Intelligent sensor and controller framework for the power grid
Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with the software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.
qFeature
This package contains statistical routines for extracting features from multivariate time-series data which can then be used for subsequent multivariate statistical analysis to identify patterns and anomalous behavior. It calculates local linear or quadratic regression model fits to moving windows for each series and then summarizes the model coefficients across user-defined time intervals for each series. These methods are domain agnostic—but they have been successfully applied to a variety of domains, including commercial aviation and electric power grid data.
ULTRAMICRO TO MESOPORE FRAMEWORKS FOR SELECTIVE SEPARATION AND STORAGE OF NOBLE GASES (iEdison No. 0685901-17-0011)
The global demand for xenon, a noble gas with applications in electronics, lighting, and the medical industry is expected to rise significantly over the next decades. However, the low abundance of xenon in earth's atmosphere and costly cryogenic distillation process that is used to obtain xenon commercially via air separation limited the scale of applications of xenon. A physisorption-based separation using porous materials may be a viable and cost-effective alternative to cryogenic distillation. In particular, open framework structures consists of organic, inorganic and metal organic materials have shown to be very promising for selective Xe removal at room temperature. We at PNNL have demonstrated, materials with small pore geometry are selective for Xe over other complex gas mixtures relevant to nuclear re-processing and from air. Similarly, materials with large pore consist of small and large pores relevant to Xenon recycle and re-use from medical anaesthetic gas mixture and semiconductor applications. Finally materials with high surface area are important for Xenon storage applications.
EMSL Arrows - Software Portal (Open Source)
The code receives requests to perform chemistry calculations. The received request is then compared to a database of existing calculations. Any additional needed calculations are then sent off to an appropriate computer for calculation using NWChem. For example, the calculation can be done using PIC's Olympus computer. Knowledge of the different computers is built into the software. Once all the necessary computations are done the result is returned to the sender. Right now the code receives requests via email. Requests can be single energies or reactions. The code also can scan twitter feeds for requested reactions.
TRANSFORMER POWER MANAGEMENT CONTROLLERS AND TRANSFORMER POWER MANAGEMENT METHODS
This method to use controllable loads (e.g., PEV charging rates) to determine the distribution transformer loading condition is unique. The process to calculate the distribution transformer load condition is described in the following steps: (1) Identify the transformer's full load core loss value (watts); (2) Identify the transformer's base load (e.g., 25kVA) and secondary voltage (e.g. 240VAC); (3) use the following equation representing the classical relationships between power, current and impedance (e.g., Power = Current2 * Impedance) to calculate the full load transformer impedance; Transformer Power = Impedance * [Nameplate Power (W) ]2 / [Nameplate Secondary Voltage (VAC)]2 (4) use the transformer base current and calculated full load impedance to determine the maximum transformer voltage drop before exceeding the transformer power limit; (5) implement a periodic A.C. line voltage measurement and control capability (e.g., 240VAC) that records the line voltage and minimizes the PEV charging rate during relative high A.C. voltage times to determine a second A.C. line voltage value; (6) the two A.C. voltage and power values are then used to calculate a no-load transformer voltage. This no-load A.C. voltage estimate can be used to verify transformer voltage remains above its minimum voltage and determine the transformer's current loading; (7) these controls take into account variations in no-load line voltage and can be as simple as a short-term (e.g., ~one-hour) history of the highest line voltage as most residential loads cycle within that time period.
SocialSim Metrics Library
We present example measurements obtained using approximately 3 years of GitHub data (aka GitHub training data): from January 2015 to August 2017. The original GitHub graph size is 52,260,372 nodes and 870,532,947 edges. We first subsampled the original GitHub graph to eliminate non-active user and repo nodes using weekly connected components implemented in networkX. The subsampled GitHub graph has 50,677,259 nodes and 773,974,620 edges. We present node-level measurement examples for popular repos e.g., tensorflow or rockstar users, and population-level measurement examples. See: https://confluence.pnnl.gov/confluence/display/SOCIALSIM/Implementing+Measurements
Magnesium-Based Energy Storage Systems and Methods Having Improved Electrolytes
Electrolytes for Mg-based energy storage devices can be formed from non-nucleophilic Mg2+ sources to provide outstanding electrochemical performance and improved electrophilic susceptibility compared to electrolytes employing nucleophilic sources. The instant electrolytes are characterized by high oxidation stability (up to 3.4 V vs Mg), improved electrophile compatibility and electrochemical reversibility (up to 100% coulombic efficiency). Synthesis of the Mg2+ electrolytes utilizes inexpensive and safe magnesium dihalides as non-nucleophilic Mg2+ sources in combination with Lewis acids, MRaX3-a (for 3≧a≧1). Furthermore, addition of free-halide-anion donors can improve the coulombic efficiency of Mg electrolytes from nucleophilic or non-nucleophilic Mg2+ sources.
USE OF CARBON METAL COMPOSITE MATERIAL FOR SURFACE TREATMENT TO IMPROVE SODIUM WETTABILITY ON SOLID STATE ELECTROLYTES (iEdison No. 0685901-21-0116)
This present invention reports a method for drastically improving sodium (Na) wettability on the surface of solid-state electrolytes, such as beta"-alumina solid-state electrolyte (BASE), to augment the performance of Na batteries at lower temperatures. This method describes modify the BASE surface by adding a thin composite layer consisting of carbon black and metal oxide/metal submicron particles. The overall surface treatment process is simple and easy for scaling up. Initially, the BASE surface is simply brushed with thick aqueous ink made of carbon black and metal compound precursors, and then followed by a heat treatment under an inert or a reducing environment.
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).
ION EXTRACTION AND FOCUSING FROM A FIELD-FREE REGION TO AN ION MOBILITY SPECTROMETER AT ATMOSPHERIC PRESSURE (iEdison No. 0685901-21-0100)
This invention was developed to improve ion movement at atmospheric pressure to enhance ion signal and reduce ion loss for mass spectrometry (MS) and ion mobility spectrometry (IMS). This invention is demonstrated with the atmospheric flow tube (AFT) and involves ion manipulation (e.g., extraction, focusing, and confinement) at atmospheric pressure. There are two components that have been observed to increase ion signal and reduce ion loss. The first is associated with combining the AFT with IMS, in which adjusting electric field gradients between the AFT and IMS improves ion extraction or focuses ions at atmospheric pressure. The second is by modifying the AFT to place a wire down the center of the length of the tube and applying either an AC or a DC voltage to this wire. Placing a square wave voltage on the wire increases ion throughput down the AFT to the detector compared to when the wire is at the same DC potential as the tube. The ability to manipulate ions is more pronounced at slower flows down the tube. Detailed description, figures, and data are provided in the attachment (Figures 1-7).