The U.S. Department of Energy (DOE) Solar Energy Technologies Office Lab Call FY2022-24 funding program funds systems integration projects that support modeling and simulating behaviors of various elements of the electric power grid, including loads and distributed solar photovoltaic (PV) generation.
As part of this lab call, the national labs will also conduct research in photovoltaics, soft costs, and concentrating solar-thermal power.
Approach
In order to improve solar systems integration, this lab call focuses on analytics. The electric power grid is a fully-connected system with many generation, transmission, distribution, and load assets. Traditional modeling approaches treat the bulk power systems and distribution systems separately. Those approaches will not be sufficient as the contribution of solar generation increases to a much higher level. These projects are analyzing the transient and dynamic behaviors of various elements of the electric power grid, then fully integrating those behaviors into models that reflect the true behaviors of the entire system.
Objectives
These projects will significantly advance areas of modeling and simulation that focus on transient time frames (from milliseconds to about one second) and dynamic time frames (from one second to tens of seconds), bringing greater confidence in simulations for real-time operations and short-term operational planning.
Awardees
Topic: Transient and Dynamic Models for Solar Grid Integration
Project Name: Scalable Multi-Timescale Analysis Platform Based on System Transient and Dynamic Models
Lab: Argonne National Laboratory
Location: Lemont, IL
Principal Investigator: Dongbo Zhao
Project Summary: This project is developing an open-source, transient, dynamic analysis tool that can be used for any size solar energy system. The proposed tool will empower grid operators, vendors, and regulators to fully understand the actual performance and impact of fast dynamics system components, like solar generation. This analysis tool includes 1) a comprehensive transient and dynamic model library containing all major validated fast models in the grid; 2) a super-fast simulation engine based on proven transient simulation techniques; 3) an artificial intelligence-aided model detection technique for operational derivation of required models and parameters; 4) a model reduction technique for computation speed and granularity flexibility and scalability; and 5) an interfaceable, open source simulation platform with dominant software to provide expanded functions and scenarios.
Project Name: Solar PLUS: Solar Integration through Physics-Aware Learning Based Ultra-Scalable Modeling and Analytics
Lab: Brookhaven National Laboratory
Location: Upton, NY
Principal Investigator: Peng Zhang
Project Summary: The project is developing low-complexity models and greatly accelerated simulation tools for accurate and large-scale transient and dynamic transmission, distribution, and behind-the-meter solar co-simulation. The models and tools will enable utilities and independent system operators to perform a variety of transient and dynamic contingency analysis accurately and orders of magnitudes faster than the current state-of-the-art, so they can be performed for a large number of disturbances or scenarios in an online fashion.
Project Name: Intelligent Phasor-Electromagnetic Transients Partitioning for Accelerated Large-Scale Inverter-Based Resource Integration Studies
Lab: National Renewable Energy Laboratory
Location: Golden, CO
Principal Investigator: Andy Hoke
Project Summary: This project is developing an advanced framework for hybrid electromechanical- electromagnetic transients (EMT) simulation intended for large-scale power grids, including up to 100,000 transmission- and distribution-connected inverter-based resources. Far beyond existing co-simulation frameworks, this project will develop a rigorous method to partition a network between EMT and phasor-domain zones; a new EMT solver that leverages high-performance computing and semi-analytical solver acceleration; and a novel dynamics-preserving EMT-phasor interface. The research team will then unite these innovations into a unique, open-source framework and validate speed and accuracy against a full EMT model of an extremely high- inverter-based resource system.
Project Name: Integrated Multi-Fidelity Model and Co-Simulation Platform for Distribution System Transient and Dynamic Analysis
Lab: Pacific Northwest National Laboratory
Location: Richland, WA
Principal Investigator: Wei Du
Project Summary: This project is developing models for large, distribution-connected and behind-the-meter, inverter-based resources and variable loads to be incorporated in an integrated co-simulation platform. This innovation will simulate the transient and dynamic behaviors of distribution systems and their consequent interactions with transmission systems. The platform will enable transient and dynamic simulation of distribution systems that have more than 75% of resources that are inverter-based. Additionally, it will enable large-scale transmission and distribution co-simulation with the full-size Western Electricity Coordinating Council system and 100 detailed distribution feeders on a supercomputer that leverages parallel computing. The project aims to increase the confidence of utilities and system operators in operating distribution systems with large amounts of inverter-based resources.
Project Name: Harnessing Sensor Data for Degradation Analytics and Operations and Maintenance Optimization in PV Systems: A Prognostic Approach
Lab: Argonne National Laboratory
Location: Lemont, IL
Principal Investigator: Feng Qiu
Project Summary: Operations and maintenance (O&M) effectiveness is a key enabler for enhancing photovoltaic (PV) competitiveness. Records from the wind, automotive, and manufacturing sectors demonstrate that real-time sensor data can provide significant opportunities for improving O&M. The PV industry, especially the inverters that remain the root cause for 43% of PV system failures, has not experienced a similar sensor-driven breakthrough in O&M. This project aims to develop a prognostics-driven O&M policy that models the behavior of asset degradation processes over time to determine the current state-of-health of the assets, forecast the trajectory of degradation to generate accurate predictions on the remaining life distribution, and optimize O&M decisions based on the sensor-driven prediction on asset remaining life. The proposed prognostics-based O&M will quantify the risk of every possible O&M schedule in the future, and enable a proactive fleet-wide O&M scheduling plan.
Core Capability Projects
Project Name: Open Energy Data Initiative Solar Grid Integration Data and Analytics Library
Lab: National Renewable Energy Laboratory; Pacific Northwest National Laboratory; Argonne National Laboratory; Oak Ridge National Laboratory
Location: Golden, CO; Richland, WA; Lemont, IL; Oak Ridge, TN
Principal Investigator: Yingchen Zhang; Thomas McDermott; Karthikeyan Balasubramaniam; Teja Kuruganti
Project Summary: The challenges of integrating large amounts of distributed solar photovoltaics (PV) and associated distributed energy resources, such as storage, have prompted large-scale research and development investments in monitoring, controls, and other operational solutions to provide visibility, controllability, and coordination that enhances the security and reliability of highly renewable electric power systems. Although there have been many advanced algorithms and approaches developed and shared within the academic community, widespread industry acceptance has remained elusive. This has been particularly challenging for some of the most promising technologies that rely on machine learning/artificial intelligence, distributed controls, and next generation sensors such as micro-phasor measurement units, smart meters, smart inverters, and new sensor technologies. This project will address the key parts of these challenges, including data accessibility, algorithm maturity, and effective dissemination of results in an industry-relevant way.
Project Name: The National Solar Radiation Database
Lab: National Renewable Energy Laboratory
Location: Golden, CO
Principal Investigator: Manajit Sengupta
Project Summary: This project is developing high-quality, long-term solar resource data sets through the National Solar Radiation Database (NSRDB) and providing public access to the information. These data sets encompass studies from DOE and the solar industry in grid integration, capacity expansion, resource planning and deployment, national energy modeling, production cost modeling, and regional solar deployment. The team will update NSRDB to provide timely data, incorporate new information from the Geostationary Operational Environmental Satellite system, and improve data set quality through regular research on identified weaknesses.
Project Name: Essential Grid Operations from Solar
Lab: National Renewable Energy Laboratory; Lawrence Berkeley National Laboratory; Lawrence Livermore National Laboratory; Sandia National Laboratories; Pacific Northwest National Laboratory
Location: Golden, CO; Berkeley, CA; Livermore, CA; Albuquerque, NM; Richland, WA
Principal Investigator: Andy Hoke
Project Summary: Grids with significant inverter-based resources (IBR), such as solar or wind, are controlled and subject to very different physics compared to historical operations. In this project, a consortium of national labs will seek to address these gaps by accelerating power systems standards development and harmonization for a minimum level of performance for distributed energy resources (DER) and IBR. The research team will support: bulk power system standards and IBR guidance for system reliability; critical updates to DER interconnection, interoperability, and systems DER control standards at the distribution level; development of DER and systems performance standards for microgrids; validation of proposed DER/IBR performance capabilities; and stakeholder engagement, education, and industry implementation.
Project Name: Securing Solar for the Grid (S2G): Cybersecurity Standards Development for Solar Energy, IBR, and DER
Lab: National Renewable Energy Laboratory; Lawrence Berkeley National Laboratory; Lawrence Livermore National Laboratory; Sandia National Laboratories; Pacific Northwest National Laboratory; Idaho National Laboratory
Location: Golden, CO; Berkeley, CA; Livermore, CA; Albuquerque, NM; Richland, WA; Idaho Falls, ID
Principal Investigator: Danish Saleem
Project Summary: This project will create cybersecurity standards for distributed energy resources (DER) and inverter-based resources (IBR), which includes solar inverters, for new products entering the market and operating in the field. Specific DER cybersecurity requirements will be included in communication protocol standards, interconnection and interoperability standards, and grid operator and aggregator architecture requirements. Sandia National Laboratories and the National Renewable Energy Laboratory will coordinate standards development with stakeholders, lead working groups, and accelerate codes and standards development through in-person and virtual participation. Researchers will also conduct the technical research and development required to validate the test procedures and recommendations within these standards.
Project Name: Foundational Open-Source Solar System Modeling through Improvement and Validation of the System Advisor Model and PVWatts
Lab: National Renewable Energy Laboratory
Location: Golden, CO
Principal Investigator: Janine Freeman
Project Summary: This project will leverage the National Renewable Energy Laboratory’s open-source System Advisor Model (SAM) and PVWatts platforms to provide the solar community with valuable and extensible photovoltaic (PV), battery, and financial modeling resources and tools. The team will work to maintain software, provide technical support and PV model improvements, and increase stakeholder engagement activities for the continued use and relevance of these platforms in order to foster a vibrant, open-source community around the SAM and PVWatts tools.
Learn more about other projects in the FY2022-24 Lab Call.