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DOE OSTI2022

Robust Scheduling of Networked Microgrids for Economics and Resilience Improvement

The benefits of networked microgrids in terms of economics and resilience are investigated and validated in this work. Considering the stochastic unintentional islanding conditions and conventional forecast errors of both renewable generation and loads, a two-stage adaptive robust optimization is proposed to minimize the total operating cost of networked microgrids in the worst scenario of the modeled uncertainties. By coordinating the dispatch of distributed energy resources (DERs) and responsive demand among networked microgrids, the total operating cost is minimized, which includes the start-up and shut-down cost of distributed generators (DGs), the operation and maintenance (O&M) cost of DGs, the cost of buying/selling power from/to the utility grid, the degradation cost of energy storage systems (ESSs), and the cost associated with load shedding. The proposed optimization is solved with the column and constraint generation (C&CG) algorithm. The results of case studies demonstrate the advantages of networked microgrids over independent microgrids in terms of reducing total operating cost and improving the resilience of power supply.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Designing resilient IoT and Edge Computing with federated tinyML

The rapid growth of the Internet of Things (IoT) and Edge Computing (EC) has brought significant conveniences to modern society but has also greatly expanded the cyber attack surfaces, particularly as these technologies are being increasingly integrated into critical systems such as power grids, healthcare, and smart homes. Here, to improve IoT/EC’s cybersecurity posture, we leveraged Artificial Intelligence (AI) and Machine Learning (ML) by employing tinyML to monitor voluminous IoT data for cyber threats while addressing devices’ resource constraints, and utilizing Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. Building on our three-layer architecture combining tinyML and FL to enhance autonomous cyber attack detection, this paper demonstrated that the architecture improves detection accuracy, reduces resource consumption, and enables lightweight, secure IoT device monitoring. These results were validated using the public N-BaIoT dataset as well as real IoT network traffic data collected under multiple attack scenarios from our testbeds. Additionally, we introduced an enhanced FL methodology with a novel preprocessing stage, including federated feature selection and global preprocessor construction, to address IoT/EC data heterogeneity. We developed a physical IoT testbed for attack simulations and data collection, implemented a tinyML-powered detector for realistic model validation, and also built a virtual testbed for scalable evaluations of FL models across diverse network environments.

Cognitive cyber↗

DOE OSTI2024

Leveraging PHIL for Inverter Functionality Requirement Evaluation to Ensure a Reliable Grid

This presentation showcases NREL's ongoing research on advanced Multi-point Power Hardware-in-the-Loop (PHIL) systems, enabling comprehensive evaluation of interoperability, stability, and wide-area stability in complex power grids. Key features include high-power PHIL capabilities, seamless PHIL Interfaces for effortless Grid-Following (GFL) and Grid-Forming (GFM) mode switching, and advanced multi-domain PHIL/Controller Hardware-in-the-Loop (CHIL) capabilities for evaluating diverse technology mixes, facilitating rigorous testing and validation of emerging power systems for reliable integration, enhanced resilience, and optimal performance.

lab capabilities↗

DOE OSTI2025

Controller Hardware-in-the-Loop Evaluation of a Microgrid Controller for a Microgrid System with Multiple Grid-Forming Inverters

This paper presents the laboratory evaluation of a commercial Microgrid Management System (MGMS) implemented in the real-world Bronzeville Microgrid which features a futuristic scenario with high renewable energy integration and the use of multiple Grid-Forming (GFM) inverters. The primary objective of the performance evaluation for the MGMS is to assess the MGMS's capability to dispatch GFM units, including a GFM PV unit and two GFM battery units, to maintain the system stability and ensure economic operation, thus guaranteeing the microgrid's resilience during prolonged outages and dynamic events. The laboratory controller hardware-in-the-loop provides realistic testing environment through detailed electromagnetic transient modeling of the microgrid system, hardware MGMS, and standard communication protocols (DNP3). The CHIL evaluation shows how the MGMS effectively manages the GFM inverters, highlighting its performance in maintaining stability, reliability, and survivability in a microgrid environment with a high penetration of renewable energy sources.

controller hardware-in-the-loop↗

DOE OSTI2024

Controller Hardware-in-the-Loop Evaluation of a Microgrid Controller for a Microgrid System with Multiple Grid-Forming Inverters: Preprint

controller hardware-in-the-loop↗

DOE OSTI2024

Parallel computing for power system climate resiliency: Solving a large-scale stochastic capacity expansion problem with mpi-sppy

Here we propose a nodal stochastic generation and transmission expansion planning model that incorporates the output from high-resolution global climate models through load and generation availability scenarios. We implement our model in Pyomo and perform computational studies on a realistically-sized test case of the California electric grid in a high performance computing environment. We propose model reformulations and algorithm tuning to efficiently solve this large problem using a variant of the Progressive Hedging Algorithm. We utilize the parallelization capabilities and overall versatility of mpi-sppy, exploiting its hub-and-spoke architecture to concurrently obtain inner and outer bounds on an optimal expansion plan. Initial results show that instances with 360 representative days on a system with over 8,000 buses can be solved to within 5% of optimality in under 4 h of wall clock time, a first step towards solving a large-scale power system expansion planning problem across a wide range of climate-informed operational scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Controller-Hardware-in-the-Loop Evaluation of a Microgrid Controller for a Microgrid System With Multiple Grid-Forming Inverters

This paper presents the laboratory evaluation of a commercial Microgrid Management System (MGMS) implemented in the real-world Bronzeville Microgrid which features a futuristic scenario with high renewable energy integration and the use of multiple Grid-Forming (GFM) inverters. The primary objective of the performance evaluation for the MGMS is to assess the MGMS's capability to dispatch GFM units, including a GFM PV unit and two GFM battery units, to maintain the system stability and ensure economic operation, thus guaranteeing the microgrid's resilience during prolonged outages and dynamic events. The laboratory controller hardware-in-the-loop provides realistic testing environment through detailed electromagnetic transient modeling of the microgrid system, hardware MGMS, and standard communication protocols (DNP3). This CHIL evaluation shows how the MGMS effectively manages the GFM inverters, highlighting its performance in maintaining stability, reliability, and survivability in a microgrid environment with a high penetration of renewable energy sources.

controller hardware-in-the-loop↗

DOE OSTI2020

Chapter Nine - Automated Optimal Control in Energy Systems: The Reinforcement Learning Approach

With the development of smart grid technologies an increasing number of new devices and participants have joined modern energy systems and are inevitably making them more complicated and interdependent than ever. Optimally controlling such a complex energy system and maintaining its operation in a high-efficient, secure, and resilient manner are challenging tasks to the system operators. Fortunately, the revolution in deep learning and artificial intelligence (AI), both from hardware and algorithms perspectives, has provided new ideas and solutions to many previously intractable problems. As a result, this advance in computer science also sparked great research interests in utilizing AI in solving engineering problems related to the modern energy systems. Among many AI techniques, deep reinforcement learning (DRL) has demonstrated great potential for solving sequential optimization problems, which are very common in the engineering domains. Its ability to handle nonlinearity and stochasticity in controlled systems has out-competed many traditional optimal control algorithms. Therefore in this chapter, we focus on the state-of-the-art of DRL concepts and related algorithms, compare their pros and cons with traditional optimal control approaches and discuss the typical workflow for leveraging RL in solving complex problems in modern energy systems.

artificial intelligence↗

DOE OSTI2025

Grid Reliability and U.S. Coal Fleet Attributes: Considerations for State Regulators

This briefing paper provides state utility regulators with a comprehensive and current understanding of the reliability attributes of coal as a generation resource, potential reliability impacts associated with near-term coal plant retirements, and possible mitigation strategies to ensure a stable and resilient energy system.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

Ensuring electromagnetic compatibility in grid-connected power converters: Challenges, standards, and compliance strategies

In today's rapidly advancing world, electronic devices and systems are fundamental to a wide range of industries, including renewable energy and global telecommunications infrastructure. However, as these devices become more complex and widespread, the risk of electromagnetic interference (EMI) also increases, underscoring the importance of stringent Electromagnetic Compatibility (EMC) requirements for maintaining system integrity. This paper addresses the specific challenges associated with grid-connected power converters (GCPCs), which are critical in integrating renewable energy into existing power grids. It explores the complexities of EMI in the context of GCPCs, particularly given the recent emergence of tailored EMC standards for these systems. The paper also highlights the shortcomings of applying generic or unrelated standards to GCPCs, often leading to inadequate compliance and testing protocols. Through a detailed analysis of existing standards and recent advancements in product-specific EMC requirements, this paper provides a comprehensive overview of the current landscape, offering guidance to stakeholders on navigating the intricate EMC compliance landscape, with a focus on methodologies, testing procedures, and the evolving regulatory environment for GCPCs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Hardware-in-the-Loop Testbed for Cyber-Physical Security of Photovoltaic Farms

In the last decades, modem grids with distributed energy resources, such as photovoltaic (PV) farms, are increasingly vulnerable to cyber-attacks that seriously affect the stability and performance of the power system. While cyber-physical security of smart grids is extensively studied, most of the existing work focuses on the grid level and neglects the modeling and features of device-level power electronics converters (PECs). Furthermore, establishing a high-fidelity simulation testbed that can simulate harmonic frequencies of the PV farm is in urgent need. In this paper, a high-fidelity and real-time hardware-in- the-loop testbed is built to simulate the harmonics of power electronics converters for cyber-physical security of PEC-enabled PV farms. Based on this testbed, the impact of typical cyber-attacks and physical faults on the PV converter can be analyzed, thus providing a foundation for cyber-attack detection, root cause diagnosis, and resilient control to mitigate the adverse effects of cyber-attacks.

14 SOLAR ENERGY↗

DOE OSTI2021

Roadmap for Advanced Power System Measurements

Conditions in the electric power grid are changing rapidly. Changes are driven, in particular, by the increased penetration of renewable resources in the generation mix. Part of the solution to dealing with the changing conditions is the better use of measurement systems, taking advantage of the better understanding of measurements that was heralded by digital technology. Another part of the solution is the communication of samples of the directly observable voltages and currents by means of continuous point-on-wave values. The increased bandwidth capability of such a system allows more complicated measurement models to be built at the point of use. Additional measurements and analyses can then be performed. This Roadmap hinges on these two aspects of measuring: improved measurements supported by high-bandwidth (raw data) communications. Following an introduction to the overall subject, the report explores the impact of what can be thought of as the digital revolution in measurement. In essence, that revolution has served to clarify ideas about measurement and is continuing to lead to improved processes. An extensive survey of the relevant literature was performed . Webinars were held to learn from the wider community of practitioners. Based on this information, a number of gaps were identified whose continued existence would hamper the solution of the challenges now facing measurement and communication in the power grid. The underlying value propositions are interoperability (presently not very satisfactory in many measurements); greater (and less challenging) adoption of distributed energy resources; and improved international competitiveness. Underlying all that, of course, is progress toward a more reliable and resilient power system. The identified gaps were addressed in four major thrusts: technology deployment and demonstration, education, instrumentation testing and standards, and analytical methods. For each of the thrusts, multiple goals are defined to guide the implementation. The thrusts were designed to close gaps and unlock high-value use cases. After discussing the literature review, gap analysis, high-value use cases, and research thrusts in chapters 2-5, the report culminates in chapter 6 with a roadmap that links each aspect together to form a unified plan. Developing a research portfolio aligned with this plan will ensure that advanced measurement systems are in place to support reliable operation of the power system as it modernizes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Characterization of Harsh Environments, At-Risk Microgrid Components, and Hardening Technologies (Report Version 0.1)

Microgrid implementation can help improve electrical service, reliability, and resilience for localized communities. However, they may be susceptible to damage from natural disasters and extreme weather events, which often coincide with times of greater community dependence on microgrids due to likely increased vulnerability of equipment on the main grid. Microgrid equipment can be protected against these hazards through various hardening techniques. The selection of hardening mitigations may depend on the actual risk of the hazard in the specific location and for the specific type of system, as well as cost and feasibility factors. This report summarizes a framework that can be used to characterize risk to a microgrid system from a list of natural hazards enumerated by FEMA. We also describe hardening techniques and mitigations that can be used for specific energy generation, storage, loads, and power delivery elements within a microgrid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Tools and Methods for Optimization of Nuclear Plant Outages

Refueling outages are one of the most challenging phases in a nuclear power plants (NPP) operating cycle. Refueling outages are extremely costly for a NPP due to the large amount of required resources and because of lost revenue due to plant being off the grid. Outage durations have steadily decreased across the industry over that last few decades primarily due to improved planning and coordination, but there are still many plants that struggle to meet the performance metrics accomplished by other utilities. Schedule resilience is one of the issues. NPP outages require scheduling thousands of activities in a duration of around 30 days on average. Outage staff begin working on the schedule more than a year ahead of the outage start and make every effort to build a robust schedule. Despite the robust and detailed planning, once the outage starts, numerous emergent issues typically appear along with schedule delays requiring continuous replanning and adjusting. When schedule disruption occurs during an outage, plant staff make urgent efforts to recover but often not able to maintain the planned outage duration. These outage delays can cost a utility several million dollars per day. Tools that could help outage schedulers create a more resilient schedule and allow them to optimally reschedule emergent work could significantly reduce outage delays. One key aspect of creating a resilient schedule is to have accurate estimates for activity duration. Another important outage scheduling capability is the ability to schedule emergent work with minimal disruption. The Optimization of Outage Activities project under the Risk-Informed Systems Analysis Pathway (RISA) sponsored by Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program focuses on developing tools and methods to support nuclear power plants with optimization of outage schedules. The goal of the outage optimization is the completion of all planned and emergent outage activities as fast as possible while maintaining highest level of safety. This report describes the initial development of tools to support outage management that leverage computational and machine learning methods developed in other RISA and LWRS projects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Methods and Tools To Assess Robustness of Nuclear Plant Outages

Refueling outages are one of the most challenging phases in a nuclear power plant (NPP) operating cycle. Refueling outages are extremely costly for an NPP due to the large amount of required resources and because of lost revenue due to plant being off the grid. Outage durations have steadily decreased across the industry over that last few decades primarily due to improved planning and coordination, but there are still many plants that struggle to meet the performance metrics accomplished by other utilities. Schedule resilience is one of the issues. NPP outages require scheduling thousands of activities within 30 days on average. Despite detailed planning, once the outage starts, numerous emergent issues typically appear along with schedule delays requiring continuous replanning and adjustment. When schedule disruption occurs during an outage, plant staff make urgent efforts to recover but are often not able to maintain the planned outage duration. These outage delays can cost a utility several million dollars per day. Tools that could help outage schedulers create a more resilient schedule and allow them to optimally reschedule emergent work could significantly reduce outage delays. One key aspect of creating a resilient schedule is to have accurate estimates for activity duration. Another important outage scheduling capability is the ability to schedule emergent work with minimal disruption. This paper focuses on developing tools and methods to support NPPs with outage schedule optimization and it describes the initial development of tools to support outage management that leverage computational and machine learning methods.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Long-Duration Energy Storage Grid Integration-Valuation Framework and Incentive Gaps

Given these challenges and current modeling gaps on Long Duration Energy Storage (LDES), enhancing the structure and design of existing planning, operations, and organized wholesale markets can better characterize the value of LDES to the power system. To more thoroughly assess the gaps and barriers to LDES investment and readiness for integration into a future grid, we conducted stakeholder outreach through an online survey, interviews with individual independent system operators/regional transmission organizations, and a literature review. Based on this assessment, we identified a set of opportunities for LDES focused development, including a framework to quantify the contributions of LDES on resource adequacy, reliability, and resiliency. Specifically, we identify the potential demand for and benefits of an open-source, LDES-centric evaluation framework that can guide future planning, operations, market design, and policy reforms.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Grid Value Proposition of Marine Energy

Marine energy technologies convert the energy of ocean waves, and tidal, river, and ocean currents into electricity and other forms of usable energy. The marine energy resource potential in the United States is significant and geographically diverse, with a study commissioned by the U.S. Department of Energy estimating that the nation’s annual marine energy potential is approximately 2,300 TWh/year across the 50 states, or greater than 57 percent of U.S. electricity generation in 2019. However, the marine energy industry still faces hurdles to commercialization. While high costs relative to wind and solar remain a key challenge, other hurdles relate to marine energy’s value streams not being well characterized and not captured by traditional energy comparison metrics like the levelized cost of energy. To address this challenge, this project undertakes several types of analyses to identify and illustrate value propositions for marine energy resources. It provides a fresh framework for considering electric system benefits based on unique marine energy attributes, and provides analyses illustrating and quantifying those benefits. The authors find many opportunities for the deployment of marine energy technologies both in the near term and within typical utility planning timeframes (i.e. up to 20 years). From a resource and technology perspective, marine energy resources can deliver distinct and valuable benefits to different configurations of the grid, whether the bulk system, isolated distribution systems, or remote communities, islands, and microgrids. Marine energy resources can be valuable in increasing technology diversity in a generation portfolio, providing energy where it is otherwise difficult to come by, supporting local resiliency, complementing and being complemented by other resources including solar, wind, and energy storage, and avoiding land constraints.

16 TIDAL AND WAVE POWER↗

DOE OSTI2020

State Strategies for Valuing Distributed Energy Resources in Cost-Effective Locations

The deployment of Distributed Energy Resources (DERs), small-scale electricity generation sources or controllable loads connected to the distribution system or a facility served by the distribution system, can have wide-ranging and positive impacts for the electricity grid. Interconnecting a DER in a high-value location on the grid can unlock benefits beyond those that accrue to the off-taker or asset owner. When DERs are deployed optimally, not only can the individual consumer benefit, but the local utility, the electricity system, and other ratepayers can benefit as well. By engaging in locational DER planning, states can help protect their communities and ratepayers and can help ensure the reliability and resilience of the electricity system. This report explores states' role in better integrating locational value into DER siting and development. It first outlines some of the benefits that can be achieved through the deployment of DERs in high-value locations. It then looks at state policy and regulatory roles and the tools states can use to influence the location of DER development. The report next examines the challenges of locational DER planning, with a particular focus on the challenges that states face in influencing the location of DER development. It highlights three case studies from states that engaged in locational DER planning through the Multistate Initiative to Develop Solar in Locations that Provide Benefits to the Grid and then presents several lessons learned from these efforts. The final section of this report summarizes some recent publications related to locational value of DERs in the form of an abbreviated literature review.

14 SOLAR ENERGY↗