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Advanced Measurements for Resilient Integration of Inverter-Based Resources: PROGRESS MATRIX Final Report

As nearly every aspect of the electric power grid undergoes rapid change, measurement technologies that support grid operation and planning must evolve as well. The rapid large-scale deployment of inverter-based resources (IBRs) vital to achieving the nation’s clean energy goals has in some cases led to negative impacts on the reliability and security of the bulk power system (BPS). Advanced power system measurements, including synchronized phasor and waveform measurements, are key to making IBR integration secure and reliable. To this end, the Department of Energy (DOE) initiated the PROGRESS MATRIX project to develop advanced measurement capabilities and analytics that will accelerate adoption of IBRs while improving the reliability and resilience of the BPS. This report discusses the outcomes of the project, which was a joint effort between the Pacific Northwest National Laboratory (PNNL), Oak Ridge National Laboratory (ORNL), the National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory (LBNL). In the project’s first year, PNNL, NREL, and ORNL partnered with the Bonneville Power Administration (BPA), the Western Area Power Administration (WAPA), and Kauai Island Utility Cooperative (KIUC) to understand their existing measurement capabilities and the gaps limiting deployment of IBR-focused measurement systems and analytics. The other primary activity in the first year was deployment of GridSweep instruments, which provide unprecedented precision in waveform measurement while probing distribution systems. The instruments were deployed at Dominion Energy and the University of California, Riverside. In the project’s second year, the input from partner utilities and collected measurements were used to advance measurement capabilities. Twelve analytical methods spanning disturbance analysis, power plant evaluation, feeder evaluation, and modeling were developed. Two software tools were developed, one to analyze GridSweep measurements and another to automatically evaluate the control performance of power plants connected to the BPS. Testbeds at ORNL and NREL were augmented to better enable studies of IBR integration. The project culminated in demonstrations of these analytical methods, software tools, and testbeds, both in the field and in the laboratory. This report discusses these various accomplishments and documents the significant progress in developing advanced measurement capabilities to support the secure, reliable, and accelerated adoption of IBRs in the BPS.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advanced Measurements for Resilient Integration of Inverter-Based Resources: PROGRESS MATRIX Year-1 Report

As nearly every aspect of the electric power grid undergoes rapid change, measurement technologies that support grid operation and planning must evolve as well. Recent large-scale deployments of inverter-based resources (IBRs) have brought to the forefront the critical need for new measurement technologies. Though these IBRs are vital to achieving the nation’s clean energy goals, their rapid deployment has in some cases led to negative impacts on the reliability and security of the bulk power system (BPS). Advanced power system measurements, including synchronized phasor and waveform measurements, are key to making IBR integration secure and reliable. To this end, the Department of Energy (DOE) initiated a project in 2022 to develop advanced measurement capabilities and analytics that will accelerate adoption of IBRs while improving the reliability and resilience of the BPS. This report discusses a portion of the findings from the project’s first year, which focused on surveying existing measurement capabilities of partner utilities and comparing these capabilities with the requirements of applications that support IBR integration. This report also discusses how these findings will guide the development and demonstration of a set of applications in the project’s second year.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advanced Research on Integrated Energy Systems Cyber Range

As digital technologies expand to meet the needs of a more autonomous, interconnected, and advanced power system, new cybersecurity complexities and vulnerabilities arise. The ARIES Cyber Range enables the energy sector to evaluate these evolutions and validate cybersecurity solutions without impacting live systems. Combining power grid-scale hardware with emulation and simulation approaches, the ARIES Cyber Range can faithfully replicate modern energy systems - from grid physics to communication networks, and everything in between - with real-world fidelity. At NLR, researchers and partners are answering complex power system cybersecurity questions, examining emerging threats to the electric sector, and de risking new security technologies, all at a mission-relevant speed that keeps pace with rapidly evolving systems and hazards.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Introducing the 9500 Node Distribution Test System to Support Advanced Power Applications: An Operations-Focused Approach

The 9500 Node Test System is a representative section of distribution power system model developed as a part of the GridAPPS-D™ project, an effort funded by DOE as a part of the Grid Modernization Lab Consortium (GMLC) program. The test system was developed to fulfill a growing need to represent the rapidly evolving state of electric distribution systems by combining elements of legacy infrastructure systems, modern feeder topologies, and an anticipated future with smart grid technologies. It also provides a network model capable of supporting the simulation of operational scenarios such as the ones in a utility distribution control center. This test system allows the evaluation of the performance of advanced power applications in real-time, such as one that simulates the operations of an Advanced Distribution Management Systems (ADMS), Distributed Energy Resource Management Systems (DERMS), etc. in a Distribution control center. This model is an extension of the widely used IEEE 8500 Node Test Feeder and is currently being validated to become an IEEE test case to help increase adoption and widespread usage among both academia and industry. It is a full-size model representative of a section of a utility’s distribution system with multiple feeders fed from different substations. The model includes multiple distribution circuits, a sub-transmission system, multiple substations, behind the meter customer rooftop photovoltaics (PV), and multiple utility-scale distributed energy resources. To enable accurate simulations of operational scenarios, the 9500 Node Test System is designed to support procedure-based operations, with the ability to realistically demonstrate switching operations, feeder reconfiguration, adjustment of volt-var control equipment, dispatch of distributed generation, and response to planned and unplanned outages. The 9500 Node Test System includes three radial distribution feeders with 12.3 MVA of average load, consisting of both medium voltage and low voltage equipment each supplied by a different distribution substation. The three distribution feeders are connected to each other through Normally-Open switches which can be closed when needed to simulate restoration scenarios due to a fault. One feeder represents today’s grid with low penetration of customer-side renewables. The second represents a potential future grid with microgrids and 100% renewable penetration. The third has no customer generation resources, a district steam plant, and a utility-scale solar farm. The three diverse circuits were created to allow the simulation of both today’s situation as well as potential future scenarios. All three feeders have customers connected by low-voltage secondary triplex lines. This test system meets all requirements outlined in the report for creating a simulation environment that would enable discussion between key technical stakeholders as well as having the potential to accelerate operational application development and their subsequent testing and integration. The new model is a possible representation of what we believe the distribution grid may look like in the future: a high penetration of renewables, reconfigurable radial and mesh topology, numerous DERs, islanded microgrids, and significantly increased data and measurement density. The system supports both the solution of existing and newer algorithms but also enables the evaluation of applications in a realistic operational environment defined by task oriented procedural steps that represent the interaction between the control center operator and field personnel.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Turbine-based Power System Tool

Advanced research tools are essential to illustrate the effects of turbine-based power system operations on the electric grid network. This paper presents the development of an open-source tool to visualize the operation of turbine-based electricity generation. The tool exposes power system models, control parameters, and corresponding values of the turbine model and its electrical system, allowing them to customize the simulation according to their needs. The developed tool enables users to simulate power profiles for different turbinebased energy generation such as wind, tidal, and gas turbines. It allows users to investigate the details of the generated profiles of various types of turbine systems at various scales. It can provide valuable insights into model development and facilitate the analysis of integrated power systems. By enabling access to turbine-based operations visualization, the tool aims to bridge the gap between advanced research tools and users, facilitating broader adoption of renewable energy technologies and aiding in developing sustainable power systems.

Kini, Roshan L.↗

Propulsion System Hybridization and Electrification and Energy Recovery of the Hydraulic System for a Diesel-Powered Off-Road Carry/Lift Machine Final Technical Report (FTR)

Historically, heavy-duty off-road equipment has prioritized performance, reliability, and cost, with limited emphasis on efficiency. While increasing carbon dioxide (CO 2 ) regulations have driven a focused effort for efficiency in on-road vehicles, off-road machines have remained largely overlooked, leaving significant opportunities for efficiency improvements and emissions reductions. To address this overlooked industry, Michigan Technological University’s Advanced Power Systems Research Center (APS LABS) worked with Pettibone to determine a unique electrified architecture for Pettibone’s heavy-duty off-road material handler, the Cary-Lift 204i, with a goal of 20% fuel savings. The base Cary-Lift uses a diesel engine with no electrification.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Total Power Factor Smart Contract with Cyber Grid Guard Using Distributed Ledger Technology for Electrical Utility Grid with Customer-Owned Wind Farm

In modern electrical grids, the numbers of customer-owned distributed energy resources (DERs) have increased, and consequently, so have the numbers of points of common coupling (PCC) between the electrical grid and customer-owned DERs. The disruptive operation of and out-of-tolerance outputs from DERs, especially owned DERs, present a risk to power system operations. A common protective measure is to use relays located at the PCC to isolate poorly behaving or out-of-tolerance DERs from the grid. Ensuring the integrity of the data from these relays at the PCC is vital, and blockchain technology could enhance the security of modern electrical grids by providing an accurate means to translate operational constraints into actions/commands for relays. This study demonstrates an advanced power system application solution using distributed ledger technology (DLT) with smart contracts to manage the relay operation at the PCC. The smart contract defines the allowable total power factor (TPF) of the DER output, and the terms of the smart contract are implemented using DLT with a Cyber Grid Guard (CGG) system for a customer-owned DER (wind farm). This article presents flowcharts for the TPF smart contract implemented by the CGG using DLT. The test scenarios were implemented using a real-time simulator containing a CGG system and relay in-the-loop. The data collected from the CGG system were used to execute the TPF smart contract. The desired TPF limits on the grid-side were between +0.9 and +1.0, and the operation of the breakers in the electrical grid and DER sides was controlled by the relay consistent with the provisions of the smart contract. The events from the real-time simulator, CGG, and relay showed a successful implementation of the TPF smart contract with CGG using DLT, proving the efficacy of this approach in general for implementing electrical grid applications for utilities with connections to customer-owned DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Evaluating Impacts of the Inflation Reduction Act and Bipartisan Infrastructure Law on the U.S. Power System

The Inflation Reduction Act of 2022 (IRA) and the Infrastructure Investment and Jobs Act of 2021, commonly referred to as the 'Bipartisan Infrastructure Law (BIL),' collectively represent the largest commitment of the U.S. Federal Government to invest in the modernization and decarbonization of the U.S. energy system. The Congressional Budget Office (CBO) estimates that total support for the broad range of climate and clean energy programs, tax credits, and other incentives authorized through the two laws will exceed $430 billion from 2022 through 2031 (CRS 2022; CBO 2021, 2022). While the climate and clean energy provisions are numerous and have the potential to impact all aspects of the U.S. energy system from fuel and electricity production to final consumption in industry, transportation, and buildings, the provisions relevant to the electricity sector - in particular the suite of tax credits for clean generation, storage, and carbon dioxide ( CO 2 ) capture and storage - are expected to be some of the most consequential in terms of emissions reduction and clean energy deployment (Larsen et al. 2022; Jenkins, Mayfield, et al. 2022; Mahajan et al. 2022; Zhao et al. 2022). In this report, we detail the methods and results of a study estimating the potential impacts of key provisions of IRA and BIL on the contiguous U.S. power sector from present day through 2030. The analysis employs an advanced power system planning model, the Regional Energy Deployment System (ReEDS), to evaluate how major provisions from both laws impact investment in and operation of utility-scale generation, storage, and transmission, and, in turn, how those changes impact power system costs, emissions, and climate and health damages. While not exhaustive in capturing every provision, the analysis estimates the possible scale of power-sector impacts that could result from the modeled provisions in IRA and BIL. The study is structured around two scenarios to evaluate the potential impacts of both laws on the power sector: 1) No New Policy: A counter-factual scenario that reflects all Federal and state policies enacted as of September 2022, with exception to IRA and BIL, and assumes load growth consistent with the Energy Information Administration's Annual Energy Outlook 2022 (AEO22) Reference case (EIA 2022a); 2) IRA-BIL: A scenario reflecting all Federal and state policies enacted as of September 2022, including key IRA and BIL provisions, most notably the investment and production tax credits for zero-carbon emitting electricity generation and storage (ITC and PTC), the tax credit for CO 2 capture and storage (45Q), and the tax credit for existing nuclear plants (described further in Section 2.3). To account for the impacts of IRA and BIL on electrification, assumes increased load growth consistent with a scaled version of the Medium Electrification scenario from the Electrification Futures Study (Mai et al. 2018). These scenarios are simulated across seven sets of assumptions with varying projected future electricity market conditions, including technology costs and performance, natural gas prices, and the degree of availability, feasibility, and cost of development of renewable resources, electricity transmission, and CO 2 pipeline, injection, and storage infrastructure. In addition, we simulate two sensitivities on the 'policy' treatment in which we vary key assumptions pertaining to the realized value of the clean electricity ITC and PTC: 1) the cost of monetization of tax credits, and 2) the level of bonus crediting realized by project developers. We demonstrate that IRA and BIL have the collective potential to drive substantial growth in clean electricity by 2030, while reducing costs for consumers, mitigating climate change, and decreasing the human health impacts of power sector emissions. However, we also demonstrate that if expected cost improvements of clean technologies are not realized and/or constraints on deployment driven by factors such as supply-chain challenges, regulatory hurdles, and the social acceptability of energy infrastructure development limit the rate of clean energy and associated infrastructure deployment (such as transmission), then the share of clean generation achieved and the associated emissions benefits realized may be substantively reduced.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Heavy-Duty Nonroad Material Handler Electrification Part 1: Real-World Drive Cycle Development

Knowing a detailed operating cycle is critical for developing and testing equipment. Operating cycles can be separated by two clear distinctions: (1) regulatory or non-regulatory and (2) application at the engine-only or full machine level. The Environmental Protection Agency’s (EPA) Nonroad Transient Cycle (NRTC) may be a good representation of engine use in many types of equipment, but there is a gap in standardized and validated drive cycles specifically for nonroad material handlers. Lacking a standardized drive cycle makes it difficult to accurately benchmark machine performance and validate new powertrain technologies. The objective of this investigation is to illustrate the development of a custom drive cycle augmented with real-world customer use data that serves multiple purposes: (1) understand the range of operation and utilization that formulated inputs for electrified architecture analysis and (2) develop a repetitive and consistent maneuver to establish baseline energy consumption enabling equivalent comparison to future electrified prototype builds. This article presents a solution specifically for a 23-ton nonroad material handler in which material handling, machine transport, and extended idle were homologated to form representative short cycles defined by machine velocity and hydraulic cylinder position. The most intensive material handling short cycles had a load factor of 40% and an average fuel rate of 16 L/h. Combined with a visual aid, the short cycles exhibited low variability, having less than 5% root mean square (RMS) error in lift and reach position with respect to the average. The machine’s performance on these short cycles at the Advanced Power Systems Research Center (APSRC) was compared to results from two real-world customer locations operating the instrumented test machine in a cyclical manner, and for similar ground conditions were found to be comparable in fuel consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Time Sequence Machine Learning-Based Data Intrusion Detection for Smart Voltage Source Converter-Enabled Power Grid

Smart inverters of distributed energy resources can enable cloud computing, condition monitoring, result visualization, remote control, and peer-to-peer energy trading in advanced power systems. However, the advent of data injection attacks in the communication architecture can alter measurement characteristics of power grids and have devastating consequences. In this article, we propose a time sequence machine learning-based anomaly detection methodology for detecting cyber intrusion into control signal setpoints and dc voltage signal measurement bias of the voltage source converter (VSC) in wind generators. We first investigated the effects of four types of denial of service, tampering signal, and stealthy-type data intrusion attacks on smart VSCs and overall wind farms. We then proposed a novel time sequence machine learning-based intrusion detection framework that can be implemented to detect different cyberattacks in the VSCs. The performance of the proposed framework has been compared with that of autoencoder and clustering-based intrusion detection framework. The proposed framework was validated by using the IEEE 39 bus power system in the presence of four wind farms in different locations. Using several metrics for intrusion detection performance, we validated the effectiveness of the proposed framework.

42 ENGINEERING↗

Advanced Stirling Power Generation System for Combined Heat and Power

The goal of this project was the development of an advanced Free-Piston Stirling Engine (FPSE) power generation for combined heat and power application. The innovative approach used in this project was the use of Additively Manufactured (AM) for critical components of an FPSE. A Stirling convertor consists of three major components/subassemblies, 1) Stirling engine, 2) linear alternator, and 3) gas fuel burner. The primary focus of this project was the design of the FPSE. This engine was integrated with an ITC/Qnergy 1 kW linear alternator. The integrated convertor was then coupled to a gas burner.

09 BIOMASS FUELS↗

A Review of Edge Computing Technology and Its Applications in Power Systems

Recent advancements in network-connected devices have led to a rapid increase in the deployment of smart devices and enhanced grid connectivity, resulting in a surge in data generation and expanded deployment to the edge of systems. Classic cloud computing infrastructures are increasingly challenged by the demands for large bandwidth, low latency, fast response speed, and strong security. Therefore, edge computing has emerged as a critical technology to address these challenges, gaining widespread adoption across various sectors. This paper introduces the advent and capabilities of edge computing, reviews its state-of-the-art architectural advancements, and explores its communication techniques. A comprehensive analysis of edge computing technologies is also presented. Furthermore, this paper highlights the transformative role of edge computing in various areas, particularly emphasizing its role in power systems. It summarizes edge computing applications in power systems that are oriented from the architectures, such as power system monitoring, smart meter management, data collection and analysis, resource management, etc. Additionally, the paper discusses the future opportunities of edge computing in enhancing power system applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advanced Reactor Safeguards & Security Program: Cybersecurity Scenarios

The use of digital control systems and automation in advanced nuclear power systems introduces different types of vulnerabilities compared to legacy (i.e. analog) control systems that cyber adversaries can exploit. These vulnerabilities pose a challenge to reactor operators and cyber operations staff due to the dynamic nature of the event in which a human response or a lack of response can potentially evolve into a worsening plant condition. Using the Department of Homeland Security Cyber and Infrastructure Security Agency’s (CISA) critical infrastructure exercise framework, this document presents several cyber security scenarios typical of digital control systems that could be used in advanced reactor designs. These scenarios can be used in tabletop exercises to evaluate cyber security posture or conduct training on different aspects of cyber security, including detection, threat hunting using indicators of compromise, evaluating incident response, risk mitigation, incident reporting, information sharing and recovery.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Advanced Guide to Understanding Power System Model Results for Long-Term Resource Plans

This guide is for public utility commission staff, state energy office staff, and other stakeholders who review model results for utility integrated resource plans (IRPs). It builds on the "Beginner's Guide to Understanding Power System Model Results for Long-Term Resource Plans," and delves into more advanced topics that were not included or not fully covered in the beginner's guide. The topics included here are evolving and may or may not be important to the resource plan you are evaluating. Due to limitations in resources, it's also not possible to give the highest level of detail or attention to every topic within a plan. An important part of planning for an uncertain future involves deciding which topics deserve the most focus and resources. It's all about prioritizing efforts where they will have the most impact or be most beneficial despite uncertainties ahead. As with the beginner's guide, we intend for this guide to help improve decision-making in the electricity planning process by strengthening understanding and dialogue between electricity system planners and relevant stakeholders. The following information is designed to allow you to better engage in the planning process by evaluating results, asking questions, and thinking through what is most important. We allocate significant discussion in the guide to electricity demand evolution, demand-side resources, and resource adequacy. These topics have garnered increasing attention, hence their prominence in this guide. Other topics are also presented, but their incorporation into the planning process might vary based on interest and relevance. The absence of certain topics doesn't diminish their importance; rather, it reflects the reality that in planning, trade-offs necessitate prioritizing certain aspects over others.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning

Here this article proposes a model-based deep reinforcement learning (DRL) method to design emergency control strategies for short-term voltage stability problems in power systems. Recent advances show promising results for model-free DRL-based methods in power systems control problems. But in power systems applications, these model-free methods have certain issues related to training time (clock time) and sample efficiency; both are critical for making state-of-the-art DRL algorithms practically applicable. DRL-agent learns an optimal policy via a trial-and-error method while interacting with the real-world environment. It is also desirable to minimize the direct interaction of the DRL agent with the real-world power grid due to its safety-critical nature. Additionally, the state-of-the-art DRL-based policies are mostly trained using a physics-based grid simulator where dynamic simulation is computationally intensive, lowering the training efficiency. We propose a novel model-based DRL framework where a deep neural network (DNN)-based dynamic surrogate model (SM), instead of a real-world power grid or physics-based simulation, is utilized within the policy learning framework, making the process faster and more sample efficient. However, having stable training in model-based DRL is challenging because of the complex system dynamics of large-scale power systems. We addressed these issues by incorporating imitation learning to have a warm start in policy learning, reward-shaping, and multi-step loss in surrogate model training. Finally, we achieved 97.5% reduction in samples and 87.7% reduction in training time for an application to the IEEE 300-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Powernet in Farms Project

Coordinating behind-the-meter (BTM) distributed energy resources (DERs) is critical to ensuring efficiency and reliability for consumers facing an increasingly variable grid supply. Outside of very controlled environments, however, such coordination of heterogeneous resources at scale has remained a challenge due to harsh field conditions, the lack of adequate communication infrastructure, and the difficulty of modeling the system. The intent of this research was to refine the Powernet system deployed in a California dairy farm to achieve the following objectives: a) validate the results of the previous deployment and b) validate new hypothesis about system performance based on the simulation of the new system. The new system design would reduce the overall system cost, and achieve a payback period of less than 3 years, demonstrating the feasibility of such system and its relevance for a segment not well known for technology advancements in power systems. The new proposed system was significantly cheaper than the original design, which would enable the solution to be cost effective and likely economically viable. However, due to significant delays in project start date which affected funding availability, overlap with prior scheduled mandatory military leave from key members of the project team, and customer drop-out, due to the significant delays, which could not be replaced in time, caused the project to be ended prior to completion.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The USAID-NREL Partnership

The United States Agency for International Development is drawing on U.S. Department of Energy national laboratory expertise to advance clean, resilient, and equitable energy systems in the developing world through the USAID-NREL Partnership.

advanced power systems↗