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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A parallel-in-time algorithm for variable step multistep methods

This paper presents a multigrid reduction in time (MGRIT) algorithm for achieving time parallelism using multistep backward difference formula (BDF) methods on variably-spaced temporal grids. This MGRIT approach transforms the linear multistep methods into single step methods applied to groups of time steps. Stability considerations are addressed through lowering of the order on coarse grids. The methods are presented for fixed and variable time step formulations. Furthermore, numerical results show moderate speedups for the heat equation as well as two IEEE power grid test problems characterized by nonlinear differential algebraic equations (DAE) of index 1. The performance of MGRIT with BDF is compared to MGRIT with Runge-Kutta for both the fixed and variable step methods of the same order.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Modernizing Distribution System Restoration to Achieve Grid Resiliency Against Extreme Weather Events: An Integrated Solution

Recent severe power outages caused by extreme weather hazards have highlighted the importance and urgency of improving the resilience of the electric power grid. As the distribution grids still remain vulnerable to natural disasters, the power industry has focused on methods of restoring distribution systems after disasters in an effective and quick manner. The current distribution system restoration practice for utilities is mainly based on predetermined priorities and tends to be inefficient and suboptimal, and the lack of situational awareness after the hazard significantly delays the restoration process. As a result, customers may experience an extended blackout, which causes large economic loss. On the other hand, the emerging advanced devices and technologies enabled through grid modernization efforts have the potential to improve the distribution system restoration strategy. However, utilizing these resources to aid the utilities in better distribution system restoration decision-making in response to extreme weather events is a challenging task. Therefore, this paper proposes an integrated solution: a distribution system restoration decision support tool designed by leveraging resources developed for grid modernization. We first review the current distribution restoration practice and discuss why it is inadequate in response to extreme weather events. Then we describe how the grid modernization efforts could benefit distribution system restoration, and we propose an integrated solution in the form of a decision support tool to achieve the goal. The advantages of the solution include improving situational awareness of the system damage status and facilitating survivability for customers. The paper provides a comprehensive review of how the existing methodologies in the literature could be leveraged to achieve the key advantages. The benefits of the developed system restoration decision support tool include the optimal and efficient allocation of repair crews and resources, the expediting of the restoration process, and the reduction of outage durations for customers, in response to severe blackouts due to extreme weather hazards.

Automated feeder switch↗
DOE OSTI2022

Grid Utility Asset Vulnerability Assessment (GUAVA) Software Tool

Increasing demand and changes in generation portfolios is pushing power grid to operate towards the limit. However, due to lack of analytical tools for understanding various scales of impact on grid, it is becoming more vulnerable to wide scale power outages and blackouts. A vulnerable grid operating at its limit can be easily disrupted by asset failures caused by devastating hurricanes which has been known to damage transmission and distribution lines along its track. In this direction, researchers have focused on determining these assets by conducting Monte Carlo simulations of hurricanes with uncertainties and collected a large set of simulation data. To determine the infrastructure updates necessary for mitigating wide scale impact of hurricanes on the grid, we propose a software tool named “Grid Utility Asset Vulnerability Analysis” (GUAVA) framework. GUAVA presents a novel data-driven probabilistic analytical approach to (1) post-process hurricane failure scenarios, (2) identify/rank assets that are most vulnerable and critical to failing and are associated with highest impact/risk, and (3) to inform system upgrade decisions & prioritization. Based on the observed results and employed data-driven methodology, it is expected GUAVA can be adapted to provide power system planners with a recommendation engine for making informed decisions to improve resilience of grid.

Mahapatra, Kaveri↗
DOE OSTI2019

Graph Laplacian Spectrum and Primary Frequency Regulation: Preprint

We present a framework based on spectral graph theory that captures the interplay among network topology, system inertia, and generator and load damping in determining overall power grid behavior and performance. Specifically, we show that the impact of network topology on a power system can be quantified through the network Laplacian eigenvalues, and such eigenvalues determine the grid robustness against low frequency disturbances. Moreover, we can explicitly decompose the frequency signal along scaled Laplacian eigenvectors when damping-intertia ratios are uniform across buses. The insight revealed by this framework suggests why load-side participation in frequency regulation not only makes the system respond faster, but also helps lower the system nadir after disturbance. Finally, by presenting a new controller specifically tailored to suppress high frequency disturbances, we demonstrate that our results can provide useful guidelines in the controller design for load-side primary frequency regulation. We simulate the improved controller on the IEEE 39-bus New England interconnection system to illustrate its robustness against high frequency oscillation compared to both the conventional droop control and a recent controller design.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2009

Development and Testing of a Prototype Grid-Tied Photovoltaic Power System

The NASA Glenn Research Center (GRC) has developed and tested a prototype 2 kW DC grid-tied photovoltaic (PV) power system at the Center. The PV system has generated in excess of 6700 kWh since operation commenced in July 2006. The PV system is providing power to the GRC grid for use by all. Operation of the prototype PV system has been completely trouble free. A grid-tied PV power system is connected directly to the utility distribution grid. Facility power can be obtained from the utility system as normal. The PV system is synchronized with the utility system to provide power for the facility, and excess power is provided to the utility. The project transfers space technology to terrestrial use via nontraditional partners. GRC personnel glean valuable experience with PV power systems that are directly applicable to various space power systems, and provide valuable space program test data. PV power systems help to reduce harmful emissions and reduce the Nation s dependence on fossil fuels. Power generated by the PV system reduces the GRC utility demand, and the surplus power aids the community. Present global energy concerns reinforce the need for the development of alternative energy systems. Modern PV panels are readily available, reliable, efficient, and economical with a life expectancy of at least 25 years. Modern electronics has been the enabling technology behind grid-tied power systems, making them safe, reliable, efficient, and economical with a life expectancy of at least 25 years. Based upon the success of the prototype PV system, additional PV power system expansion at GRC is under consideration. The prototype grid-tied PV power system was successfully designed and developed which served to validate the basic principles described, and the theoretical work that was performed. The report concludes that grid-tied photovoltaic power systems are reliable, maintenance free, long life power systems, and are of significant value to NASA and the community.

Eichenberg, Dennis J.↗
DOE OSTI2023

Smart Data Mapping for Connecting Power System Model and Geospatial Data

Knowing the geospatial locations of power system model elements is the foundation for analyzing system vulnerability to natural hazards and connecting loads with end users and their communities. However, power system models and geospatial data for power grid assets may have been developed asynchronously without close coordination. Creating a direct mapping between the two may be a challenging task, considering heterogeneous data structures, target uses, historical legacies, and human errors. This work aims to build an automatic data mapping workflow to connect power system model elements and geospatial data for transmission network, and to support energy grid resilience studies for Puerto Rico. The primary steps in this workflow include constructing graphs using geospatial data, and aligning them to the transmission networks defined in the power system data. The results have been evaluated against existing manual mapping practices for part of the Puerto Rico Power Grid model to illustrate the performance of such auto-mapping solutions.

Resilience, geospatial data, grid transmission net↗
NASA NTRS2009

Development and Testing of the Glenn Research Center Visitor's Center Grid-Tied Photovoltaic Power System

The NASA Glenn Research Center (GRC) has developed, installed, and tested a 12 kW DC grid-tied photovoltaic (PV) power system at the GRC Visitor s Center. This system utilizes a unique ballast type roof mount for installing the photovoltaic panels on the roof of the Visitor s Center with no alterations or penetrations to the roof. The PV system has generated in excess of 15000 kWh since operation commenced in August 2008. The PV system is providing power to the GRC grid for use by all. Operation of the GRC Visitor s Center PV system has been completely trouble free. A grid-tied PV power system is connected directly to the utility distribution grid. Facility power can be obtained from the utility system as normal. The PV system is synchronized with the utility system to provide power for the facility, and excess power is provided to the utility. The project transfers space technology to terrestrial use via nontraditional partners. GRC personnel glean valuable experience with PV power systems that are directly applicable to various space power systems, and provides valuable space program test data. PV power systems help to reduce harmful emissions and reduce the Nation s dependence on fossil fuels. Power generated by the PV system reduces the GRC utility demand, and the surplus power aids the community. Present global energy concerns reinforce the need for the development of alternative energy systems. Modern PV panels are readily available, reliable, efficient, and economical with a life expectancy of at least 25 years. Modern electronics has been the enabling technology behind grid-tied power systems, making them safe, reliable, efficient, and economical with a life expectancy of at least 25 years. Based upon the success of the GRC Visitor s Center PV system, additional PV power system expansion at GRC is under consideration. The GRC Visitor s Center grid-tied PV power system was successfully designed and developed which served to validate the basic principles described, and the theoretical work that was performed. The report concludes that grid-tied photovoltaic power systems are reliable, maintenance free, long life power systems, and are of significant value to NASA and the community.

Eichenberg, Dennis J.↗
DOE OSTI2015

Control voltage and power fluctuations when connecting wind farms

Voltage, frequency, active power and reactive power are very important parameters in terms of power quality. These parameters are followed when connecting any power plant, the more the connection of wind farms. Connecting wind farms to the electricity system must not cause interference outside the limits set by regulations. Modern solutions for fast and automatic voltage control and power fluctuations using electronic control systems of reactive power flows. FACTS (Flexible Alternating Current Transmision System) systems, established on the basis of power electronic circuits ensure control of electrical status quantities to achieve the necessary transfer of power to the power grid. FACTS devices can quickly control parameters and sizes of state power lines, such as impedance line voltages and phase angles of the voltages of the two ends of the line. Their use can lead to improvement in power system operation by increasing the transmission capacity of power lines, power flow control lines, improved static and transient stability reserve.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Optimal Siting of EV Fleet Charging Station Considering EV Mobility and Microgrid Formation for Enhanced Grid Resilience

Coordinating infrastructure planning for transportation and the power grid is essential for enhanced reliability and resilience during operation and disaster management. This paper presents a two-stage stochastic model to optimize the location of electric vehicle fleet charging stations (FEVCSs) to enhance the resilience of a distribution network. The first stage of this model deals with the decision to place an FEVCS at the most favorable and optimized location, whereas the second stage aims to minimize the weighted sum of the value of lost load in multiple potential scenarios with different faults. Indeed, the second stage is a joint grid restoration scheme with network reconfiguration and microgrid formation using available distributed generators and fleet electric vehicles. The proposed model is tested on a modified IEEE-33 node distribution network and a four-node transportation network. Case studies demonstrate the effectiveness of the proposed model.

25 ENERGY STORAGE↗
DOE OSTI2013

Parallel Implementation of Power System Dynamic Simulation

Dynamic simulation of power system transient stability is important for planning, monitoring, operation, and control of electrical power systems. However, modeling the system dynamics and network involves the computationally intensive time-domain solution of numerous differential and algebraic equations (DAE). This results in a transient stability implementation that may not maintain the real-time constraints of an online security assessment. This paper presents a parallel implementation of the dynamic simulation on a high-performance computing (HPC) platform using parallel simulation algorithms and computation architectures. It enables the simulation to run even faster than real time, enabling the “look-ahead” capability of upcoming stability problems in the power grid.

dynamic simulation↗
DOE OSTI2016

Distribution-Agnostic Stochastic Optimal Power Flow for Distribution Grids

This paper outlines a data-driven, distributionally robust approach to solve chance-constrained AC optimal power flow problems in distribution networks. Uncertain forecasts for loads and power generated by photovoltaic (PV) systems are considered, with the goal of minimizing PV curtailment while meeting power flow and voltage regulation constraints. A data- driven approach is utilized to develop a distributionally robust conservative convex approximation of the chance-constraints; particularly, the mean and covariance matrix of the forecast errors are updated online, and leveraged to enforce voltage regulation with predetermined probability via Chebyshev-based bounds. By combining an accurate linear approximation of the AC power flow equations with the distributionally robust chance constraint reformulation, the resulting optimization problem becomes convex and computationally tractable.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

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↗
DOE OSTI2020

Scalable Stochastic Transmission Expansion: A Use Case for ExaSGD

The intermittent nature of renewable energy poses new challenges for power grids due to its variable and un- certain power output. These features of renewable generation are becoming more relevant to transmission planning as grids reach higher penetration levels of renewable energy. In this paper we present an approach for transmission planning based on scalable computational approaches which enable the explicit consideration of operational uncertainties in the planning process. Using three-stage stochastic programming and the progressive hedging algorithm, we compute transmission expansion decisions on a modified RTS-GMLC test system. We augment the grid with large amounts of wind generation and consider many operational scenarios subject to wind uncertainty. This is an example of a possible use of the ExaSGD security constrained AC optimal power flow solver.

Exascale Computing Project↗
DOE OSTI2024

Digital Twin + AI: Control Room of the Future

A digital twin enhances power grid control room operations by providing real-time monitoring, predictive insights, simulation capabilities, remote control, training opportunities, data integration, and decision support. This technology empowers control room operators to effectively manage the grid, optimize performance, and ensure reliable and efficient energy distribution.

control room of the future↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (control-lable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2023

Subordinated Gaussian Processes for Solar Irradiance

Traditionally the power grid has been a one-way street with power flowing from large transmission-connected generators through the distribution network to consumers. This paradigm is changing with the introduction of distributed renewable energy resources (DERs), and with it, the way the grid is managed. There is currently a dearth of high fidelity solar irradiance datasets available to help grid researchers understand how expansion of DERs could affect future power system operations. Realistic simulations of by-the-second solar irradiances are needed to study how DER variability affects the grid. Irradiance data are highly non-stationary and non-Gaussian, and even modern time series models are challenged by their distributional properties. We develop a subordinated non-Gaussian stochastic model whose simulations realistically capture the distribution and dependence structure in measured irradiance. We illustrate our approach on a fine resolution dataset from Hawaii, where our approach outperforms standard nonlinear time series models.

MATHEMATICS AND COMPUTING,SOLAR ENERGY↗