Results for “operational controller loops” — Page 44

NASA NTRS2019

The International Space Station (ISS) Port 1 (P1) External Active Thermal Control System (EATCS) Ammonia Leak

Ammonia is used in the Starboard 1 (S1) and Port 1 (P1) External Active Thermal Control System (EATCS) to cool the pressurized modules, and some of the external electrical power distribution hardware. Leaks that develop in these critical cooling systems that deplete in-line tanks can ultimately result in loss of cooling, which can have devastating impacts to the mission, science and crew onboard the ISS. A slow ammonia leak was initially observed from the P1 EATCS in 2011, but later in 2013 the leak rate began to accelerate. The ammonia inventory eventually began to decay exponentially, raising concerns that the inventory could drop to levels where the system would not be operational.The Robotic External Leak Locator (RELL) was built and launched to the ISS to detect and help locate ammonia leaks using the ISS Robotic Arm and remote ground operator control without constant crew involvement. RELL pinpointed the ammonia leak to the two flexible jumper hose assemblies connecting one of two fluid loops in one of the three deployable radiators to the P1 EATCS. The ammonia inside the two hose assemblies and that radiator fluid loop was isolated and vented to space in 2017. This stopped the leak and an Extravehicular Activity was conducted to remove the two hose assemblies so they could be returned to ground for further Test, Teardown and Evaluation (TT&E). The purpose of this presentation is to discuss this leakage scenario and the TT&E efforts.

Cowan, Darnell T.↗

DOE OSTI2017

Active control of one or more EGR loops

Active control of one or more exhaust gas recirculation loops is provided to manage and EGR fraction in the charge flow to produce desired operating conditions and/or provide diagnostics in response to at least one of an oxygen concentration and a NOx concentration in the charge flow and in the exhaust flow.

42 ENGINEERING↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

DOE OSTI2024

Power-Hardware-in-the-Loop Interfaces for Inverter-Based Microgrid Experiments Including Transitions

Microgrids continue to proliferate, particularly those that rely on inverter-based resources as the microgrid's voltage and frequency leader. Hardware-in-the-loop simulations can de-risk microgrid deployments, and therefore we need power-hardware-in-the-loop (PHIL) interfaces for grid-forming (GFM) inverters to enable simulations of seamless transitions between islanded and grid-connected operation. Such interfaces are particularly challenging when the inverters need to switch modes, i.e., between grid-following (GFL) and GFM as the microgrid transitions between grid-connected and islanded operation. This paper presents two PHIL interfaces for such microgrids and the preliminary experimental results.

experiments↗

DOE OSTI2018

Interconnection Standard Grid-Support Function Evaluations Using an Automated Hardware-in-the-Loop Testbed

Grid operators are increasingly turning to advanced grid-support functions in distributed energy resources (DER) to assist with distribution circuit voltage regulation, bulk system frequency control, and power system protection. The U.S. DER certification standard, Underwriters Laboratories (UL) 1741, was revised in September 2016 to add test procedures for multiple grid-support functions. Sandia National Laboratories, SunSpec Alliance, and growing community of collaborators have undertaken a multiyear effort to create an open-source system validation platform (SVP) that automates DER interconnection and interoperability test procedures by communicating with grid simulators, photovoltaic (PV) simulators, data acquisition systems, and interoperable equipment under test. However, the power hardware required for generating the test conditions may be untenable for many organizations. In this paper, we discuss development of the SVP testing capabilities for UL 1741 tests utilizing a controller hardware-in-the-loop testbed that precludes the need for power hardware using a 34.5 kW Austrian Institute of Technology smart grid controller. Finally, analysis of normal ramp rate, soft start ramp rate, specified power factor, volt-VAr, and frequency-watt advanced grid functions, and the effectiveness of the UL 1741 test protocols are included.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2013

Integration Test of the High Voltage Hall Accelerator System Components

NASA Glenn Research Center is developing a 4 kilowatt-class Hall propulsion system for implementation in NASA science missions. NASA science mission performance analysis was completed using the latest high voltage Hall accelerator (HiVHAc) and Aerojet-Rocketdyne's state-of-the-art BPT-4000 Hall thruster performance curves. Mission analysis results indicated that the HiVHAc thruster out performs the BPT-4000 thruster for all but one of the missions studied. Tests of the HiVHAc system major components were performed. Performance evaluation of the HiVHAc thruster at NASA Glenn's vacuum facility 5 indicated that thruster performance was lower than performance levels attained during tests in vacuum facility 12 due to the lower background pressures attained during vacuum facility 5 tests when compared to vacuum facility 12. Voltage-Current characterization of the HiVHAc thruster in vacuum facility 5 showed that the HiVHAc thruster can operate stably for a wide range of anode flow rates for discharge voltages between 250 and 600 volts. A Colorado Power Electronics enhanced brassboard power processing unit was tested in vacuum for 1,500 hours and the unit demonstrated discharge module efficiency of 96.3% at 3.9 kilowatts and 650 volts. Stand-alone open and closed loop tests of a VACCO TRL 6 xenon flow control module were also performed. An integrated test of the HiVHAc thruster, brassboard power processing unit, and xenon flow control module was performed and confirmed that integrated operation of the HiVHAc system major components. Future plans include continuing the maturation of the HiVHAc system major components and the performance of a single-string integration test.

Hall propulsion system↗

DOE OSTI2019

TRANSP-based closed-loop simulations of current profile optimal regulation in NSTX-Upgrade

Active control of the toroidal current density profile is critical for the upgraded National Spherical Torus eXperiment device (NSTX-U) to maintain operation at the desired high-performance, MHD-stable, plasma regime. Initial efforts towards current density profile control have led to the development of a control-oriented, physics-based, plasma-response model, which combines the magnetic diffusion equation with empirical correlations for the kinetic profiles and the non-inductive current sources. The developed control-oriented model has been successfully tailored to the NSTX-U geometry and actuators. Moreover, a series of efforts have been made towards the design of model-based controllers, including a linear-quadratic-integral optimal control strategy that can regulate the current density profile around a prescribed target profile while rejecting disturbances. In this work, the tracking performance of the proposed current-profile optimal controller is tested in numerical simulations based on the physics-oriented code TRANSP. These high-fidelity closed-loop simulations, which are a critical step before experimental implementation and testing, are enabled by a flexible framework recentlydeveloped to perform feedback control design and simulation in TRANSP.

current profile control↗

DOE OSTI2020

Accelerating Large-Format Metal Additive Manufacturing: How Controls R&D is Driving Speed, Scale, and Efficiency

This article highlights work at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility to develop closed-loop, feedback control for laser-wire based Directed Energy Deposition, a form of metal Big Area Additive Manufacturing (m-BAAM), a process being developed in partnership with GKN Aerospace specifically for the production of Ti-6Al-4V pre-forms for aerospace components. A large-scale structural demonstrator component is presented as a case-study in which not just control, but the entire 3D printing workflow for m-BAAM is discussed in detail, including design principles for large-format metal AM, toolpath generation, parameter development, process control, and system operation, as well as post-print net-shape geometric analysis and finish machining. In terms of control, a multi-sensor approach has been utilized to measure both layer height and melt pool size, and multiple modes of closed-loop control have been developed to manipulate process parameters (laser power, print speed, deposition rate) to control these variables. Layer height control and melt pool size control have yielded excellent local (intralayer) and global (component-level) geometry control, and the impact of melt pool size control in particular on thermal gradients and material properties is the subject of continuing research. Further, these modes of control have allowed the process to advance to higher deposition rates (exceeding 7.5 lb/hr), larger parts (1-meter scale), shorter build times, and higher overall efficiency. The control modes are examined individually, highlighting their development, demonstration, and lessons learned, and it is shown how they operate concurrently to enable the printing of a large-scale, near net shape Ti-6Al-4V component.

Gibson, Brian↗

NASA NTRSDate not supplied

Wire-break Ignition Testing of Materials for Spacesuit Fire Hazard Control

The input design constraints applied to the extravehicular activity (EVA) spacesuit pose a significant challenge for mitigation of fire hazards. To minimize fatigue and increase comfort of the crewmember operating the suit, the suit pressure is lowered below sea level conditions with typical EVA suit designs operating with 4.3 psia (29.7 kPa). With the lowered operating pressures and the use of closed-loop life support, the suit requires elevated concentrations of oxygen, typically >95%. At these oxygen concentrations, nearly the entirety of the suit internal materials are flammable. This leaves one remaining possible control leg of the fire triangle: ignition sources. Since the Gemini and Apollo programs, this has been a risk that has undergone constant reassessment, with a focus on improved mitigation. After the Apollo I fire, an arc ignition method was developed and used to quantify ignition thresholds for in-suit materials resulting in a current limit for powered in-suit devices applied to all subsequent suit designs. After the discovery of a frayed spacesuit biomed cable on STS-113 during the Shuttle Program, the previous arcing method was repeated with additional methods developed to extend the testing further. One of those methods was wire-break ignition testing, in which the current in a single strand of wire was progressively increased, preheating the material in proximity with a resultant break and the application of a reasonably repeatable arc to ignite the material, all while exposed in the selected environment. This method was used to test a suite of spacesuit materials providing relative performance with respect to ignition with this configuration for application of energy. This paper discusses extension of the current data set to address recent material additions, lowering of energy test levels for quantification of materials too low to measure in previous testing, as well as future plans to improve this method.

Colin Campbell↗

DOE OSTI2019

TRANSP-based closed-loop simulations of current profile optimal regulation in NSTX-Upgrade

Active control of the toroidal current density profile is critical for the upgraded National Spherical Torus eXperiment device (NSTX-U) to maintain operation at the desired high-performance, MHD-stable, plasma regime. Initial efforts towards current density profile control have led to the development of a control-oriented, physics-based, plasma-response model, which combines the magnetic diffusion equation with empirical correlations for the kinetic profiles and the non-inductive current sources. The developed control-oriented model has been successfully tailored to the NSTX-U geometry and actuators. Moreover, a series of efforts have been made towards the design of model-based controllers, including a linear-quadratic-integral optimal control strategy that can regulate the current density profile around a prescribed target profile while rejecting disturbances. In this work, the tracking performance of the proposed current-profile optimal controller is tested in numerical simulations based on the physics-oriented code TRANSP. Furthermore, these high-fidelity closed-loop simulations, which are a critical step before experimental implementation and testing, are enabled by a flexible framework recently developed to perform feedback control design and simulation in TRANSP.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1988

The poststall nonlinear dynamics and control of an F-18: A preliminary investigation

The successful high angle of attack (HAOA) operation of fighter aircraft will necessarily require the introduction of a new onboard control methodology that address the nonlinearity of the system when flown at the stall/poststall limits of the craft's flight envelope. As a precursor to this task, a researcher endeavored to familarize himself with the dynamics of one specific aircraft, the F-18, when it is flown at HAOA. This was accomplished by conducting a number of real time flight sorties using the NASA-Langley Research Center's F-18 simulator, which was operated with a pilot in the loop. In addition to developing a first hand familarity with the aircraft's dynamic characteristic at HAOA, work was also performed to identify the input/output operational footprint of the F-18's control surfaces. This investigator proposes to employ the nonlinear models of the plant identified this summer in a subsequent research effort that will make it possible to fly the F-18 effectively at poststall angles of attack. The controller design used there will rely on a new technique proposed by this investigator that provides for the automatic generation of online optimal control solutions for nonlinear dynamic systems.

Patten, William N.↗

NASA NTRS2001

Application of Physiological Self-Regulation and Adaptive Task Allocation Techniques for Controlling Operator Hazardous States of Awareness

Prinzel, Hadley, Freeman, and Mikulka found that adaptive task allocation significantly enhanced performance only when used at the endpoints of the task workload continuum (i.e., very low or high workload), but that the technique degraded performance if invoked during other levels of task demand. These researchers suggested that other techniques should be used in conjunction with adaptive automation to help minimize the onset of hazardous states of awareness (HSA) and keep the operator 'in-the-loop.' The paper reports on such a technique that uses psychophysiological self-regulation to modulate the level of task engagement. Eighteen participants were assigned to three groups (self-regulation, false feedback, and control) and performed a compensatory tracking task that was cycled between three levels of task difficulty on the basis of the electroencephalogram (EEG) record. Those participants who had received self-regulation training performed significantly better and reported lower NASA-TLX scores than participants in the false feedback and control groups. Furthermore, the false feedback and control groups had significantly more task allocations resulting in return-to-manual performance decrements and higher EEG difference scores. Theoretical and practical implications of these results for adaptive automation are discussed.

Prinzel, Lawrence J., III↗

NASA NTRS2011

Allocation of Functions in a Far-Term Air Traffic Control Environment

A human-in-the-loop exploration of a ground-based automated separation assurance concept was conducted that involved the allocation of certain functions between humans and automation. This exploration included operations that were sustained for prolonged periods of time with high levels of traffic in the presence of convective weather and scheduling constraints. An investigation into the acceptability of the defined roles and performance of tasks was conducted where it was found that the participants rated the concept and allocation of functions with a high level of acceptability. However, issues were encountered with the automation related to the detection of and response to tactical conflicts. Lower ratings were given on account of these concerns, and it was found that a key contributor to the underlying problems was transitioning aircraft and the uncertainty of their trajectories. Stemming from those results, participants responded that they would rather have direct control over aircraft transitions as well as more control over the tactical conflict resolution automation. In contrast, participants responded that they would rather have the automation place aircraft back on trajectory, and perform weather avoidance and scheduling tasks.

Homola, Jeffrey↗

NASA NTRSDate not supplied

Hybrid-Electric Aero-Propulsion Controls Testbed Results with Energy Storage

Electrified aircraft propulsion (EAP) research is a priority of the National Aeronautics and Space Administration (NASA) for its potential to increase propulsion system efficiency, performance, and operability at the subsystem and vehicle levels while decreasing emissions. These EAP systems demand more advanced control algorithms due to increased complexity. NASA has developed a reconfigurable, hardware-in-the-loop rig to verify control algorithm performance using a sub-scale electro-mechanical system. A novel capability of this rig is the ability to test full scale EAP control algorithms on a sub-scale representation of the electro-mechanical system without turbomachinery/rotors. A novel feature is the use of a physical energy storage device within the electro-mechanical system. A dual spool, parallel hybrid-electric turbofan architecture and energy management control system is tested with the goal of verifying the ability to obtain turbomachinery model operability benefits while controlling sub-scale electro-mechanical hardware. Pre-test predictions of the turbofan model, control, and rig performance were obtained through simulation using a software model of the rig. Theoretical results showing the true performance of the turbofan model were obtained through a software simulation using full-scale mechanical shaft models. The paper compares theoretical, predicted, and actual test results from the turbofan model, energy management control and rig perspectives. The results show that the presence of sub-scale electro-mechanical hardware did not inhibit the energy management algorithm from achieving turbomachinery operability benefits.

hybrid↗

NASA NTRSDate not supplied

Hybrid-Electric Aero-Propulsion Controls Testbed Results with Energy Storage

Electrified aircraft propulsion (EAP) research is a priority of the National Aeronautics and Space Administration (NASA) for its potential to increase propulsion system efficiency, performance, and operability at the subsystem and vehicle levels while decreasing emissions. These EAP systems demand more advanced control algorithms due to increased complexity. NASA has developed a reconfigurable, hardware-in-the-loop rig to verify control algorithm performance using a sub-scale electro-mechanical system. A novel capability of this rig is the ability to test full scale EAP control algorithms on a sub-scale representation of the electro-mechanical system without turbomachinery/rotors. A novel feature is the use of a physical energy storage device within the electro-mechanical system. A dual spool, parallel hybrid-electric turbofan architecture and energy management control system is tested with the goal of verifying the ability to obtain turbomachinery model operability benefits while controlling sub-scale electro-mechanical hardware. Pre-test predictions of the turbofan model, control, and rig performance were obtained through simulation using a software model of the rig. Theoretical results showing the true performance of the turbofan model were obtained through a software simulation using full-scale mechanical shaft models. The paper compares theoretical, predicted, and actual test results from the turbofan model, energy management control and rig perspectives. The results show that the presence of sub-scale electro-mechanical hardware did not inhibit the energy management algorithm from achieving turbomachinery operability benefits.

hybrid↗

DOE OSTI2023

Multi-Timescale Integrated Dynamics and Scheduling for Solar (MIDAS-Solar) (Final Technical Report)

Solar photovoltaic (PV) installations have experienced unprecedented growth in the United States. PV will become not only an energy producer but also a necessary provider of ancillary services at multiple timescales. Conventional methods to simulate power systems operations - such as long-term production simulation (which typically considers schedules from hours to minutes by using an optimization framework) and short-term transient studies (which simulate dynamics from seconds to sub-seconds using state variables and differential equations) - are not sufficient for studying the multiple-timescale variation of solar generation and its impact on system reliability. Long-term system economics and short-term system dynamics are highly coupled, particularly when the penetration level of renewable generation is extremely high, because the uncertainty and variability of solar generation will impact both power system steady-state and dynamic performance. This project helps meet and exceed the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office goal of systems integration by directly addressing this stability and reliability challenge for power grid planning and operation. We have developed a temporally comprehensive, closed-loop simulation model, named Multi-timescale Integrated Dynamics and Scheduling (MIDAS), that seamlessly simulates power system operations from economic scheduling (day-ahead to hours) to dynamic response analysis (seconds to sub-seconds). For schedules with very high levels of inverter-based resources (IBRs), up to and including 100%, the stability of grid controls has been evaluated through electromagnetic transient (EMT) simulations and power-hardware-in-the-loop (PHIL) simulations of key transient events at key schedule points. Specifically, MIDAS provides: 1) a closed-loop simulation framework for simulating timescales from economic scheduling to dynamic stability analysis; 2) machine learning-based stability assessment; 3) EMT modeling and analysis for large-scale power systems; 4) MIDAS PHIL test bed. We worked with Hawaii Electric Companies to apply the MIDAS study framework to a Maui grid study. The entire island's transmission system was modeled in detail - from a yearly scheduling model, to a second-level frequency dynamic model, down to a sub-second-scale EMT model to address critical stability issues. The project demonstrated how MIDAS can help system planners and operators assess system reliability and stability while the power grid is marching toward a high-renewable, high-IBR future. In this Maui grid study, we found that 100% instantaneous IBR operation is achievable in EMT simulation and PHIL testing, and grid planners and operators might need new analysis/simulation tools to assess grid reliability and stability in the scheduling stage. MIDAS will bring Maui and other systems closer to 100% clean and stable energy futures. (In this study, we examined transient stability. Other topics necessary for 100% IBR operation, such as protection and resource adequacy, were not examined.)

100% Renewables↗