Current Projects


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M-47: Enhancing Resource Adequacy Accreditation and Operational Incentives for Energy-Limited Resources (ending July 2026)

Summary Resource adequacy has been a central concern of liberalized electricity markets since their inception, with concern only growing due to greater frequency of extreme weather events and ambitious goals for decarbonization. Increasingly, it is expected that systems will rely on energy-limited resources, such as storage, to help ensure reliable and resilient grid operations during emergency events. However, existing methods for resource adequacy accreditation are inconsistent with the market incentives provided for energy-limited resources during scarcity events, potentially leading to inconsistencies between system needs and private profit maximization and, therefore, challenges in ensuring reliable operations. This project aims to address the practical and theoretical challenges raised by the incorporation of energy-limited resources in resource adequacy mechanisms, including consideration of factors related to operational uncertainty, financial risk, and market power mitigation. 
Academic Team Members Project Leader: Jacob Mays (Cornell,
Team members: Josue Campos do Prado (Washington State, and Elnaz Kabir (Texas A&M,
Industry Team Members Jessica Kuna (NREL), Akshay Korad (MISO), Eduardo Ibanez (MISO), Dustin Grethen (MISO), Anthony Giacomoni (PJM), Nikita Singhal (EPRI), Jo Ann Rañola (EPRI), Mike Swider (NYISO), Kurt LaFrance (CMS Energy), Sara Walz (CMS Energy), Becky Robinson (CAISO)
Project Period August 1, 2024 to July 31, 2026

M-46: Toward Large-Scale DER Aggregation: Competitive Aggregation, Operation Support, and ISO-Aggregator-Utility Coordination (ending August 2025)

Summary This project focuses on the practical challenges of DER aggregations for wholesale market participation under FERC Order 2222. We propose a bottom-up approach to address key technological barriers at the interfaces between (a) a DER aggregator (DERA) and its customers where generation, storage, and flexible demand resources are aggregated;  (b) a DERA and a market operator (ISO) where DERAs participate in wholesale energy, reserve and regulation markets; (c)  a DERA and a distribution utility where the utility provides planning and operation support for delivering the aggreged DER; (d) a utility and an ISO where the ISO maximizes net benefits of market participants and mitigates risk subject to system constraints. In particular, this project investigates large-scale, competitive, and profit-maximizing aggregation technologies that benefit DERA customers more than the prevailing net energy metering-based retail tariffs. The project examines the impacts of DER aggregation uncertainties at all interfaces and develops risk mitigation strategies. The project investigates distribution system planning and operation solutions supporting DER aggregation, DERA bidding strategies in the wholesale markets, and ISO market clearing and settlement solutions. The project delivers technical assessments and comparative studies on the feasibility and cost/benefit analysis. 
Academic Team Members Project Leader: Lang Tong (Cornell,
Team members: Tim Mount (Cornell,, Subhonmesh Bose (UIUC,, and Meng Wu (Arizona State,
Industry Team Members Mike Swider (NYISO), Tongxin Zheng (ISO-NE), Jianzhong Tong (PJM), Hong Chen (PJM), Clyde Loutan (CAISO), Yonghong Chen (MISO), Anupam Thatte (MISO), Akshay Korad (MISO), Arezou Ghesmati (MISO), Patrick Dalton (MISO), Megan Pamperin (MISO), Patrick Panciatici (RTE) Ahmed Zamzam (NREL), Bo Yang (Hitachi), Yanzhu Ye (Hitachi), Ryan Fox (GE), Harvey Scribner (SPP), Nikita Singhal (EPRI), Ibrahim Krad (EPRI), Nitin Padmanabhan (EPRI), Arun Sukumaran Nair (Eaton)
Project Period July 1, 2023 to August 31, 2025

M-45G: Bidding Generation Tool (ending January 2024)

Summary The new FERC Order 2022 has paved the way for market participation of DERs through aggregators. Although these aggregators can now be market players, they are unlike the normal traditional generation participating in bulk power system services. These DERs can provide both distribution services as well as bulk system services. A new framework is being investigated and developed through this work where a bidding generation tool will be created to develop bids, optimizing distribution and wholesale market participation.
Academic Team Members Project Leader: Mojdeh Khorsand (Arizona State,
Industry Team Members Abrez Mondal (EPRI), Nikita Singhal (EPRI), Ahmed Saad (EPRI)
Project Period November 1, 2022 to January 31, 2024

M-44: The Future of Markets and DERs: Providing Essential Grid Services and Managing Performance Risk (ending August 2024)

Summary FERC Order 2222 mandates incorporation of distributed energy resources (DERs) in wholesale markets. With this new requirement, one main power systems change is the push towards not just DER integration but also the reliance on these resources to be able to provide essential grid services. Electricity markets, grid operations, and reliability requirements are designed for classical assets, not emerging assets with distinct characteristics, i.e., higher probability of failure, lower capacity firmness, and lower impact of failure. This project addresses the concern of DER integration from multiple fronts: a) effective aggregation and management of DERs to ensure their profitability and the quality of services provided by these aggregated resources, b) essential market and operational reform, and c) coordination of transmission and distribution services provided by DERs. This project will develop a virtual power plant DER aggregation strategy to demonstrate that, while DERs possess new challenges in comparison to conventional assets, they can be optimally managed such that they perform similar to conventional assets. An intra-day DER evaluator module will be developed to assess whether the aggregated DER will be able to satisfy their offering to ensure a high level of real-time performance during both normal and outlier/extreme events. Moreover, this project provides an effective transmission and distribution coordination strategy by leveraging untapped flexibilities such as optimal mode of operation and setpoint identification of smart inverters within the allowable range of IEEE 1547.  
Academic Team Members Project Leader: Kory W. Hedman (Arizona State,
Team members: Mojdeh Khorsand (Arizona State, and Shmuel Oren (UC Berkeley,
Industry Team Members Oluwaseyi Akinbode (MISO), Guillermo Bautista Alderete (CAISO), Sumit Bose (GE), Hong Chen (PJM), Yonghong Chen (MISO), Kwok Cheung (GE), Richard Dillon (SPP), Erik Ela (EPRI), Jesse Gantz, (GE), Anthony Giacomoni (PJM), Bo Gong (SRP) Majid Heidarifar (EPRI), Avnaesh Jayantilal (GE), Akshay Korad (MISO), Sobia Naqvi (APS), Dane Schiro (ISO-NE), Nikita Singhal (EPRI), Yohan Sutjandra (The Energy Authority), Arun Nair (Eaton), Clyde Loutan (CAISO)
Project Period July 1, 2022 to August 31, 2024

M-43: Integrating RTO and utility processes in planning and cost allocation (ending August 2024)

Summary We address resource and transmission (R&T) investment planning methods, focusing on four objectives: (1) Determine ways new software tools can facilitate long-term planning while exploring interdependencies within RTO interconnection queues, transmission expansion processes, capacity markets, and interregional transmission considerations; (2) Implement a reliability evaluation toll that coordinates with a long-term expansion planning application, explicitly accounting for utility-scale renewables, storage, and DER. (3) We will test an implementation of our tools using large-scale industry-size models, developing results to illustrate relationships between investment robustness, resource adequacy, and operational flexibility. (4) Develop a new cost allocation approach which incorporates investment robustness in identifying benefit.
Academic Team Members Project Leader: James McCalley (Iowa State,
Team members: Jacob Mays (Cornell,, Lizhi Wang (Iowa State,
Industry Team Members Wes Hall (GE), Eduardo Ibanez (GE), Yifan Li (MISO), Haifeng Liu (CAISO), Harvey Scribner (SPP), Casey Cathey (SPP), Greg Brinkman (NREL), Anthony Giacomoni (PJM), Patrick Panciatici (RTE), Anish Gaikwad (EPRI), Parag Mitra (EPRI), Miguel Ortega-Vazquez (EPRI), Mohamed Osman (NERC)
Project Period July 1, 2021 to August 31, 2024


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S-111: Multiple Event Recordings for Grid Evaluation (MERGE) (ending July 2026)

Summary Complex electric grid disturbances require comprehensive assessment to determine whether the disturbances may lead to contingencies such as oscillations, instability, cascades, or relay misoperations. The typical utility substation equipment that captures recordings of field events are phasor measurement units (PMUs), digital protection relays (DPRs), digital fault recorders (DFRs), and sequence of event recorders (SoEs). This project focuses on the use of ML/AI to develop automated analysis of multiple event recordings for grid evaluation (MERGE) during disturbances. MERGE’s special emphasis will be on the use of Point-on-wave (PoW) triggered and/or streaming data to enhance the grid performance assessmentIt is an extension of the ongoing DECODE project that uses ML/AI to automatically analyses PMU data. MERGE extends the application of ML/AI to the POW data and merges such results with the results of automated analysis using phasors for a comprehensive view of fast and slow changing waveforms reflecting evolving disturbance dynamics. The automated tracking of a combination of fast and slow changing transients is the MERGE’s novel feature not tackled before. MERGE Illustrates how such studies may be utilized for operations, planning, engineering, or protection applications. 
Academic Team Members Project Leader: Mladen Kezunovic (TAMU,
Team members: Vijay Vittal (Arizona State,, Mani Venkatasubramanian (Washington State,, and Anamitra Pal (Arizona State,
Industry Team Members Evangelos Farantatos (EPRI), Lin Zhu (EPRI), Tongxin Zheng (ISO-NE), Rui Yang (NREL), Jianzhong Tong (PJM), Gilles Torresan (RTE), Justin Lee (SRP), Matthew Rhodes (SRP)
Project Period August 1, 2024 to July 31, 2026

S-110: Data-Driven Resilience Modeling, Prediction, and Enhancement (ending July 2026)

Summary New analytics that quantify the risk of extreme events and relate this to engineering decisions are needed to sensibly invest in grid resilience and to be able to advocate for these investments based on data. We propose a comprehensive framework to model and quantify grid resilience from historical data, and exploit it to predict resilience performance under various extreme events, evaluate DERs’ impacts on resilience, and optimize infrastructure investments to enhance resilience. Our framework leverages outage and restoration data that is already recorded by PSERC utilities as well as weather data to quantify resilience metrics and estimate probability distributions of these metrics with respect to weather variables for optimal resilience-oriented investments. Compared to existing work that relies only on detailed models, our framework will overcome difficulties of simulation of resilience based on detailed models by leveraging statistical models driven by real utility data, thus making it faster, more realistic, and easier to implement  
Academic Team Members Project Leader: Ian Dobson (Iowa State,

Team members: Zhaoyu Wang (Iowa State, and Anamika Dubey (Washington State,

Industry Team Members Jianzhong Tong (PJM), Jay Liu (PJM), Hong Chen (PJM), Haifeng Liu (CAISO), Yoshihisa Okamoto (Hitachi), Fei Ding (NREL), Atena Darvishi (NYPA), Venkat Banunarayanan (NRECA), Svetlana Ekisheva (NERC), Anupam Thatte (MISO), Ruchi Rajasekhar (MISO)
Project Period August 1, 2024 to July 31, 2026

S-109G: Impact Analysis of Synchronous Generators and Inverter-Based Resources on System Modes (ending June 2025)

Summary With large-scale integrations of renewable energy sources, the dynamics of the power systems is becoming more complex in power grids all over the world. Fast dynamic controls and switches that are built into the newer power electronic-based energy interfaces are interacting with the traditional power grid controls in unpredictable ways. These complex and non-smooth dynamic mechanisms are impacting the small-signal stability properties of bulk power systems. This project will focus on the impact analysis of inverter-based resources (IBRs) and synchronous generators on the damping properties of system modes. The project will assess the overall contribution of the increased presence of IBRs in medium-scale power system models. The project will also develop novel signal theoretic algorithms for estimating the impact of synchronous machines and IBRs on the damping levels of interarea modes using ambient synchrophasor measurements.
Academic Team Members Project Leader: Vaithianathan (Mani) Venkatasubramanian (Washington State,
Industry Team Members Patrick Panciatici (RTE), Gilles Torresan (RTE), Adrien Guironnet (RTE)
Project Period June 16, 2023 to June 15, 2025

S-108G: Guidelines for Voltage Stability Assessment on Systems with Large Integrations of IBRs (ending August 2024)

Summary Large integration of renewable variable generation and inverter-based resources (IBR) alters the system’s response to contingencies and fault events, and consequently the ability of the system to preserve stable operation under critical conditions. Renewables and IBRs affect voltage stability in various ways, and consequently the methodologies and simulation tools used for the assessment of voltage stability and control. To address these challenges, this project will develop practical guidelines for power system operation and planning engineers to perform voltage stability assessment in transmission systems, especially in conditions where large penetration of IBRs (in the transmission and distribution grids) affects the behavior and response of the bulk power system. This project is intended to initiate the development and implementation of various improved methodologies and tools for voltage stability assessment.
Academic Team Members Project Leader: Amarsagar Reddy Ramapuram Matavalam (Arizona State,
Industry Team Members A.D. Rosso (EPRI)
Project Period July 1, 2023 to August 31, 2024

S-107: Adaptive Transmission and Distribution Modeling and Simulation Tools for Supporting Integration and Operation of High Penetration of DERs (ending August 2025)

Summary As the implementation of FERC Order 2222 is coming and DERs proliferate, it is imperative to (i) adequately model and efficiently analyze the dynamic impacts of DERs on transmission and distribution (T&D) systems, (ii) capture and leverage full capabilities of DER to facilitate large-scale DER integration and T&D system operation. This project 1) Develops adaptive, multi-fidelity modeling and AI-accelerated co-simulation approaches to improve the computational efficiency of dynamic simulation for large-scale T&D systems; 2) Builds an automated tool to create a multi-fidelity model library for adequately representing distribution systems and DERs while maintaining consistency for different dynamic and transient studies; 3) Derives aggregated reactive power capability curves at T&D interfaces by considering DER control capabilities and leverages them to provide reactive power ancillary services. The main outcomes will be open-source tools that help industry members efficiently plan and reliably operate their systems with high penetration of DERs. 
Academic Team Members Project Leader: Qiuhua Huang (Colorado School of Mines,
Team members: Venkataramana Ajjarapu (Iowa State,, Meng Wu (Arizona State,
Industry Team Members Kwok Cheung (GE), Panitarn (Joseph) Chongfuangprinya (Hitachi), Hung-Ming Chou (Dominion Energy), Bo Gong (SRP), Akshay Korad (MISO), Weijia Liu (NREL), Yi Liu (Eaton), Parag Mitra (EPRI), Alberto Del Rosso (EPRI), Deepak Ramasubramanian (EPRI), Harvey Scribner (SPP), Mohit Singh (ComEd), Sid Suryanarayanan (Eaton)
Project Period July 1, 2023 to August 31, 2025

S-106: Data-Driven Stability Analysis of IBR-rich Grids with hybrid EMT+Phasor models (ending August 2025)

Summary We propose to develop tools for stability analysis of inverter-based resources (IBR)-rich grids represented by hybrid electro-magnetic transient (EMT) and phasor models for planning and operations to (i) localize the cause of instabilities, and (ii) identify limits on transfer flows and IBR injection for secure grid operation. As a result, we directly address NERC recommendations that recognizes the importance of EMT modeling within stability studies. Conventional stability assessment tools currently used by the industry do not support hybrid multi-timescale models, necessitating this work. We will build upon our preliminary results that merge concepts from data-science and dynamical systems to perform transient-stability analysis purely from time-domain simulation results of the hybrid models. The analysis can be used to guide the development of a comprehensive stability assessment tool that will augment the intuition of the planner/operator in identifying critical grid assets. We will validate the proposed methods on network models developed by DOE/NREL.  
Academic Team Members Project Leader: Amarsagar Reddy Ramapuram Matavalam (Arizona State,
Team members: Vijay Vittal (Arizona State,, Subhonmesh Bose (UIUC,
Industry Team Members C. Mishra (Dominion Energy), J.D.L. Ree (Dominion Energy), P. Mitra (EPRI), D. Ramasubramanian (EPRI), W. Baker (EPRI), E. Farantatos (EPRI), S. Akinbode (MISO), R. Rajasekhar (MISO), M. Pamperin (MISO), P. Dalton (MISO), B. Gong (SRP), H. Scribner (SPP), M. Parashar (GE), K. Cheung (GE), M. Singh (ComEd), R. Jain (NREL)
Project Period July 1, 2023 to August 31, 2025

S-105: Integration of Protection and Control Systems in Dynamic Security Assessment Methods (ending August 2025)

Summary The protection and control (P&C) system has been the top contributor to system disturbances as consistently shown in the annual NERC reports. This reality is expected to continue and worsen as the penetration level of inverter based resources (IBRs) increases. Specifically, IBRs change the characteristics of the system response during faults and disturbances: reduced fault currents, reduced negative and zero sequence components of fault currents and faster transients. The performance of many legacy protection schemes will deteriorate and mis-operations will increase. We propose to develop a framework for assessing the impact of P&C schemes on the security of the system as the presence of IBRs increases. An effective tool for this purpose, is our proposed co-model of the power system and the P&C system that will enable quantification of the interactions between these two systems. By necessity, the co-model will be a three-phase, breaker-oriented, physically-based, P&C inclusive system for analysis of system response during fault conditions. For post fault DSA, we propose the automatic extraction of the RMS-EMT co-model  from the above described model. The approach will enable to assess the vulnerability of the system to common mode outages, cascading events, effects from circuit breaker failures, effects of hidden failures and cyber-attacks on the P&C system. Two novel dynamic security assessment methods are proposed based on the co-model: (a) a stability assessment method based on identification of the center of oscillations and the energy method and (b) Artificial Intelligent (AI) based approach to selectively identify critical outage scenarios for further analyses. The proposed work will also provide the framework for power system resiliency analysis by developing effective quantifiable resiliency metrics. 
Academic Team Members Project Leader: A. P. Meliopoulos (Georgia Tech,
Team members: Mojdeh Khorsand Hedman (Arizona State,
Industry Team Members Evangelos Farantatos (EPRI), Paul Myrda (EPRI), Bruce Fardanesh (NYPA), Kumaraguru Prabakar (NREL), Bo Gong (SRP), Akshay Korad (MISO), Yonghong Chen (MISO), Jianzhong Tong (PJM), Cheung Kwok (GE), Harvey Scribner (SPP), David Till (NERC)
Project Period July 1, 2023 to August 31, 2025

S-104G: Data Development & Composite Probabilistic Adequacy Evaluation (ending December 2024)

Summary The objective of this project is to develop and illustrate a functional system of data development and probabilistic adequacy assessment to enable planners in organizations such as the New York Power Authority to evaluate the adequacy of their generation and transmission systems and use this evaluation to inform planning-related decision-making.
Academic Team Members Project Leader: James McCalley (Iowa State University,
Industry Team Members Shayan Behzadirafi (NYPA)
Project Period January 1, 2023 to December 31, 2024

S-103G: Oscillation Analysis with SCADA using Inferential Statistics (OASIS) (ending August 2024)

Summary This project will develop rigorous statistical methods that can use widely available SCADA measurements for the detection and analysis of power system oscillations. Even though millions of SCADA measurements are available in a typical power utility company, they are used mostly for quasi-steady-state analysis in the present-day power system owing to their slow sampling rate. In this project, we propose the use of SCADA for detecting problematic dynamic oscillations in the power grid.  This is accomplished by exploiting the asynchronous sampling inherent in SCADA technology. While the oscillation period cannot be determined from SCADA data as implied by the sampling Theorem, the inferential statistical formulation will enable estimating the oscillation amplitude at a specified confidence level. In this project, we will develop the statistical algorithms for SCADA-based oscillation detection and analysis by estimating the amplitude of oscillations in power plant outputs and transmission line power flows and test the methodology using simulations and archived SCADA data from RTE France.
Academic Team Members Project Leader: Vaithianathan (Mani) Venkatasubramanian (Washington State University,
Industry Team Members Patrick Panciatici (RTE), Gilles Torresan (RTE), Marie-Sophie Devry (RTE)
Project Period September 1, 2022 to August 31, 2024

S-102G: Second Stage in Feasibility Assessment of Synchronous Operations of the North American Eastern and Western Interconnections (ending January 2024)

Summary This project will focus on the second stage in considering the feasibility of synchronous operations of the actual North American Eastern and Western Interconnections, along with an analysis using the synthetic versions of each of these interconnects. The idea is to build on the work of the previous SPP funded PSERC project (S-92G) with a greater focus in this project on the economic benefits of such an interconnection.
Academic Team Members Project Leader: Thomas J. Overbye (Texas A&M University,
Team members: Farnaz Safdarian (Texas A&M University,, Jonathan Snodgrass (Texas A&M University,
Industry Team Members Harvey Scribner (SPP), Casey Cathey (SPP)
Project Period August 15, 2022 to January 31, 2024

S-101G: Comparison of Positive-Sequence Simulation Versus Three-Phase Simulation of IBRs and Rotating Loads in Time Domain Simulation (ending August 2024)

Summary This project compares positive-sequence time domain simulation of IBRs in power systems versus three-phase simulation of IBRs.
Academic Team Members Project Leader: Vijay Vittal (Arizona State,
Team members: Mojdeh Hedman (Arizona State,
Industry Team Members Deepak Ramasubramanian (EPRI), Parag Mitra (EPRI), Jens Boemer (EPRI), Anish Gaikwad (EPRI)
Project Period July 1, 2022 to August 31, 2024

S-100: Detection, Characterization, and Mitigation of Disruptive Events (DECODE) by Combining Machine Learning/Artificial Intelligence on Synchrophasors and Physics-based Analysis (ending August 2024)

Summary To leverage over 20 years of research that used physics-based analysis to correlate synchrophasor data to disruptive events, we propose to develop the automated tools by combining various data-based and physics-based solutions in real-time to help system operators detect and classify faults, oscillations, impending instability, and other events that may lead to system emergencies. To achieve this goal, the project:  1) Offers data wrangling techniques for collecting large synchrophasor historical datasets to improve bad data detection, feature engineering, and event label assignment for automated ML/AI solutions; 2) Defines the most effective ML/AI techniques for unsupervised, supervised, semisupervised, and transfer learning solutions, and 3) Combines ML/AI-based and physics-based solutions for cost-effective and computationally efficient automated event characterization, 4) Implements the tool that ranks operator actions to mitigate the events as needed. 
Academic Team Members Project Leader: Mladen Kezunovic (Texas A&M,
Team members: Vijay Vittal (Arizona State,, Mani Venkatasubramanian (Washington State,, Anamitra Pal (Arizona State,
Industry Team Members Casey Cathey (SPP), David Riekel (Hubbell), Bajarang Agrawal (APS), Bo Yang (Hitachi), Jianzhong Tong (PJM), Evangelos Farantatos (EPRI), Tongxin Zheng (ISO-NE), Ben Kroposki (NREL), Bo Gang (SRP), Gilles Torresan (RTE), Arun Nair (Eaton)
Project Period July 1, 2022 to August 31, 2024

S-99: Incorporating climate impacts into electricity system planning models: review and case study (ending August 2024)

Summary The impacts of climate change on the U.S. electricity system are increasingly tangible, but current electricity system models are not well equipped to analyze the new types of common mode events driven by a changing climate. This project seeks to comprehensively survey climate-change-related extreme events and identify common mode impacts on the grid, as well as how these integrate into electricity system planning models. After identifying knowledge gaps and the current state of the art, we will select a case study (type of extreme event and regional extent) and create scenarios for use in grid modeling. Focusing on this case study, we will extend current electricity modeling capabilities to incorporate the relevant climate change scenario and address questions across time scales ranging from real-time operation to long-term planning. The outcomes will be open source tools and publications that seek to advance modeling capabilities for understanding climate-forced extreme event impacts on power systems.
Academic Team Members Project Leader: Ana Dyreson (Michigan Tech,
Team members: Line Roald (Univ. of Wisconsin-Madison,, Thomas Overbye (Texas A&M,, Hao Zhu (Univ. of Texas,
Industry Team Members Aftab Alam (CAISO), Don Lynd (CMS), Laura Fischer (EPRI), Eknath Vittal (EPRI), Xiaochuan Luo (ISO-NE), Jinye Zhao (ISO-NE), Akshay Korad (MISO), Felicia Ruiz (MISO), Barry Mather (NREL), Mike Swider (NYISO), Laurent Dubus (RTE), Bo Gong (SRP), Stanley Palmer (WAPA), Stacy Russ (WAPA), Ron Horstman (WAPA)
Project Period July 1, 2022 to August 31, 2024

S-98G: Model reduction and translation for coordinated expansion planning studies (ending August 2024)

Summary The objective of this project is to develop an integrated grid reduction/translation package to facilitate application of expansion planning software on large industry-grade planning models, where reduction provides a reduced-order network, together with economic data and line limits, and translation identifies investments made on the reduced model in terms of the original large planning model.
Academic Team Members Project Leader: James McCalley (Iowa State University,
Team members: Ali Jahanbani Ardakani (Iowa State University,
Industry Team Members Xavier Florent (RTE), Patrick Panciatici (RTE)
Project Period September 1, 2021 to August 31, 2024

Transmission and Distribution Technologies (T&D):

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T-69: Grid Integration and Interoperability Evaluation of Multi-Vendor IBRs and Protection Systems for Reliable Power Grid Operation (ending July 2026)

Summary Power grids hosting high shares of heterogeneous inverter-based resources (IBRs) equipped with grid following and grid forming controllers coming from variety of manufacturers will become more prevalent in the future. This trend is driven by the increasing adoption of large-scale IBRs such as solar and wind generation, and battery energy storage systems. The controllers in such a heterogeneous system of IBRs interact with protection systems that may also be supplied by different vendors. Ensuring verifiable grid integration and interoperability of the controllers in such a complex multi-vendor system is of crucial importance. Accordingly, standards and grid code requirements are introduced and updated to meet such needs. Notably, the recently approved IEEE Std 2800-2022 defines the IBR interconnection requirements.  

The objective of this project encompasses two primary goals: (1) To devise a comprehensive approach for confirming performance requirements and assessing the configurations of IBR controllers in grid interconnection studies, while taking into account the interactions among heterogeneous IBRs and their interactions with protection systems, and (2) To put forth a methodology for evaluating and enhancing the interoperability, dependability, and security of protection systems in such heterogeneous IBR dominated power grids that comply with the IEEE Std 2800-2022 requirements.  

We will demonstrate and validate the proposed solutions and findings through use case scenarios defined and implemented using modeling and simulation, and further validate actual relay interactions using a system in the loop (SIL) platform. The platform will be used to: a) emulate IBR controllers in a Typhoon simulator interfaced in real-time to the power system model implemented in an RTDS. This will allow us to validate the IBR integration requirements b) use actual protective relays connected to RTDS with the Typhon IBR-emulated interface to study the interaction between IBRs and relays during power grids disturbances.   

The outcomes of this project can help the system operators and planners, as well as IBR and relay vendors to validate IBR grid integration studies and demonstrate how interoperability of IBRs and relays may affect power systems reliability. The outcomes may further inform development of IBR grid codes, as well as interconnection and interoperability standards, including future revisions of or supplements to IEEE Std 2800. 

Academic Team Members Project Leader: Saeed Lotfifard (Washington State,
Team members: Mladen Kezunovic (TAMU,
Industry Team Members Kurt LaFrance (CMS Energy), Evangelos Farantatos (EPRI), Aboutaleb Haddadi (EPRI), Mahendra Patel (EPRI), Dongbo Zhao (Eaton), Kwok Cheung (GE), Deepak Konka (GE), Chongfuangprinya Panitarn (Hitachi), Xiaochuan Luo (ISO-NE), Akshay Korad (MISO), Venkat Banunarayanan (NRECA), Ben Kroposki (NREL), Bruce Fardanesh (NYPA), Jianzhong Tong (PJM), Casey Cathey (SPP), Bo Gong (SRP)
Project Period August 1, 2024 to July 31, 2026

T-68: Advancing Control, Protection, and Stability in Hybrid AC/DC Grids (ending July 2026)

Summary While DC and AC transmission have coexisted for decades, the emergence of hybrid AC/DC networks has introduced new challenges and opportunities in transmission and distribution. Hybrid AC/DC networks have the potential to improve resilience and efficiency but face the formidable task of maintaining stability while regulating AC frequency and DC voltages. The interactions between DC grids and host AC grids remain poorly understood. The absence of effective stability analysis tools and a clear understanding of root causes for instabilities in such hybrid systems exacerbates these complexities. Additionally, there is a lack of research on fault characteristics and protection strategies for these hybrid systems. This research aims to explore integrated control, resilience and reliability assessment, and protection of hybrid AC/DC systems, tackling the challenges they pose and developing innovative strategies for their smooth integration, stable operation, control, and protection.  
Academic Team Members Project Leader: Maryam Saeedifard (Georgia Tech,
Team members: Dominic Groß (UWisc,
Industry Team Members Kwok Cheung (GE), Bo Gong (SRP), Alberto Del Rosso (EPRI), Geoff Love (EPRI), Benjamin Kroposki (NREL), Dongbo Zhao (Eaton), Thibault Prevost (RTE), Rambabu Adapa (EPRI), Philip Hart (GE), Ahmad Tbaileh (ISO-NE), Nathanael Martin-Nelson (MISO)
Project Period August 1, 2024 to July 31, 2026

T-67: Smart Meter-Driven Distribution Grid Visibility and Control (ending August 2025)

Summary To unlock the capabilities of smart meters for distribution system applications, this project will develop data-driven models for distribution systems and associated algorithms for real-time state estimation and control applications. The project will use actual smart meter data from Hubble and consider practical limitations on communication bandwidth in both developing and validating the proposed models and algorithms. 
Academic Team Members Project Leader: Daniel Molzahn (Georgia Tech,
Team members: Line Roald (UW Madison,, Dan Fuhrmann (Michigan Tech,
Industry Team Members David Rieken (Hubbell), Kurt LaFrance (CMS Energy), Venkat Banunarayanan (NRECA), Bo Gong (SRP), Dongbo Zhao (Eaton), Shakil Hossan (Eaton), Arun Sukumaran Nair (Eaton), Benjamin Kroposki (NREL), Jouni Peppanenlectric (EPRI), Mohit Singh (ComEd)
Project Period July 1, 2023 to August 31, 2025

T-66: Modeling, Characterization and Suppression of Temporary Overvoltages in Power Grids with High Share of Inverter-Based Resources (ending August 2024)

Summary The recent power outage incidents in power grids with high share of inverter-based resources (IBRs) reveal temporary overvoltages, which may follow fault clearing events, could contribute to major power outages. Motivated by the real-world need for the modeling, characterization and suppression of temporary overvoltages in IBR dominated power grids, as identified by several event analysis reports, this project aims to develop the followings: (1) Proper representation of IBRs in dynamic models for realistic assessments of temporary voltage excursions (2) Defining proper system performance indicators associated with temporary voltage excursions in IBR-dominated power grids with different control strategies, (3) Identifying key influential factors on the dynamics of temporary overvoltages in IBR-dominated power grids by using analytical methods such as state space analysis and impedance-based analysis, and (4) Proposing controllers for IBRs to tolerate and suppress the temporary overvoltages subsequent to disturbances, for both grid forming and grid following converters. The proposed methodologies will be implemented and evaluated in large power grids such as WECC transmission systems and large power distribution systems. Different types of IRBs such as HVDC systems, battery energy storage systems (BESS), and wind and solar power plants will be considered. 
Academic Team Members Project Leader: Saeed Lotfifard (Washington State University,
Team members: Sakis Meliopoulos (Georgia Tech,
Industry Team Members Aftab Alam (CAISO), Ran Xu (CAISO), Alan Engelmann (ComEd), Shikhar Pandey (ComEd), Mohit Singh (ComEd), Kurt Lafrance (CMS), Dennis R. Woycehoski (CMS), Evangelos Farantatos (EPRI), Aboutaleb Haddidi (EPRI), Alberto Del Rosso (EPRI), Deepak Ramasubramanian (EPRI), Kwok Cheung (GE), Deepak Konka (GE), Miaolei Shao (GE), Bishnu Sapkota (GE), Rijesh Akkanusery (GE), Panitarn Chongfuangprinya (Hitachi), Bo Yang (Hitachi) Mingguo Hong (ISO-NE), David Rieken (Hubbell), Xiaochuan Luo (ISO-NE), Yonghong Chen (MISO), Akshay Korad (MISO), Kun Zhu (MISO), David Till (NERC), Hongtao Ma (NERC), Fathalla Eldali (NRECA), Benjamin Kroposki (NREL), Kumaraguru Prabakar (NREL), Gab-Su Seo (NREL), Jianzhong Tong (PJM), Casey Cathey (SPP), Harvey Scribner (SPP), Bo Gong (SRP), Wisam Al Sudani (WAPA)
Project Period July 1, 2022 to August 31, 2024