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Tuffner, Francis

Publications and source records attributed to Tuffner, Francis.

Inverter Model Validation and Calibration Using Phasor Measurement Unit Data

As the penetration of inverter-based renewable energy resources increases in the power grid, especially at the distribution and microgrid levels, the need to accurately represent them in planning studies increases as well. However, due to the lack of well-established standard procedures, and vendor reluctance towards the detailed sharing of proprietary models, automated dynamic model validation and parameter calibration tools for inverter based resources (IBRs) remain scarce. This work presents a model validation and parameter calibration platform for representing IBRs with generic phasor-domain models. Phasor measurements of power system events are used for continuous validation using the data playback method, and model parameters are re-calibrated if a significant mismatch between measurements and model response is observed. Unique features of the proposed platform include- (a) an iterative Bayesian optimization approach towards parameter calibration to address a possible mismatch between the structures of generic models implemented in simulation softwares and actual commercial inverters, (b) error metrics designed to account for a possible mismatch between the time resolution of simulation and measurements, and (c) analysis of the measurement-simulation mismatch to provide guidance to engineering personnel regarding model shortcomings. The performance of the platform has been illustrated using both simulated data and field measurements to validate/calibrate inverter models in GridLAB-D.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Grid Capacity – What is it, what determines it, does one number work, and how does it relate to electric vehicles?

Grid capacity is effectively how much power the system can reliably deliver, whether that is to serve loads (load service capacity) or accept generation (hosting capacity). Grid capacity can also mean different things at different scales. On the whole power system, grid capacity may be the maximum amount of power generation available. For a specific region, grid capacity may be limited by how much power the transmission and distribution lines can safely carry to that region. At the feeder level, it may be how much photovoltaic generation can be included before reliability or operations are impacted. At the end-use or residential level, grid capacity may be the size of the service breaker for that house.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Microgrid Modeling for Stability Analysis

Here this document is a summary of a report prepared by the IEEE PES Task Force (TF) on Microgrid (MG) Dynamic Modeling, IEEE Power and Energy Society, Tech. Rep. PES-TR106, 2023. In this paper, the major issues and challenges in microgrid modeling for stability analysis are discussed, and a review of state-of-the-art modeling approaches and trends is presented. In the context of the IEEE 1547 standard, the document covers issues associated with component models for MG dynamic studies and simulations, including generator and grid modeling, full and average converter models, unbalanced and balanced system conditions, dynamic and static loads, protection requirements, and detailed and simplified controls considering communications delays, packet losses, and security issues. Considering the future integration of grids and MGs to form broad integrated networks, a discussion is presented of the use of phasor vis-à-vis electromagnetic transient simulation tools for MG dynamic stability studies, as well as modeling scale-up issues and MG equivalent models. Specifically white-, grey-, and black-box models, are presented. This TF paper and companion report constitute a modeling guide for R&D groups working on developments and standards of MGs with a focus on stability issues.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Improving Resiliency for Electric Vehicle Charging

Electric vehicles are seeing growing adoption. However, challenges with range anxiety persists. While charging infrastructure is anticipated to expand, EV charger systems have not been as robust to challenges. This paper discusses potential outage conditions associated with EV charging and presents new technology in development to improve EV charging resilience.

Electric vehicle charging, electric vehicle chargi↗

Scoping Study on Research and Development Priorities for Distribution-System Phasor Measurement Units

This report addresses the potential use of phasor measurement units (PMUs) within electricity distribution systems, and was written to assess whether or not PMUs could provide significant benefit, at the national level. We analyze examples of present and emerging distribution-system issues related to reliability, integration of distributed energy resources, and the changing electrical characteristics of load. We find that PMUs offer important and irreplaceable advantages over present approaches. However, we also find that additional research and development for standards, testing and calibration, demonstration projects, and information sharing is needed to help industry capture these benefits.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Prony Ringdown GUI (CERTS Prony Ringdown, part of the DSI Tool Box)

The PNNL Prony Ringdown graphical user interface is one analysis tool included in the Dynamic System Identification toolbox (DSI Toolbox). The Dynamic System Identification toolbox is a MATLAB-based collection of tools for parsing and analyzing phasor measurement unit data, especially in regards to small signal stability. It includes tools to read the data, preprocess it, and perform small signal analysis. 5. Method of Solution: The Dynamic System Identification Toolbox (DSI Toolbox) is designed to provide a research environment for examining phasor measurement unit data and performing small signal stability analysis. The software uses a series of text-driven menus to help guide users and organize the toolbox features. Methods for reading in populate phasor measurement unit data are provided, with appropriate preprocessing options for small-signal-stability analysis. The toolbox includes the Prony Ringdown GUI and basic algorithms to estimate information on oscillatory modes of the system, such as modal frequency and damping ratio.

Tuffner, Francis↗

Modal Analysis for Grid Operation

MANGO software is to provide a solution for improving small signal stability of power systems through adjusting operator-controllable variables using PMU measurement. System oscillation problems are one of the major threats to the grid stability and reliability in California and the Western Interconnection. These problems result in power fluctuations, lower grid operation efficiency, and may even lead to large-scale grid breakup and outages. This MANGO software aims to solve this problem by automatically generating recommended operation procedures termed Modal Analysis for Grid Operation (MANGO) to improve damping of inter-area oscillation modes. The MANGO procedure includes three steps: recognizing small signal stability problems, implementing operating point adjustment using modal sensitivity, and evaluating the effectiveness of the adjustment. The MANGO software package is designed to help implement the MANGO procedure.

Zhou, Ning↗