EXTRACTING MAXIMAL FREQUENCY RESPONSE POTENTIAL IN CONTROLLABLE LOADS
The Grid FriendlyTM Appliance (GFA) controller, developed at Pacific Northwest National Laboratory, was originallydesigned to autonomously switch off appliances by detecting under-frequency events. In this paper, the feasibility of usingthe GFA controller to provide primary frequency response is investigated. In particular, the impacts of an important designparameter, i.e., curtailing frequency threshold, on the primary frequency response are carefully analyzed for different situations. In the normal situation, the current method of selecting curtailing frequency thresholds for GFAs is found to be insufficient to guarantee the desired performance especially when the frequency deviation is shallow. In the extreme situations, the power reduction of online GFAs could be so excessive that it can even impact the system frequency negatively. As the first step towards the efforts to make GFAs suitable for providing primary frequency response, the existing controller design is improved by modifying the strategy of selecting curtailing frequency thresholds to ensure the effectiveness of GFAs in the normal situation.
FREQUENCY THRESHOLD DETERMINATION FOR FREQUENCY-RESPONSIVE LOAD CONTROLLERS
The Grid FriendlyTM Appliance (GFA) controller, developed at Pacific Northwest National Laboratory, was originallydesigned to autonomously switch off appliances by detecting under-frequency events. In this paper, the feasibility of usingthe GFA controller to provide primary frequency response is investigated. In particular, the impacts of an important designparameter, i.e., curtailing frequency threshold, on the primary frequency response are carefully analyzed for different situations. In the normal situation, the current method of selecting curtailing frequency thresholds for GFAs is found to be insufficient to guarantee the desired performance especially when the frequency deviation is shallow. In the extreme situations, the power reduction of online GFAs could be so excessive that it can even impact the system frequency negatively. As the first step towards the efforts to make GFAs suitable for providing primary frequency response, the existing controller design is improved by modifying the strategy of selecting curtailing frequency thresholds to ensure the effectiveness of GFAs in the normal situation.
Thomas Wild
James Ang
James (Jim) Ang, is the Chief Scientist for Computing in the Physical and Computational Sciences Directorate at Pacific Northwest National Laboratory (PNNL).
Jason Fuller
Michael Kintner-Meyer
Michael Kintner-Meyer is a research engineer and systems analyst at Pacific Northwest National Laboratory.
Method and Apparatus for Enhanced in Vivo MRI Imaging
Techniques described herein combine conventional proton magnetic resonance imaging (MRI) with novel image processing and analysis tools to develop methods for evaluating localized disease state in patients with emphysema, fibrosis, edema, or any combination of these. The imaging techniques employed are spatially sensitive, allowing for more precise diagnosis than spirometry, and do not expose the patient to ionizing radiation. Emphysema will be detected through imaging and analysis that is sensitive to local compliance changes, while fibrosis and edema will be detected and classified through measurements of the distribution, density, and environment of water molecules. It is envisioned that both of these imaging techniques would be employed, if necessary, during a single imaging session. Combination of these techniques into one image/analysis package would provide a powerful MRI tool for disease evaluation and diagnosis. In addition to clinical application, these combined tools would be valuable for large-scale pre-clinical animal studies for assessment of: disease phenotype, severity, progression, and localization; thereby facilitating targeted tissue harvesting, guiding molecular analysis, and preventing blind sacrifice.
DISTRIBUTED HIERARCHICAL CONTROL ARCHITECTURE FOR INTEGRATING SMART GRID ASSETS DURING NORMAL AND DISRUPTED OPERATIONS
Distributed generation, demand response, distributed storage, smart appliances, electric vehicles, and other emerging distributed smart grid assets are expected to play a key part in the transformation of the American power system. Due to the variability and uncertainty associated with these resources, there is much trepidation from the part of system planners and operators about the controllability of such resources, and how they affect the stability of the grid infrastructure. It is proposed to develop a hierarchical, distributed control architecture, enabling smart grid assets to effectively contribute to grid operations in a controllable manner, while ensuring system stability and equitably rewarding their contribution. The architecture will unify the dispatch of these resources to provide both market-based and balancing services. A means to dynamically select and arm the autonomous responses from these assets, enabling them to offer significant reliability benefits under the full range of grid operating conditions, will be developed. Transmission-level controls will be integrated with new and existing distribution-level control strategies, within a market structure, under both normal and disrupted operations (disrupted communications and other unforeseen events).
METHODS AND SYSTEMS FOR EVALUATING AND IMPROVING DISTRIBUTION-GRID OBSERVABILITY
The invention is a means to quantify grid observability (the ability to determine a set of operating parameters such as voltages, currents, and real and reactive power flows) from a set of (possibly sparse) grid sensor readings and a distribution grid system model and to determine the "islands of observability" where such determination is possible, and by exclusion, where it is not possible (resulting in deficiencies in grid observability that may have to be remedied for proper grid operation). The primary innovations here are in the means to determine the relationships among the sensors and the grid parameters needed for observability for three phase unbalanced distribution circuits, given the sensor placement and grid system model (topology and admittance matrix, or just the topology alone); taking into account grid model uncertainty and communication system characteristics (transportability), and further to determine zones where full observability is possible("islands of observability") and where it is not; to allow for interactive placement of sensors with continual re-calculation of observability indices and observability islands, to provide automatic allocation of sensors to a grid model via sensor allocation strategies, again with calculation of indices and islands, and finally to automatically optimize sensor allocation and placement.
NWPEsSe (North West Potential Energy Surface Search Engine)
Global optimization of nanosized clusters is an important and fundamental problem in theoretical studies in many chemical fields, like catalysis, material, or energy chemistry, etc. In this paper, the powerful artificial bee colony (ABC) algorithm, which has been applied successfully in the global optimization of atomic and molecular clusters, has been developed for nanosized clusters of complex structures. The new ABC algorithm is applied to the global optimization of 4 systems of different chemical nature: gas phase Au55, ligated Au82+, graphene oxide and defected rutile-supported Au8, and cluster assemble . These clusters have sizes lie between 1 to 3 nm and contain up to 1000 atoms, raising great challenges to the algorithm. Reliable global minima (GMs) are obtained for all cases, some of which are better than those reported in literature, indicating the excellent performance of the new ABC algorithm. These GMs provide chemically important insights into the systems. The new ABC algorithm has been coded into the latest version of ABCluster, making it a promise tool for chemists from broad fields to rapidly carry out global optimizations of nanosized clusters.