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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Large-Scale Stochastic Optimization for Unit Commitment and Economic Dispatch

Our FY 2012 LDRD research on stochastic optimization with its application in power grid planning and operations has advanced the state-of-the-art of this area in the following aspects: (1) Deploying stochastic unit commitment on large real-world applications, (2) Stochastic optimization coupled with real-time production costsimulation (interleaved), and (3) Real-time stochastic optimization with rolling-horizon look-ahead. In conjunction, a number of computational experiments have been performed to evaluate the capability of the latest stochastic optimization software and explore opportunities for future research. In what follows, we discuss each of these contribution areas, including the results of our computational experiments and their implications on the scalability and solvability of large-scale stochastic optimization models.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Sparsity-Promoting Optimal Wide-Area Control of Power Networks

Inter-area oscillations in bulk power systems are typically poorly controllable by means of local decentralized control. Recent research efforts have been aimed at developing wide-area control strategies that involve communication of remote signals. In conventional wide-area control, the control structure is fixed a priori typically based on modal criteria. In contrast, here we employ the recently-introduced paradigm of sparsity-promoting optimal control to simultaneously identify the optimal control structure and optimize the closed-loop performance. To induce a sparse control architecture, we regularize the standard quadratic performance index with an ℓ 1 -penalty on the feedback matrix. The quadratic objective functions are inspired by the classic slow coherency theory and are aimed at imitating homogeneous networks without inter-area oscillations. We use the New England power grid model to demonstrate that the proposed combination of the sparsity-promoting control design with the slow coherency objectives performs almost as well as the optimal centralized control while only making use of a single wide-area communication link. In addition to this nominal performance, we also demonstrate that our control strategy yields favorable robustness margins and that it can be used to identify a sparse control architecture for control design via alternative means.

25 ENERGY STORAGE↗
DOE OSTI2013

Sensor Characteristics Reference Guide

The Buildings Technologies Office (BTO), within the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), is initiating a new program in Sensor and Controls. The vision of this program is: • Buildings operating automatically and continuously at peak energy efficiency over their lifetimes and interoperating effectively with the electric power grid. • Buildings that are self-configuring, self-commissioning, self-learning, self-diagnosing, self-healing, and self-transacting to enable continuous peak performance. • Lower overall building operating costs and higher asset valuation. The overarching goal is to capture 30% energy savings by enhanced management of energy consuming assets and systems through development of cost-effective sensors and controls. One step in achieving this vision is the publication of this Sensor Characteristics Reference Guide. The purpose of the guide is to inform building owners and operators of the current status, capabilities, and limitations of sensor technologies. It is hoped that this guide will aid in the design and procurement process and result in successful implementation of building sensor and control systems. DOE will also use this guide to identify research priorities, develop future specifications for potential market adoption, and provide market clarity through unbiased information.

Cree, Johnathan V.↗
DOE OSTI2013

Protocol for uniformly measuring and expressing the performance of energy storage systems.

The U.S. Department of Energy s Energy Storage Systems (ESS) Program, through the support of Pacific Northwest National Laboratory (PNNL) and Sandia National Laboratories (SNL), facilitated the development of the protocol provided in this report. The focus of the protocol is to provide a uniform way of measuring, quantifying, and reporting the performance of ESSs in various applications; something that does not exist today and, as such, is hampering the consideration and use of this technology in the market. The availability of an application-specific protocol for use in measuring and expressing performance-related metrics of ESSs will allow technology developers, power-grid operators and other end-users to evaluate the performance of energy storage technologies on a uniform and comparable basis. This will help differentiate technologies and products for specific application(s) and provide transparency in how performance is measured. It also will assist utilities and other consumers of ESSs to make more informed decisions as they consider the potential application and use of ESSs, as well as form the basis for documentation that might be required to justify utility investment in such technologies.

Ferreira, Summer Kamal Rhodes↗
DOE OSTI2014

Development and Demonstration of a Security Core Component

In recent years, the convergence of a number of trends has resulted in Cyber Security becoming a much greater concern for electric utilities. A short list of these trends includes: · Industrial Control Systems (ICSs) have evolved from depending on proprietary hardware and operating software toward using standard off-the-shelf hardware and operating software. This has meant that these ICSs can no longer depend on “security through obscurity. · Similarly, these same systems have evolved toward using standard communications protocols, further reducing their ability to rely upon obscurity. · The rise of the Internet and the accompanying demand for more data about virtually everything has resulted in formerly isolated ICSs becoming at least partially accessible via Internet-connected networks. · “Cyber crime” has become commonplace, whether it be for industrial espionage, reconnaissance for a possible cyber attack, theft, or because some individual or group “has something to prove.” Electric utility system operators are experts at running the power grid. The reality is, especially at small and mid-sized utilities, these SCADA operators will by default be “on the front line” if and when a cyber attack occurs against their systems. These people are not computer software, networking, or cyber security experts, so they are ill-equipped to deal with a cyber security incident. Cyber Security Manager (CSM) was conceived, designed, and built so that it can be configured to know what a utility’s SCADA/EMS/DMS system looks like under normal conditions. To do this, CSM monitors log messages from any device that uses the syslog standard. It can also monitor a variety of statistics from the computers that make up the SCADA/EMS/DMS: outputs from host-based security tools, intrusion detection systems, SCADA alarms, and real-time SCADA values – even results from a SIEM (Security Information and Event Management) system. When the system deviates from “normal,” CSM can alert the operator in language that they understand that an incident may be occurring, provide actionable intelligence, and informing them what actions to take. These alarms may be viewed on CSM’s built-in user interface, sent to a SCADA alarm list, or communicated via email, phone, pager, or SMS message. In recognition of the fact that “real world” training for cyber security events is impractical, CSM has a built-in Operator Training Simulator capability. This can be used stand alone to create simulated event scenarios for training purposes. It may also be used in conjunction with the recipient’s SCADA/EMS/DMS Operator Training Simulator. In addition to providing cyber security situational awareness for electric utility operators, CSM also provides tools for analysts and support personnel; in fact, the majority of user interface displays are designed for use in analyzing current and past security events. CSM keeps security-related information in long-term storage, as well as writing any decisions it makes to a (syslog) log for use forensic or other post-event analysis.

Turke, Andy↗
DOE OSTI2014

Where Big Data and Prediction Meet

Our ability to assemble and analyze massive data sets, often referred to under the title of “big data”, is an increasingly important tool for shaping national policy. This in turn has introduced issues from privacy concerns to cyber security. But as IBM’s John Kelly emphasized in the last Innovation, making sense of the vast arrays of data will require radically new computing tools. In the past, technologies and tools for analysis of big data were viewed as quite different from the traditional realm of high performance computing (HPC) with its huge models of phenomena such as global climate or supporting the nuclear test moratorium. Looking ahead, this will change with very positive benefits for both worlds. Societal issues such as global security, economic planning and genetic analysis demand increased understanding that goes beyond existing data analysis and reduction. The modeling world often produces simulations that are complex compositions of mathematical models and experimental data. This has resulted in outstanding successes such as the annual assessment of the state of the US nuclear weapons stockpile without underground nuclear testing. Ironically, while there were historically many test conducted, this body of data provides only modest insight into the underlying physics of the system. A great deal of emphasis was thus placed on the level of confidence we can develop for the predictions. As data analytics and simulation come together, there is a growing need to assess the confidence levels in both data being gathered and the complex models used to make predictions. An example of this is assuring the security or optimizing the performance of critical infrastructure systems such as the power grid. If one wants to understand the vulnerabilities of the system or impacts of predicted threats, full scales tests of the grid against threat scenarios are unlikely. Preventive measures would need to be predicated on well-defined margins of confidence in order to take mitigating actions that could have wide ranging impacts. There is a rich opportunity for interaction and exchange between the HPC simulation and data analytics communities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Integration of a Self-Coherence Algorithm into DISAT for Forced Oscillation Detection

With the increasing number of phasor measurement units on the power system, behaviors typically not observable on the power system are becoming more apparent. Oscillatory behavior on the power system, notably forced oscillations, are one such behavior. However, the large amounts of data coming from the PMUs makes manually detecting and locating these oscillations difficult. To automate portions of the process, an oscillation detection routine was coded into the Data Integrity and Situational Awareness Tool (DISAT) framework. Integration into the DISAT framework allows forced oscillations to be detected and information about the event provided to operational engineers. The oscillation detection algorithm integrates with the data handling and atypical data detecting capabilities of DISAT, building off of a standard library of functions. This report details that integration with information on the algorithm, some implementation issues, and some sample results from the western United States’ power grid.

Forced oscillations↗
DOE OSTI2013

Final Report. Analysis and Reduction of Complex Networks Under Uncertainty

The project was a collaborative effort among MIT, Sandia National Laboratories (local PI Dr. Habib Najm), the University of Southern California (local PI Prof. Roger Ghanem), and The Johns Hopkins University (local PI Prof. Omar Knio, now at Duke University). Our focus was the analysis and reduction of large-scale dynamical systems emerging from networks of interacting components. Such networks underlie myriad natural and engineered systems. Examples important to DOE include chemical models of energy conversion processes, and elements of national infrastructure—e.g., electric power grids. Time scales in chemical systems span orders of magnitude, while infrastructure networks feature both local and long-distance connectivity, with associated clusters of time scales. These systems also blend continuous and discrete behavior; examples include saturation phenomena in surface chemistry and catalysis, and switching in electrical networks. Reducing size and stiffness is essential to tractable and predictive simulation of these systems. Computational singular perturbation (CSP) has been effectively used to identify and decouple dynamics at disparate time scales in chemical systems, allowing reduction of model complexity and stiffness. In realistic settings, however, model reduction must contend with uncertainties, which are often greatest in large-scale systems most in need of reduction. Uncertainty is not limited to parameters; one must also address structural uncertainties—e.g., whether a link is present in a network—and the impact of random perturbations, e.g., fluctuating loads or sources. Research under this project developed new methods for the analysis and reduction of complex multiscale networks under uncertainty, by combining computational singular perturbation (CSP) with probabilistic uncertainty quantification. CSP yields asymptotic approximations of reduceddimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing uncertainty in this context raised fundamentally new issues, e.g., how is the topology of slow manifolds transformed by parametric uncertainty? How to construct dynamical models on these uncertain manifolds? To address these questions, we used stochastic spectral polynomial chaos (PC) methods to reformulate uncertain network models and analyzed them using CSP in probabilistic terms. Finding uncertain manifolds involved the solution of stochastic eigenvalue problems, facilitated by projection onto PC bases. These problems motivated us to explore the spectral properties stochastic Galerkin systems. We also introduced novel methods for rank-reduction in stochastic eigensystems—transformations of a uncertain dynamical system that lead to lower storage and solution complexity. These technical accomplishments are detailed below. This report focuses on the MIT portion of the joint project.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Advanced Offshore Wind Turbine/Foundation Concept for the Great Lakes

This project investigated a conceptual 2-bladed rotor wind turbine design and assessed its feasibility for installation in the Great Lakes. The levelized cost of energy was used for this purpose. A location in Lake Erie near the coast of Cleveland, Ohio was selected as the application site. The loading environment was defined using wind and wave data collected at a weather station in Lake Erie near Cleveland. In addition, the probability distributions of the annual significant wave height and wind speed were determined. A model of the dependence of the above two quantities was also developed and used in the study of wind turbine system loads. Loads from ice floes and ridges were also included.The NREL 5 MW 3-bladed rotor wind turbine concept was used as the baseline design. The proposed turbine design employs variable pitch blade control with tip-brakes and a teeter mechanism. The rotor diameter, rated power and the tower dimensions were selected to closely match those of the NREL 5 MW wind turbine.A semi-floating gravity base foundation was designed for this project primarily to adapt to regional logistical constraints to transport and install the gravity base foundation. This foundation consists of, from bottom to top, a base plate, a buoyancy chamber, a taper zone, a column (with ice cone), and a service platform. A compound upward-downward ice cone was selected to secure the foundation from moving because of ice impact.The turbine loads analysis was based on International ElectroTechnical Committee (IEC) Standard 61400-1, Class III winds. The NREL software FAST was the primary computational tool used in this study to determine all design load cases. An initial set of studies of the dynamics of wind turbines using Automatic Dynamic Analysis of Mechanical Systems (ADAMS) demonstrated that FAST and ADAMS load predictions were comparable. Because of its relative simplicity and short run times, FAST was selected for this study. For ice load calculations, a method was developed and implemented in FAST to extend its capability for ice load modeling.Both upwind and downwind 2-bladed rotor wind turbine designs were developed and studied. The new rotor blade uses a new twist angle distribution design and a new pitch control algorithm compared with the baseline model. The coning and tilt angles were selected for both the upwind and downwind configurations to maximize the annual energy production. The risk of blade-tower impact is greater for the downwind design, particularly under a power grid fault; however, this risk was effectively reduced by adjusting the tilt angle for the downwind configuration.

17 WIND ENERGY↗
DOE OSTI2015

SIND Operational Analysis and Tools Improvement (Final Technical Report)

The goal of the SIND Toolkit project is to create a new national solar database with higher temporal and spatial resolution to reduce the costs and risks of integrating solar power systems into the electric power grid. Previous versions of this dataset from the WWSIS2 study and the ERGIS study have already been widely utilized by academics, utilities, and others after having been made publically available. This dataset, along with its companion WIND Toolkit dataset (Draxl, Clifton, Hodge, & McCaa, 2015), will be utilized for the next 5 – 10 years as the foundation for the vast majority of new grid integration studies.

14 SOLAR ENERGY↗
DOE OSTI2016

Game Theory for Proactive Dynamic Defense and Attack Mitigation in Cyber-Physical Systems

While there has been a great deal of security research focused on preventing attacks, there has been less work on how one should balance security and resilience investments. In this work we developed and evaluated models that captured both explicit defenses and other mitigations that reduce the impact of attacks. We examined these issues both in more broadly applicable general Stackelberg models and in more specific network and power grid settings. Finally, we compared these solutions to existing work in terms of both solution quality and computational overhead.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Assessment of Industrial Load for Demand Response across U.S. Regions of the Western Interconnect

Demand response has the ability to both increase power grid reliability and potentially reduce operating system costs. Understanding the role of demand response in grid modeling has been difficult due to complex nature of the load characteristics compared to the modeled generation and the variation in load types. This is particularly true of industrial loads, where hundreds of different industries exist with varying availability for demand response. We present a framework considering industrial loads for the development of availability profiles for demand response that can provide more regional understanding and can be inserted into analysis software for further study.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Nuclear Hybrid Energy Systems Initial Integrated Case Study Development and Analysis

The US Department of Energy Office of Nuclear Energy established the Nuclear Hybrid Energy System (NHES) project to develop a systematic, rigorous, technically accurate set of methods to model, analyze, and optimize the integration of dispatchable nuclear, fossil, and electric storage with an industrial customer. Ideally, the optimized integration of these systems will provide economic and operational benefits to the overall system compared to independent operation, and it will enhance the stability and responsiveness of the grid as intermittent, nondispatchable, renewable resources provide a greater share of grid power.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Ensemble of Thermostatically Controlled Loads: Statistical Physics Approach

Thermostatically Controlled Loads (TCL), e.g. air-conditioners and heaters, are by far the most wide-spread consumers of electricity. Normally the devices are calibrated to provide the so-called bang-bang control of temperature - changing from on to off , and vice versa, depending on temperature. Aggregation of a large group of similar devices into a statistical ensemble is considered, where the devices operate following the same dynamics subject to stochastic perturbations and randomized, Poisson on/off switching policy. We analyze, using theoretical and computational tools of statistical physics, how the ensemble relaxes to a stationary distribution and establish relation between the re- laxation and statistics of the probability flux, associated with devices' cycling in the mixed (discrete, switch on/off , and continuous, temperature) phase space. This allowed us to derive and analyze spec- trum of the non-equilibrium (detailed balance broken) statistical system. and uncover how switching policy affects oscillatory trend and speed of the relaxation. Relaxation of the ensemble is of a practical interest because it describes how the ensemble recovers from significant perturbations, e.g. forceful temporary switching o aimed at utilizing flexibility of the ensemble in providing "demand response" services relieving consumption temporarily to balance larger power grid. We discuss how the statistical analysis can guide further development of the emerging demand response technology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

An Improved Global Wind Resource Estimate for Integrated Assessment Models: Preprint

This paper summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquely detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.

17 WIND ENERGY↗
DOE OSTI2017

Christmas Valley Renewable Energy Assessment

In partnership with the Oregon Military Department, the Department of Energy used the award to assess and evaluate renewable resources in a 2,622-acre location in Lake County, central Oregon, leading to future development of up to 200 MW of solar electricity. In partnership with the Oregon Military Department, the Department of Energy used the award to assess and evaluate renewable resources in a 2,622-acre location in Lake County, central Oregon, leading to future development of up to 200 MW of solar electricity. The Oregon Military Department (Military) acquired a large parcel of land located in south central Oregon. The land was previously owned by the US Air Force and developed for an Over-the-Horizon Backscatter Radar Transmitter Facility, located about 10 miles east of the town of Christmas Valley. The Military is investigating a number of uses for the site, including Research and Development (R&D) laboratory, emergency response, military operations, developing renewable energy and related educational programs. One of the key potential uses would be for a large scale solar photovoltaic power plant. This is an attractive use because the site has excellent solar exposure; an existing strong electrical interconnection to the power grid; and a secure location at a moderate cost per acre. The project objectives include: 1. Site evaluation 2. Research and Development (R&D) facility analysis 3. Utility interconnection studies and agreements 4. Additional on-site renewable energy resources analysis 5. Community education, outreach and mitigation 6. Renewable energy and emergency readiness training program for veterans

14 SOLAR ENERGY↗
DOE OSTI2017

Enabling Fast Charging: A Technology Gap Assessment

The transportation sector accounts for the largest percentage of energy use in the United States. Decreasing energy consumption across this sector, especially in commercial light duty transportation, is essential for the U.S. to gain energy independence. Recently, powertrain electrification with plug-in electric vehicles (PEVs) have gained traction as an alternative due to their inherent efficiency advantages compared to the traditional internal combustion engine vehicle (ICEV). Accounting for 500,000 vehicle on the road today, these PEVs will reduce oil imported into the U.S. by five billion gallons and save two billion dollars in fuel costs to consumers over their useful life. Though there are many different classes of PEV, the intent of this study is to focus on non-hybrid powertrains, or battery electric vehicles (BEVs). Despite rapid drops in cost within the BEV powertrain of over 4x in the last 10 years, the PEV market still only accounts for approximately 1% of new light duty vehicle sales annually. Though BEV powertrain costs are not quite at parity with the ICEV, another gap to wider adoption of BEVs that have been identified is the ability to refuel quickly, or to fast charge. Though the majority of recharging BEVs is done at home, having access to fast charge stations has a big impact on BEV utility from a consumer perspective. To address the fast charge barrier, charging at 350 kW, or extreme fast charging (XFC), has been proposed and will serve as the basis for discussion in this report. Studies have shown that in areas where drivers have access to 50 kW or 120 kW fast charge stations, annual electric vehicle miles traveled (eVMT) increased by over 25%, even in cases where fast charging was used for 1-5% of total charging events [1, 2]. Having access to these fast charge stations can help alleviate the “range anxiety” that is cited as a common reason for consumers to hesitate to buy a BEV. Though, to be truly competitive to the ICEV refueling experience, even higher power stations are necessary. These extreme fast charge stations (XFC) should be able to recharge a BEV in less than 10 minutes and provide approximately 175 additional miles of driving. However, this introduces a host of new challenges that need to be addressed. As a result, it is expected that packs designed to meet XFC will be significantly more expensive initially than BEVs optimized for range that can reach 140kW with current technology. From the battery cell to the power grid to which these 350 kW chargers are connected, this study will discuss the issues that need to be addressed at each level in order to implement a 350 kW charging network. Although this report is U.S.-focused, the findings should be applicable to other countries with mature automotive infrastructures.

25 ENERGY STORAGE↗
DOE OSTI2017

After Action Report: Idaho National Laboratory Continuity of Operations Program 2017 Exercise September 26, 2017

On September 26, 2017, the Battelle Energy Alliance, LLC (BEA) Continuity of Operations Program (COOP) conducted an annual exercise to demonstrate the COOP responder’s ability to maintain COOP’s primary mission essential function (PMEF) and essential supporting activities (ESAs) during a national loss of commercial power caused by a malware attack to the United States power grid. The continuity emergency management team (CEMT) and continuity emergency response group (CERG) responded to CERG notifications and worked through simulated challenges, using COOP’s 3-D scenario visualization tool (3DSVT), that challenged COOP’s PMEF, essential support activities (ESAs), and impacted mission critical personnel’s human capital. The PMEF and ESAs were successfully maintained as the CERG developed incident action plans through several phases of the scenario, addressing appropriate needs, concerns and strategic planning.

99 GENERAL AND MISCELLANEOUS↗

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