Current Projects


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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)
Project Period July 1, 2022 to August 31, 2024

M-43: Integrating RTO and utility processes in planning and cost allocation (ending August 2023)

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 Gas Power), Eduardo Ibanez (GE Gas Power), Yifan Li (MISO), Haifeng Liu (CAISO), Harvey Scribner (SPP), Casey Cathey (SPP), Greg Brinkman (NREL), Anthony Giacomoni (PJM), Patrick Panciatici (RTE), Renchang Dai (GEIRINA), Anish Gaikwad (EPRI), Parag Mitra (EPRI), Miguel Ortega-Vazquez (EPRI), Mohamed Osman (NERC)
Project Period July 1, 2021 to August 31, 2023

M-42: Modeling and Coordinating Distributed Energy Resources in Power Systems and Markets (ending August 2022)

Summary This project proposes appropriate DER aggregated modeling, low-voltage ride-through, output coordination, and aggregated market offer techniques to analyze/mitigate DER-induced voltage stability challenges as well as ensure DERs’ optimal market participation. The following technical tasks are proposed: 1) quantitative analysis of DER’s dynamic response to fault-induced delayed voltage ride-through (LVRT) capability, through electro-magnetic transient (EMT) modeling of DER-penetrated unbalanced distribution feeders; 2) optimization-based calibration of transmission-level ‘DER_A’ dynamic model (along with the dynamic composite load model), with an integration of physical laws and engineering justifications on the configurations of DER-penetrated distribution systems, for accurate representation of various voltage stability issues on the load site of the system; 3) optimal DER coordination control and aggregated offer strategies, for DER aggregators to optimally participate in the wholesale energy and regulation markets.
Academic Team Members Project Leader: Meng Wu (Arizona State,
Team members: Vijay Vittal (Arizona State,, Alejandro Domginguez-Garcia (UIUC,
Industry Team Members Deepak Ramasubramanian (EPRI), Bo Gong (SRP), Hung-Ming Chou (Dominion Energy), Qiang Zhang (ISO-NE), Di Shi (GEIRI North America), Miaolei Shao (GE Global Research), Yingchen Zhang (NREL), Jianzhong Tong (PJM), Aung Oo (CAISO), Yohan Sutjandra (TEA)
Project Period July 1, 2020 to August 31, 2022


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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, and Mani Venkatasubramanian (Washington 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)
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 2023)

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, 2023

S-97G: System identification tools for power systems using synchronized measurements (ending June 2023)

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 on the small-signal and transient stability properties of bulk power systems. This project will focus on the development of novel system identification tools that will use synchronized measurements to derive insight on the input-output properties of power system components. The project will assess which of the internal linear and nonlinear features of the models of specific inverter-based resources can be characterized and estimated using external measurements. For improving adaptive control designs, efficient probing signals will be designed for online estimation of transfer functions. An open-source model identification toolbox will be developed for verifying and validating the dynamic performance of power system components using available synchrophasor measurements.
Academic Team Members Project Leader: Vaithianathan (Mani) Venkatasubramanian (Washington State University,
Industry Team Members Patrick Panciatici (RTE), Gilles Torresan (RTE) and Marie-Sophie Devry (RTE)
Project Period June 16, 2021 to June 15, 2023

S-96: Data driven control of DERs & hybrid PV plants for enhancing voltage stability with TSO-DSO interactions over multiple timescales (ending August 2023)

Summary This project addresses control & coordination of distribution system assets like DERs and hybrid PV plants with storage to provide real-time active/reactive power support to mitigate voltage instability in transmission systems over multiple timescales. A novel controller for hybrid PV plants will be developed that delivers the requested P/Q/V to the bulk grid. The control is robust to PV variability and disturbances in the grid and exploits the capabilities of DERs like storage. We will utilize physics-based data driven techniques to develop the control scheme of DERs and hybrid PV plants for mitigating the voltage instability in real-time using message-passing machine learning architecture. The control strategies will mitigate/contain inverter tip cascading during delayed voltage recovery events (seconds timeframe) and ensure a safe stability margin for credible Transmission-Distribution (TD) co-simulation platform (PSSE/GridLab-D [1] & OpenDSS) to implement proposed methodologies demonstrating their ability to mitigate voltage instability on practical systems while capturing TSO-DSO interactions. Further (HIL) real-time T&D test bed to ensure that controls are effective under noisy measurements & communication delay.
Academic Team Members Project Leader: V. Ajjarapu (Iowa State University,
Team members: Hugo N. Villegas-Pico (Iowa State University,, Anurag K.Srivastava (Washington State University,, and Anjan Bose (Washington State University,
Industry Team Members B. Leonardi (EPRI), F. Eladi (NRECA), C. Mishra (Dominion Energy), D. Ramasubramanian (EPRI), A.D. Rosso (EPRI), Y. Zhang (NREL), H. Scribner (SPP), K. Zhu (MISO), J. Tong (PJM), V. Krishnan (NREL), X. Zhang (GEIRINA), D. Shi (GEIRINA), B. Kroposki (NREL), P. Chongfuangprinya (Hitachi), W. Qiu (NERC), M. Parashar (GE), Bo Gong (SRP)
Project Period July 1, 2021 to August 31, 2023

S-95: Reliable fault-ride through and protection of converter-dominated power systems under unbalanced conditions (ending August 2023)

Summary Power electronics interfacing renewables, storage, and novel transmission technologies are envisioned to be the cornerstone of tomorrow’s resilient and sustainable power systems. While state-of-the-art power converter control can replace grid-forming and grid-supporting functionalities of synchronous machines, their design typically neglects crucial aspects such as unbalanced faults and the interaction between converter protections (e.g., current limiting) and system-level protection. This jeopardizes system reliability and resilience and has already resulted in large-scale system outages and explicitly accounts for current limits, unbalanced conditions, and protection in the control design. The proposed approach will enable reliable and predictable fault-ride through capabilities that do not rely on heuristics, avoid adverse interactions with system protection, and retain the positive impact of grid-forming control on system-level stability when feasible.
Academic Team Members Project Leader: Dominic Gross (University of Wisconsin-Madison,
Team members: Maryam Saeedifard (Georgia Tech,
Industry Team Members David Till (NERC), Hongtao Ma (NERC), Ben Kroposki (NREL), Kumaraguru Prabkar (NREL), Hung-Ming Chou (Dominion Energy), Aditya Korad (MISO), Evangelos Farantatos (EPRI), Deepak Ramasubramanian (EPRI), Wenzong Wang (EPRI), Harvey Scribner (SPP), Thibault Prevost (RTE), Guillaume Denis (RTE), Bo Gong (SRP)
Project Period July 1, 2021 to August 31, 2023

S-94G: Explore the Efficacy of Machine Learning Based Preventive and Corrective Controls to Prevent Cascading Failures Following Large Disturbances (ending November 2021)

Summary This project applies advanced machine learning methods in conjunction with detailed time domain simulations to develop preventive and corrective controls to prevent cascading failures following large disturbances. The project will utilize detailed time domain simulations interfaced with multi-agent reinforcement learning to determine appropriate control actions.
Academic Team Members Project Leader: Vijay Vittal (Arizona State,
Industry Team Members Di Shi (GEIRINA)
Project Period June 1, 2020 to November 30, 2021

S-91: Generating Value from Detailed, Realistic Synthetic Electric Grids (ending August 2022)

Summary The goal of this project is to work closely with the industrial team to generate value from large-scale, detailed and realistic synthetic electric grids. The project builds on recent ARPA-E work by the PIs to develop grids that can be used for research, education, commercial development and public engagement. This four project tasks are 1) developing customized grids, 2) developing specific grid scenarios, 3) develop scenarios to explore decision making with uncertainty, and 4) expanding the scope of synthetic grids for coupling with other infrastructures.
Academic Team Members Project Leader: Thomas J. Overbye (Texas A&M,
Team members: Kate Davis (Texas A&M,, Bernie Lesieutre (Wisconsin,, Line Roald (Wisconsin,
Industry Team Members Harvey Scribner (SPP), Jim Price (CAISO), Bryan Palmintier (NREL), Di Shi (GEIRI), Evangelos Farantatos (EPRI), Cho Wang (AEP), Steven Judd (ISO-NE), Melvin Schoech (CenterPoint), Al Engelmann (ComEd), Yazhou Jiang (GE), Anil Jampala (GE), Mahesh Morjaria (First Solar), Patrick Panciatici (RTE), Jianzhong Tong (PJM), Baj Agrawal (APS), Felicia Ruiz (MISO), Casey Cathey (SPP), Atena Darvishi (NYPA), Paul Myrda (EPRI)
Project Period July 1, 2020 to August 31, 2022

S-90: Grid Supporting Controllers for Enabling 100% Penetration of Inverter Based Resources (ending August 2022)

Summary Future power systems are envisioned to transition to significant amount of renewable energy. For example, California has mandated 100% renewable energy supply by 2045 and Minnesota has passed laws to move to full renewable energy supply by 2050. New technologies such as HVDC systems will be also integrated into the conventional AC systems forging hybrid AC-DC systems. To assure reliable integration of such a massive amount of renewable inverter-based resources (IBRs), the IBRs should be augmented with grid support capabilities and compatibility features. To this end, this project proposes a multi-pronged research effort as follows: i) Grid Firming Converters: proposing methods to achieve desired voltage and frequency supports from IBRs such as wind and PV farms in the future grid, ii) Grid Forming Converters: developing controls to enable cold start capability of a system with high penetration of renewables, and iii) Resilient Converters: Designing fault ride through capability and post-fault recovery control strategies to avoid massive dropouts of renewables following a disturbance such as what happened in the Western system.
Academic Team Members Project Leader: Maryam Saeedifard (Georgia Tech,
Team members: Sakis Meliopoulos (Georgia Tech,, Saeed Lotfifard (Washington State,
Industry Team Members Deepak Konka (GE Renewable Energy), Harvey Scribner (SPP), Kwok Cheung (GE Renewable Energy), Mehmet Cintuglu (ABB), Nivad Navid (PARS), Melvin Schoech (CenterPoint), Miaolei Shao (GE Power), Evangelos Farantatos (EPRI), Deepak Ramasubramanian (EPRI), Wenzong Wang (EPRI), Doug Bowman (SPP), Mahesh Morjaria (First Solar), Alan Engelmann (Exelon), Mohit Singh (ConEd)
Project Period July 1, 2020 to August 31, 2022

S-86G: Input-Output Metrics for the Power-Grid's Swing Dynamics (ending December 2020)

Summary New technologies are providing new opportunities for wide-area control of poorly damped oscillations in the bulk power grid. A foundational need in wide-area controller design is the assessment of input-output channel properties of the power system dynamics, in addition to its internal or modal properties. The purpose of this project is to undertake a comprehensive analysis of a suite of input-output metrics for the system dynamics, from both numerical and graph-theoretic perspectives. The metric analysis will then be used to develop model-reduction techniques that maintain key input-output properties, and to support estimation of channel properties from ambient synchrophasor data.
Academic Team Members Project Leader: Sandip Roy (Washington State,
Team Members: Vaithianathan (Mani) Venkatasubramanian (Washington State,
Industry Team Members Florent Xavier (RTE-France), Patrick Panciatici (RTE-France), Thibault Prevost (RTE-France), Denis Guillaume (RTE-France)
Project Period January 1, 2019 to December 31, 2020

Transmission and Distribution Technologies (T&D):

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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 Yanh (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), Wisam Al Sudani (WAPA)
Project Period July 1, 2022 to August 31, 2024

T-65: Identification and Mitigation of T&D Operational Security Vulnerabilities in Inverter Dominated Power Systems (ending August 2023)

Summary This project seeks to identify operational security vulnerabilities in T&D assets that grid integration of massive amounts of inverter-based resources (e.g. wind and solar generations, HVDC systems and inverter-interfaced energy storages) creates. We will investigate how the likely cascading outages in inverter-dominated power systems will look like as the result of new dynamics and fault response of inverter-based resources (IBRs). The project will focus on the following three main factors (1) Stability of inverters: we will analyze grid synchronization instability of IBRs and identify conditions tat controllers of IBRs negatively affect the stability of the power systems and different operating modes of IBRs (i.e. grid following, grid supporting, and grid forming modes). (2) Protection systems response: we will identify the root cause of protection system vulnerabilities versus penetration levels of IBRs and develop mitigation methods, (3) Dynamic response of loads: we will identify impacts of distinct dynamics of active power distribution systems on transmission systems as the result of large integration of IBRs in distribution systems. According to the identified vulnerabilities, we will propose mitigation strategies. Investigations and mitigation methods will be verified using commercial software such as PSS/E, CAPE, ETAP, PSCAD and realistic power system models.
Academic Team Members Project Leader: Saeed Lotfifard (Washington State University,
Team members: Venkataramana Ajjarapu (Iowa State University, and Sakis Meliopoulos (Georgia Tech,
Industry Team Members Evangelos Farantatos (EPRI), Deepak Ramasubramanian (EPRI), Parag Mitra (EPRI), Aboutaleb Haddadi (EPRI), MAsoud Abbaszadeh (GE Research), Kwok Cheung (GE Renewable Energy), Deepak Konka (GE Renewable Energy), Miaolei Shao (GE Research), Bishnu Sapkota (GE), Doug Bowman (SPP), Harvey Scribner (SPP), Wisam Alsudani (WAPA), Jianzhong Tong (PJM), Di Shi (GEIRINA), Yonghong Chen (MISO), Felicia Ruiz (MISO), Aftab Alam (CAISO), Adarsh Nagarajan (NREL), Venkat Krishnan (NREL), Murali Baggu (NREL), Ben Kroposki (NREL), Yingchen Zhang (NREL), Mehmet Cintuglu (Hitachi), Bo Yang (Hitachi), Panitarn Chongfuangprinya (Hitachi), Yohan Sutjandra (The Energy Authority), Atena Darvishi (NYPA), Mingguo Hong (ISO-NE)
Project Period July 1, 2021 to August 31, 2023

T-64: Who controls the DERs? Increasing DER hosting capacity through targeted modeling, sensing, and control (ending August 2022)

Summary Distributed energy resources (DERs) offer many opportunities for providing grid services but may also cause issues in distribution grid operations. This project develops modeling and analysis techniques for systems with many DERs that have potentially conflicting control objectives. Using DER models developed by applying machine learning to actual device data, this project will first identify a small number of locations for placing sensors relevant to monitoring key distribution grid constraints and then develop a framework for analyzing and comparing the impacts of various DER controllers on distribution grid operations.
Academic Team Members Project Leader: Line Roald (Wisconsin,
Team members: Daniel Molzahn (Georgia Tech,, Mojdeh Hedman (Arizona State,
Industry Team Members Melvin Schoech (CenterPoint), Venkat Banunarayanan (NRECA), Yohan Sutjandra (TEA), George Stefopoulos (NYPA), Patrick Panciatici (RTE-France), Jim Price (CAISO), Philip J. Hart (GE Global Research), Yazhou Jian (GE Global Research), Rajni Burra (First Solar), William Kouam (AEP), Evangelos Farantatos (EPRI), Adarsh Nagarajan (NREL), Jenny Zhao (AEP), Jesse Gantz (Centrica), Kwok Cheung (GE Renewable Energy), Bo Yang (Hitachi), Oluwaseyi Akinbode (MISO), Deepak Ramasubramanian (EPRI), Nikita Singhal (EPRI), Heng Chen (ComEd)
Project Period July 1, 2020 to August 31, 2022