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At least 451 records · Page 25

Evaluation of Optimal Net Load Management in Microgrids Using Hardware-in-the-Loop Simulation

This presentation discusses the performance evaluation of a net load management (NLM) engine that balances load and generation in an isolated community to power a critical facility after a grid interruption event (e.g., the loss of a large generation unit). This NLM engine is particularly important for microgrid systems because it provides a high-speed, cost-optimal control solution to coordinate grid-forming inverters and to dispatch grid-following inverters and deferrable loads in microgrid systems to enhance grid resilience and reliability. The NLM algorithm cost-optimally dispatches the grid-following inverters and deferrable loads based on the demanded power and load priorities, and the grid-forming inverters use droop control to form system voltages and share active and reactive power. A controller-hardware-in-the-loop platform is developed to evaluate the control performance of the NLM algorithm with two sequential contingency events of lost generation units. The experimental results indicate that the NLM engine can maintain system stability, achieve the targeted system voltage and frequency, and balance load and generation to serve the critical facility with improved system resilience and reliability.

droop control↗

Financing Microgrids in the Federal Sector

Recent high-impact events such as hurricanes and wildfires highlight the need for energy system resilience. One potential impact of these events is the loss of utility grid power to federal sites, negatively affecting the ability to carry out their missions. Depending on the need to sustain critical functions, it may be important to continue operations during an outage of the electric grid, or at least have power restored quickly after the event. One approach to addressing this need is through a microgrid. Microgrids can provide a more reliable solution than the traditional approach of using a backup generator at individual buildings. A microgrid can enhance a site’s electrical power system during normal operations, as well as provide reliable backup power to critical loads when electric utility power is interrupted. Many times, certain components of a microgrid (and potentially the entire system) can be justified economically and paid for out of energy savings or avoided costs. In cases where savings can cover the project costs, one of several privately financed procurement mechanisms may be used to implement the project. Procurement options available to all federal agencies include utility energy services contracts (UESC), energy savings performance contracts (ESPC), and utility services contracts (USC); other mechanisms such as a power purchase agreement (PPA), enhanced use lease (EUL), and utility privatization (UP) may also be useful to agencies that have the authority to use them. Implementing a microgrid in a comprehensive effort that also includes energy efficiency can provide an important savings component, while reducing power requirements for critical loads, thus reducing the cost of the microgrid and associated distributed energy resources (DER). However, it can be difficult to achieve enough savings and avoided costs to cover the entire microgrid system, so leveraging these avoided costs in combination with appropriated funds may be necessary to implement the full project. When a site is deciding if a microgrid is the best solution, activities early in the process include identifying critical loads and existing DERs, conversations with the local electric utility, and implementation options that work best for the agency and site. This paper explores procurement options and agreements that may be useful to federal agencies interested in implementing microgrids at their sites. Microgrid complexities, implementation considerations, and suggestions to get started are also discussed. This information will be most useful to agencies when they are exploring electric energy system resilience options and/or considering different procurement options to meet their needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Guidance for Grid Resilience Decisions in Rural Minnesota

This report assesses the hazard landscape of the state of Minnesota, identifies weather hazards that are most impactful to the distribution system, includes a statewide assessment of household access to services dependent on reliable power, reviews resilience planning activities of electric utilities in Minnesota, and presents analysis of distribution grid performance in the face of extreme weather events with data from seven electric cooperatives dispersed throughout outstate Minnesota. This information is synthesized to provide considerations for resilience investment prioritization.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Makah Tribe Strategic Energy Plan

The U.S. Department of Energy’s (DOE) Energy Transitions Initiative Partnership Project (ETIPP) connects remote and island communities, regional partners, and the DOE national laboratories to support communities as they seek to build resilience in their energy systems. The Makah Tribe faces several energy challenges, including frequent power outages and the potential for an extended outage due to an earthquake or tsunami. The Tribe joined ETIPP in 2022 to address those challenges, seeking to build energy resilience and sovereignty in the community. The Makah Tribe, Spark Northwest, the Pacific Northwest National Laboratory (PNNL), and the National Renewable Energy Laboratory (NREL) collaborated to develop a strategic energy plan as part of the second cohort of ETIPP communities. The long-term energy vision of the Makah Tribe includes increasing energy efficiency in the community, improving energy management capacity, and developing the renewable energy generation and storage sufficient to independently power the Reservation for one year. Additionally, the ETIPP team worked with Makah leadership, staff, and community members to identify a set of community priorities, values, and goals to guide energy development as the Tribe takes the incremental steps toward their vision for energy sovereignty. Those energy values include ecosystem-based management, energy sovereignty and project ownership, workforce development and capacity, economic opportunity, community wellbeing and priorities, and emergency disaster resilience. To understand what would be needed for a year for energy independence, the PNNL team conducted an assessment to determine the current energy usage of the Tribe and also modeled several scenarios for future energy use. Using the energy usage values, the team estimated how two types of renewable energy technology, specifically locally deployed solar and small-scale wind, could contribute towards the energy independence goal. The energy baseline and resource assessment produced the following key findings:

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Valuing Resilience for Microgrids: Challenges, Innovative Approaches, and State Needs

The United States depends on the delivery of reliable, affordable, clean, and safe electricity. Electric utilities invest billions of dollars each year in generation, transmission, and distribution assets to meet this need. However, experiences with recent natural disasters of increasing frequency and duration demonstrate the shortcomings of this approach in the face of modern threats. Further, as customers rely on electricity for a broader range of important needs, such as transportation, as well as critical life-saving services and mission critical facilities such as water treatment, medical care, shelters, telecommunications, and more, the need to minimize the likelihood and impacts of outages grows. Against this backdrop, resilience has emerged as a key consideration to guide electricity spending, whether from utilities, customers, or taxpayers. Although reliability has been defined and measured for decades with broadly accepted metrics that measure how many customers lose power and at what frequency and duration, resilience considers the electricity system’s response to a disruption and its subsequent impacts on customers. Developing tools and methods to accurately assess the costs and benefits of resilience investments is a critical step toward the goal of mitigating the impacts of outages on customers and society. Today, electric system resilience is largely treated as an externality due to challenges estimating the costs of long-duration outages, impacts of outages on society, and increasing reliance on electricity for a growing set of interdependent services. These interdependencies include the water, wastewater, telecommunications, natural gas, and health sectors. Without knowing how much a given resilience investment will benefit customers or society more broadly, investors, policymakers, and regulators are less likely to make or approve such investments, and less able to prioritize those investments. State Energy Offices and public utility commissions (PUCs) lead the development of state-level energy policy and utility regulation, respectively, and each has interests in encouraging appropriate public and private investments in resilience. To this end, the National Association of State Energy Officials (NASEO) and National Association of Regulatory Utility Commissioners (NARUC), with the support of the U.S. Department of Energy (DOE) Office of Electricity (OE), formed a joint Microgrids State Working Group to explore the costs and benefits of microgrids, barriers to broader deployment of microgrids to meet resilience and other objectives, and policy and regulatory strategies to optimize investments in resilience, including but not limited to microgrids. Although no universally accepted valuation tool for resilience exists, National Laboratories, utilities, researchers, and state and federal agencies have collaborated to develop, apply, and improve a number of approaches to quantify resilience, several of which are still in progress at the time this report is published. This report seeks to share these important advances by discussing current definitions of resilience (Section 1), how microgrids are defined and used to meet resilience objectives (Section 2), new approaches to valuing resilience (Section 3), steps State Energy Offices and PUCs have taken to further resilience valuation efforts (Section 4), and finally, considerations and suggested next steps for State Energy Offices and PUCs (Section 5). Relevant examples of specific microgrid projects and resilience valuation efforts are included throughout the report. While this report is written specifically for NASEO and NARUC members, it may be useful for utilities, local governments, and individual customers interested in improving the way public and private dollars are spent to achieve resilience outcomes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Transactive Approach for Service Restoration Utilizing Customer Load Flexibility and Grid-Edge Resources

This paper develops a transactive energy system model to restore electricity to customers in an isolated distribution system after an outage. The model is developed to engage a variety of customer types - prosumers, flexible loads, critical/noncritical customers, and distributed generators - as active participants in the restoration process. Unlike many existing transactive approaches, the proposed model is developed for service restoration and accounts for various customer types and their autonomy and privacy through an iterative approach to determine the optimal market price, while maintaining systemlevel power flow and voltage constraints. The advantages of the proposed approach are numerically validated on a modified IEEE 123-bus test system.

distributed energy resources↗

A Transactive Approach for Service Restoration Utilizing Customer Load Flexibility and Grid-Edge Resources: Preprint

This paper develops a transactive energy system model to restore electricity to customers in an isolated distribution system after an outage. The model engages a variety of customer types -- prosumers, flexible loads, critical/noncritical customers, and distributed generators -- as active participants in the restoration process. Unlike many existing transactive approaches, the proposed model is developed for service restoration and accounts for various customer types and their \textit{autonomy} and \textit{privacy} through an iterative approach to determine the optimal market price, while maintaining system-level power flow and voltage constraints. The advantages of the proposed approach are numerically validated on a modified IEEE 123-bus test system.

distributed energy resources↗

A Transactive Approach for Service Restoration Utilizing Customer Load Flexibility and Grid-Edge Resources

This paper develops a transactive energy system model to restore electricity to customers in an isolated distribution system after an outage. The model engages a variety of customer types -- prosumers, flexible loads, critical/noncritical customers, and distributed generators -- as active participants in the restoration process. Unlike many existing transactive approaches, the proposed model is developed for service restoration and accounts for various customer types and their autonomy and privacy through an iterative approach to determine the optimal market price, while maintaining system-level power flow and voltage constraints. The advantages of the proposed approach are numerically validated on a modified IEEE 123-bus test system.

distributed energy resources↗

A Deep Learning Approach for In-Network Synchrophasor Missing Data Recovery Using Programmable Network Switches

Phasor measurement unit (PMU) networks deliver accurate and timely measurements, which is essential for managing today’s electric power systems. To ensure data quality and enhance the cyber-resilience of PMU networks against malicious attacks and data errors, this study presents an online PMU missing data recovery scheme by leveraging P4 programmable switches. The data plane incorporates a customized PMU protocol parser that abstracts the necessary payload data for recovery. Recovery processes are executed in the control plane using a pre-trained machine learning model. Both traditional and advanced ML models, such as transformer and TimeGPT, are explicitly employed for data prediction. This approach ensures rapid and precise data recovery. Performance evaluations focus on recovery speed and accuracy, using a real dataset from a campus microgrid. With 20% missing PMU data, the mean absolute percentage error for voltage magnitude is 0.0384%, and the phase angle error discrepancy is approximately 0.4064%.

Phasor Measurement Unit, Machine Learning, Program↗

The Statistical Spread of Transmission Outages on a Fast Protection Time Scale Based on Utility Data

When there is a fault, the protection system automatically removes one or more transmission lines on a fast time scale of less than one minute. The outaged lines form a pattern in the transmission network. We extract these patterns from utility outage data, determine some key statistics of these patterns, and then show how to generate new patterns consistent with these statistics. The generated patterns provide a new and easily feasible way to model the overall effect of the protection system at the scale of a large transmission system. This new data-driven generative modeling of protection is expected to contribute to simulations of disturbances in large grids so that they can better quantify the risk of blackouts. Analysis of the pattern sizes suggests an index that describes how much outages spread in the transmission network at the fast timescale.

Transmission↗

Battery Storage for Resilience

As the capital costs of battery storage systems are decreasing, new opportunities to cost-effectively deploy the technology, often paired with renewable energy technologies, are emerging. At the same time, the duration and frequency of natural disasters is increasing. As a result, a growing number of institutions are deploying battery storage systems as a resilient energy solution because traditional back-up power solutions, like diesel generators, are not always sufficient, especially during longer-duration and larger-scale disasters. This fact sheet describes how battery storage, along with additional generation sources, can be used both to provide cost savings while grid-connected and to provide backup power when the grid goes down.

25 ENERGY STORAGE↗

Robust Decentralized Secondary Control Scheme for Inverter-based Power Networks

Inverter-dominated microgrids are quickly becoming a key building block of future power systems. They rely on centralized controllers that can provide reliability and resiliency in extreme events. Nonetheless, communication failures due to cyber-physical attacks or natural disasters can make autonomous operation of islanded microgrids challenging. This paper examines a unified decentralized secondary control scheme that is robust to inverter clock synchronization errors and can be seamlessly applied to grid-following or grid-forming control architectures. The proposed scheme overcomes the well-known stability problem that arises from parallel operation of local integral controllers. Theoretical guarantees for stability are provided along with criteria to appropriately tune the secondary control gains to achieve good frequency regulation performance while ensuring fair power sharing. The efficacy of our approach is demonstrated through simulations on a 5-bus microgrid with four grid-forming inverters.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Artificial Intelligence-Driven Management of Sustainable Energy Resources: Visibility, Operation, and Control

The rapid global transition toward sustainable energy resources (SERs) is reshaping how modern power systems are observed, optimized, and controlled. While SERs have significantly advanced decarbonization, their weather dependence, variability, and inverter-dominated characteristics challenge traditional, centralized, and deterministic grid operation. At the same time, the proliferation of high-resolution data from inverters, smart meters, and sensors offers unprecedented visibility into system dynamics. Yet, it also exceeds the analytical capability of conventional model-based approaches. Artificial intelligence (AI) provides a new foundation for addressing these challenges by bridging physical laws with data-driven learning, enabling accurate state awareness, adaptive operation, and coordinated control across distributed assets. This article examines how AI transforms the management of SER-rich power systems along three critical dimensions: 1) enhancing visibility by inferring behind-the-meter (BTM) activities, assessing SER flexibility, and reconstructing system states from sparse or noisy measurements; 2) improving operation through AI-enhanced SER service provision, volt/var control (VVC), and dynamic operating envelopes (DOE) for efficiency and security; and 3) advancing control by embedding learning-based intelligence into inverter coordination, voltage and frequency regulation, and long-term dispatch. Together, these developments reveal how AI can convert the variability of SERs from an operational challenge into a source of flexibility, resilience, and intelligence, paving the way toward sustainable, adaptive, and self-optimizing power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Guided Resilience Self Assessment Application

Reliable electricity access is vital for everything from hospitals to national security. When grid disturbances occur, it is crucial to minimize the amount of time it takes to recover. Grid resiliency considers both the preparation for and recovery from high-impact low-frequency disturbances (HILF) such as weather events and cyber attacks. The Department of Energy (DOE) Wind Energy Technologies Office (WETO) funds the multi-laboratory Microgrids, Infrastructure Resilience, and Advanced Control Launchpad (MIRACL) project to investigate technologies to support and grow distributed wind. Researchers at Idaho National Laboratory (INL) contribute to resilience and cybersecurity efforts for the project, and have produced a resilience framework to evaluate system resilience based on individual system specifications. In order to make this framework easy for anyone to apply, I have coded a web application that allows users to input their power system qualities, goals, and perceived risks and then receive suggestions on how to improve their grid resiliency. The web application follows the seven steps in the planning stage of the framework process, allowing the user to input information about their grid and select from common goals, metrics, and hazards, as well as add their own. The application currently provides information about how to complete each step, requiring minimal prior knowledge of the framework. Future work for this application will include allowing the user to submit line drawings of their system and incorporate modeling tools so that the hazard simulations of applying the framework is completed for the user.

97 MATHEMATICS AND COMPUTING↗

Water & Energy Interdependencies Across Economic Sectors of the United States

The motivation of the Integrated Water Power Resilience Project is to identify and develop opportunities for improving resilience in the water and power sectors through coordinated planning, investment, and operations and thereby provide benefits to power and water utilities, consumers, and the environment. Water and power systems are interdependent, subject to many of the same natural and manmade hazards, and are critical for the well-being of communities and society. Because of the interconnectedness of water and power systems, there are substantial economic, social, and environmental benefits to co-managing the market sectors for resilience instead of managing them separately. To support this initiative and future research in this area, a county level water and energy flow dataset was developed to build, calculate, and visualize interconnections in water and energy between various sectors. This report presents county and regional water and energy visualizations across nine economic sectors of the United States: agriculture, commercial, electricity generation, industrial, mining, public water supply, residential, transportation, and wastewater treatment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Bad River Band of Lake Superior Chippewa Indians Solar Project

The Bad River Band of Lake Superior Chippewa (the Tribe) implemented its first phase of energy independence through the installation of approximately 520 kW DC of solar photovoltaic (PV) at three tribal buildings: 200kW DC at the Wastewater Treatment Plant (WWTP), 300 kW DC at the Health & Wellness Center (Health Clinic), and 20 kW AC at the Chief Blackbird Administration Building (Administration Building). The solar PV systems were integrated with the existing utility grid and can operate independent of the grid using Battery Energy Storage Systems (BESS) in combination with solar and existing back-up gas generators. The BESS also creates resiliency, providing power when the grid is down. All three buildings are essential Tribal buildings.

14 SOLAR ENERGY↗