2022 SETO Peer Review – Systems Integration Projects

Project Name: Advanced Grid-Forming (GFM) Inverter Controls, Modeling and System Impact Study for Inverter Dominated Grids
Awardee: GE Global Research
Location: Niskayuna, New York
DOE Award Amount: $4,200,000
Principal Investigator: Maozhong Gong
Project Summary: This project is developing a modeling method and automation tool to analyze the stability of a large energy system with mixed resources, such as inverter-based generation and traditional generators, and see how they interact with each other. The team will also develop controls for individual and clusters of grid-forming photovoltaic (PV) inverters to improve grid stability under various conditions. The technology will be implemented in GE’s commercial PV inverter, thereby facilitating its commercialization.

Project Name: GridSweeper: Frequency Response of Bulk Low-Inertia Grids
Awardees: Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory, Pacific Northwest National Laboratory
Location: Berkeley, California; Livermore, California; Richland, Washington
SETO Award Amount: $1,400,000
Principal Investigator: Sascha von Meier
Project Summary: The project team is creating a new class of measuring instrument that reveals subtle dynamics of bulk grids. Probes inject a tiny signal and analyzes the response with ultra-high precision, applying novel devices and techniques.

Project Name: PV Inverter Systems Enabled by Monolithically Integrated Silicon Carbide-Based Four Quadrant Power Switch
Awardee: North Carolina State University
Location: Raleigh, North Carolina
DOE Award Amount: $1,517,146
Principal Investigator: Subhashish Bhattacharya
Project Summary: This project creates an ultra-high-density, low-cost power conversion device using a newly developed single die Silicon Carbide-based power semiconductor switch that can block voltage and carry current in all polarities or quadrants of the power switch. The proposed scalable power conversion device can enable single-stage power conversion and then be used as a building block for photovoltaic inverters to meet and exceed efficiency, reliability and power density targets when compared to conventional two-stage cascaded solutions.

Project Name: Autonomous Grid-forming Inverters Enabled by Always-on Universal Droop Control without External Communication or Phase-Locked Loops
Awardee: Syndem
Location: Chicago, Illinois
DOE Award Amount: $600,000 
Principal Investigator: Qing-Chang Zhong
Project Summary: This project develops a hacker-proof grid-forming inverter that doesn’t rely on a communication network, can avoid cascading blackouts even when there are grid faults, and can start up the grid without the help of a traditional generator in what’s known as black start. The inverter will be able to autonomously resynchronize with the grid while supplying local loads, including during a black start. The project will address a major challenge of high penetration of solar and other distributed energy resources (DER) and offer guidelines for DER integration to improve grid stability, resiliency, security, and reliability.

Project Name: A Reliable, Cost-Effective Transformerless Medium-Voltage Inverter for Grid Integration of Combined Solar and Energy Storage
Awardee: University of Arkansas
Location: Fayetteville, Arkansas
DOE Award Amount: $2,765,138
Principal Investigator: Yue Zhao
Project Summary: This project aims to enhance PV plant reliability with significantly reduced lifetime costs for a high-density 300 kilowatt central inverter. It converts 1.5 kilovolt direct current output of the photovoltaic systems to 4.16 kilovolt alternating current without the use of bulky 60 hertz transformers. The proposed technology lowers the lifetime costs of Silicon Carbide inverters through the simultaneous electro-thermal design of the subsystem and the components of the inverter. This project establishes a basis for new innovations by addressing the challenge of multi-objective optimization while accounting for inverter cost and reliability constraints.

Project Name: Compact and Low-Cost Microinverter for Residential Systems
Awardee: University of Maryland College Park
Location: College Park, Maryland
DOE Award Amount: $1,872,818
Principal Investigator: Alireza Khaligh
Project Summary: This project aims to create a holistic design of microinverters using the emerging gallium nitride semiconductors combined with a novel circuit with reduced components and filters. The project models thermal stresses and their effect on reliability by using a multi-physics-based approach resulting in an improved assembly design. It is anticipated that the microinverter will yield over 250,000 hours of operation with no failures under consumer rooftop and commercial installation use conditions, while simultaneously achieving lower costs.

Project Name: Modular, Multifunction, Multiport, and Medium-Voltage Utility Scale Silicon Carbide PV Inverter
Awardee: University of Texas at Austin
Location: Austin, Texas
DOE Award Amount: $2,999,400
Principal Investigator: Alex Q. Huang
Project Summary: This project is developing the next-generation utility-scale photovoltaic (PV) inverter referred to as a modular, multi-function, multiport, and medium-voltage utility-scale silicon carbide solar inverter. Called the M4 Inverter, it directly converts the direct current output of solar panels to medium-voltage alternating current, eliminating the bulky and costly low-frequency transformer. The inverter also has a direct current port to interface with an additional energy storage device. The device has multiple functionalities and can be used for reactive power support, fast frequency regulation, and peak power reduction, and enables synthetic inertia to be integrated into the inverter for grid support. Taken together, these advances will enable the inverter to drastically reduce the levelized cost of energy.

Project Name: A Scalable Control Architecture for 100% PV Penetration with Grid Forming Inverters
Awardee: University of Washington
Location: Seattle, Washington
DOE Award Amount: $4,900,000 
Principal Investigator: Brian Johnson 
Project Summary: This project is developing two kinds of grid-forming controls: fast communication-free controls for inverters for solar-plus-storage systems, and slower controls that use a distributed communication architecture for system-wide energy management. These controls will be immune to communication outages and be compatible with small solar energy systems as well as the bulk power grid.

Project Name: Modular Wide-Bandgap String Inverters for Low-Cost Medium-Voltage Transformerless PV Systems
Awardee: University of Washington
Location: Seattle, Washington
DOE Award Amount: $2,837,106
Principal Investigator: Brian Johnson
Project Summary: The proposed string inverter uses integrated circuit+control (C2) blocks, each comprised of a wide-bandgap-based power converter and local controller that can be assembled in a modular fashion to produce ultra-low-cost medium-voltage transformerless photovoltaic (PV) inverters. Each C2 block will be fabricated on high-voltage printed circuit boards with planar magnetics, such that automated manufacturing processes can be leveraged for maximum cost savings and throughput. This eliminates costly passive components and low-frequency transformers, substantially reducing electrical balance-of-system costs.

Project Name: Ultra Compact Electrolyte-Free Microinverter with Megahertz Switching
Awardee: Virginia Polytechnic Institute and State University (Virginia Tech)
Location: Blacksburg, Virginia
DOE Award Amount: $1,031,317
Principal Investigator: Jason Lai
Project Summary: The objective of this project is to develop a cost-effective photovoltaic (PV) microinverter that fully utilizes the potential of wide-bandgap semiconductor devices, like gallium-nitride devices, which have shown potential of switching at megahertz frequencies. By operating the PV microinverter at such high frequencies, passive component size can be drastically reduced while still maintaining ultra-high efficiency of the microinverter. With the tallest component in the entire package measuring less than 0.2 inch, the potting compound material can be reduced by 80% as compared to typical designs with a one inch tall package, further reducing the cost of the product.

Project Name: Firmware Command and Control
Awardees: Argonne National Laboratory, Idaho National Laboratory, National Renewable Energy Laboratory, Sandia National Laboratories
Location: Lemont, Illinois; Idaho Falls, Idaho; Golden, Colorado; Albuquerque, New Mexico
DOE Award Amount: $4,500,000
Principal Investigator: Rita Foster
Project Summary: This project creates an agile embedded response capability foundational with baselined firmware and behaviors with bidirectional sharing of threat to upstream energy security operations.

Project Name: Validation, Restoration, and Black Start Testing of Sensing, Controls, and Distributed Energy Resource Technologies at Plum Island
Awardees: Idaho National Laboratory, Lawrence Livermore National Laboratory, Pacific Northwest National Laboratory
Location: Idaho Falls, Idaho; Livermore, California; Richland, Washington
DOE Award Amount: $3,000,000
Principal Investigator: Hannah Burroughs
Project Summary: This project is transforming black start with distributed energy resources and storage, from foundational research based demonstrations, to a viable method for restarting and restoring the bulk power system after critical outages. This will dramatically increasing the toolbox for operators in the face of both physical and cyber incidents.

Project Name: Enabling Cybersecurity, Situational Awareness and Resilience in Distribution Grids with High Penetration of Photovoltaics
Awardee: Kansas State University
Location: Manhattan, Kansas
DOE Award Amount: $2,900,000
Principal Investigator: Bala Natarajan
Project Summary: This project team is working to invent a compressive sensing method that requires fewer inputs than usual so grid operators can observe quickly changing grid conditions and determine vulnerabilities in critical infrastructure. The team is developing smart inverter controls to detect cyber intrusions and initiate network defenses. 

Project Name: Reorg: Resilience and Stability Oriented Cellular Grid Formation and Optimization for Communities with Solar PVs and Mobile Energy Storages
Awardee: National Renewable Energy Laboratory
Location: Golden, Colorado
DOE Award Amount: $3,500,000
Principal Investigator: Fei Ding
Project Summary: This project is working to 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.

Project Name: Resilient Operation of Networked Community Microgrids with High Solar Penetration
Awardee: Oak Ridge National Laboratory
Location: Oak Ridge, Tennessee
DOE Award Amount: $3,800,000
Principal Investigator: Ben Ollis
Project Summary: This project is working on the development and evaluation of a microgrid controller that coordinates the operation of a network of microgrids with high solar penetration. The goal of the networked microgrid is to enhance resilient operation during long-term outages caused by natural disasters, including preventive and corrective functionalities in the optimization to meet operation criteria. The technology will be tested on community-based and community-operated microgrids in Adjuntas, Puerto Rico, which was severely impacted by Hurricane Maria in 2017. This microgrid will be based on 100% solar and battery storage. The microgrid controller will coordinate these independent microgrids as a cluster to enhance system resiliency and reliability while providing cost-effective operation.

Project Name: Cybersecure Utility DER Networking with Integrated Multi-Party Trust
Awardee: Operant Networks
Location: Santa Rosa, California
DOE Award Amount: $2,600,000
Principal Investigator: Randall King 
Project Summary: This project team works with the power company Exelon to develop and deploy communications technology that securely shares information about solar and other distributed energy resources (DER) with multiple parties across multiple connections, including the internet. With new capabilities and protections, the technology will connect to existing utility software platforms. This will allow utilities to comply with new regulations requiring direct communication with DER, restrict access to trusted partners, and improve cybersecurity.

Project Name: Grid Resiliency with a 100% Renewable Microgrid
Awardee: San Diego Gas and Electric Company
Location: San Diego, California
DOE Award Amount: $4,500,000
Principal Investigator: Laurence Abcede 
Project Summary: This project researches and validates microgrid technologies that enable the use of solar and other distributed energy resources (DER) with grid-forming photovoltaic and battery inverters. These devices can improve grid stability and resilience by maintaining voltage and frequency during changing conditions, especially microgrid islanding, which independently provides power. The team will develop new controls and software for smart photovoltaic (PV) inverters and DER management systems that may allow more flexibility for the interconnection and operation of small-scale PV and other DER systems.

Project Name: Secure Monitoring and Control of Solar PV Systems through Dynamic Watermarking
Awardee: Texas A&M Engineering Experiment Station
Location: College Station, Texas
DOE Award Amount: $4,400,000
Principal Investigator: Le Xie 
Project Summary: This project develops and demonstrates an active defense mechanism of cyber-resilient PV distribution system operation using a dynamic watermarking technique to monitor cybersecurity. The technique involves injecting a probe signal onto the grid to authenticate grid actions. The approach will include real-time deployment of online computational algorithms in real-world critical locations. The team will test and validate the integrated communication, control, and computational framework using an existing system.

Project Name: Multilevel Cybersecurity for Photovoltaic Systems
Awardee: University of Arkansas
Location: Fayetteville, Arkansas
DOE Award Amount: $3,500,000
Principal Investigator: Alan Mantooth 
Project Summary: This project addresses cybersecurity at both the inverter and system levels for photovoltaic energy systems. First, the team will develop an inverter to address supply-chain security, real-time intrusion detection methods, vulnerability mitigation, control system security, safety protocols, and other concerns. Then, at the system level, the team will use machine-learning algorithms, a multilayered blockchain platform, and model-based intrusion detection.

Project Name: Autonomous Inverter Controls for Resilient and Secure Grid Operation 
Awardee: University of Central Florida
Location: Orlando, Florida
DOE Award Amount: $3,000,000
Principal Investigator:  Zhihua Qu
Project Summary: This project aims to provide a unified control design framework to enhance photovoltaic inverter controls and address the technical challenges of keeping the grid secure. It will coordinate grid-forming and grid-following inverters and black-start capability, which enables systems to restart independently after a power outage; ensure scalability and system stability; and protect against cyberattacks. The team will validate the technology using software simulations and lab field tests.

Project Name: Resilient Community Microgrids with Dynamic Reconfiguration to Serve Critical Loads in the Aftermath of Severe Events
Awardee: University of North Carolina at Charlotte
Location: Charlotte, North Carolina
DOE Award Amount: $3,600,000
Principal Investigator: Badrul Chowdhury
Project Summary: As part of a collaborative effort among state government, utility companies, industry, and universities, this project is developing an advanced microgrid control architecture. It will be able to seamlessly coordinate with the bulk power grid at multiple points of common coupling, automatically balance load and generation, provide critical services (hospitals, emergency shelter, etc.) at a minimum, detect faulty conditions on a continuous basis, communicate with distributed energy resources, form networked microgrids with neighboring communities when needed, and maintain safe operating conditions at all times. The proposed control architecture will be tested utilizing a unique digital-twin approach in which laboratories will have direct, real-time connections to microgrids operated by the major utilities in North Carolina. A field demonstration at Duke Energy's Hot Springs microgrid is also planned.

Project Name: Solar-Assisted State-Aware and Resilient Infrastructure System
Awardee: University of Utah
Location: Salt Lake City, Utah
DOE Award Amount: $4,400,000
Principal Investigator: Florian Solzbacher
Project Summary: This project is inventing an automated resilience management system that will use distributed solar photovoltaics, distributed energy resources, sensors, and distribution monitoring and switching equipment to improve the resilience of critical infrastructure and emergency centers. The system will include a cyber detection and outage management tool. PacificCorp is partnering with the university in order to validate the system.

Project Name: Achieving Cyber-Resilience for Power Systems using a Learning, Model-Assisted Blockchain Framework
Awardee: Virginia Polytechnic Institute and State University (Virginia Tech)
Location: Arlington, Virginia
DOE Award Amount: $3,000,000
Principal Investigator: Ryan Gerdes
Project Summary: This project uses a blockchain-based overlay network to provide a security layer on the existing power grid network that addresses security vulnerabilities and risks in command and control protocols, which is currently used for control and management of distributed energy resources (DER) and distribution systems. The team will integrate a model-assisted machine learning (MAML) framework with a secure blockchain overlay network (SBON) to enable protection, attack detection, and incident response capabilities to provide power grid network resiliency against sophisticated threats involving compromised DER and power aggregators. This approach will be tested on a novel photovoltaic (PV) inverter design. The team will also enable the protection of DER through development of a plug-and-play security module, incorporating both the blockchain and MAML elements of the project, that will communicate with and protect DER via standard interfaces. The module will be demonstrated through field trials that include utility-grade PV inverters and battery energy storage systems.

Project Name: Artificial Intelligence for Robust Integration of AMI and PMU Data to Significantly Boost Renewable Penetration
Awardee: Arizona State University
Location: Tempe, Arizona
DOE Award Amount: $750,000
Principal Investigator: Yang Weng
Project Summary: This project uses artificial intelligence and machine learning techniques to combine, synchronize, clean-up, and interpolate electric data from numerous sources in order to more accurately estimate the state of the electric grid. This will ultimately allow for the interconnection and/or operation of more photovoltaic (PV) systems and other distributed energy resources (DER) in power systems while simultaneously enhancing reliability, resiliency and power quality. The research team will innovative measurement synchronization, data mining for bad data detection and identification, robust algorithm design of machine learning for unobservable areas.

Project Name: Enhancing Grid Reliability and Resilience through Novel Distributed Energy Resource Control, Total Situational Awareness, and Integrated Distribution-Transmission Representation
Awardee: Arizona State University
Location: Tempe, Arizona
DOE Award Amount: $3,000,000
Principal Investigator: Raja Ayyanar
Project Summary: Arizona State University is building enhanced grid models by integrating transmission and distribution analyses. Using sensors and communications equipment, this tool can enable coordinated distributed resource responses, which can help increase the amount of renewable power operating in the distribution system.

Project Name: Asynchronous Distributed and Adaptive Parameter Tuning (ADAPT) for Hybrid PV Plants
Awardee: Binghamton University
Location: Binghamton, New York
DOE Award Amount: $2,600,000
Principal Investigator: Ziang Zhang
Project Summary: This project is developing a two-stage hybrid PV plant control framework that will enable the coordination of multiple hybrid photovoltaic (PV) plants with generation uncertainty and enhance grid stability through grid-forming inverter controls. The team will rely on state-of-the-art technologies, such as distributed control, dynamic state estimation, multi-agent reinforcement learning, distributed fault management, and GPU-parallel grid simulation. The framework will be demonstrated at a 1 megawatt hybrid PV plant controlled by grid-forming inverters at Brookhaven National Laboratory (BNL) and through the use of a hardware-in-the-loop system with 70% renewable penetration that will demonstrate the scalability and replicability of the proposed controls at New York Power Authority.

Project Name: Improving Grid Awareness by Empowering Utilities with Machine Learning and Artificial Intelligence
Awardee: Camus Energy
Location: San Francisco, California
DOE Award Amount: $750,000
Principal Investigator: Cody Smith
Project Summary: This project uses artificial intelligence and machine learning methods to provide grid operators and engineers with real-time analysis and visualization capabilities of the electric power system. Cloud computing approaches to system monitoring and real-time analytics provide a model for leveraging multiple data sources to correlate, verify, and interpret system telemetry in environments with high scale and low data fidelity. Experience from systems design in related fields shows that in sufficiently complex systems, no single data source can be entirely accurate or trustworthy, but an approach that leverages multiple sources and applies intelligent data interpretation can provide an extremely reliable, high-fidelity systems view. This project leverage the team’s past experience with cloud systems monitoring approaches and abundant data for artificial intelligence model training, along with capabilities in integrated power system simulation and monitoring data analytics with machine learning and deep learning to provide advanced, integrated situational awareness for the distribution grid and contributions to area-wide flexibility.

Project Name: Microgrid-Integrated Solar-Storage Technology (MISST)
Awardee: Commonwealth Edison
Location: Oakbrook Terrace, Illinois
Amount Awarded: $4,000,000
Principal Investigator: Aleksi Paaso
Project Summary: This project addresses availability and variability issues inherent in solar photovoltaic (PV) technology by utilizing smart inverters for solar PV and battery storage and by working synergistically with other components within a microgrid community. MISST utilizes the existing DOE-funded microgrid technologies and testbed and is designed to work seamlessly with a dedicated solar PV/storage controller that will be developed in this project. The PV/storage controller will demonstrate the economic, reliability, and resilience benefits of a microgrid-based solar PV/storage solution.

Project Name: Risk-Informed Hierarchical Control of Behind-the-Meter DER with AMI Data Integration
Awardee: Eaton Corporation
Location: Golden, Colorado
DOE Award Amount: $3,000,000
Principal Investigator: Yi Yang 
Project Summary: This project develops a real-time controller of behind-the-meter distributed energy resources (DER), such as solar and battery storage, and loads to ensure that bulk power system operators or distribution utilities get enough power. Integrating data from smart meters will enable optimal provision of grid services to improve grid reliability in distribution systems with high solar penetration. To enable scaling and minimize adoption risk, the team—along with the National Renewable Energy Laboratory, Electric Power Research Institute, Pecan Street, Provo City Power, and Commonwealth Edison—will work with existing utility infrastructure.

Project Name: Enable BTM DER-Provided Grid Services that Maximize Customer and Grid Benefits
Awardee: Electric Power Research Institute
Location: Knoxville, Tennessee
DOE Award Amount: $3,000,000
Principal Investigator: Aminul Huque
Project Summary: This project team aims to research, develop, and demonstrate collected data and controls to enable behind-the-meter (BTM) solar photovoltaics and other distributed energy resources (DER). The goal is to cost-effectively provide grid services in both distribution and bulk power systems while enhancing system reliability. The team will conduct advanced transmission, distribution, and DER simulations to validate the merit and performance of DER-provided services, and better estimate the potential need for network upgrades. The team will lead an industry collaboration to develop BTM DER grid services guidelines to expand the provision of grid services and address existing regulatory barriers.

Project Name: Solar Critical Infrastructure Energization System
Awardee: Electric Power Research Institute
Location: Knoxville, Tennessee
DOE Award Amount: $6,000,000
Principal Investigator: Brian Seal
Project Summary: This project aims to create a system that can recognize and react to grid emergencies and use solar energy to help provide power to critical infrastructure, like hospitals, during an outage. The project team will also identify grid regions that can operate reliably under cyber and physical threats, and develop new technologies, such as advanced inverters and decentralized control systems, to support regional emergency operations, with a focus on cybersecurity and resilient communications.

Project Name: Faster-than-Real-Time Simulation with Demonstration for Resilient Distributed Energy Resource Integration
Awardee: Electrical Distribution Design
Location: Blacksburg, Virginia
DOE Award Amount: $3,000,000
Principal Investigator: Robert Broadwater
Project Summary: Electrical Distribution Design is inventing a technique to speed analysis of power flow using graphic trace analysis, or outputs from a bar graph instead of complex calculations, and then validate it in the field with its project partner, Pepco. This will enable evaluation of the distribution network down to the secondary network and allow for rapid detection of power system abnormalities caused by instability, cyber intrusion, or other factors.

Project Name: Unified Universal Control and Coordination of Inverter-Based Resources, AI Forecasting, and Demonstration for PV+Battery Hybrid Plants
Awardee: Florida State University
Location: Tallahassee, Florida
DOE Award Amount: $3,800,000
Principal Investigator: Fang Peng
Project Summary: This project is developing an innovative unified universal control and coordination of inverter-based resources for photovoltaic (PV) plus battery hybrid power plants. This technology will provide flexibility and stability over wide ranges of inverter operation, from grid-following to islanding and local grid-forming. The team is using a multilayer approach that includes artificial intelligence PV forecasts and energy management, intelligent coordination outer-loop control, and unified universal inner-loop control. These three layers together deal with systematic integration and coordination of the hybrid power plant with bulk grid and co-located PV and battery within the plant in various time scales from a day to micro-seconds.

Project Name: Autonomous, Adaptive, and Secure Distribution Protection
Awardee: Georgia Institute of Technology
Location: Atlanta, Georgia
DOE Award Amount: $2,600,000
Principal Investigator: Athanasios Meliopoulos
Project Summary: This project is developing an autonomous protection system that uses dynamic models to determine the state of the grid based on a physical area that the system protects. It will be able to identify the parameters of the protected area to continuously correct and verify the models. The system will not contain settings or be affected by the direction or level of fault currents. This protection system will be compatible with distribution systems that have very high penetrations of solar and other distributed energy resources.

Project Name: Artificial-Intelligence-Driven Smart Community Control for Accelerating PV Adoption and Enhancing Grid Resilience 
Awardee: National Renewable Energy Laboratory       
Location: Golden, Colorado   
DOE Award Amount: $2,500,000
Principal Investigator: Xin Jin
Project Summary: This project addresses challenges in community-scale coordination of behind-the-meter resources by building on the National Renewable Energy Laboratory’s efforts on home energy management, grid hosting capacity, and device characterization for grid services. Using smart meter data, the team will develop artificial intelligence that can learn to identify homeowner preferences and enable day-ahead planning. The project aims to evaluate how to best use solar energy paired with flexible building loads like electric water heating or electric vehicle charging. Since solar energy is intermittent, the algorithms will try to schedule the loads when the sun is out. When there is excess solar energy, the project will determine the smallest battery energy storage (BES) system so the community can use that energy later in the day. This analysis will provide insight into cost-effective ways to minimize the need for BES systems. The team will validate the solution using hardware-in-the-loop laboratory testing, which simulates real-time embedded systems, and field demonstration in a net-zero-energy community.

Project Name: SAPPHIRE: Stability-Augmented Optimal Control of Hybrid PV Plants with Very High Penetration of Inverter-based Resources
Awardee: National Renewable Energy Laboratory
Location: Golden, Colorado
DOE Award Amount: $3,600,000
Principal Investigator: Jin Tan
Project Summary: Hybrid photovoltaic (PV) plants (HPPs are providing an increasing proportion of energy, but because advanced, fast-responding HPP controls are not being used, synchronous generation is still the source of grid stability. This project is developing a hierarchical control framework to value and deploy HPP stability services. This work will include real-time probing-based inertia estimation, bulk power system-connected grid forming controls (GFM), and reactive power services. Plant-level control will ensure HPPs deliver system-level services while optimizing utilization of PV and battery energy storage while considering batteries’ state-of-charge and state-of-health. The technology will demonstrated at the National Renewable Energy Laboratory and at a 60-MW field demonstration in Hawaii.

Project Name: Photovoltaic Analysis and Response Support Platform for Solar Situational Awareness and Resiliency Services
Awardee: North Carolina State University
Location: Raleigh, North Carolina
DOE Award Amount: $3,000,000
Principal Investigator: Ning Lu
Project Summary: North Carolina State University is designing a modeling tool to determine the optimal response of renewables on transmission and distribution systems, as well as behind-the-meter response for small-scale solar energy systems. With real-time sensor readings and a cost-benefit analysis, this tool can be used for grid planning and to help restore power during an outage.

Project Name: Graph-Learning-Assisted State and Event Tracking for Solar-Penetrated Power Grids with Heterogeneous Data Sources
Awardee: Northeastern University
Location: Boston, Massachusetts
DOE Award Amount: $750,000
Principal Investigator: Ali Abur
Project Summary: This project uses artificial intelligence and machine learning techniques to integrate electric data and use it to calculate the state of the electric network. The resulting tool will be able to detect connectivity changes and faults in the grid and update grid models accordingly, which will improve the situational awareness of power grids with large amounts of solar energy by exploiting a large volume of data and measurements available from a highly diverse set of sources. The project will also provide tools to detect and identify network topology changes due to unexpected disturbances or switching events by exploiting the recently developed sparse estimation methods in the data analytics area.

Project Name: Optimization of Excess Solar and Storage Capacity for Grid Services
Awardee: NV Energy
Location: Las Vegas, Nevada
DOE Award Amount: $3,000,000
Principal Investigator: Michael Brown 
Project Summary: This project evaluates using behind-the-meter (BTM) storage, demand response, and utility “electric storage as a service” to extend the benefits and adoption of BTM solar through grid services. These services will be enabled by artificial intelligence (AI) and blockchain-powered smart contracts that can track and settle transactions leveraging information from smart meters and smart inverters. The team will develop AI to use excess storage capacity for grid operations and to pay customers for their extra capacity.

Project Name: Security Constrained Economic Optimization of PV and Other Distributed Assets
Awardee: Opus One Solutions
Location: San Francisco, California
Award Amount: $3,200,000
Principal Investigator: Raina Kang
Project Description: This project takes a holistic approach to address critical challenges that prevent high levels of distributed solar penetration in power system networks. The team coordinated interaction of solar generation units, electric cars, energy storage devices, and demand-side management programs to provide multiple grid services in real time. This project aimed to deploy a general-purpose software platform to create an optimal dispatch of distributed resources while ensuring secure and normal operations of electric power distribution networks. The project will ultimately enable large-scale deployment of the solution to other cooperatives and municipal- and investor-owned utilities. 

Project Name: Citadels
Awardees: Lawrence Livermore National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory, Sandia National Laboratories
Location: Livermore, California; Oak Ridge, Tennessee; Richland, Washington; Albuquerque, New Mexico
DOE Award Amount: $3,000,000
Principal Investigator: Kevin Schneider
Project Summary: This project enables networked microgrids, and their component distributed energy resources, to operate in a distributed manner using collaborative autonomy concepts implemented in an OpenFMB architecture.

Project Name: Adaptive Protection and Control for High-Penetration PV and Grid Resilience
Awardee: Sandia National Laboratories
Location: Albuquerque, New Mexico 
DOE Award Amount: $4,900,000
Principal Investigator: Matthew Reno
Project Summary: This project team is designing a scalable adaptive protection platform for distribution systems and microgrids with high penetrations of distributed energy resources, like solar photovoltaics (PV), that improves the selectivity and sensitivity of the protection system. The team will create communication-free modular units that attach to intelligent protection devices to guarantee the protection system’s operation during extreme weather, equipment failures, and other events. This project will transform power system protection from static settings that are not sufficiently reliable for high penetrations of solar to a platform that can adapt to real-time grid conditions.

Project Name: Autonomous and Resilient Operation of Energy Systems with Renewables
Awardee: Siemens Corporation
Location: Princeton, New Jersey
DOE Award Amount: $5,000,000
Principal Investigator: Ulrich Muenz
Project Summary: Siemens Corporation will create a microgrid control system that can coordinate distributed microgrids to work together. The system will include a communications-free method to increase grid resilience and autonomously restore power during a blackout using smart inverters.

Project Name: Optimal Reconfiguration and Resilient Control Framework for Real-Time Photovoltaic Dispatch to Manage Critical Infrastructure
Awardee: University of North Carolina at Charlotte
Location: Charlotte, North Carolina
DOE Award Amount: $3,700,000
Principal Investigator: Sukumar Kamalaasdan
Project Summary: This project is devising a grid management tool that detects cyber and physical threats and can form dynamic clusters to optimally manage photovoltaics and energy storage to improve grid resiliency and support critical infrastructure. This tool will have two-level control with reconfigurable grid networks, which allow operators to isolate damaged sections while still powering the rest of the grid. 

Project Name: Modeling and Control of Solar Photovoltaics for Large Grid Disturbances and Weak Grids
Awardee: University of South Florida
Location: Tampa, Florida
DOE Award Amount: $1,200,000
Principal Investigator: Lingling Fan
Project Summary: This project is designing dynamic models of utility-scale solar plants and their interactions on grids with large penetrations of generation through distributed energy resources like solar-plus-storage systems and wind power. These models will be used to construct a coordination strategy and a stability enhancement module for photovoltaic and storage systems so they can respond to rapidly changing grid conditions.

Project Name: Hierarchal Engine for Large-Scale Infrastructure Co-Simulation Plus: From a Facilitator to a Hub
Awardees: Argonne National Laboratory, Idaho National Laboratory, Lawrence Livermore National Laboratory, National Renewable Energy Laboratory, Pacific Northwest National Laboratory 
Location: Lemont, Illinois; Idaho Falls, Illinois; Livermore, California; Golden, Colorado; Richland, Washington
DOE Award Amount: $2,000,000
Principal Investigator: Bryan Palmintier
Project Summary: The Grid Modernization Lab Consortium and the energy industry as a whole have been using Hierarchical Engine for Large-Scale Infrastructure Co-Simulation in their projects to comprehensively analyze and assess the increasing interdependency among critical infrastructures. This project addresses gaps in in scalable integration with diverse infrastructures and usability for co-simulation complexity.

Project Name: Adaptive Protection and Validated Models to Enable Deployment of High Penetrations of Solar PV
Awardee: Electric Power Research Institute
Location: Palo Alto, California
DOE Award Amount: $4,100,000
Principal Investigator: Jens Boemer
Project Summary: This project is developing and testing trustworthy models of solar photovoltaic (PV) facilities to enable power system engineers to plan, operate, and protect transmission and distribution systems. The models will inform system designs so that they can leverage smart inverter capabilities for microgrids and islanded systems, which operate independently of the national grid, to ensure the resilience of critical infrastructure and maintain grid safety and reliability. The team will also demonstrate adaptive protection systems that use advanced PV capabilities.

Project Name: Deep-Learning-Powered Probabilistic Net-Load Forecasting with Enhanced Behind-the-Meter PV Visibility
Awardee: National Renewable Energy Laboratory
Location: Golden, Colorado
DOE Award Amount: $750,000
Principal Investigator: Rui Yang
Project Summary: This project uses artificial intelligence and machine learning techniques to predict the electric load one day in advance in areas that have large amounts of behind-the-meter solar. That information will allow operators to manage the electric grid more efficiently and cost-effectively. The deep-learning-powered probabilistic forecasting framework for day-ahead net-load at substations will separate behind-the-meter photovoltaic (PV) generation from net-load measurements and quantify its impact on net-load patterns. A novel transfer learning method will be developed to transfer the knowledge learned from geographic locations with rich sensor data to diverse locations where only the substation measurements are available. The framework will be validated using measurement data from Hawaiian Electric Company and on the Solar Forecast Arbiter platform.

Project Name: Day-Ahead Probabilistic Forecasting of Net-Load and Demand Response Potentials with High Penetration of Behind-the-Meter Solar-plus-Storage
Awardee: North Carolina State University
Location: Raleigh, North Carolina
DOE Award Amount: $750,000
Principal Investigator: Wenyuan Tang
Project Summary: This project leverages artificial intelligence and machine learning techniques to predict the electric load in areas with large amounts of solar energy and enable more efficient grid operation. The technology will also be able to forecast the capacity available to the grid from electric loads that can be turned on or off depending on the balance between electric demand and generation. Recent advances in artificial intelligence can enhance the accuracy of net-load forecasting, the observability of net-load variability, and the understanding of the coupling between net-load and demand response potentials. The two models under development for addressing hybrid probabilistic forecasting can provide better spatiotemporal information.

Project Name: Multi-time-scale Integrated Dynamics and Scheduling for Solar (MIDAS-Solar)     
Awardee: National Renewable Energy Laboratory       
Location: Golden, Colorado
DOE Award Amount: $2,900,000
Principal Investigator: Jin Tan
Project Summary: This project team is creating and validating advanced grid models by developing simulation models that seamlessly and cost-effectively combine dispatching and dynamic response analysis, where dispatching ranges from a day ahead to minutes, and dynamic response from seconds to subseconds. To study the impacts of photovoltaic (PV) variability on system reliability at different times, the team will develop a multi-time-scale grid model and an integrated PV model. These models will give operators a more complete understanding of how short-term PV variability affects transmission-system operations like reserve scheduling and energy deployment. They will also help operators accurately assess system reliability when deploying energy and reserve-scheduling under transient instability events, such as the failure of a major generator, and allow them to see how quickly standby generators can ramp up. The team will study interactions among all types of essential reliability services provided by PV power plants.    

Project Name: PV Plant and Battery Energy Storage System Integration
Awardee: National Renewable Energy Laboratory       
Location: Golden, Colorado
DOE Award Amount: $750,000
Principal Investigator: Vahan Gevorgian
Project Summary: The BESS, due to its tremendous range of uses and configurations, may assist PV integration in any number of ways by increasing power system flexibility. These uses include, (1) matching generation to loads through time shifting, PV curtailment reduction, transmission congestion management, and elements of power flow control; (2) promoting higher levels of PV penetrations by balancing the grid through ancillary services, load-following, ramp limiting and load-levelling; and (3) managing forecast uncertainty and short-term variability in PV generation through reserves; (4) smoothing output from individual solar plants; and (5) island and microgrid applications. In addition, in distribution applications, BESS can play crucial roles in increasing hosting capacities of distribution feeders for large levels of PV penetration by retail energy time-shifting, providing voltage support and improving power quality. This collaboration will produce analyzed test data and a comprehensive performance evaluation to understand the impacts of a combination of PV and BESS for all above uses. This will be the first and one-of-its kind demonstration of all types of active and reactive power controls by PV and BESS utilizing controlled grid conditions emulated by the 7 MVA power electronic grid simulator.

Project Name: Library of Advanced Models for Large-Scale PV Systems
Awardee: Oak Ridge National Laboratory
Location: Knoxville, Tennessee
DOE Award Amount: $2,000,000
Principal Investigator:  Suman Debnath
Project Summary: This project delivers three kinds of models—dynamic, high-fidelity, and advanced—of utility-scale photovoltaic (PV) generators, as well as power systems with high penetrations of distributed energy resources in distribution feeders. These models will capture the system dynamics under different conditions to better understand how the grid responds to various events. Advanced control functionalities aim to reduce momentary power cessation, increase system stability, and improve grid reliability.

Project Name: Development of the Next Weather Research and Forecasting Model – Improving Solar Forecasts
Awardee: Pacific Northwest National Laboratory
Location: Richland, Washington
DOE Award Amount: $1,214,872
Principal Investigator: Larry Berg
Project Description: This project is developing the next generation of solar resource capabilities integrated into the weather research and forecasting (WRF) model to include enhancements for intra-day and day-ahead forecasts of solar irradiance. The new or improved treatments include absorptive aerosol, cloud microphysics, subgrid variability in irradiance, and application of uncertainty quantification techniques.

Project Name: VRN3P: Variational Recurrent Neural Network Based Net-Load Prediction under High Solar Penetration
Awardee: Pacific Northwest National Laboratory
Location: Richland, Washington
DOE Award Amount: $750,000
Principal Investigator: Soumya Kundu
Project Summary: This project is using artificial intelligence and machine learning techniques to create an open-source tool that can predict the day-ahead electric load in areas with large amounts of behind-the-meter solar and deliver savings in the operation of the electric network. The project team will develop and validate a variational recurrent model-based algorithm for time-series forecasting of net-load under high solar penetration scenarios. Considering the uncertainty of cloud covering, solar irradiance, geographical information, and end-use load, theoretically guaranteed tight bounds on the net-load prediction will be delivered. Comprehensive validation of the proposed variational recurrent model-based net-load prediction algorithm will be performed using real-world industry and utility data.

Project Name: Open Source Evaluation Framework for Solar Forecasting
Awardee: University of Arizona
Location: Tucson, Arizona
DOE Award Amount: $1,000,000
Principal Investigator: William Holmgren
Project Description: This project develops an open-source framework that enables evaluations of irradiance, solar power, and net-load forecasts. Team members have previously collaborated on forecasting trials for utilities, developed operational solar and wind forecasts, and led projects using the open-source PVLib simulation and performance tool. The goal is to make the open-source evaluation framework more easily available for forecast providers, utilities, balancing authorities and fleet operators for non-biased forecast model assessment.