Verification and Enhancement of VIIRS Day-Night Band (DNB) Power Outage Detection Product

This case study of Hurricane Matthew (October 2016) uses the NASA Short-Term Prediction Research and Transition (SPoRT) Center DNB power outage product (using GSFC VIIRS DNB preliminary Black Marble product, Roman et al.. 2017) and 2013 LandScan Global population data to look for correlations between the post-event %-of-normal radiance and the utility company-reported outage numbers (obtained from EAGLE-1)

Application of Spatial Data Modeling and Geographical Information Systems (GIS) for Identification of Potential Siting Options for Various Electrical Generation Sources

Oak Ridge National Laboratory (ORNL) initiated an internal National Electric Generation Siting Study, which is an ongoing multiphase study addressing several key questions related to our national electrical energy supply. This effort has led to the development of a tool, OR-SAGE (Oak Ridge Siting Analysis for power Generation Expansion), to support siting evaluations. The objective in developing OR-SAGE was to use industry-accepted approaches and/or develop appropriate criteria for screening sites and employ an array of Geographic Information Systems (GIS) data sources at ORNL to identify candidate areas for a power generation technology application. The initial phase of the study examined nuclear power generation. These early nuclear phase results were shared with staff from the Electric Power Research Institute (EPRI), which formed the genesis and support for an expansion of the work to several other power generation forms, including advanced coal with carbon capture and storage (CCS), solar, and compressed air energy storage (CAES). Wind generation was not included in this scope of work for EPRI. The OR-SAGE tool is essentially a dynamic visualization database. The results shown in this report represent a single static set of results using a specific set of input parameters. In this case, the GIS input parameters were optimized to support an economic study conducted by EPRI. A single set of individual results should not be construed as an ultimate energy solution, since US energy policy is very complex. However, the strength of the OR-SAGE tool is that numerous alternative scenarios can be quickly generated to provide additional insight into electrical generation or other GIS-based applications. The screening process divides the contiguous United States into 100 x 100 m (1-hectare) squares (cells), applying successive power generation-appropriate site selection and evaluation criteria (SSEC) to each cell. There are just under 700 million cells representing the contiguous United States. If a cell meets the requirements of each criterion, the cell is deemed a candidate area for siting a specific power generation form relative to a reference plant for that power type. Some SSEC parameters preclude siting a power plant because of an environmental, regulatory, or land-use constraint. Other SSEC assist in identifying less favorable areas, such as proximity to hazardous operations. All of the selected SSEC tend to recommend against sites. The focus of the ORNL electrical generation source siting study is on identifying candidate areas from which potential sites might be selected, stopping short of performing any detailed site evaluations or comparisons. This approach is designed to quickly screen for and characterize candidate areas. Critical assumptions supporting this work include the supply of cooling water to thermoelectric power generation; a methodology to provide an adequate siting footprint for typical power plant applications; a methodology to estimate thermoelectric plant capacity while accounting for available cooling water; and a methodology to account for future ({approx}2035) siting limitations as population increases and demands on freshwater sources change. OR-SAGE algorithms were built to account for these critical assumptions. Stream flow is the primary thermoelectric plant cooling source evaluated in this study. All cooling was assumed to be provided by a closed-cycle cooling (CCC) system requiring makeup water to account for evaporation and blowdown. Limited evaluations of shoreline cooling and the use of municipal processed water (gray) cooling were performed. Using a representative set of SSEC as input to the OR-SAGE tool and employing the accompanying critical assumptions, independent results for the various power generation sources studied were calculated

Real Time Simulation of Power Grid Disruptions

DOE-OE and DOE-SC workshops (Reference 1-3) identified the key power grid problem that requires insight addressable by the next generation of exascale computing is coupling of real-time data streams (1-2 TB per hour) as the streams are ingested to dynamic models. These models would then identify predicted disruptions in time (2-4 seconds) to trigger the smart grid s self healing functions. This project attempted to establish the feasibility of this approach and defined the scientific issues, and demonstrated example solutions to important smart grid simulation problems. These objectives were accomplished by 1) using the existing frequency recorders on the national grid to establish a representative and scalable real-time data stream; 2) invoking ORNL signature identification algorithms; 3) modeling dynamically a representative region of the Eastern interconnect using an institutional cluster, measuring the scalability and computational benchmarks for a national capability; and 4) constructing a prototype simulation for the system s concept of smart grid deployment. The delivered ORNL enduring capability included: 1) data processing and simulation metrics to design a national capability justifying exascale applications; 2) Software and intellectual property built around the example solutions; 3) demonstrated dynamic models to design few second self-healing

Data Analysis for Real Time Identification of Grid Disruptions

The U.S. electric power system comprises multiple distinct interconnections of generators, high voltage transmission systems, and local distribution systems that maintain a continuous balance between generation and load with impressive levels of efficiency and reliability. This critical infrastructure has served the nation remarkably well, but is likely to see more changes over the next decade than it has seen over the past century. In particular, the widespread deployment of renewable generation, smart-grid controls, energy storage, and new conducting materials will require fundamental changes in grid planning and the way we run the power grid. Two challenges in the realization of the smart grid technology are the ability to visualize the deluge of expected data streams for global situational awareness; as well as the ability to detect disruptive and classify such events from spatially-distributed high-speed power system frequency measurements. One element of smart grid technology is the installation of a wide-area frequency measurement system on the electric poles in the streets for conditions monitoring of the distribution lines. This would provide frequency measurements about the status of the electric grid and possible information about impending problems before they start compounding and cascading. The ability to monitor the distribution lines is just one facet of proposed smart grid technology. Other elements include the installation of advanced devices such as smart meters, the automation of transmission lines, the integration of renewable energy technologies such as solar and wind, and the advancement of plug-in hybrid electric vehicle technology. This chapter describes recent advancements in the area of intelligent data analysis for real time detection of disruptive events from power system frequency data collected using an existing internet-based frequency monitoring network (FNET), which is a precursor for future smart-grid systems

Evaluation of Suitability of Selected Set of Department of Defense Military Bases and Department of Energy Facilities for Siting a Small Modular Reactor

This report summarizes the approach that ORNL developed for screening a sample set of US Department of Defense (DOD) military base sites and DOE sites for possible powering with an SMR; the methodology employed, including spatial modeling; and initial results for several sample sites. The objective in conducting this type of siting evaluation is demonstrate the capability to characterize specific DOD and DOE sites to identify any particular issues associated with powering the sites with an SMR using OR-SAGE; it is not intended to be a definitive assessment per se as to the absolute suitability of any particular site

Evaluation of Suitability of Selected Set of Department of Defense Military Bases and Department of Energy Facilities for Siting a Small Modular Reactor

This report summarizes the approach that ORNL developed for screening a sample set of US Department of Defense (DOD) military base sites and DOE sites for possible powering with an SMR; the methodology employed, including spatial modeling; and initial results for several sample sites. The objective in conducting this type of siting evaluation is demonstrate the capability to characterize specific DOD and DOE sites to identify any particular issues associated with powering the sites with an SMR using OR-SAGE; it is not intended to be a definitive assessment per se as to the absolute suitability of any particular site

The Impact of an Urban Growth Boundary on Land Development in Knox County, Tennessee: A Comparison of Two-Stage Probit Least Squares and Multilayer Neural Network Models

The impact of an urban growth boundary (UGB) on land development in Knox County, TN is estimated via two-stage probit and neural-network models. The insignificance of UGB variable in the two-stage probit model and more visible development patterns in the western part of Knoxville and the neighboring town of Farragut during the post-UGB period in both models suggest that the UGB has not curtailed urban sprawl. Although the network model is found to be a viable alternative to more conventional discrete choice approach for improving the predictability of land development, it is at the cost of evaluating marginal effects

Evaluation of Suitability of Selected Set of Coal Plant Sites for Repowering with Small Modular Reactors

This report summarizes the approach that ORNL developed for screening a sample set of small coal stations for possible repowering with SMRs; the methodology employed, including spatial modeling; and initial results for these sample plants. The objective in conducting this type of siting evaluation is to demonstrate the capability to characterize specific sample coal plant sites to identify any particular issues associated with repowering existing coal stations with SMRs using OR-SAGE; it is not intended to be a definitive assessment per se as to the absolute suitability of any particular site