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Results for “Distributed optimization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Optimal shield mass distribution for space radiation protection

Computational methods have been developed and successfully used for determining the optimum distribution of space radiation shielding on geometrically complex space vehicles. These methods have been incorporated in computer program SWORD for dose evaluation in complex geometry, and iteratively calculating the optimum distribution for (minimum) shield mass satisfying multiple acute and protected dose constraints associated with each of several body organs.

Billings, M. P.↗
NASA NTRS1979

Optimal nodal point distribution for improved accuracy in computational fluid dynamics

In applying finite-difference techniques to flow field problems, the accuracy attained for a fixed number of node points can be improved using unequally-spaced node points. The distribution of these node points is chosen here by minimizing a measure of local truncation error with respect to the parameters which define a transformation between the computational space of equally-spaced node points and the physical space of unequally-spaced node points. The problem then becomes a nonlinear programming problem. Numerical results are presented for two one-dimensional test problems: the Blasius boundary layer problem and the inviscid Burgers' equation.

Pierson, B. L.↗
NASA NTRS1991

Distributed-Computer System Optimizes SRB Joints

Initial calculations of redesign of joint on solid rocket booster (SRB) that failed during Space Shuttle tragedy showed redesign increased weight. Optimization techniques applied to determine whether weight could be reduced while keeping joint closed and limiting stresses. Analysis system developed by use of existing software coupling structural analysis with optimization computations. Software designed executable on network of computer workstations. Took advantage of parallelism offered by finite-difference technique of computing gradients to enable several workstations to contribute simultaneously to solution of problem. Key features, effective use of redundancies in hardware and flexible software, enabling optimization to proceed with minimal delay and decreased overall time to completion.

Rogers, James L., Jr.↗
DOE OSTI2020

Optimal Energy Dispatch of Distributed PVs for the Next Generation of Distribution Management Systems

Advanced Distribution Management Systems (ADMS) are being widely adopted by electric utilities for managing and optimizing the operations of their distribution systems. Distributed photovoltaic (DPV) systems with smart inverters can be controlled to adjust active power and reactive power outputs, and they are envisioned to become a part of (centrally or distributed) controllable assets managed by the ADMS for optimizing grid operations. This paper proposes an optimal energy dispatch strategy controlling DPV systems for regulating distribution voltages and achieving conservation voltage reduction. A convex optimization model is proposed with the use of linearized power flow, and the gradient projection algorithm is used to solve the optimal active power and reactive power outputs of smart inverters. The proposed optimal energy dispatch is implemented using an open-source ADMS platform, and simulation results have demonstrated the effectiveness of the proposed approach on improving distribution grid operations.

42 ENGINEERING↗
DOE OSTI2020

Multi-Level Optimal Power Flow Solver in Large Distribution Networks: Preprint

Solving optimal power flow (OPF) problem for large distribution networks incurs high computational complexity. We consider a large multi-phase distribution networks of tree topology with deep penetration of active devices. We divide the network into collaborating areas featuring subtree topology and subareas featuring subsubtree topology. We design a multi-level implementation of the primal-dual gradient algorithm for solving the voltage regulation OPF problems while preserving nodal voltage information and topological information within areas and subareas. Numerical results on a 4,521-node system verifies that the proposed algorithm can significantly improve computational speed without compromising any optimality.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2025

Distribution Substation Planning Toolkit (dsp-toolkit) v1.0

The Distribution Substation Planning Toolkit (DSP Toolkit) is a software suite designed to streamline the planning and optimization of distribution substations. This toolkit offers a comprehensive set of tools and APIs for data curation, short-term electric load forecasting, and weather-sensitive load adjustment, making it an essential resource for utility companies, engineers, and researchers. Features • Data Preprocessing and Curation: Efficiently manage and preprocess large datasets to ensure high-quality input for analysis. • Short-Term Load Forecasting: Utilize data-driven models to predict short-term electric loads accurately. • Weather-Sensitive Modeling: Automatically adjust load forecasts based on weather data to predict future peak demands more precisely. Uses The DSP Toolkit is ideal for planning and optimizing distribution substations, providing a user-friendly interface and comprehensive documentation. It is suitable for both novice and experienced users, facilitating efficient and accurate planning processes. Advantages • Efficiency: Automates complex planning tasks, reducing manual effort and minimizing errors. • Scalability: Handles large datasets and complex models, making it suitable for large-scale projects. • Community and Support: Open-source with active community contributions, ensuring continuous improvement and support. • Extensibility: Easily extendable with custom modules and plugins, allowing users to tailor the toolkit to their specific needs. The DSP Toolkit stands out by offering a robust, flexible, and user-friendly solution for distribution substation planning. Public Abstract

Li, Han [Lawrence Berkeley National Laboratory (LB↗
DOE OSTI2023

QuComm: Optimizing Collective Communication for Distributed Quantum Computing

Distributed quantum computing (DQC) is a scalable way to build a large-scale quantum computing system while the error-prone nonlocal communication between DQC nodes may heavily degrade the fidelity of the distributed quantum program and thus demands specific compiler optimizations. Previous compilers on DQC communication optimization either assumes unlimited communication resource or a few communication qubits due to the hardware limitation. The former compilers may not be efficient when interfacing with communication-resource-constrained DQC hardware while the latter compilers lose the opportunities of optimizing collective communication and routing concurrent communication as they unnecessarily couple limited communication qubits with the implementation of expensive inter-node operations. In this paper, we invent the communication buffer, a communication facility consisting of idle qubits in each compute node, to decouple the execution of inter-node quantum operations from communication qubits: communication qubits are devoted to generating inter-node entanglement while internode operations are conducted in the communication buffer. The communication buffer provides an intermediate layer for inter-node communication and paves the way for collective communication optimization. We then propose QuComm, a buffer-based compiler framework that first performs smart buffer allocation according to communication characteristics of the distributed quantum program and then optimizes and collectively routes inter-node quantum operations. Experimental results on a hierarchical DQC system show that the proposed QuComm can reduce the most expensive inter-node communication request and the latency of various distributed quantum programs by 50.4% and 47.6% on average, respectively.

Wu, Anbang↗
DOE OSTI2025

Resilient Operation of Networked Community Microgrids with High Solar Penetration

This project, funded by the US Department of Energy’s Solar Energy Technologies Office (SETO), focused on the operation of microgrids as a coordinated network. The primary objective, which was successfully achieved, was to develop both control strategies and hardware solutions to support the resilient and efficient operation of networked microgrids with high solar penetration. The work was structured around the following four main tasks: • Development of distributed and scalable optimization algorithms for AC-coupled networked microgrids. • Design and implementation of a novel DC interconnection hardware to enable precise power exchange between microgrids. • Laboratory operational validation of the developed technologies using 480 V testbeds and commercially available hardware. • Field operational validation of the complete solution in Adjuntas, Puerto Rico, interconnecting two kW-scale, split-phase microgrids of Casa Pueblo’s microgrids. This project addressed multiple technical challenges across the domains of optimization, control, hardware interconnection, and protection. One of its key contributions was delivering tangible, real-world solutions for networking microgrids. In contrast to purely theoretical or simulation-based work, this project included full-scale hardware operational validation both in the lab and in the field. The work conducted as part of this project—in collaboration with the University of Puerto Rico; the University of Tennessee, Knoxville; the University of Central Florida; and Casa Pueblo—has advanced the state of the art in networked microgrids. Key contributions include the development of distributed control strategies, practical solutions for real-world implementation challenges, and the introduction of a novel DC interlink approach for microgrid interconnection. The project featured both laboratory and field validation using commercial off-the-shelf components. The field deployment successfully validated that a group of microgrids can operate in a coordinated manner, enabling precise power flow between systems and mutual support during extreme events. This project resulted in 15 journal publications and 15 conference papers; 5 graduate students and 15 undergraduate students were supported. The codes of distributed optimization and forecasting were made open-source through OSTI.gov for distributed optimization and forecasting. All the publications are available in the ORNL-hosted project landing page. The DC interlink with state-of-charge balancing control was operationally validated in Adjuntas by interconnecting two real-world, 240 V split-phase microgrids. To the best knowledge of the team, this represents the first operational validation of AC microgrids interconnected via DC-interlinks. As a culmination of this project, a follow-on grant was awarded to support the technology transfer of the distributed optimization framework to a commercial microgrid controller, Stellar Edge, developed by the California-based company New Sun Road.

14 SOLAR ENERGY↗
NASA NTRS1972

Optimal control of first order distributed systems

The problem of characterizing optimal controls for a class of distributed-parameter systems is considered. The system dynamics are characterized mathematically by a finite number of coupled partial differential equations involving first-order time and space derivatives of the state variables, which are constrained at the boundary by a finite number of algebraic relations. Multiple control inputs, extending over the entire spatial region occupied by the system ("distributed controls') are to be designed so that the response of the system is optimal. A major example involving boundary control of an unstable low-density plasma is developed from physical laws.

Johnson, T. L.↗
DOE OSTI2024

pnnl/oedisi_dopf

OpenEDI - System Integration (OEDI-SI) - PNNL Distributed Optimal Power Flow (DOPF)

Slay, Tylor↗