Results for “emissions control technologies” — Page 8

NASA NTRSDate not supplied

Update on Subsonic Single Aft Engine (SUSAN) Electrofan Trade Space Exploration

NASA is conducting an ongoing trade study analysis of the SUSAN Electrofan aircraft concept, which utilizes 20-MW-class electrified aircraft propulsion to enable propulsive, aerodynamic, and control benefits while retaining the range, speed, and size of typical narrow-body regional aircraft. The study is constrained by the ground rules of operating within the current airport and airspace infrastructure. This ongoing study seeks to find a configuration and combination of technologies that yield significant fuel burn and emissions benefits. Another key goal is to reduce cost per passenger mile. Currently, the study is focused on a configuration that utilizes jet A or sustainable aviation fuels, however, we plan to consider other fuel alternatives in the future. This paper describes the progress in defining the architecture of the aircraft, engine, power system, control system, and initial understandings of the sensitivity of the potential configurations to technology assumptions based on key performance parameters. Additionally, progress towards definition and refinement of driving operational, economic, infrastructure, certification, and technical requirements is discussed.

aircraft concept↗

NASA NTRSDate not supplied

Update on Subsonic Single Aft Engine (SUSAN) Electrofan Trade Space Exploration

NASA is conducting an ongoing trade study analysis of the SUSAN Electrofan aircraft concept, which utilizes 20-MW-class electrified aircraft propulsion to enable propulsive, aerodynamic, and control benefits while retaining the range, speed, and size of typical narrow-body regional aircraft. The study is constrained by the ground rules of operating within the current airport and airspace infrastructure. This ongoing study seeks to find a configuration and combination of technologies that yield significant fuel burn and emissions benefits. Another key goal is to reduce cost per passenger mile. Currently, the study is focused on a configuration that utilizes jet A or sustainable aviation fuels, however, we plan to consider other fuel alternatives in the future. This presentation describes the progress in defining the architecture of the aircraft, engine, power system, control system, and initial understandings of the sensitivity of the potential configurations to technology assumptions based on key performance parameters. Additionally, progress towards definition and refinement of driving operational, economic, infrastructure, certification, and technical requirements is discussed.

Ralph H. Jansen↗

DOE OSTI2021

The role of chalcogen vacancies for atomic defect emission in MoS 2

For two-dimensional (2D) layered semiconductors, control over atomic defects and understanding of their electronic and optical functionality represent major challenges towards developing a mature semiconductor technology using such materials. Here, we correlate generation, optical spectroscopy, atomic resolution imaging, and ab initio theory of chalcogen vacancies in monolayer MoS 2 . Chalcogen vacancies are selectively generated by in-vacuo annealing, but also focused ion beam exposure. The defect generation rate, atomic imaging and the optical signatures support this claim. We discriminate the narrow linewidth photoluminescence signatures of vacancies, resulting predominantly from localized defect orbitals, from broad luminescence features in the same spectral range, resulting from adsorbates. Vacancies can be patterned with a precision below 10 nm by ion beams, show single photon emission, and open the possibility for advanced defect engineering of 2D semiconductors at the ultimate scale.

36 MATERIALS SCIENCE↗

NASA NTRS1982

Energy efficient engine combustor test hardware detailed design report

The combustor for the Energy Efficient Engine is an annular, two-zone component. As designed, it either meets or exceeds all program goals for performance, safety, durability, and emissions, with the exception of oxides of nitrogen. When compared to the configuration investigated under the NASA-sponsored Experimental Clean Combustor Program, which was used as a basis for design, the Energy Efficient Engine combustor component has several technology advancements. The prediffuser section is designed with short, strutless, curved-walls to provide a uniform inlet airflow profile. Emissions control is achieved by a two-zone combustor that utilizes two types of fuel injectors to improve fuel atomization for more complete combustion. The combustor liners are a segmented configuration to meet the durability requirements at the high combustor operating pressures and temperatures. Liner cooling is accomplished with a counter-parallel FINWALL technique, which provides more effective heat transfer with less coolant.

Zeisser, M. H.↗

NASA NTRS1989

Wood Bond Testing

A joint development program between Hartford Steam Boiler Inspection Technologies and The Weyerhaeuser Company resulted in an internal bond analyzer (IBA), a device which combines ultrasonics with acoustic emission testing techniques. It is actually a spinoff from a spinoff, stemming from a NASA Lewis invented acousto-ultrasonic technique that became a system for testing bond strength of composite materials. Hartford's parent company, Acoustic Emission Technology Corporation (AET) refined and commercialized the technology. The IBA builds on the original system and incorporates on-line process control systems. The IBA determines bond strength by measuring changes in pulsar ultrasonic waves injected into a board. Analysis of the wave determines the average internal bond strength for the panel. Results are displayed immediately. Using the system, a mill operator can adjust resin/wood proportion, reduce setup time and waste, produce internal bonds of a consistent quality and automatically mark deficient products.

Source record↗

NASA NTRS1999

Combustion Instabilities Modeled

NASA Lewis Research Center's Advanced Controls and Dynamics Technology Branch is investigating active control strategies to mitigate or eliminate the combustion instabilities prevalent in lean-burning, low-emission combustors. These instabilities result from coupling between the heat-release mechanisms of the burning process and the acoustic flow field of the combustor. Control design and implementation require a simulation capability that is both fast and accurate. It must capture the essential physics of the system, yet be as simple as possible. A quasi-one-dimensional, computational fluid dynamics (CFD) based simulation has been developed which may meet these requirements. The Euler equations of mass, momentum, and energy have been used, along with a single reactive species transport equation to simulate coupled thermoacoustic oscillations. A very simple numerical integration scheme was chosen to reduce computing time. Robust boundary condition procedures were incorporated to simulate various flow conditions (e.g., valves, open ends, and choked inflow) as well as to accommodate flow reversals that may arise during large flow-field oscillations. The accompanying figure shows a sample simulation result. A combustor with an open inlet, a choked outlet, and a large constriction approximately two thirds of the way down the length is shown. The middle plot shows normalized, time-averaged distributions of the relevant flow quantities, and the bottom plot illustrates the acoustic mode shape of the resulting thermoacoustic oscillation. For this simulation, the limit cycle peak-to-peak pressure fluctuations were 13 percent of the mean. The simulation used 100 numerical cells. The total normalized simulation time was 50 units (approximately 15 oscillations), which took 26 sec on a Sun Ultra2.

Paxson, Daniel E.↗

NASA NTRS2022

Low-Speed Performance Enhancement Using Localized Active Flow Control: Localized Active Flow Control Simulations on a Reference Aircraft (2/4)

A study of the potential implementations of localized active flow control (AFC) technology onto future airplanes is presented. This collaborative investigation addresses key objectives of the NASA Advanced Air Transport Technology (AATT) Project, in terms of reduction in fuel consumption and lower emission. It specifically targets the goals set forth in a roadmap developed by the NASA/Boeing team. The roadmap is a result of a series of meetings held between the two parties over the years and it represents a shared vision for practical implementations, leading up to flight demonstrations of localized flow control. If successful, localized flow control may lead to important ramifications for next generation airplanes from both the economic and environmental perspectives. Under this contract localized AFC has been used to improve aerodynamic performance during high-lift operations using Computational Fluid Dynamics (CFD). Specifically, AFC has been applied at the aileron and at various location in the wing leading edge (LE) regions. The applications target reduced drag and enhanced lift over the range of practical angles of attack, including stall. These benefits translate to airplane performance improvements, such as longer range or larger payload. The CFD results are used to quantify potential aerodynamic benefits, as well as the input required for actuation. This helps identify the most promising candidates, which potentially provide material net airplane level enhancements using onboard fluidic sources. The airplane configuration selected for the CFD study is a representative of a future short/medium-range twin-engine airplane dubbed the Reference Aircraft. A slew of AFC applications has been explored and their aerodynamic performance enhancements were benchmarked against the baseline Reference Aircraft. Promising AFC candidates have been deemed practical and potentially suitable for both the aileron and the wing LE implementations. The findings on the Reference Aircraft are used to guide the development of the AFC-enhanced aileron for the CRM-HL. The wind-tunnel model of the CRM-HL will be used by NASA to validate the AFC concepts, complementing the CFD-based analysis and the integration study (final report document #3).

CFD↗

DOE OSTI2024

Carbon Management Projects (CONNECT) Database and Explorer

Overview The Carbon Management Projects (CONNECT) Toolkit is an online exploratory visualization tool developed by the U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management (FECM) with support from other federal agencies such as the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Transportation (DOT). It provides a single point of access to authoritative information on federal agency investment in a portfolio of research, development, and demonstration (RD&D) projects that have been publicly announced to advance technologies for point source carbon capture, carbon dioxide removal, transport, storage, and conversion, collectively referred to as carbon management. The RD&D programs covered in this tool are authorized by annual congressional appropriations ("Base Program") and the 2021 Infrastructure Investment and Jobs Act (IIJA). The tool also incorporates public information on other federal initiatives, such as the Regional Clean Hydrogen Hubs, and public information released by other government agencies, such as the Environmental Protection Agency's (EPA) and Primacy States’ Underground Injection Control Class VI permits and EPA’s facility level greenhouse gas (GHG) emissions. Developed in a geographic information system, the tool organizes carbon management projects into five groups based on the primary technology that a project aims to advance, each visually represented as a digital layer ("carbon management project layer"). Only federally funded projects are included, which can be awarded projects that are completed or ongoing, or projects that have been selected but are currently under negotiation. Project information can be viewed in the map or in the attribute table below it when turned on. In the map view, each project is displayed at either its host site (for field work), where available, or its performer site (project lead's location, further explained in the table below). Host sites and performer sites are represented in distinct icons. Several reference layers offer additional public information on infrastructural and natural resource environment for carbon management. These reference layers, combined with multiple geographical basemaps, enable users to visualize the carbon management project layers in context. Carbon management project information will be updated monthly based on feedback and information availability. Carbon management project layers Point Source Carbon Capture (PSC) This layer contains DOE-funded projects focused on capturing carbon dioxide (CO2) from power plants or industrial facilities. Carbon Dioxide Removal (CDR) This layer contains DOE-funded projects focused on capturing CO2 from the atmosphere, including direct air capture (DAC) and DAC hubs, direct ocean capture, enhanced mineralization, and biomass carbon removal and storage. For projects with multiple host sites, each of the sites are displayed individually with the project cost and cost sharing information representing the total for the entire project. Carbon Transport This layer contains DOE- and DOT-funded projects focused on CO2 transport. The Transport Research and Development sublayer contains projects that do not involve physical infrastructure; the Proposed Transport Corridor sublayer contains projects for which either a route for the transport infrastructure has been proposed or a general area for the transport infrastructure has been identified. Carbon Storage This layer contains DOE-funded key projects focused on CO2 storage. For projects with multiple field-work sites, each of the sites are displayed individually on the map with the project cost and cost sharing information representing the overall total for the entire project. Carbon Conversion This layer contains DOE-funded projects focused on converting CO2 into economically valuable products. Reference layers The following layers provide additional information in the geographic proximity of carbon management projects. Users should reference the original sources for more details (weblinks provided below and in pop-up windows on the map). Regional Clean Hydrogen Hub and Facility These layers illustrate the approximate areas of the Regional Clean Hydrogen Hubs announced by DOE's Office of Clean Energy Demonstrations (OCED) and the approximate locations of individual facilities that constitute the hubs (see "Where are the H2Hubs located?" on the webpage linked above). EPA Facility Level GHG Emissions (direct emitter) This layer shows direct CO2 emissions from stationary sources in 2022, using data extracted from EPA's Facility Level Information on GreenHouse gases Tool (FLIGHT). Captured and injected CO2 are not deducted from direct emitters’ total emissions. Contact EPA for additional details. Underground Injection Control Class VI permit/permit application This layer shows the locations of CO2 injection wells that are granted or in the process of applying for an Underground Injection Control Class VI permit by EPA or a Primacy State (currently Louisiana, North Dakota, and Wyoming). The URLs for the permits or permit applications are provided in the pop-up windows associated with the well locations. Contact EPA for additional details. Carbon Storage Resource This layer contains information on prospective CO2 storage resources in saline formations and oil and gas reservoirs provided by the National Carbon Sequestration Database and Geographic Information System (NATCARB) spatial database. Contact NETL for additional details. Existing CO2 pipeline This layer shows active CO2 pipelines based on information digitized from the map issued by the Pipeline and Hazardous Materials Safety Administration (PHMSA). Contact PHMSA for additional details.

Carbon Conversion↗

NASA NTRSDate not supplied

Piloted Evaluation of a Fault Recovery System for an Aircraft with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.

Electrified Aircraft Propulsion↗

NASA NTRS2025

Piloted Evaluation of a Fault Recovery System for an Aircraft with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.

Electrified Aircraft Propulsion↗

NASA NTRSDate not supplied

Piloted Evaluation of a Fault Recovery System for an Aircraft with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.

Electrified Aircraft Propulsion↗

DOE OSTI2023

Evaluation of Torque-Dense Electric Machine Technology for Off-Highway Vehicle Electrification

Electrification of off-highway vehicles offers the benefits of improved energy efficiency, enhanced control, and reduction in greenhouse gas emissions. However, progress towards electrification has been limited by the low torque density (30 kNm/m 3 ) of conventional electric machines compared to mobile hydraulic machines (up to approximately 1000 kNm/m 3 ). This paper reviews emerging variants of electric machines that offer a step improvement in torque density and potential pathway to enable electrified off-highway vehicles. First, sizing approaches for electric and hydraulic machines are developed, and torque-dense electric machines reviewed in literature are compared to commercial hydraulic machines to identify design trends in terms of speed, torque density, and power density. Next, key metrics are identified for the electric machine, based on which the following four emerging electric machine variants that promise to improve torque density are reviewed: i) multi-harmonic machines injection, ii) combined radial-axial flux machines, iii) magnetic gears, and iv) magnetically-geared machines. Here, the findings from this review show that these new electric machines can achieve upwards of 300% improvement in electric machine torque density, with several designs exceeding 100 kNm/m 3 , making them worthy candidates for further research to bridge the torque density gap with hydraulic machines.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Ducted Fuel Injection and Cooled Spray Technologies for Particulate Control in Heavy-Duty Diesel Engines

Heavy-Duty diesel engine manufacturers are continuously in pursuit of simple and low-cost technologies that can reduce emissions. Ducted fuel injection (DFI) and Cooled Spray (CS) technologies are two technologies that continue to show promise for significant particulate emissions reductions. These technologies represent a breakthrough in diesel engine combustion from the potential of nearly sootless diesel combustion. This can provide a significant decrease in harmful PM emissions and may enable further system optimization for reduced NOx emissions and increased efficiency. Combustion vessel experiments and engine demonstrations at Sandia, together with the large bore engine tests performed by Wabtec show that this technology may be applicable to heavy duty diesel engines across a wide range of engine sizes and speeds representing the majority of off-road diesel engines. However, very little is known about the ideal geometry, scaling properties or effectiveness of these technologies over the engine operating map. This project will address those uncertainties through a series of experiments performed in an optical and a metal single-cylinder engine.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2005

Wireless Phone Threat Assessment for Aircraft Communication and Navigation Radios

Emissions in aircraft communication and navigation bands are measured for the latest generation of wireless phones. The two wireless technologies considered, GSM/GPRS and CDMA2000, are the latest available to general consumers in the U.S. A base-station simulator is used to control the phones. The measurements are conducted using reverberation chambers, and the results are compared against FCC and aircraft installed equipment emission limits. The results are also compared against baseline emissions from laptop computers and personal digital assistant devices that are currently allowed to operate on aircraft.

Nguyens, T. X.↗

DOE OSTI2024

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been proposed; however, these technologies lack comprehensive validation under real-world application scenarios. This paper addresses this gap by designing and developing a controller-hardware-in-the-loop framework to evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. Simulation results indicate the superior performance of an ML-based approach compared to the conventional reference-control grouping-based approach, showcasing its potential to support grid stability and operational efficiency.

closed-loop validation↗

DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗

DOE OSTI2025

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been proposed; however, these technologies lack comprehensive validation under real-world application scenarios. This paper addresses this gap by designing and developing a controller-hardware-in-the-loop framework to evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. Simulation results indicate the superior performance of an ML-based approach compared to the conventional reference-control grouping-based approach, showcasing its potential to support grid stability and operational efficiency.

14 SOLAR ENERGY↗

DOE OSTI2024

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services: Preprint

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been proposed; however, these technologies lack comprehensive validation under real-world application scenarios. This paper addresses this gap by designing and developing a controller-hardware-in-the-loop framework to evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. Simulation results indicate the superior performance of an ML-based approach compared to the conventional reference-control grouping-based approach, showcasing its potential to support grid stability and operational efficiency.

closed-loop validation↗