Search NASA⌕ Search

SEARCH · Search NASA

Results for “Contingency”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

A Divergence Statistics Extension to VTK for Performance Analysis

This report follows the series of previous documents ([PT08, BPRT09b, PT09, BPT09, PT10, PB13], where we presented the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k -means, order and auto-correlative statistics engines which we developed within the Visualization Tool Kit ( VTK ) as a scalable, parallel and versatile statistics package. We now report on a new engine which we developed for the calculation of divergence statistics, a concept which we hereafter explain and whose main goal is to quantify the discrepancy, in a stasticial manner akin to measuring a distance, between an observed empirical distribution and a theoretical, "ideal" one. The ease of use of the new diverence statistics engine is illustrated by the means of C++ code snippets. Although this new engine does not yet have a parallel implementation, it has already been applied to HPC performance analysis, of which we provide an example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Final Report for Grant DOE DE-FG02-08ER64573 (Relating to Turbulence Modeling)

Turbulence enhances transport and mixing. Turbulent ocean currents can increase the encounter rate between fish larvae and their prey. Without turbulence, the fuel and air injected into the cylinder of an internal combustion engine would mix too slowly to be effective. Birds extract energy from turbulent winds to soar for great distances without flapping their wings. Turbulence can be detrimental as well. The efficiencies of vehicles, pipelines, and industrial equipment are all hindered by turbulence. Turbulence can also cause structural fatigue, generate unwanted noise, and distort the propagation of electromagnetic signals. These observations highlight the importance of turbulence research. Our ability to predict and control turbulence and, thus, to intensify or suppress its effects as circumstances warrant is contingent on our understanding of the underlying mechanisms. Turbulence is also immensely interesting from a purely scientific perspective and is a great source of fundamentally important, challenging problems for physicists, engineers, and mathematicians. Moreover, various methods and tools developed in the field have found applications in other fields, including nonlinear optics, nonlinear acoustics, pattern formation, image processing, data compression, and econophysics. It is possible, at least away from walls, to derive LES models of very high-order accuracy. However, these models also lead to correspondingly intense computational complexity for their numerical solution. Some also introduce yet more questions on the already difficult problem of specifying needed and sometimes artificial local boundary conditions for the inherently nonlocal flow averages. For these two (and other) reasons, there has been a resurgence of interest in basing simulations of turbulent flows on much simpler regularizations of the Navier–Stokes equations rather than on full models of local averages--i.e., LES models. Initially these were developed as pure theoretical tools. The influx of ideas from LES and the added constraint that the regularization be amenable to numerical simulation have breathed new perspective and thus new life into this thread of ideas.Over the past year, a significant portion of our research activity has focused on numerical studies of the Navier–Stokes-$αβ$ model and extensions thereof. Our results regarding these and other approaches to turbulence modeling are described below.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Notification of General Class 1 Permit Modification for the Los Alamos National Laboratory (LANL) Hazardous Waste Facility Permit, EPA ID # NM0890010515

This document contains a notification for a Class 1 Permit Modification to modify the Los Alamos National Laboratory (LANL) Hazardous Waste Facility Permit (Permit). The text modifications are provided herein and have been made to the Permit by the Department of Energy (DOE) and Los Alamos National Security, LLC (LANS), collectively the Permittees. The modifications to the text of the Permit have been identified using red text and red lines through the texts for deletions. Description: This modification includes three changes. One change includes an address change within the Attachment D, Contingency Plan, and the remaining changes correct two typographical errors in Permit Section 2.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Fast Dynamic Simulation-Based Small Signal Stability Assessment and Control

Power grid planning and operation decisions are made based on simulation of the dynamic behavior of the system. Enabling substantial energy savings while increasing the reliability of the aging North American power grid through improved utilization of existing transmission assets hinges on the adoption of wide-area measurement systems (WAMS) for power system stabilization. However, adoption of WAMS alone will not suffice if the power system is to reach its full entitlement in stability and reliability. It is necessary to enhance predictability with "faster than real-time" dynamic simulations that will enable the dynamic stability margins, proactive real-time control, and improve grid resiliency to fast time-scale phenomena such as cascading network failures. Present-day dynamic simulations are performed only during offline planning studies, considering only worst case conditions such as summer peak, winter peak days, etc. With widespread deployment of renewable generation, controllable loads, energy storage devices and plug-in hybrid electric vehicles expected in the near future and greater integration of cyber infrastructure (communications, computation and control), monitoring and controlling the dynamic performance of the grid in real-time would become increasingly important. The state-of-the-art dynamic simulation tools have limited computational speed and are not suitable for real-time applications, given the large set of contingency conditions to be evaluated. These tools are optimized for best performance of single-processor computers, but the simulation is still several times slower than real-time due to its computational complexity. With recent significant advances in numerical methods and computational hardware, the expectations have been rising towards more efficient and faster techniques to be implemented in power system simulators. This is a natural expectation, given that the core solution algorithms of most commercial simulators were developed decades ago, when High Performance Computing (HPC) resources were not commonly available.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Framework for Modeling High-Impact, Low-Frequency Power Grid Events to Support Risk-Informed Decisions

Natural and man-made hazardous events resulting in loss of grid infrastructure assets challenge the electric power grid’s security and resilience. However, the planning and allocation of appropriate contingency resources for such events requires an understanding of their likelihood and the extent of their potential impact. Where these events are of low likelihood, a risk-informed perspective on planning can be problematic as there exists an insufficient statistical basis to directly estimate the probabilities and consequences of their occurrence. Since risk-informed decisions rely on such knowledge, a basis for modeling the risk associated with high-impact low frequency events (HILFs) is essential. Insights from such a model can inform where resources are most rationally and effectively expended. The present effort is focused on development of a HILF risk assessment framework. Such a framework is intended to provide the conceptual and overarching technical basis for the development of HILF risk models that can inform decision makers across numerous stakeholder sectors. The North American Electric Reliability Corporation (NERC) 2014 Standard TPL-001-4 considers severe events for transmission reliability planning, but does not address events of such severity that they have the potential to fail a substantial fraction of grid assets over a region, such as geomagnetic disturbances (GMD), extreme seismic events, and coordinated cyber-physical attacks. These are beyond current planning guidelines. As noted, the risks associated with such events cannot be statistically estimated based on historic experience; however, there does exist a stable of risk modeling techniques for rare events that have proven of value across a wide range of engineering application domains. There is an active and growing interest in evaluating the value of risk management techniques in the State transmission planning and emergency response communities, some of this interest in the context of grid modernization activities. The availability of a grid HILF risk model, integrated across multi-hazard domains which, when interrogated, can support transparent, defensible and effective decisions, is an attractive prospect among these communities. In this report, we document an integrated HILF risk framework intended to inform the development of risk models. These models would be based on the systematic and comprehensive (to within scope) characterization of hazards to the level of detail required for modeling risk, identification of the stressors associated with the hazards (i.e., the means of impacting grid and supporting infrastructure), characterization of the vulnerability of assets to these stressors and the probabilities of asset compromise, the grid’s dynamic response to the asset failures, and assessment of subsequent severities of consequence with respect to selected impact metrics, such as power outage duration and geographic reach. Specifically, the current framework is being developed to;1. Provide the conceptual and overarching technical paradigms for the development of risk models; 2. Identify the classes of models required to implement the framework - providing examples of existing models, and also identifying where modeling gaps exist; 3. Identify the types of data required, addressing circumstances under which data are sparse and the formal elicitation of informed judgment might be required; and 4. Identify means by which the resultant risk models might be interrogated to form the necessary basis for risk management.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

VersiCharge-SG - Smart Grid Capable Electric Vehicle Supply Equipment (EVSE) for Residential Applications

In his 2011 State of the Union address, President Obama called for one million electric vehicles on the road by 2015 [1]. With large-scale Electric Vehicle (EV) or Plug-in Electric Vehicle (PEV or EV for short) or Plug-in Hybrid Electric Vehicle (PHEV) penetration into the US market, there will be drastic reduction in fossil fuel consumption, thus significantly reducing our dependency on foreign oil [2-6]. There will also be significant reduction on Green House Gas (GHG) emissions and smog in the major US cities [3, 7, 8]. Similar studies have also been done other industrial counties [9]. For the fuel cost, with the home electricity rate around $0.13 per kWh, it would cost about $0.05 per mile for DC operation and $0.03 cents per mile for AC operation. But, assuming 25 miles per gallon for a typical vehicle and $4 per gallon, fossil fuel will cost $0.16 per mile [10]. The overall lifecycle cost of PEVs will be several folds lower than the existing fossil fueled vehicles. Despite the above advantages of the EVs, the current cost of EVSE is not affordable for the average consumer. Presently, the cost of installing state-of-the-art residential EVSE ranges from $1500 to $2500 [11]. Low priced EVSE technology, which is easy to install, and affordable to operate and maintain by an average consumer, is essential for the large-scale market penetration of EVs. In addition, the long-term success of this technology is contingent on the PEVs having minimal excessive load and shift impact on the grid, especially at peak times. In a report [2] published by the Pacific Northwest National Laboratory (PNNL), the exiting electric power generation infrastructure, if used at its full capacity 24 hours a day, would support up to 84% of the nation’s cars, pickup trucks and SUVs for an average daily drive of 33 miles. This mileage estimate is certainly much below what an average driver would drive his/her vehicle per day. Another report [3] by the National Renewable Energy Laboratory (NREL) shows that an increased PEV penetration would significantly increase pressure on the peak generation, if no controlled charging strategy was put in place. Investigations from Oak Ridge National Laboratory (ORNL) show that in many regions, additional power generation facilities must be put in place and operate in evening times to recharge the EVs [12]. By all accounts, large PEV penetration will bring to the power grid enormous challenges due to the excessive and stochastic demand, and can entirely change the peak time distribution and behavior, perhaps, into a bi-modal distribution capable of exhausting primary, secondary and even reserves (spinning or non-spinning). To minimize the infrastructure upgrade costs and risks to the grid, and to ensure that power quality and reliability remain within the set standards, the demand for EV plug-ins must then be controlled and coordinated locally and at regional levels. Novel control techniques must be devised to allow for close collaboration between neighboring plug-in requestors, between neighboring communities, and between these and more central power authorities. The concept of electric drive vehicle is not new. The development of electric vehicle has been around since 19th century [13]. But due to a number of reasons and practical limitations at the time, including lower cost of gasoline compared to electricity, excessive refueling times, and abundance of gasoline, the automobile industry embraced gasoline-powered vehicles worldwide [13]. With the global warming, ever reducing reservoirs of fossil oil around the world and increasing political pressure to reduce the national dependency on foreign oil, the last decade of the 20th century witnessed major technological breakthroughs in Alternative Fueled Vehicle (AFV) technologies, including electric vehicles. With GHG emissions and carbon footprint in the minds of many more consumers and politicians, the first decade of the 21stCentury witnessed more breakthroughs with some real life experimentation and sporadic deployment of these technologies [14]. By many accounts, the second decade of the 21st Century is expected to be the time when mass volume production and popular usage of these AFV technologies, especially EV, will materialize. The current DOE request for proposals recognizes the need for major technological changes to ensure that the above national goal is realizable. Two major challenges have been identified: (1) major reduction in the cost of ownership of EVSEs, and (2) managing additional EV loads in the power grid while maintaining power quality, reliability, and affordability. We note that the two challenges are closely linked – A holistic approach to true lifecycle cost of EVSE ownership will certainly include any taxes and surcharges that can be put in place for major potential investments in the grid, and higher electricity charges in case of more frequent and longer peak periods. From a societal perspective, this cost could also include the lost GDP (computed on a local basis) and revenue for businesses at local and regional levels when the grid is no longer capable of meeting the demand and unexpected outages occur. A typical end-point electrical distribution system delivers power to a residential EVSE from the neighborhood distribution pole, as shown in Fig.1. This pole has a transformer (neighboring step-down transformer) that steps down the utility medium voltage to dual 120VAC single phase (also called 240VAC split phase). This voltage is fed through a meter into the residential load control center. The load control center consists of branch circuit breakers and distributes the power supply within various areas of the residential unit. One of the branch circuits from the load control center feeds EV charging station for the unit. An electric vehicle charger is plugged into the socket of the EV charging station and other end of this charger is connected to the vehicle during charging. Figure 1 illustrates a typical configuration of the power grid. The left side of the figure shows the power grid from the power generation to the neighboring step-down transformer, while the right side of the figure shows multiple EVs with the respective charging stations. The typical step-down transformer has an upper limit representing the maximum load that can be requested from these neighboring houses altogether (typically 24 kW). In case the total load increases beyond the supported limit, the protection system (e.g. a circuit breaker) attached to the step-down transformer gets activated automatically.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Eastern Renewable Generation Integration Study

The Eastern Interconnection (EI) is one of the largest power systems in the world, and its size and complexity have historically made it difficult to study in high levels of detail in a modeling environment. In order to understand how this system might be impacted by high penetrations (30% of total annual generation) of wind and solar photovoltaic (PV) during steady state operations, the National Renewable Energy Laboratory (NREL) and the U.S. Department of Energy (DOE) conducted the Eastern Renewable Generation Integration Study (ERGIS). This study investigates certain aspects of the reliability and economic efficiency problem faced by power system operators and planners. Specifically, the study models the ability to meet electricity demand at a 5-minute time interval by scheduling resources for known ramping events, while maintaining adequate reserves to meet random variation in supply and demand, and contingency events. To measure the ability to meet these requirements, a unit commitment and economic dispatch (UC&ED) model is employed to simulate power system operations. The economic costs of managing this system are presented using production costs, a traditional UC&ED metric that does not include any consideration of long-term fixed costs. ERGIS simulated one year of power system operations to understand regional and sub-hourly impacts of wind and PV by developing a comprehensive UC&ED model of the EI. In the analysis, it is shown that, under the study assumptions, generation from approximately 400 GW of combined wind and PV capacity can be balanced on the transmission system at a 5-minute level. In order to address the significant computational burdens associated with a model of this detail we apply novel computing techniques to dramatically reduce simulation solve time while simultaneously increasing the resolution and fidelity of the analysis. Our results also indicate that high penetrations of wind and PV (collectively variable generation (VG)), significantly impact the operation of traditional generating resources and cause these resources to be used less frequently and operate across a broader output range because wind and PV have lower operating costs and variable output levels.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Best Practices for NPT Transit Matching

Transit matching is the process for relating or matching reports of shipments and receipts submitted to the International Atomic Energy Agency (IAEA). Transit matching is a component used by the IAEA in drawing safeguards conclusions and performing investigative analysis. Transit matching is part of IAEA safeguards activities and the State evaluation process, and it is included in the annual Safeguards Implementation Report (SIR). Annually, the IAEA currently receives reports of ~900,000 nuclear material transactions, of which ~500,000 are for domestic and foreign transfers. Of these the IAEA software can automatically match (i.e., machine match) about 95% of the domestic transfers and 25% of the foreign transfers. Given the increasing demands upon IAEA resources, it is highly desirable for the machine-matching process to match as many transfers as possible. Researchers at Oak Ridge National Laboratory (ORNL) have conducted an investigation funded by the National Nuclear Security Administration through the Next Generation Safeguards Initiative to identify opportunities to strengthen IAEA transit matching. Successful matching, and more specifically machine matching, is contingent on quality data from the reporting States. In February 2016, ORNL hosted representatives from three States, the IAEA, and Euratom to share results from past studies and to discuss the processes, policies, and procedures associated with State reporting for transit matching. Drawing on each entity's experience and knowledge, ORNL developed a best practices document to be shared with the international safeguards community to strengthen transit matching. This paper shares the recommendations that resulted from this strategic meeting and the next steps being taken to strengthen transit matching.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2016

Mid-Atlantic Offshore Wind Interconnection and Transmission (MAOWIT)

This project has carried out a detailed analysis to evaluate the pros and cons of offshore transmission, a possible method to decrease balance-of-system costs and permitting time identified in the DOE Office Wind Strategic Plan (DOE, 2011). It also addresses questions regarding the adequacy of existing transmission infrastructure and the ability of existing generating resources to provide the necessary Ancillary Services (A/S) support (spinning and contingency reserves) in the ISO territory. This project has completed the tasks identified in the proposal: 1. Evaluation of the offshore wind resource off PJM, then examination of offshore wind penetrations consistent with U.S. Department of Energy’s (DOE) targets and with their assumed resource size (DOE, 2011). 2. Comparison of piecemeal radial connections to the Independent System Operator (ISO) with connections via a high-voltage direct current (HVDC) offshore network similar to a team partner. 3. High-resolution examination of power fluctuations at each node due to wind energy variability 4. Analysis of wind power production profiles over the Eastern offshore region of the regional ISO to assess the effectiveness of long-distance, North- South transmission for leveling offshore wind energy output 5. Analysis of how the third and fourth items affect the need for ISO grid upgrades, congestion management, and demand for Ancillary Services (A/S) 6. Analysis of actual historic 36-hr and 24-hr forecasts to solve the unit commitment problem and determine the optimal mix of generators given the need to respond to both wind variability and wind forecasting uncertainties.

17 WIND ENERGY↗
DOE OSTI2016

Interactions of aquatic animals with the ORPC OCGen® in Cobscook Bay, Maine: Monitoring behavior change and assessing the probability of encounter with a deployed MHK device

Commercial viability of the marine hydrokinetic (MHK) energy industry is contingent on numerous and diverse factors. A major factor is the effects deployed devices have on animals. This factor is multi-faceted since it is dependent on the availability of appropriate scientific approaches to detect these effects. One of the animal groups with overlapping distributions of MHK devices are fishes. As such, individual fish behavior is likely to be influenced by the presence and operation of MHK devices. Depending on the scale of deployment there are implications for changes to essential fish habitat and effects that can be explored during deployment of a single device yet most changes are likely to be realized when multiple devices are deployed over large areas. It is not only important to document these effects and examine the need for mitigation, but also determine whether the methods involved can be used within the economic constraints of this nascent industry. The results presented in this report benefit the MHK industry by providing transferrable environmental monitoring approaches for MHK projects, specifically related to the interactions between static and dynamic tidal turbines and fish. In addition, some of the data can be used to generalize conditions (e.g., the temporal periodicity of fish presence in tidal regions and probability of fish encountering a device) at other MHK sites with similar physical conditions and fish assemblages. Ocean Renewable Power Company, LLC (ORPC) deployed and tested a prototype OCGen® tidal module in Cobscook Bay, Maine, in the summer of 2014. University of Maine researchers proposed an approach to inform other researchers, regulators, and industry members of the effects of this deployment on fish. While the approach was specifically applied to the OCGen® module, results are applicable to other pilot projects and inform future array deployments. Research funded under this grant allowed us to quantify fish presence as well as individual and group-level behavior changes in the presence of the deployed OCGen® module along with a bottom support frame from a previously deployed device (TidGen®). Specific objectives associated with fish behavior changes were (1) continuation of two long-term datasets: (a) stationary down-looking hydroacoustic dataset near an MHK device (group-level) and (b) stationary side-looking hydroacoustics near the bottom-support frame of a previously deployed MHK device (individual-level); (2) application of new processing methods to down-looking hydroacoustic datasets to improve fish species identification (group-level); and (3) development of an encounter probability model using data on fish abundance, vertical distribution, and behavior.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

Sample EP Flow Analysis of Severely Damaged Networks

These are slides for a presentation at the working group meeting of the WESC SREMP Software Product Integration Team on sample EP flow analysis of severely damaged networks. The following topics are covered: ERCOT EP Transmission Model; Zoomed in to Houston and Overlaying StreetAtlas; EMPACT Solve/Dispatch/Shedding Options; QACS BaseCase Power Flow Solution; 3 Substation Contingency; Gen. & Load/100 Optimal Dispatch; Dispatch Results; Shed Load for Low V; Network Damage Summary; Estimated Service Areas (Potential); Estimated Outage Areas (potential).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Renewable Electricity Futures: Operational Analysis of the Western Interconnection at Very High Renewable Penetrations

The goal of this work was to perform a detailed, sub-hourly analysis of very high penetration scenarios for a single interconnection (the Western Interconnection). The scenarios analyzed for this study included a variety of generation infrastructure buildouts and power system operational assumptions, with three different portfolios of renewable generators. The primary conclusion of this study is that sub-hourly operation of the grid is possible with renewable generation levels between 80% and 90%. Dynamic studies will need to be done to understand any impacts on reliability during contingencies and transient events.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

The Middle East. Domestic sufficiency of fossil fuel resources

In this paper, we’ve compared energy production and consumption across the broader Middle East, paying special attention to three different countries; Saudi Arabia, one of the world’s largest oil producers (second in the CIA World Factbook ranking of crude oil producing countries), with a growing population in the mid-range (47th in the world, according to the CIA World Factbook, and fifth among the nations in this region), a large GDP and GDP per capita (15th in the world, second in this region in GDP, and 21st in GDP per capita in the world, just behind the US at 19th); Qatar, the world’s fourth largest producer of natural gas, with a small native population (and a relatively large foreign labor contingent) that is very wealthy (with the world’s highest GDP per capita, more than twice that of the US); and Egypt, the most populous nation in the region (with the world’s 16th largest population), but relatively poor (with a GDP per capita of about a fifth that of the US and a twelfth that of Qatar); Egypt is a significant energy producer – 29th in the world in crude oil production and 17th in natural gas production – but production has stalled or declined in recent years, and domestic consumption has overtaken production.

02 PETROLEUM↗
DOE OSTI2016

Lakeview, Oregon, Disposal Site

9.1 Compliance Summary The Lakeview, Oregon, Uranium Mill Tailings Radiation Control Act (UMTRCA) Title I Disposal Site was inspected September 16 and 17, 2015. Other than some ongoing concern with erosion-control rock riprap degradation, the disposal cell was in good condition. Some minor fence repairs and vegetation removal, and minor erosion repair work along the west site fence is planned. Inspectors identified no other maintenance needs or cause for a follow-up or contingency inspection. Disposal cell riprap is evaluated annually to ensure continued long-term protection of the cell from erosion during a severe precipitation event. Degradation of the rock riprap was first observed at the site in the mid-1990s. Rock gradation monitoring of the riprap on the west side slope has been performed as part of the annual inspection since 1997 to determine the mean diameter (D 50 ) value. As prescribed by the monitoring procedure, the rock monitoring is routinely conducted at random locations. However, at the U.S. Nuclear Regulatory Commission’s (NRC’s) request, the 2015 rock monitoring approach deviated from the normal procedure by using a pre-established monitoring grid in a subset area of the west side slope. This changed the monitoring approach from random sampling to biased sampling. The D 50 value measured during the 2015 gradation monitoring is 2.39 inches, which falls below the original D 50 design size range of 2.7–3.9 inches for the Type B size side slope riprap. At NRC’s request, rock durability monitoring was added to the gradation monitoring in 2009 to monitor durability by rock type. Results of the 2015 durability monitoring showed that74 percent of the total rock sampled is durability class code A rock with an assigned durability class of “highly durable” or durability class code B “durable” rock, and that over 90 percent of the 3-inch or larger rock is durability class code A or B. The rock durability classifications are further explained in Section 9.4.2.2.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Idaho National Laboratory Emergency Readiness Assurance Plan — Fiscal Year 2016

Battelle Energy Alliance, LLC, the prime contractor for Idaho National Laboratory (INL), provides this Emergency Readiness Assurance Plan (ERAP) for Fiscal Year 2016 in accordance with DOE O 151.1C, “Comprehensive Emergency Management System.” The ERAP documents the readiness of the INL Emergency Management Program using emergency response planning and preparedness activities as the basis. It describes emergency response planning and preparedness activities, and where applicable, summarizes and/or provides supporting information in tabular form for easy access to data. The ERAP also provides budget, personnel, and planning forecasts for Fiscal Year 2017. Specifically, the ERAP assures the Department of Energy Idaho Operations Office that stated emergency capabilities at INL are sufficient to implement PLN 114, “INL Emergency Plan/RCRA Contingency Plan.”

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Cost Comparison in 2015 Dollars for Radioisotope Power Systems -- Cassini and Mars Science Laboratory

Radioisotope power systems (RPSs) have enabled missions requiring reliable, long-lasting power in remote, harsh environments such as space since the early 1960s. Costs for RPSs are high, but are often misrepresented due to the complexity of space missions and inconsistent charging practices among the many and changing participant organizations over the years. This paper examines historical documentation associated with two past successful flight missions, each with a different RPS design, to provide a realistic cost basis for RPS production and deployment. The missions and their respective RPSs are Cassini, launched in 1997, that uses the general purpose heat source (GPHS) radioisotope thermoelectric generator (RTG), and Mars Science Laboratory (MSL), launched in 2011, that uses the multi-mission RTG (MMRTG). Actual costs in their respective years are discussed for each of the two RTG designs and the missions they enabled, and then present day values to 2015 are computed to compare the costs. Costs for this analysis were categorized into two areas: development of the specific RTG technology, and production and deployment of an RTG. This latter category includes material costs for the flight components (including Pu-238 and fine weave pierced fabric (FWPF)); manufacturing of flight components; assembly, testing, and transport of the flight RTG(s); ground operations involving the RTG(s) through launch; nuclear safety analyses for the launch and for the facilities housing the RTG(s) during all phases of ground operations; DOE’s support for NEPA analyses; and radiological contingency planning. This analysis results in a fairly similar 2015 normalized cost for the production and deployment of an RTG—approximately $118M for the GPHS-RTG and $109M for the MMRTG. In addition to these two successful flight missions, the costs for development of the MMRTG are included to serve as a future reference. Note that development costs included herein for the MMRTG do not include costs from NASA staff or facilities for their development efforts—they only include the amounts costed by DOE and DOE contractors. The 2015 value for MMRTG development is $83M. Both of the RPS types analyzed herein use the general purpose heat source (GPHS) module as the “heart of the RPS.” The estimates presented herein do not include development costs for the GPHS. These estimates also do not include the RPS infrastructure cost to maintain the facilities, equipment, and personnel necessary to enable the production of RPSs, except to the extent that the infrastructure is utilized during the production campaigns to provide RPSs for missions. It was not until after the Cassini mission that an RPS infrastructure funding structure was defined and funded separately from mission-specific elements. The information presented herein could allow for more accurate budget planning estimates for space missions being considered over the next decade and beyond.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2017

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I -- National Study

The use of renewable energy (RE) sources, primarily wind and solar generation, is poised to grow significantly within the Indian power system. The Government of India has established a target of 175 gigawatts (GW) of installed RE capacity by 2022, including 60 GW of wind and 100 GW of solar, up from 29 GW wind and 9 GW solar at the beginning of 2017. Thanks to advanced weather and power system modeling made for this project, the study team is able to explore operational impacts of meeting India's RE targets and identify actions that may be favorable for integration. Our primary tool is a detailed production cost model, which simulates optimal scheduling and dispatch of available generation in a future year (2022) by minimizing total production costs subject to physical, operational, and market constraints. Our team comprises a core group from the Power System Operation Corporation, Ltd. (POSOCO), which is the national grid operator (with representation from the National, Southern, and Western Regional Load Dispatch Centers) under Ministry of Power, National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory (LBNL), and a broader modeling team that includes Central Electricity Authority (CEA), POWERGRID (the central transmission utility, CTU), and State Load Dispatch Centers in Maharashtra, Gujarat, Tamil Nadu, Karnataka, Rajasthan, and Andhra Pradesh. Our model includes high-resolution wind and solar data (forecasts and actuals), unique properties for each generator, CEA/CTU's anticipated buildout of the power system, and enforced state-to-state transmission flows. Assuming the fulfillment of current efforts to provide better access to the physical flexibility of the power system, we find that power system balancing with 100 GW of solar and 60 GW of wind is achievable at 15-minute operational timescales with minimal RE curtailment. This RE capacity meets 22% of total projected 2022 electricity consumption in India with annual RE curtailment of 1.4%, in line with experiences in other countries with significant RE penetrations (Bird et al. 2016). Changes to operational practice can further reduce the cost of operating the power system and reduce RE curtailment. Coordinating scheduling and dispatch over a broader area is the largest driver to reduce costs, saving INR 6300 crore (USD $920 million) annually when optimized regionally. Lowering minimum operating levels of coal plants (from 70% to 40%) is the biggest driver to reduce RE curtailment - from 3.5% down to 0.76%. In fact, this operating property is more influential than faster thermal generation ramp rates in lowering the projected levels of curtailment. While this study does not answer every question relevant to planning for India's 2022 RE targets, it is an important step toward analyzing operational challenges and cost saving opportunities using state-of-the-art power system planning tools. Further analysis can build upon this basis to explore optimal renewable resource and intrastate transmission siting, system stability during contingencies, and the influence of total power system investment costs on customer tariffs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Loads as a Resource: Frequency Responsive Demand

Current power grid operation predominantly relies on scheduling and regulating generation resources to supply loads and balance load changes. Due to the inherent intermittency of renewable energy, more flexible and fast ramping capacity is required to compensate for the uncertainty and variability introduced by renewable energy resources. With the advancement of information technologies, power system end-use loads are becoming more agile and can participate in provision of balancing energy and other grid services. The use of demand response can greatly reduce the required generation reserve in a clean and environmentally friendly way. In this report, a new frequency responsive load (FRL) controller was proposed based on the GFA controller, which can respond to both over and under-frequency events. A supervisory control was introduced to coordinate the autonomous response from FRLs in order to overcome the issues of excessive system response due to high penetration of FRLs. The effectiveness of the proposed FRL controller was demonstrated by large-scale simulation studies on the WECC system. Specifically, the FRLs were deployed in the WECC system at different penetration levels to analyze the performance of the proposed strategy both with and without supervisory level control. While both methods have their own advantages, the case without supervisory control could lead to system-wide instability depending on the size of the contingency and the number of FRLs deployed in the system. In addition, the voltage impacts of this controller on distribution system were also carefully investigated. Finally, a preliminary measurement and verification approach was also developed.

24 POWER TRANSMISSION AND DISTRIBUTION↗