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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Analysis of axial‐induction‐based wind plant control using an engineering and a high‐order wind plant model

Abstract Wind turbines are typically operated to maximize their performance without considering the impact of wake effects on nearby turbines. Wind plant control concepts aim to increase overall wind plant performance by coordinating the operation of the turbines. This paper focuses on axial‐induction‐based wind plant control techniques, in which the generator torque or blade pitch degrees of freedom of the wind turbines are adjusted. The paper addresses discrepancies between a high‐order wind plant model and an engineering wind plant model. Changes in the engineering model are proposed to better capture the effects of axial‐induction‐based control shown in the high‐order model. Copyright © 2015 John Wiley & Sons, Ltd.

Annoni, Jennifer↗
DOE OSTI2013

SOWFA Super-Controller: A High-Fidelity Tool for Evaluating Wind Plant Control Approaches

This paper presents a new tool for testing wind plant controllers in the Simulator for Offshore Wind Farm Applications (SOWFA). SOWFA is a high-fidelity simulator for the interaction between wind turbine dynamics and the fluid flow in a wind plant. The new super-controller testing environment in SOWFA allows for the implementation of the majority of the wind plant control strategies proposed in the literature.

17 WIND ENERGY↗
DOE OSTI2022

Proposal for New Plant Controller and Electrical Controller

This is the first revision of this memo capturing in more detail some items discussed at the last WECC MVS meeting in January, 2022 during the REMWG part of the meeting. The items here are presented for further enhancements in the electrical controls model and plant controller model (specifically for hybrid-plants or plants with multiple aggregated inverter-based generation models). These will need to be discussed and refined, and then implemented for benchmark testing and final approval.

42 ENGINEERING↗
DOE OSTI2018

Lessons Learned from Performing a Human Factors Engineering Validation of an Upgraded Digital Control System in a Nuclear Power Plant Control Room

The United States' fleet of nuclear power plants (NPPs) have exceeded their original 40-year licenses and many are seeking license renewals to continue operations into the future. To support continued operation the Department of Energy's (DOE) Light Water Reactor Sustainability Program (LWRS) provides support for utilities to maintain and upgrade their power production capabilities. Control room modernization is one focus area, which aims to modernization the analog control rooms with digital controls and human-system interfaces (HSIs). The Turbine Control System (TCS) is a non-safety related system undergoing modernization efforts at multiple plants and utilities. Considerable human factors research efforts, comprised of expert reviews and operator in the loop studies were performed to develop human factors compliant and usable TCS. This report documents the final phase of the human factors engineering program used to design and validate the new digital TCS. According to the NUREG-0711 review guide, one of the last steps of human factors engineering program prior to implementation is human factors validation. This report details the method, results and conclusions from the human factors validation study of a collaborating utilities TCS slated to be implemented in one of their plants. One control room team consisting of two control room supervisors and two reactor operators participated in the validation. All team members had participated in the BNP TCS training program foregoing the TCS validation. Performance measures included task performance, situation awareness and workload, expert observation of any negative influences of human-system interface features on control room team performance, and interviews with the participating operators. Performance criteria were based on the performance scores and the topics identified by interviews and expert observations. The results showed that the crew using the new TCS clearly could achieve their overall objectives in the test scenarios with sufficient situation awareness. The new TCS compared to the old system provided clear improvements of the control room work regarding shell and chest warming and regarding valve and other system testing. However, a number of Human Engineering Discrepancies (HEDs) were identified. HEDs were prioritized (level 1, 2 or 3) according to potential safety, plant availability, operability or personnel performance consequences. Since no priority 1 HEDs were identified there is no HFE reason not to continue implementation of the TCS. The TCS upgrade is acceptable if the Priority 2 HEDs are resolved and dispositioned in a satisfactory way. Priority 3 HEDs should be noted and considered for future modifications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Aeroacoustic Assessment of Wind Plant Controls

The Aeroacoustic Assessment project aims to quantify changes in aeroacoustic noise generation by a utility scale wind turbine operating under imposed yaw offsets common for wake steering and wind plant control strategies. Active plant control utilizing wake deflection control strategies have been shown experimentally and computationally to reliably produce 1-2% of additional annual energy production (AEP) without significant changes in turbine structural loads, the potential impact on aeroacoustic emissions has yet to be quantified or completely understood. Yawed operation of a wind turbine changes the three-dimensional aerodynamic interaction between the rotor blades and the incoming atmospheric flow, leading to changes in noise generation. This work quantifies the extent to which active control induces additional aeroacoustic emissions from additional separation and other flow interaction dynamic effects. Given public concerns about wind turbine noise and the need for observational data required for regulators to establish noise restrictions, we must understand potential acoustic emissions resulting from active control prior to commercial deployment and the development of practical noise reduction methods and technologies. The work outlined in this report details the new aeroacoustic measurement capability developed at NREL and its application to making full-field observations of noise from a utility-scale wind turbine. Preliminary noise modeling with the aeroacoustics module in OpenFAST helped to establish the design of the experiment, specifically targeting the noise observed at observers distributed around the DOE-owned GE 1.5 MW wind turbine. Low-frequency and infrasound measurement capability implemented in this project establish an operational baseline for the wind turbine, setting the stage for future control, rotor blade, and turbine design research.

17 WIND ENERGY↗
DOE OSTI2025

Standard Library Plant Controller Model Specification for a Grid-Forming Hybrid Control Inverter-Based Resource (REPCGFM_C1)

This document describes a standard library plant controller model to interface with the grid-forming hybrid control inverter-based resource (IBR) model. The initial version of model specification was jointly developed by Pacific Northwest National Laboratory (PNNL), Tesla Energy, and EPRI, and it was revised multiple times later to incorporate suggestions from WECC MVS members. Tesla Energy provided main control algorithms to support the development of this model specification. This standard library model is developed to help the utility industry better understand the GFM technology. The model could be used to represent equipment for long-term planning studies where vendor-specific models are not available. As equipment matures and improves, standard library models will be updated to capture the new functionalities of GFMs. It is not intended that these models will always remain representative of all future GFM technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Machine learning enables national assessment of wind plant controls with implications for land use

Summary As deployment of wind energy continues to expand, computationally efficient tools for predicting wind plant performance over a wide range of layout designs, technology innovations, and spatial locations are increasingly important for policy and investment decisions. We demonstrate two approaches to training a surrogate model to predict annual energy production (AEP) of parameterized wind plant layouts: one using a Gaussian process (GP) and the other using a fully convolutional neural network (FCNN). We leverage the powerful FCNN architecture by encoding wind plant design parameters and output response surface as an image. The FCNN produces more accurate results than the GP with mean absolute errors equivalent to 1% and 1.9% of plant rated power, respectively, although the GP performs well under limited training data and provides useful uncertainty information. We also evaluate a surrogate model for wake steering, enabling a nationwide assessment of the impact of plant control strategies and plant layout decisions. Across two million locations, we find that wake steering strategies boost AEP with relative gains upwards of 3%. Gains are most pronounced at sites without a dominant wind direction and where layout optimization is less fruitful. Additionally, we perform a nationwide sensitivity analysis showing that wake steering can mitigate wake losses from higher density plant layouts. Our results suggest that regions which have not been previously viable for wind deployment due to moderate wind resources are especially well enhanced by wake steering strategies that could help overcome land constraints and inflexible layout options, potentially identifying new deployment opportunities.

17 WIND ENERGY↗
DOE OSTI2024

Human Factors Challenges in Modernizing Nuclear Power Plant Control Rooms

Jeffrey Joe has been invited to give a presentation entitled, “Human Factors Challenges in Modernizing Nuclear Power Plant Control Rooms,” at the 2024 Human Systems Symposium. Experts conducting human factors and human systems research will gather and share research at this conference. This conference is a good opportunity to develop new business for INL via research collaborations, as attendees exchange knowledge and explore the latest trends, advancements, and challenges in the field of human systems research across the DOE national laboratories.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Design themes for future hybrid nuclear power plant control rooms - 383

As nuclear power plants (NPP) control rooms are updated and new technologies added, a new hybrid control room is set to emerge and with it new safety implications for design. This paper highlights two technologies determined to be highly relevant for control room modernization: overview displays and computer-based procedures. Control room operators were observed in the simulator, while conducting abnormal and emergency scenarios. Additionally, operators were observed and interviewed in the control room during normal operations. Design themes for both of the technologies are discussed. Results revealed ten main design themes for overview displays, including observations of the system used currently in order to provide overview information. The results revealed three main design themes for computer-based procedures that were more directed at an envisioned world, since these technologies are not deployed currently. This evaluation elicited considerations for requirements for future control room system designs and recommendations for hybrid NPP control rooms. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Combining Wind Plant Control With Systems Engineering (Presentation)

This presentation was given at the third Wind Energy Systems Engineering Workshop in Boulder, Colorado, and focused on wind plant controls research, combined optimization, a case study on the Princess Amalia Wind Park, results from the case study, and future work.

17 WIND ENERGY↗
DOE OSTI2022

1.2.4.404 - Data-Driven Approach for Hydropower Plant Controller Prototyping Using Remote Hardware in the Loop (DR-HIL)

Real-time prototyping of hydropower plant controls is important for reducing the cost and the risk of field deployment. This project will 1) collect design and operational data from actual hydro plants and 2) use a physics-informed machine learning approach for real-time emulation of hydropower plants, including hydro turbine and hydrodynamics. The data-driven models will be interfaced with digital real-time simulation at NREL’s Flatirons campus for hardware-in-the-loop (HIL) testing of the governor hardware device or controller-HIL (CHIL). The proposed approach will also establish the connectivity based remote CHIL testing capability using real-time data streams from an actual hydro plant. This integrated hydro-plant emulation with CHIL will be used to prototype hydro-governor controls and eventually provide an opportunity to test hydropower integrated with various technologies (e.g. conventional and renewable generation, energy conversion, etc.) as HIL.

controls prototyping↗
DOE OSTI2015

Measuring Human Performance in Simulated Nuclear Power Plant Control Rooms Using Eye Tracking

Control room modernization will be an important part of life extension for the existing light water reactor fleet. As part of modernization efforts, personnel will need to gain a full understanding of how control room technologies affect performance of human operators. Recent advances in technology enables the use of eye tracking technology to continuously measure an operator’s eye movement, which correlates with a variety of human performance constructs such as situation awareness and workload. This report describes eye tracking metrics in the context of how they will be used in nuclear power plant control room simulator studies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

Digital Full-Scope Simulation of a Conventional Nuclear Power Plant Control Room, Phase 2: Installation of a Reconfigurable Simulator to Support Nuclear Plant Sustainability

The U.S. Department of Energy’s Light Water Reactor Sustainability program has developed a control room simulator in support of control room modernization at nuclear power plants in the U.S. This report highlights the recent completion of this reconfigurable, full-scale, full-scope control room simulator buildout at the Idaho National Laboratory. The simulator is fully reconfigurable, meaning it supports multiple plant models developed by different simulator vendors. The simulator is full-scale, using glasstop virtual panels to display the analog control boards found at current plants. The present installation features 15 glasstop panels, uniquely achieving a complete control room representation. The simulator is also full-scope, meaning it uses the same plant models used for training simulators at actual plants. Unlike in the plant training simulators, the deployment on glasstop panels allows a high degree of customization of the panels, allowing the simulator to be used for research on the design of new digital control systems for control room modernization. This report includes separate sections discussing the glasstop panels, their layout to mimic control rooms at actual plants, technical details on creating a multi-plant and multi-vendor reconfigurable simulator, and current efforts to support control room modernization at U.S. utilities. The glasstop simulator provides an ideal testbed for prototyping and validating new control room concepts. Equally importantly, it is helping create a standardized and vetted human factors engineering process that can be used across the nuclear industry to ensure control room upgrades maintain and even improve current reliability and safety.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

COMMERCIAL UTILITY PERSPECTIVES ON NUCLEAR POWER PLANT CONTROL ROOM MODERNIZATION

Commercial nuclear power plants (NPPs) in the United States need to modernize their main control rooms (MCR). Many NPPs have done partial upgrades with some success and with some challenges. The Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program, and in particular the Advanced Instrumentation and Controls (I&C) and Information Systems Technologies Research and Development (R&D) Pathway within LWRS, is designed to assist commercial nuclear power industry with their MCR modernization efforts. As part of this framework, a survey was issued to utility representatives of the LWRS Program Advanced Instrumentation, Information, and Control Systems/Technologies (II&C) Utility Working Group to obtain their views on a range of issues related to MCR modernization, including: drivers, barriers, and technology options, and the effects these aspects will have on concepts of operations, modernization strategies, and staffing. This paper summarizes the key survey results and discusses their implications.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Nuclear Power Plant Control Room Modernization - Simulation Based Design

As many plants age and equipment modifications are implemented, the industry has the opportunity to address the issue of control room obsolescence through technology application and enhanced engineering techniques using existing systems. This paper addresses the practice of Simulation Based Design (SBD) for control room modernization driven by plant modifications and upgrades.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Chapter 7: Wind-Plant-Controller Design

The main purpose of this chapter is the introduction, explanation, and categorization of wind-farm-control algorithms and present their place in a detailed wind farm simulation framework. Specifically, this section will continue to give an introduction to the current practice in wind-farm operation, and the objectives and turbine control methods presented in the literature for coordinated wind farm control.

17 WIND ENERGY↗
DOE OSTI2020

Report for 2.2.1 Task 5: Develop and Document a State-Based Alarm System for a Nuclear Power Plant Control Room Using Machine Learning

Idaho National Laboratory (INL) has contracted IFE to support human factors research and the development of leading-edge technology to support control room operators as the U.S. fleet undergoes modernization and digitalization in legacy plants and control rooms. As the nuclear industry starts to shift to more digital controls and systems, these upgrades provide more information to the main control room in the form of digital signals and values. Also, an increase in the number of alarms points is provided by the vendors. New digital control rooms shift from main control boards to soft controls, and alarm panels to a single display. This change to a single display has created a problem of alarm waterfall, a situation in which the addition of new alarm points causes an overload of information to the operator during either a plant disturbance or other than normal full power operations. IFE’s goal is to find a workable solution to assist operators in both handling and understanding incoming alarms during emergency situations under these waterfall conditions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Human Performance Measures for the Evaluation of Nuclear Power Plant Control Room Interfaces: A Systematic Review - 265

The purpose of this study was to review the literature related to measuring human performance in the design and evaluation of the human-system interface (HSI) of nuclear power plant (NPP) control rooms and synthesize lessons learned and future directions for research and practice in this field. The design and evaluation of digital or hybrid HSI requires comprehensive measurement of human performance to ensure quality and safety of the nuclear power process control. Human factors evaluation frameworks have been proposed to guide the measurement of human performance constructs. However, there are few guides for selecting appropriate measures for those constructs. A systematic review of empirical research literature was conducted. Studies were identified through academic publication databases and grey literature searches. Eligible studies were coded and information regarding human performance measures was extracted and analyzed. A total of 80 studies met the criteria. Human performance measures extracted from the reviewed studies included measures of: behavioral performance; workload; situation awareness; human-human or human-machine cooperation; other cognitive performance indicators; and system performance. Behavioral performance (speed and accuracy), workload, and situation awareness were the most frequently measured constructs with validated and domain-specific instruments. The results of the literature review provided an overview of the human performance constructs and their corresponding measures for NPP control room HSI evaluation. These results can be used as an initial guide to establish appropriate and comprehensive measurements of human performance for such evaluations. Future directions in measure development are also discussed. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗