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62 records · Page 4

GLIMPSE of Future Power Grid Models

Power grid is one of the critical national infrastructures with social, economics, and national security impacts. Particularly, power distribution systems represent part of the infrastructure between power distribution substations and customers such as residential, commercial, and industrial. To address various grid modernization challenges, state-of-the-art algorithms and methodologies have been developed to deploy, operate, and expand a secure and resilient power grid. At the same time, there is a need to develop capabilities to assist power grid stakeholders to quickly get insight into the design and structure of the grid. Data visualization is a key approach to comprehend and understand complex systems such as the power grid. We present GLIMPSE Grid Layout Interface for Model Preview and System Exploration), a graph-based semantic-aware application to visualize and update distribution power grid models. The GLIMPSE can be used with standard IEEE models to search and highlight power grid objects such as generators, loads, overhead lines, etc. Additionally, it supports updating attributes and model export to integrate with GridLAB-D simulations.

Cybersecurity, power grid, visualization↗

Per-phase Phasor Modeling of GFL and GFM Inverters for Distribution System Dynamic Studies

A significant increase in inverter-based distributed energy resources (DERs) is expected in the near future. Existing electromagnetic models and sequential electromechanical models of DERs supporting dynamic analysis cannot be extended to largescale three-phase distribution systems usually with unbalanced construction. As such, there is a need for appropriate industry models that can support distribution system dynamic studies. This paper describes the latest phasor models of grid-following (GFL) and grid-forming (GFM) inverters that can capture distribution system dynamics under grid disturbances. The overall modeling performance is examined and compared with results from other platforms such as controller hardware-in-the-loop (CHIL), MATLAB/Simulink and PSCAD with electromagnetic transient (EMT) and/or phasor simulation capabilities under balanced and unbalanced faults.

Distribution system, Grid modelling, GridLAB-D, Po↗

Evaluating Synthetic Smart Meter Locations For Communication System Modeling

An important part of good communication models for smart grid applications, particularly when wireless protocols are used, is the location information of the nodes. We’ve developed metrics to assist in evaluating whether a given model with such information is representative of feeders found in the world. These metrics are applied to a set of feeder models with known good location information for the smart meter locations and compared to a set of feeder models with similar location information that is not expected to be representative of real-world feeders. The comparison reveals that the suspect models do not pass statistical tests utilizing the developed metrics, providing initial validation of the analysis technique.

smart meter, feeder model, GridLAB-D↗

Grid Friendly Appliance Controllers to Increase the Dynamic Stability of Networked Resiliency-based Microgrids

Microgrids provide the ability to maintain service to critical end-use loads when utility service is not available. Despite their ability to increase resiliency, they can have high capital and operating costs; this can be compounded by the complexities associated with low inertia systems. One option to mitigate the costs is to more effectively engage the assets within the microgrids, specifically the end-use loads. Previous work has shown that by using Grid Friendly™ Appliance controllers, it is possible to increase the dynamic stability of multiple microgrids during switching transients, without the need to oversize generation assets or to install energy storage devices. Building on the previous work, this paper will present a method for determining the set-points of decentralized controllers, accounting for the different characteristics and sizes of loads, to facilitate multiple microgrid switching operations. By effectively engaging the end-use load as a resource, the switching operations necessary to network low inertia microgrid for resiliency applications can be supported without the need to oversize generation assets or for energy storage.

GridLAB-D, Distribution Analysis↗

Modeling Load Dynamics to Support Resiliency-based Operations in Low-Inertia Microgrids

Microgrids have repeatedly demonstrated the ability to provide uninterrupted service to critical end-use loads during normal outages, severe weather events, and natural disasters. While their ability to provide critical services is well documented, microgrids present a more dynamic operational environment than grid-connected distribution systems. The dynamics of a microgrid are commonly driven by the high inertia of rotating generators, which are common in many microgrids. In such high-inertia systems, the impact of end-use load dynamics are often not examined. However, with the increased penetration of inverter-based generation with little or no inertia, it is necessary to consider the impact that the dynamics of the end-use loads have on the operations of microgrids, particularly for a resiliency-based operation. These operations include, but are not limited to, switching operations, loss of generating units, and the starting of induction motors. This paper examines the importance of including dynamic models of the end-use load when evaluating the operations of low inertia microgrids, and shows that by properly representing their behavior, it is possible to cost effectively size equipment while supporting resilient operations of critical end-use loads.

Tuffner, Francis K.↗

Improving Distribution Resiliency with Microgrids and State and Parameter Estimation

Modern society relies on low-cost reliable electrical power, both to maintain industry, as well as provide basic social services to the populace. When major disturbances occur, such as Hurricane Katrina or Hurricane Sandy, the nation’s electrical infrastructure can experience significant outages. To help prevent the spread of these outages, as well as facilitating faster restoration after an outage, various aspects of improving the resiliency of the power system are needed. Two such approaches are breaking the system into smaller microgrid sections, and to have improved insight into the operations to detect failures or mis-operations before they become critical. Breaking the system into smaller sections of microgrid islands, power can be maintained in smaller areas where distribution generation and energy storage resources are still available, but bulk power generation is no longer connected. Additionally, microgrid systems can maintain service to local pockets of customers when there has been extensive damage to the local distribution system. However, microgrids are grid connected a majority of the time and implementing and operating a microgrid is much different than when islanded. This report discusses work conducted by the Pacific Northwest National Laboratory that developed improvements for simulation tools to capture the characteristics of microgrids and how they can be used to develop new operational strategies. These operational strategies reduce the cost of microgrid operation and increase the reliability and resilience of the nation’s electricity infrastructure. In addition to the ability to break the system into microgrids, improved observability into the state of the distribution grid can make the power system more resilient. State estimation on the transmission system already provides great insight into grid operations and detecting abnormal conditions by leveraging existing measurements. These transmission-level approaches are expanded to using advanced metering infrastructure and other distribution-level measurements to create a three-phase, unbalanced distribution state estimation approach. With distribution-level state estimation, the grid can be operated more efficiently, and outages or equipment failures can be caught faster, improving the overall resilience and reliability of the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Introducing FNCS: Framework for Network Co-Simulation

This video provides a basic overview of the PNNL Future Power Grid Initiative-developed Framework for Network Co-Simulation (FNCS). It discusses the increasing amounts of data coming from the power grid, and the need for a tool like FNCS that brings together data, transmission and distribution simulators. Included is a description of the FNCS architecture, and the advantages this new open source tool can bring to grid research and development efforts.

24 POWER TRANSMISSION AND DISTRIBUTION↗