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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Robust Adaptive Control for Large-scale Inverter-based Resources with Partial and Complete Loss of Inverters

This article proposes an approach to address the current and the aggregated active power control challenge for large-scale inverter-based resources subjected to partially or completely loss of inverters and grid voltage variations. To address this problem, a distributed active power mechanism is proposed which generates desired inverters current. Then an adaptive mechanism distributes the voltage control input automatically between inverters in response to the partial or complete loss of inverters. An L2-gain-based controller is designed for each inverter to track the desired current and rejects the grid voltage disturbance. Here, simulation results show a significant robust tracking for collective active power and current.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Distributed Automatic Load-Frequency Control with Optimality in Power Systems

With the increasing penetration of renewable energy resources, power systems face new challenges in balancing power supply and demand and maintaining the nominal frequency. This paper studies load control to handle these challenges. In particular, a fully distributed automatic load control algorithm, which only needs local measurement and local communication, is proposed. We prove that the control algorithm globally converges to an optimal operating point which minimizes the total disutility of users, restores the nominal frequency and the scheduled tie-line power flows, and respects the thermal constraints of transmission lines. It is also shown that the convergence still holds even when inaccurate system parameters are used in the control algorithm. Lastly, the effectiveness, optimality, and robustness of the proposed algorithm are demonstrated via numerical simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Distributed Automatic Load-Frequency Control with Optimality in Power Systems: Preprint

With increasing penetrations of renewable energy resources, power systems face new challenges in balancing supply and demand and maintaining nominal frequency. This paper studies load control to handle these challenges. In particular, a fully distributed automatic load control algorithm, which needs only local measurement and local communications, is proposed. We prove that the control algorithm globally converges to an optimal operating point that minimizes the total disutility of users, restores the nominal frequency and the scheduled tie-line power flows, and respects the thermal constraints of transmission lines. We also show that the convergence holds even when inaccurate system parameters are used in the control algorithm. Last, the effectiveness, optimality, and robustness of the proposed algorithm are demonstrated via numerical simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Modeling and Rapid Prototyping of Integrated Transmission-Distribution OPF Formulations with PowerModelsITD.jl

Conventional electric power systems are composed of different unidirectional power flow stages of generation, transmission, and distribution, managed independently by transmission system and distribution system operators. However, as distribution systems increase in complexity due to the integration of distributed energy resources, coordination between transmission and distribution networks will be imperative for the optimal operation of the power grid. However, coupling models and formulations between transmission and distribution is non-trivial, in particular due to the common practice of modeling transmission systems as single-phase, and distribution systems as multi-conductor phase-unbalanced. To enable the rapid prototyping of power flow formulations, in particular in the modeling of the boundary conditions between these two seemingly incompatible data models, we introduce PowerModelsITD.jl, a free, open-source toolkit written in Julia for integrated transmission-distribution (ITD) optimization that leverages mature optimization libraries from the InfrastructureModels.jl-ecosystem. The primary objective of the proposed framework is to provide baseline implementations of steady-state ITD optimization problems, while providing a common platform for the evaluation of emerging formulations and optimization problems. In this work, we introduce the nonlinear formulations currently supported in PowerModelsITD.jl, which include AC-polar, AC-rectangular, current-voltage, and a linear network transportation model. Results are validated using combinations of IEEE transmission and distribution networks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Power Density Waterfalls Plots for AGR-1, AGR-2 US UCO, and AGR-5/6/7 Experiments

Task: Generate plots of the distribution of power per particle per power bin over time. Kairos needs these for licensing purposes. Basically, they need to know which power/particle was sustained by which fraction of the fuel and for how long. The idea is to leverage AGR results. However, Kairos wants to operate at relatively high power/particle and, therefore, they need to check how much of their range is covered by AGR. These plots are made for AGR-1, AGR-2 US UCO, and what is predicted for AGR-5/6 and AGR-7 (for which there are no daily as-run values but projected values for every cycle). The predicted AGR-5/6/7 data was provided by the attached Excel file in an Email by Blaise Collin to Cam Binh Pham on May 21, 2018.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

MCNP AND CFD MODELING OF A SODIUM FAST REACTOR SUB-ASSEMBLY CHANNEL TO CAPTURE LOCALIZED TEMPERATURE PEAKING

Typical evaluation tools for sodium-cooled fast reactors (SFR) use simplified neutronic/thermal models to efficiently compute the power and temperature distributions within the core. However, their modeling capability can be limited in extreme cases such as when sharp inter-assembly power gradients occur, or for non-standard SFR assembly geometries. Higher fidelity tools that rely on Monte Carlo methods for neutron transport, and Computational Fluid Dynamics (CFD) for thermal analysis, are better suited in these instances. The higher accuracy comes at the cost of higher computational expense. MCNP and STAR CCM+ were selected for this analysis. While MCNP is capable of generating pin-level power distributions for a whole-core SFR model, it is prohibitively expensive to then conduct CFD analysis for every single assembly. A semi-empirical model was therefore developed to rapidly estimate pin temperature distributions throughout the whole core. It relies on a geometric correction factor for turbulent flow-mixing. The correction factor is obtained from a CFD simulation of a single fuel assembly with a uniform power distribution and an adiabatic boundary condition. Without using CFD, each sub-channel outlet temperature is calculated separately using 1-D heat-balance and Nusselt number correlations and the MCNP calculated pin-powers. The rudimentary 1-D model is then corrected for the flow-mixing effect based on the CFD data. The temperature calculation is performed by a code written in the Python language called CFD Monte-Carlo Developed Reconstruction of Sub-channel at a Quasi-Representative Level (CMDR-SQRL). CMDR-SQRL was shown to adequately predict CFD evaluated temperature distribution for a wide range of SFR configurations, including an extreme case with fuel assemblies nearby containing moderating material. The agreement demonstrates how geometric and power-driven effects can be decoupled within an SFR assembly. CMDR-SQRL is intended to be mainly used for scoping studies to provide core-wide evaluations efficiently.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

A Transparent Framework for Evaluating the Effects of DGPV on Distribution System Costs

Assessing the costs and benefits of distributed photovoltaic generators (DGPV) to the power system and electricity consumers is key to determining appropriate policies, tariff designs, and power system upgrades for the modern grid. We advance understanding of this topic by providing a transparent framework, terminology, and data set for evaluating distribution system upgrade costs, line losses, and interconnection costs as a function of DGPV penetration level.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Change in Brooklyn and Queens: How New York?s Reforming the Energy Vision Program and Con Edison Are Reshaping Electric Distribution Planning

The New York City boroughs of Brooklyn and Queens are undergoing a period of gentrification, infrastructure rebuilding, new construction, and load growth not experienced in decades. Significant numbers of residents are moving in, and structures that had been abandoned or were in disrepair are being refurbished and modernized to accommodate the burgeoning population. Homes, businesses, and industries are reviving areas long in decline, and Brooklyn's growth has made it the nation's fourth most populous city, according to the U.S. Census Bureau.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Stability of Transactive Energy Market-Based Power Distribution System Under Data Integrity Attack

Future smart power distribution system with multiple active consumers and aggregators exchanging real-time electricity pricing and electricity consumption information over a communication network is prone to cyberattack. The goal of this paper is to understand the impact of attacks on pricing/load signals on the physical grid within a transactive energy market framework. First, this paper models the interaction between real-time electricity price and total energy demand in the form of a discrete time nonlinear autonomous dynamical system. Second, equilibrium electricity price and energy demand associated with this coupled dynamical system is derived and conditions for bounded input bounded output (BIBO) stability are identified. Third, a BIBO stable algorithm to design real-time electricity pricing scheme from a techno-economic perspective is developed. Finally, the impact of various levels of false data injection (FDI) attack on price of electricity, demand, and distribution system voltage is investigated. The proposed model is analyzed using simulations on the IEEE 69-bus test system and the impact of FDI attack on both electricity price/demand and distribution grid voltage is quantified. In conclusion, this paper shows that impact of FDI attack on electricity prices is more severe than an attack on electricity demand.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Induced Markov chain for wind farm generation forecasting

Systems and methods for forecasting power generation in a wind farm are disclosed. The systems and methods utilize an induced Markov chain model to generate a forecast of power generation of the wind farm. The forecast is at least one of a point forecast or a distributional forecast. Additionally, the systems and methods modify at least one of: (i) a generation of electricity at a power plant coupled to a common power grid as the wind farm; or (ii) a distribution of electricity in the common power grid based on the forecast of power generation of the wind farm. In an exemplary approach, utilizing the induced Markov chain model to generate the forecast may include determining a series of time adjacent power output measurements based on historical wind power measurements and calculating a time series of difference values based on the series of time adjacent power output measurements.

17 WIND ENERGY↗
DOE OSTI2019

Systems and methods for regulating a microgrid

A microgrid system includes one or more power generators configured to provide electrical energy. The microgrid system also includes a localized distribution network coupled to the one or more power generators, coupled to the one or more loads, and coupled to an external grid. The microgrid system further includes a microgrid controller configured to predict microgrid demand for the one or more loads for a predetermined period of time. The microgrid controller is also configured to receive demand information for the external grid for the predetermined period of time. The microgrid controller is further configured to determine an operation plan for the one or more power generators based on the predicted microgrid demand and the received demand information. Moreover, the microgrid controller is configured to determine a schedule to transmit electrical energy to the external grid based on the operation plan.

Baone, Chaitanya Ashok↗
DOE OSTI2018

On a Future for Smart Inverters with Integrated System Functions

The modern electric power grid is gradually evolving to include high penetration power electronics in a distributed architecture which will pose pressing new challenges on power quality, system control, and operation. The state-of-the-art smart inverters for solar photovoltaics may not be sufficient to address some of the stability and control challenges such as harmonic resonances due to the interactions of multiple power electronics converters. This paper discusses a future of smart inverters with integrated system functions and its associated challenges, and identifies smart inverter research trends and features in the context of flexible control architectures. Future power electronics research will shift from hardware solutions to more control solutions with integrated system functions under distributed power grid scenarios with small-scale power electronics interfaced with distributed generations and loads.

Xue, Yaosuo↗
DOE OSTI2020

Synthetic Ancillary Service Generator (SynAS) v1

The balance of demand and supply in the electric power grid is a crucial element to grid reliability. While balancing is typically provided by conventional power plants, with spinning generators, distributed energy resources (DER) and especially electric vehicles (EVs) pose a great potential to provide such service. This project conducted a field demonstration at the Los Angeles Air Force Base (LA-AFB) where a fleet of mixed-use bi-directional EVs were actively participating in the California Independent System Operator (CAISO) market for frequency regulation. While participation in regulation markets is promising, a major drawback in designing control systems and assessing potential revenue is the lack of example frequency regulation signals. This project introduces an open-source dataset for 143 days of four-second regulation data, and the SynAS Python module to synthetically generate frequency regulation signals of arbitrary length.

Black, DouglasR↗
DOE OSTI2022

Storm DEPART(Damage Estimate Prediction And Recovery Tool)

Damage prediction, materials needed, and resource allocation modeling capability in order to support pre-incident planning and preparation by predicting damage to the power generation capacity, transmission grids, distribution networks, and communications assets. The capabilities will be developed by multiple factors to include wind bands, storm surge, and flooding forecasts to participant’s assets which will result in a report of predicted damages. Additional factors to include available participants infrastructure data to include class, age, construction, location, wind rating, and additional information not in the public domain. Based on predicted damages, the output will be a bill of materials (BOM) to support short-term recovery operations. The extensiveness and level of detail for this BOM will depend on the replacement configuration specifications provided for each individual participant asset. Any limiting factors for the model will be applied related supply chain and resource constraints.

Klett, Mary↗
DOE OSTI2017

ARPA-E Impacts: A Sampling of Project Outcomes, Volume II

The Advanced Research Projects Agency-Energy (ARPA-E) is demonstrating that a collaborative model has the power to deliver real value. The Agency’s first compilation booklet of impact sheets, published in 2016, began to tell the story of how ARPA-E has already made an impact in just seven years—funding a diverse and sophisticated research portfolio on advanced energy technologies that enable the United States to tackle our most pressing energy challenges. One year later our research investments continue to pay off, with a number of current and alumni project teams successfully commercializing their technologies and advancing the state of the art in transformative areas of energy science and engineering. There is no single measure that can fully illustrate ARPA-E’s success to date, but several statistics viewed collectively begin to reveal the Agency’s impact. Since 2009, ARPA-E has provided more than $1.5 billion in funding for 36 focused programs and three open funding solicitations, totaling over 580 projects. Of those, 263 are now alumni projects. Many teams have successfully leveraged ARPA-E’s investment: 56 have formed new companies, 68 have partnered with other government agencies to continue their technology development, and 74 teams have together raised more than $1.8 billion in reported funding from the private sector to bring their technologies to market. However, even when viewed together, those measures do not capture ARPA-E’s full impact. To best understand the Agency’s success, the specific scientific and engineering challenges that ARPA-E project teams have overcome must be understood. This booklet provides concrete examples of those successes, ranging from innovations that will bear fruit in the future to ones that are beginning to penetrate the market as products today. Importantly, half of the projects highlighted in this volume stem from OPEN solicitations, which the agency has run in 2009, 2012, and 2015. ARPA-E’s OPEN programs are an extraordinary opportunity for the R&D community to challenge ARPA-E in areas of technology not covered by the agency’s focused technology programs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗