- PI: “Probabilistic Power System Risk Assessment with Uncertain Renewable Generations and Loads”, ISO New England, 12/2022-11/2023.
- PI: “Proactive: Predictive Community Outage Preparedness and Active Last Mile Visibility Feedback Autonomous Restoration,” DOE Solar Energy Technology Office, 05/2023-04/2026.
- Co-PI: “Physics-Informed Intelligent and Proactive Building Load Management for Energy Resilience,” DoD ESTCP, 11/2022-10/2024 (PI: NREL).
- PI: “DeepMining for Distribution Grid Visibility with High Penetration of DERs,” Eversource Energy, 07/01/2021-4/30/2023.
- PI: “Distribution System Cyber Security Detection, Localization and Response with DERs,” UConn Research Excellence Program, 09/01/2022-08/31/2023.
- Co-PI, “Reorg: Resilience and Stability Oriented Cellular Grid Formation and Optimization for Communities with Solar PVs and Mobile Energy Storages“, US Department of Energy and National Renewable Energy Lab, 04/01/2021-3/31/2024.
- PI: “Macro-Resiliency of the North American Power Grid,” US Department of Energy and Argonne National Laboratory, 06/2020-12/2023.
- PI: “Load Sculptor: Robust Dynamic Load Modeling and Uncertainty Quantification,” US Department of Energy and Lawrence Livermore National Laboratory, 06/2020-12/2023.
- Co-PI: “CLEAN EARTH: CoLlaboratory of Environmental Advocacy, Net-zEro-Carbon And Renewable TecHnologies“, OVPR at University of Connecticut, 01/01/2022-12/31/2022.
- PI: “Data-Driven Decision Making under Uncertainties with High Share of Variable Distributed Energy Resources” US Department of Energy and Lawrence Livermore National Laboratory, 05/01/2021-12/31/2022.
- Co-PI: “Risk Assessment of Power Systems to Extreme Events using Polynomial-Chaos-based Methods,” National Science Foundation, 07/2019-12/2022.
- PI: “Modeling and Analytics for WI Near Term Resilience and Reliability,” US Department of Energy and National Renewable Energy Lab, 03/01/2021-4/30/2022.
- PI: “Algorithm Development and Validation for EMS 2.0,” US Department of Energy and Pacific Northwest National Laboratory, 08/2019-02/2021.
- PI: “Grid Data Integration Development and Demonstration,” US Department of Energy and Lawrence Livermore National Laboratory, 01/2020-07/2020.
- PI: “Robust Distribution System State Estimation with Distributed Energy Resources,” US Department of Energy and Lawrence Livermore National Laboratory, 09/2018-12/2018.
|This project will develop, validate, and demonstrate a resilience- and stability-oriented cellular grid formation and optimization approach to achieve scalable and reconfigurable community microgrid operations for distribution feeders with solar photovoltaics (PV) and mobile battery energy storage. Using self-organizing, map-based resilience quantification, stability analysis, and distributed energy resource (DER) optimization, this project will transform traditionally centralized grid operations into time-varying cellular operations that can enable scalable distributed controls of over 10,000 DERs, achieve fast bottom-up service restoration using PVs and grid-forming inverters, adapt to time-varying system conditions, and maintain optimal system-level resilience. This will be demonstrated in a community in Colorado with 100% PV penetration.|
|With the collaborative effort among state government, utility companies, communities, industry, and universities, this project proposes to develop and demonstrate a predictive community outage preparedness and active last mile visibility feedback autonomous restoration solution, termed PROACTIVE, to achieve community resiliency with PVs and other distributed energy resources (DERs). PROACTIVE will transform traditional manual and time-consuming grid restoration into two-layer outage prediction preparedness and real-time robust grid visibility informed optimal and autonomous and fast restoration processes. The team will closely work with community stakeholders throughout the project to design and demonstrate the PROACTIVE technologies at Hartford and West Hartford communities in Connecticut serviced by Eversource Energy distribution feeders.|