of building loads will be delivered as the outcome of the project. This capability enables greater participation of loads in electricity markets and ancillary services that are both useful for the utility and financially beneficial for building owners.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Intelligent Hierarchical Resilient Operation of Distribution Systems: Implementation and Validation in a Power Hardware-in-the-Loop Simulation Testbed

This paper reports on the structure of a power hardware-in-the-loop (PHIL) simulation testbed that implements, tests, and validates a novel AI-based hierarchical resilient operation model for distribution systems. The testbed implements the central and distributed controllers of the hierarchical resilient operation model and integrates a Digital Real-Time Simulator (DRTS), protective relays, a Real-Time Automation Controller (RTAC), a Software Defined Network (SDN) switch, and a battery energy storage (BES) system. The testbed provides comprehensive real-time visualization and monitoring capability as an advanced situational awareness and operator interface solution. The IEEE 33-node system is used as a test case to test and validate the operation of the model in normal operation and recovery operation after major outages in a fully automated fashion.

Ganjkhani, Mehdi↗
DOE OSTI2025

Guideline 36 Conformance Test v2.0

ASHRAE Guideline 36 provides guidance for how typical commercial building HVAC systems should be controlled to reduce energy costs and improve the indoor environmental quality for occupants. An industry-led effort is developing test scripts for how control manufacturers can test that the control logic in their control products follows Guideline 36. This software intends to support that effort in two ways. First, by providing a testbed for control manufacturers to run the test scripts against their own control products and compare their generated results to the expected results provided by the test scripts. Second, by providing a testbed that can be used during the development of test scripts to rapidly and repeatably verify they exercise Guideline 36 logic as desired and generate accurate expected results that control products can be compared to. An initial version of the software has already been developed and released open-source by a previous CEC-funded project that implemented the first use case (https://github.com/LBNL-ETA/guideline36_conformance_test/blob/master/LICENSE.txt), while this software disclosure will add the functionality of the second use case, as well as update the software where needed, all open-source. We intend to extend and contribute to the existing open-source software repository.

Blum, David [Lawrence Berkeley National Laboratory↗
DOE OSTI2022

PSUADE

PSUADE (Problem Solving testbed for Uncertainty Analysis and Design Exploration) is a mathematical software useful for performing uncertainty quantification and sensitivity analysis.

Tong, CharlesH↗
DOE OSTI2025

ACTIVE

The Automated Control Testbed for Integration, Verification, and Emulation (ACTIVE) framework is a software platform designed to support the optimized operation and management of a wide range of building types. It enables the development, testing, and validation of diverse control strategies, including AI-based, rule-based, and model-based approaches. The platform facilitates a seamless transition from simulation-based evaluation of control strategies to real-world field validation and deployment. ACTIVE supports the full building management lifecycle, encompassing data acquisition and management, system monitoring, optimized control, adaptive learning services, device dispatch and coordination, as well as advanced analytics and visualization. Together, these capabilities provide an integrated environment for improving building performance, operational efficiency, reducing energy cost, and reliability.

Smith, Robert [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2016

DERlab Report

With the rapidly changing landscape of grid codes and interconnection standards, manufacturers of DER components are under increasing pressure to reliably update and validate the interoperability and performance of their equipment for different regional requirements and grid conditions. To help vendors meet these standards, AIT and Sandia have teamed up and introduced an approach for the rapid, concurrent development of controls and application software through a controller hardware-in-the-loop (CHIL) testbed integrated with an automated testing platform.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Making Uintah Performance Portable for Department of Energy Exascale Testbeds

To help ease ports to forthcoming Department of Energy (DOE) exascale systems, testbeds have been made available to select users. These testbeds are helpful for preparing codes to run on the same hardware and similar software as in their respective exascale systems. This paper describes how the Uintah Computational Framework, an open-source asynchronous many-task (AMT) runtime system, has been modified to be performance portable across the DOE Crusher, DOE Polaris, and DOE Sunspot testbeds in preparation for portable simulations across the exascale DOE Frontier and DOE Aurora systems. The Crusher, Polaris, and Sunspot testbeds feature the AMD MI250X, NVIDIA A100, and Intel PVC GPUs, respectively. This performance portability has been made possible by extending Uintah’s intermediate portability layer [18] to additionally support the Kokkos::HIP, Kokkos::OpenMPTarget, and Kokkos::SYCL back-ends. This paper also describes notable updates to Uintah’s support for Kokkos, which were required to make this extension possible. Results are shown for a challenging radiative heat transfer calculation, central to the University of Utah’s predictive boiler simulations. These results demonstrate single-source portability across AMD-, NVIDIA-, and Intel-based GPUs using various Kokkos back-ends.

Holmen, John↗
DOE OSTI2019

EGS Collab Earth Modeling: Integrated 3D Model of the Testbed

The EGS Collab project is conducting a series of stimulation and interwell flow tests in an intermediate scale (~10-20 m) testbed located on the 4850 level in the Sanford Underground Research Facility (SURF) in Lead, South Dakota. The testbed consists of eight ~200 ft (~60 m) HQ-diameter (9.6 cm) boreholes that are drilled into the Poorman Formation from the western rib of the West Access Drift. Of the eight boreholes, one borehole is used as an injection/stimulation well, another sub-parallel borehole located about 10 m away from the injection well is used as a production well, and rest of the other boreholes are used as monitoring wells. For 3D visualization of the testbed as well as to provide spatially accurate and consistent parameter data for geomechanical and geophysical process modeling tasks, we are using Leapfrog Software (Seequent Limited). For analysis of fractures and creation of conditioned stochastic discrete fracture network (CS-DFN) model of the testbed, we are using FracMan (Golder Associates Inc.). As of mid-May 2019, the EGS Collab Leapfrog database contains the general layout of the drifts/shafts at the 4850 and 4100 levels; generalized geologic framework model of a domain that spans both the 4850 and 4100 levels; the CS-DFN of the testbed; and layouts of the EGS Collab testbed boreholes, kISMET testbed boreholes, and other existing boreholes at the 4850 level. This information has been obtained from the SURF Vulcan database, detailed laser scan and point surveys of borehole collar locations, directional surveys of borehole trajectories, and mapping of features in the drifts, boreholes, and cores. Similarly, other types of data that have been incorporated into the Leapfrog database include static features of the testbed such as natural discontinuities (e.g., fractures, weeps), location of monitoring instruments, and stimulation notches. Baseline geophysical characterization results (e.g., seismic, ERT, temperature, etc.) are also imported into the Leapfrog database. The location and size of packers, various point-source signals detected during stimulation and flow tests (e.g., temperature anomalies, micro-earthquake events, etc.) are also compiled in the database. All feature locations are reported using the local Homestake Mine coordinate system. In this paper, we present some of the geostructural characteristics as well as the status of the testbed as represented by Leapfrog/FracMan database/visualizations.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

A hardware-in-the-loop approach for laboratory performance verification of flexible building equipment in a typical commercial building

The overall objective of the project is to develop datasets that measure the holistic load flexibility performance of a suite of commonly-used commercial building HVAC and thermal storage equipment using a hardware-in-the-loop test method. The development of the software side of the hardware-in-the-loop flexible load testbed is summarized in this paper.

Chen, Zhelun↗
DOE OSTI2025

QUANT-NET Control Plane Framework (QNCP) v1.0.0

The QUANT-NET Control Plane (QNCP) provides a software framework for expressing and managing quantum network resources. It may be used to orchestrate a physical quantum testbed with real device driver implementations, or it may be used as a proving ground when developing new protocols and management functions. In practice, both approaches may be useful when undertaking research and development in emerging quantum testbeds. While a number of control systems have been developed for specific quantum platform demonstrations, an openly available and general solution for operating quantum networks has not emerged. QNCP is designed to fill this gap. The framework has been designed to provide extensible, modular capabilities that include scheduling, routing, monitoring, and pluggable protocols. A number of reference implementations in each module category have been included in the installable packages; however, the intent is that each of these modules may be extended or re-implemented to meet the needs of the particular deployment or research need. The software is currently being used in the QUANT-NET testbed project, which spans resources between LBNL and UC Berkeley Physics.

Zhang, Liang [Lawrence Berkeley National Laborator↗
DOE OSTI2014

FTP 100: An Ultra-High Speed Data Transfer Service Over Next Generation 100 Gigabit Per Second Network

Data-intensive applications, including high energy and nuclear physics, astrophysics, climate modeling, nano-scale materials science, genomics, and financing, are expected to generate exabytes of data over the coming years, which must be transferred, visualized, and analyzed by geographically distributed teams of users. High-performance network capabilities must be available to these users at the application level in a transparent, virtualized manner. Moreover, the application users must have the capability to move large datasets from local and remote locations across network environments to their home institutions. To solve these challenges, the main goal of our project is to design and evaluate high-performance data transfer software to support various data-intensive applications. First, we have designed a middleware software that provides access to Remote Direct Memory Access (RDMA) functionalities. This middleware integrates network access, memory management and multitasking in its core design. We address a number of issues related to its efficient implementation, for instance, explicit buffer management and memory registration, and parallelization of RDMA operations, which are vital to delivering the benefit of RDMA to the applications. Built on top of this middleware, an implementation and experimental evaluation of the RDMA-based FTP software, RFTP, is described and evaluated. This application has been implemented by our team to exploit the full capabilities of advanced RDMA mechanisms for ultra-high speed bulk data transfer applications on Energy Sciences Network (ESnet). Second, we designed our data transfer software to optimize TCP/IP based data transfer performance such that RFTP can be fully compatible with today’s Internet. Our kernel optimization techniques with Linux system calls sendfile and splice, can reduce data copy cost. In this report, we summarize the technical challenges of our project, the primary software design methods, the major project milestones achieved, as well as the testbed evaluation work and demonstrations during our project life time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Integrate Latimer Controls' Solution into RTAC (CRADA Final Report, CRD-23-24672)

Latimer Controls, Inc. was awarded two vouchers under the Department of Energy's American-Made Solar Prize Round 6 to conduct collaborative research at a national laboratory. The National Renewable Energy Laboratory (NREL) was selected as a partner to assist Latimer Controls in the performance evaluation of its photovoltaic (PV) control software. This collaboration focuses on developing a hardware-in-the-loop (HIL) testbed at NREL, which will be used to test and validate the Latimer PV control technology in a realistic yet de-risked environment. Both Latimer and NREL teams will work together to analyze the collected test data, derive insights, and disseminate the scientific findings. Recent studies underscore the potential of solar energy as a zero-marginal-cost and zero-emission flexibility resource within the bulk power system, particularly when integrated with advanced control systems. To enhance the performance of such systems, Latimer Controls has developed leading-edge technologies, including machine learning (ML) algorithms and hierarchical inverter set-point allocation methods. These innovations are designed to estimate the operational headroom of large PV plants for grid integration and control. However, comprehensive validation under real-world conditions remains necessary. To address this gap, the concurrent CRADA project proposes the real-world application and validation of the Latimer Control solution within a HIL environment. Initially, the Latimer algorithm was developed and tested within MATLAB Simulink, a platform suitable for research-level simulations and iterative development. However, transitioning this technology to a real solar site as an industry-ready solution necessitates implementation in a format compatible with widely used solar power plant controllers. In this additional CRADA work, the MATLAB Simulink-based logic will be translated into Structured Text, a programming language compliant with IEC 61131 standards, which is commonly used for custom logic implementations in industry-leading programmable logic controllers (PLCs), such as the Schweitzer SEL real-time automation controller (RTAC). This transition will facilitate the deployment of the Latimer Control solution in real-world solar power plants, thereby advancing the technology towards commercialization.

14 SOLAR ENERGY↗
DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗
DOE OSTI2022

A simulation‐based integrated virtual testbed for dynamic optimization in smart manufacturing systems

Abstract In a manufacturing system, production control‐related decision‐making activities occur at different levels. At the process level, one of the main control activities is to tune the parameters of individual manufacturing equipment. At the system level, the main activity is to coordinate production resources and to route parts to appropriate workstations based on their processing requirement, priority indices, and control policy. At the factory level, the goal is to plan and schedule the processing of parts at different operations for the entire system in order to optimize certain objectives. Note that the results of such activities at different levels are closely coupled and affect the overall performance of the manufacturing system as a whole. Therefore, it is important to systematically integrate these control and optimization activities into one unified platform to ensure the goal of each individual activity is aligned with the overall performance of the system. In this paper, we develop a simulation‐based virtual testbed that implements dynamic optimization, automatic information exchange, and decision‐making from the process‐level, system‐level, and factory‐level of a manufacturing system into an integrated computation environment. This is demonstrated by connecting a Python‐based numerical computation program, discrete‐event simulation software (Simul8), and an optimization solver (CPLEX) via a third‐party master program. The application of this simulation‐based virtual testbed is illustrated by a case study in a machining shop.

Sun, Yuting↗