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All sources NASA NTRS DOE OSTI

DOE OSTI2019

Incentive-Based Control and Coordination of Distributed Energy Resources. Final Report

The rapid growth of low-inertia renewable energy resources represents an immense opportunity for the U.S. to minimize its carbon footprint, while presenting a challenge for system operators as traditional “spinning” generation resources are displaced. This transformation requires solutions to robustly and cost-effectively manage dynamic changes on the grid while ensuring quality of service. There is growing recognition that distributed energy resources (DERs – loads, distributed generation, storage, electric vehicles, etc.) represent a great potential to perform this function. This report details a scalable hierarchical control strategy for coordinating thousands of heterogeneous DERs in order to provide three ancillary gird services: 1) frequency response, a rapid (within 2 seconds) service used to maintain the grid at 60 Hz; 2) regulation response, a larger response used to balance on-going differences in supply and demand on the grid; and, 3) ramping reserve, used to bring on capacity to replace lost generation. The developed control architecture consists of 1) a Distribution Reliability Coordinator (DRC), 2) aggregator controllers, and finally, 3) DER controllers. The DRC coordinates all the flexible loads and distributed energy resources on the distribution system and bids the aggregate flexibility into the wholesale market. The DRC also performs resource allocation (deciding how the flexible devices on the distribution system will be dispatched) to meet the requirements for each of the three ancillary services. The aggregators control a collection of devices that are geographically co-located and provide a platform to aggregate their flexibility and mitigate uncertainty associated with a single flexible load by managing a large aggregation of similar loads (so that any stochastic effects average out). Finally, DER controllers (for example, thermostats for air conditioners, chargers for electric vehicles) adjust the power consumption of individual devices to ensure accurate and reliable delivery of the requested grid services. Evaluation and validation of this approach was conducted with a mixture of simulation and hardware testing for a range of DERs in residential (air conditioners and water heaters), commercial HVAC (ventilation fans and central chiller plants), and micro-grids (battery energy storage, solar PV etc.). This culminated in DER hardware and simulation models operating in conjunction with grid simulations as part of a large scale federated test-bed demonstration. Simulations of over 10,000 controllable residential devices (a combination of air conditioners, water heaters, batteries, and electric vehicles) demonstrated that this advanced control approach could simultaneously meet all three grid services. Furthermore, hardware-in-the-loop testing was performed with operational micro-grid and commercial building HVAC equipment. The micro-grid equipment (representing PV, battery storage, and back-up generators) demonstrated the ability to meet all frequency response requirements (except ramping time). The commercial building HVAC ventilation equipment successfully provided the regulating response service. An Industry Advisory Board (IAB) was formed and engaged throughout the project to get feed-back on project risks and potential commercialization barriers. Their input was invaluable in identify key risks stemming from regulatory and market access challenges, financial risks from under-performance, and competitive threats from utility-scale solutions such as integrated storage. A phased commercialization plan was developed that addresses continued risk reduction (value proposition refinement and performance uncertainty assessments), piloting through field demonstrations with key stakeholders, and finally, deployment as an emerging standard for DER control.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Battery Electric Vehicle Eco-Cooperative Adaptive Cruise Control in the Vicinity of Signalized Intersections

This study develops a connected eco-driving controller for battery electric vehicles (BEVs), the BEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The developed controller can assist BEVs while traversing signalized intersections with minimal energy consumption. The calculation of the optimal vehicle trajectory is formulated as an optimization problem under the constraints of (1) vehicle acceleration/deceleration behavior, defined by a vehicle dynamics model; (2) vehicle energy consumption behavior, defined by a BEV energy consumption model; and (3) the relationship between vehicle speed, location, and signal timing, defined by vehicle characteristics and signal phase and timing (SPaT) data shared under a connected vehicle environment. The optimal speed trajectory is computed in real-time by the proposed BEV eco-CACC-I controller, so that a BEV can follow the optimal speed while negotiating a signalized intersection. The proposed BEV controller was tested in a case study to investigate its performance under various speed limits, roadway grades, and signal timings. In addition, a comparison of the optimal speed trajectories for BEVs and internal combustion engine vehicles (ICEVs) was conducted to investigate the impact of vehicle engine types on eco-driving solutions. Lastly, the proposed controller was implemented in microscopic traffic simulation software to test its networkwide performance. The test results from an arterial corridor with three signalized intersections demonstrate that the proposed controller can effectively reduce stop-and-go traffic in the vicinity of signalized intersections and that the BEV Eco-CACC-I controller produces average savings of 9.3% in energy consumption and 3.9% in vehicle delays.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Current profile and normalized beta control via feedback linearization and Lyapunov techniques

Abstract Simultaneous control of the current profile and normalized plasma beta is an essential control problem in the development of advanced tokamak scenarios. However, this control problem is especially challenging due to the nonlinear nature of the current, heat, and particle transport dynamics, as well as the difficulty to understand and accurately model such processes. In this work, a nonlinear, robust, model-based controller for the simultaneous regulation of the current profile and normalized beta has been designed using feedback linearization and Lyapunov redesign techniques. Feedback linearization avoids approximate linearization of the plasma dynamics, retaining the original physics content of the model. Moreover, the use of Lyapunov redesign techniques makes the controller robust against the uncertainties arising during the modeling process. The controller’s performance in the presence of unknown dynamics is tested in nonlinear, one-dimensional simulations using the Control Oriented Transport SIMulator (COTSIM) code, which employs plasma models that are significantly more complex than those employed for control synthesis.

Physics↗

DOE OSTI2021

Time-Disciplined Non-PLL Active Synchronization for Grid-Forming Inverters: Preprint

Grid Forming Inverters (GFMIs) are a critical component of the future Grid. One major challenge with GFMIs is synchronization. Currently, most research in GFMI synchronization is focused around specific transition types but this is only a subcategory of the possible events facing GFMIs. In this paper, we propose categorizing all possible synchronization events into four categories: (1) Initial Grid Synchronization, (2) Ride-Through, (3) Blackstart Coordination, (4) Grid Reconnection Coordination. By categorizing events, we can better compare and integrate different control strategies under specific test conditions as demonstrated in simulation. This paper’s framework helps guide GFMI primary-level control design to further research towards the 100% inverter-dominant Grid.

blackstart↗

DOE OSTI2021

Time Disciplined Non-PLL Active Synchronization for Grid Forming Inverters

Grid forming inverters (GFMIs) are a critical component of the future grid. One major challenge with GFMIs is synchronization. Currently, most research in GFMI synchronization is focused around specific transition types but this is only a subcategory of the possible events facing GFMIs. In this paper, we propose categorizing all possible synchronization events into four categories: (1) initial grid synchronization, (2) ride-through, (3) blackstart coordination, (4) grid reconnection coordination. By categorizing events, we can better compare and integrate different control strategies under specific test conditions as demonstrated in simulation. This paper's framework helps guide GFMI primary-level control design to further research towards the 100% inverter-dominant grid.

blackstart↗

DOE OSTI2021

Ensuring statistical reproducibility of ocean model simulations in the age of hybrid computing

Novel high performance computing systems that feature hybrid architectures require large scale code refactoring to unravel underlying exploitable parallelism. Such redesign can often be accompanied with machine-precision changes as the order of computation cannot always be maintained. For chaotic systems like climate models, these round-off level differences can grow rapidly. Systematic errors may also manifest initially as machine-precision differences. Isolating genuine round off level differences from such errors remains a challenge. Here, we apply two-sample equality of distribution tests to evaluate statistical reproducibility of the ocean model component of US Department of Energy's Energy Exascale Earth System Model (E3SM). A 2-year control simulation ensemble is compared to a modified ensemble as a test case - after a known non-bit-for-bit change in a model component is introduced - to evaluate the null hypothesis that the two ensembles are statistically indistinguishable. To quantify the false negative rates of these tests, we conduct a formal power analysis using a targeted suite of short simulation ensembles. The ensemble suite contains several perturbed ensembles, each with a progressively different climate than the baseline ensemble - obtained by perturbing the magnitude of a single model tuning parameter, the Gent and McWilliams κ, in a controlled manner. The null hypothesis is evaluated for each of perturbed ensembles using these tests. The power analysis informs on the detection limits of the tests for given ensemble size allowing model developers to evaluate the impact of an introduced non-bit-for-bit change to the model.

Mahajan, Salil↗

DOE OSTI2017

Development of Smart Ventilation Control Algorithms for Humidity Control in High-Performance Homes in Humid U.S. Climates

Past field research and simulation studies have shown that high performance homes experience elevated indoor humidity levels for substantial portions of the year in humid climates. This is largely the result of lower sensible cooling loads, which reduces the moisture removed by the cooling system. These elevated humidity levels lead to concerns about occupant comfort, health and building durability. Use of mechanical ventilation at rates specified in ASHRAE Standard 62.2-2013 are often cited as an additional contributor to humidity problems in these homes. Past research has explored solutions, including supplemental dehumidification, cooling system operational enhancements and ventilation system design (e.g., ERV, supply, exhaust, etc.). This project’s goal is to develop and demonstrate (through simulations) smart ventilation strategies that can contribute to humidity control in high performance homes. These strategies must maintain IAQ via equivalence with ASHRAE Standard 62.2-2013. To be acceptable they must not result in excessive energy use. Smart controls will be compared with dehumidifier energy and moisture performance. This work explores the development and performance of smart algorithms for control of mechanical ventilation systems, with the objective of reducing high humidity in modern high performance residences. Simulations of DOE Zero-Energy Ready homes were performed using the REGCAP simulation tool. Control strategies were developed and tested using the Residential Integrated Ventilation (RIVEC) controller, which tracks pollutant exposure in real-time and controls ventilation to provide an equivalent exposure on an annual basis to homes meeting ASHRAE 62.2-2013. RIVEC is used to increase or decrease the real-time ventilation rate to reduce moisture transport into the home or increase moisture removal. This approach was implemented for no-, one- and two-sensor strategies, paired with a variety of control approaches in six humid climates (Miami, Orlando, Houston, Charleston, Memphis and Baltimore). The control options were compared to a baseline system that supplies outdoor air to a central forced air cooling (and heating) system (CFIS) that is often used in hot humid climates. Simulations were performed with CFIS ventilation systems operating on a 33% duty-cycle, consistent with 62.2-2013. The CFIS outside airflow rates were set to 0%, 50% and 100% of 62.2-2013 requirements to explore effects of ventilation rate on indoor high humidity. These simulations were performed with and without a dehumidifier in the model. Ten control algorithms were developed and tested. Analysis of outdoor humidity patterns facilitated smart control development. It was found that outdoor humidity varies most strongly seasonally—by month of the year—and that all locations follow the similar pattern of much higher humidity during summer. Daily and hourly variations in outdoor humidity were found to be progressively smaller than the monthly seasonal variation. Patterns in hourly humidity are driven by diurnal daily patterns, so they were predictable but small, and were unlikely to provide much control benefit. Variation in outdoor humidity between days was larger, but unpredictable, except by much more complex climate models. We determined that no-sensor strategies might be able to take advantage of seasonal patterns in humidity, but that real-time smart controls were required to capture variation between days. Sensor-based approaches are also required to respond dynamically to indoor conditions and variations not considered in our analysis. All smart controls face trade-offs between sensor accuracy, cost, complexity and robustness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Deep reinforcement learning control for co-optimizing energy consumption, thermal comfort, and indoor air quality in an office building

With the recent demand for decarbonization and energy efficiency, advanced HVAC control using Deep Reinforcement Learning (DRL) becomes a promising solution. Due to its flexible structures, DRL has been successful in energy reduction for many HVAC systems. However, only a few researches applied DRL agents to manage the entire central HVAC system and control multiple components in both the water loop and the air loop, owing to its complex system structures. Moreover, those researches have not extended their applications by incorporating the indoor air quality, especially both CO2 and PM2.5concentrations, on top of energy saving and thermal comfort, as achieving those objectives simultaneously can cause multiple control conflicts. What's more, DRL agents are usually trained on the simulation environment before deployment, so another challenge is to develop an accurate but relatively simple simulator. Therefore, we propose a DRL algorithm for a central HVAC system to co-optimize energy consumption, thermal comfort, indoor CO2 level, and indoor PM2.5 level in an office building. To train the controller, we also developed a hybrid simulator that decoupled the complex system into multiple simulation models, which are calibrated separately using laboratory test data. The hybrid simulator combined the dynamics of the HVAC system, the building envelope, as well as moisture, CO2, and particulate matter transfer. Three control algorithms (rule-based, MPC, and DRL) are developed, and their performances are evaluated on the hybrid simulator environment with a realistic scenario (i.e., with stochastic noises). The test results showed that, the DRL controller can save 21.4 % of energy compared to a rule-based controller, and has improved thermal comfort, reduced indoor CO2 concentration. The MPC controller showed an 18.6 % energy saving compared to the DRL controller, mainly due to savings from comfort and indoor air quality boundary violations caused by unmeasured disturbances, and it also highlights computational challenges in real-time control due to non-linear optimization. Finally, we provide the practical considerations for designing and implementing the DRL and MPC controllers based on their respective pros and cons.

Guo, Fangzhou↗

DOE OSTI2018

An agent-based hardware-in-the-loop simulation framework for building controls

In general, a hardware-in-the-loop (HIL) building simulation has lower cost and fewer practical limitations (e.g., scheduling issues) than field tests in occupied buildings, while also overcoming limitations of simulations alone by capturing the full behavior of some physical systems, equipment, and components. However, the implementation of an HIL can be difficult due to the scarcity of appropriate tools. Here, this paper presents an agent-based framework for HIL simulation. It can be used for investigation of controller performance via controller-in-the-loop simulations and also HIL for system synthesis. In the latter case, both controllers and major equipment participate in tests to ensure that dynamics of equipment operation are correctly captured in addition to controller performance. The HIL simulation framework presented allows such actual physical parts to be included in the framework while representing others for which behaviors are better known and modeled in simulation models. The mechanism implemented in the framework to synchronize simulations in software with real-time operation of physical equipment is described. Lastly, as an example, use of the HIL simulation framework is illustrated through a brief study of speed control of the supply fan in the air handling unit of a variable-air-volume building heating, ventilating and air-conditioning system.

42 ENGINEERING↗

DOE OSTI2022

Tundra SGS – Critical Importance of Site-Specific Injectivity Testing for Carbon Dioxide Injection Well Simulation Calibration

Paper presented at 16th International Conference on Greenhouse Gas Control Technologies (GHGT-16), October 23–27, 2022, Lyon, France. Brine injectivity tests were conducted on both the Broom Creek (BC) and Deadwood (DW) storage formations in one of the cored stratigraphic test wells prior to finalized simulations. The injectivity tests entailed injection of brine into the formations, followed by shutting in the wells. The shut-in duration represents the fall-off period which was used to carry out pressure transient analyses of the tests. The analysis of injectivity tests indicated that core-indicated and modeled permeability distributions should be conservatively multiplied by 2.5× and 5× in the BC and DW geologic models, respectively, prior to numerical simulations of CO 2 injection using Computer Modelling Group’s (CMG’s) GEM equation-of-state reservoir simulator. The scaler permeability multipliers allowed the fluid flow simulations to fully represent well test-measured injection well rates in the respective formations.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2017

Development of performance specifications for hybrid modeling of floating wind turbines in wave basin tests

Hybrid modeling—combining physical testing and numerical simulation in real time$-$opens new opportunities in floating wind turbine research. Wave basin testing is an important validation step for floating support structure design, but the conventional approaches that use physical wind above the basin are limited by scaling problems in the aerodynamics. Applying wind turbine loads with an actuation system that is controlled by a simulation responding to the basin test in real time offers a way to avoid scaling problems and reduce cost barriers for floating wind turbine design validation in realistic coupled wind and wave conditions. This paper demonstrates the development of performance specifications for a system that couples a wave basin experiment with a wind turbine simulation. Two different points for the hybrid coupling are considered: the tower-base interface and the aero-rotor interface (the boundary between aerodynamics and the rotor structure). Analyzing simulations of three floating wind turbine designs across seven load cases reveals the motion and force requirements of the coupling system. By simulating errors in the hybrid coupling system, the sensitivity of the floating wind turbine response to coupling quality can be quantified. The sensitivity results can then be used to determine tolerances for motion tracking errors, force actuation errors, bandwidth limitations, and latency in the hybrid coupling system. These tolerances can guide the design of hybrid coupling systems to achieve desired levels of accuracy. An example demonstrates how the developed methods can be used to generate performance specifications for a system at 1:50 scale. Results show that sensitivities vary significantly between support structure designs and that coupling at the aero-rotor interface has less stringent requirements than those for coupling at the tower base. As a result, the methods and results presented here can inform design of future hybrid coupling systems and enhance understanding of how test results are affected by hybrid coupling quality.

16 TIDAL AND WAVE POWER↗

DOE OSTI2025

Fermilab's controls development with virtual accelerator

Control Systems development is often the last thing considered when designing and building new equipment, e.g. a new detector or superconducting RF LINAC; however when the new equipment is installed, it is the first thing desired to be operational for testing. Due to frequent delays in building new equipment and project deadlines, control system development and testing is often curtailed. A way to alleviate this problem is to simulate the control system, though this will be challenging for complex systems.The Fermilab PIP-II (proton improvement plan - II) project is being constructed at Fermilab to deliver $800\,MeV$ protons of $>1\,MW$ beam power to replace the present LINAC for the remainder of the existing accelerator complex. The new LINAC consists of a warm front end (WFE), 23 superconducting RF cryomodules (of 5 types), and a beam transfer line (BTL) to the existing complex.The accelerator physics group has a parallel project to create a digital twin (DT) of the PIP-II accelerator. We have coupled the EPICS controls to this DT and are developing both the DT and EPICS software in parallel. This will allow us to develop the EPICS software framework, the HMIs, sequences, high level physics applications, and other services for use in a fully functional control system.This presentation will detail the work that we have performed to date and show demonstrations of controlling and monitoring the status of the accelerator, as well as future plans for this work.

Hanlet, Pierrick [Fermilab]↗

DOE OSTI2021

Grid-Forming Frequency Shaping Control for Low-Inertia Power Systems

As power systems transit to a state of high renewable penetration, little or no presence of synchronous generators makes the prerequisite of well-regulated frequency for grid-following inverters unrealistic. Thus, there is a trend to resort to grid-forming inverters which set frequency directly. We propose a novel grid-forming frequency shaping control that is able to shape the aggregate system frequency dynamics into a first-order one with the desired steady-state frequency deviation and Rate of Change of Frequency (RoCoF) after a sudden power imbalance. The no overshoot property resulting from the first-order dynamics allows the system frequency to monotonically move towards its new steady-state without experiencing frequency Nadir, which largely improves frequency security. We prove that our grid-forming frequency-shaping control renders the system internally stable under mild assumptions. The performance of the proposed control is verified via numerical simulations on a modified Icelandic Power Network test case.

control systems↗

DOE OSTI2018

Optimal Dispatch Controller for Fuel Cell-Integrated Building: Preprint

Stationary fuel cells can generate both electrical power and heat, making it them a promising local source to serve building loads. In this paper, we develop an optimal energy dispatch controller to operate a fuel cell-integrated building. The controller leverages the inherent thermal in the building to lower reduce its operating cost and allows the building to participate in providing grid services. The proposed controller is tested in a co-simulation setup, where the real building is represented as a high-fidelity model in EnergyPlus.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

A multivariate approach to ensure statistical reproducibility of climate model simulations

Effective utilization of novel hybrid architectures of pre-exascale and exascale machines requires transformations to global climate modeling systems that may not reproduce the original model solution bit-for-bit. Round-off level differences grow rapidly in these non-linear and chaotic systems. This makes it difficult to isolate bugs/errors from innocuous growth expected from round-off level differences. Here, we apply two modern multivariate two sample equality of distribution tests to evaluate statistical reproducibility of global climate model simulations using standard monthly output of short (~ 1-year) simulation ensembles of a control model and a modified model of US Department of Energy's Energy Exascale Earth System Model (E3SM). Both the tests are able to identify changes induced by modifications to some model tuning parameters. We also conduct formal power analyses of the tests by applying them on designed suites of short simulation ensembles each with an increasingly different climate from the control ensemble. The results are compared against those from another such test. These power analyses provide a framework to quantify the degree of differences that can be detected confidently by the tests for a given ensemble size (sample size). This will allow model developers using the tests to make an informed decision when accepting/rejecting an unintentional non-bit-for-bit change to the model solution.

Mahajan, Salil↗

DOE OSTI2025

Microreactor Automated Control System - Digital Twin Models and Advanced Control Systems Updates

Automation of control systems is expected to be important in the economic and safe operation of microreactors. Therefore, there is a need to develop and demonstrate automated control for microreactors, along with the development of testbeds for this purpose. This report provides updates on the status of a nonnuclear microreactor automated control system (MACS)—a real-time, hardware-in-the-loop testbed for non-nuclear testing of microreactor control system automation. A real-time hardware-in-the-loop testbed incorporates the realistic dynamics of physical systems into control system development and testing. The collaborative effort between Oak Ridge National Laboratory (ORNL) and Idaho National Laboratory (INL) resulted in the development of a prototypic microreactor plant-level digital twin that includes the reactor and a balance of plant system. Advanced control strategies were incorporated to demonstrate testing of control automation solutions. The gRPC communication protocol, which was implemented in the hardware-in-the-loop testbed by INL, was coupled to a digital twin model developed using the TRANsient Simulation Framework of Reconfigurable Models (TRANSFORM) library in Modelica. This digital twin simulation was tested with the ViBRANT hardware for realistic feedback and visual representation of control action in real time. A modular Python client structure was developed to manage functional mock-up unit-based simulation and real-time gRPC communication. Hardware-in-the-loop testing indicated that the modeled reactor—a natural-convection, molten-salt coolant loop configuration—responds well to control of drum positioning for modulation of reactor core power, as well as system-level control and downstream demand changes. Ongoing research is focused on integrating additional control algorithms that utilize data from newly included sensors within the MACS hardware testbed, as well as demonstrating and assessing the performance of the different automated control algorithms on multiple additional operational scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

Arion

Arion is a library and tool set that enables researchers to holistically define test system models. To define a complex system for testing an algorithm or control requires expertise across multiple domains. Simulating a complex system requires the integration of multiple simulators and test hardware, each with their own specification languages and concepts. This requires extensive set of knowledge and capabilities. Arion was developed to alleviate this challenge. Arion is a library of Java libraries that abstracts the concepts from supported simulators into a cohesive model language that allows someone to build models to their needed level of fidelity and expertise. Arion is also a software tool that translates the users model back into the specification languages of the simulators and test hardware needed for execution.

Fisher, Andy↗

DOE OSTI2016

Arion

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