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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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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Adaptive Online Model Update Algorithm for Predictive Control in Networked Systems

In this article, we introduce an adaptive on-line model update algorithm designed for predictive control applications in networked systems, particularly focusing on power distribution systems. Unlike traditional methods that depend on historical data for offline model identification, our approach utilizes real-time data for continuous model updates. This method integrates seamlessly with existing online control and optimization algorithms and provides timely updates in response to real-time changes. This methodology offers significant advantages, including a reduction in the communication network bandwidth requirements by minimizing the data exchanged at each iteration and enabling the model to adapt after disturbances. Furthermore, our algorithm is tailored for non-linear convex models, enhancing its applicability to practical scenarios. The efficacy of the proposed method is validated through a numerical study, demonstrating improved control performance using a synthetic IEEE test case.

data-driven model predictive control↗
DOE OSTI2026

Adaptive Control for Load-Following of Boiling Water Reactors Part I: Linear Systems and Fully-Observable Dynamics

Automation control is a key strategy to improve the economic competitiveness of nuclear power plants. Not only does it help reduce operational costs, but it also extends the value proposition of these plants to nontraditional markets, including unattended operations in remote villages and space. However, the dynamics of the operating environments of nuclear reactors are subject to changes over time, and there are no widely adopted methods to ensure that the automation strategy will remain effective over the extended durations required for these applications. Adaptive control is a discipline that offers the possibility to accommodate such changes online. However, it relies on mathematical assumptions that must be respected to ensure robustness and reliability. In this work, we derive an adaptive control formulation for linear systems in which all states are observable and apply it to an instance of load-follow operation for Boiling Water Reactors. We assumed uncertainty in two factors: the temperature coefficient and the control rod worth, both of which are affected over time by the evolution of the nuclear reactor core environment. With an arbitrary penalty factor of 5, we found that the mean absolute and integral time absolute errors can be reduced by more than 90%, underscoring the strength of adaptive control. To extend the application to more challenges, different uncertainties and load-follow trajectories, as well as new formulations that include non-linearity and partial observability, are currently being developed.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Oscillatory Power Control and Consensus in Unbalanced Networks Using Grid Forming Inverters

In this paper, a state-space nonlinear control previously designed for balanced operation of grid-forming (GFM) inverters is extended to unbalanced operations. Unbalanced voltages and currents are analyzed, and their time-varying direct, quadrature, and zero components are parameterized in terms of six constant parameters. These parameters provide primary control design choices for not only an inverter’s terminal voltage but also its injections of both real and oscillatory power. It is shown that the proposed GFM control can precisely achieve a desired balanced terminal voltage under unbalanced loads. It is also shown that, by allowing the terminal voltage to be slightly unbalanced, oscillatory power can be adaptively minimized. Lastly, it is illustrated that oscillatory power can also be shared among multiple GFM inverters. Case studies and their simulations demonstrate that the proposed GFM control is effective in meeting the aforementioned objectives.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Adaptive primal–dual control for distributed energy resource management

With the increased adoption of distributed energy resources (DERs) in distribution networks, their coordinated control with a DER management system (DERMS) that provides grid services (e.g., voltage regulation, virtual power plant) is becoming more necessary. One particular type of DERMS using primal–dual control has recently been found to be very effective at providing multiple grid services among an aggregation of DERs; however, the main parameter, the primal–dual step size, must be manually tuned for the DERMS to be effective, which can take a considerable amount of engineering time and labor. To this end, we design a simple method that self-tunes the step size(s) and adapts it to changing system conditions. Additionally, it gives the DER management operator the ability to prioritize among possibly competing grid services. Here we evaluate the automatic tuning method on a simulation model of a real-world feeder in Colorado with data obtained from an electric utility. Through a variety of scenarios, we demonstrate that the DERMS with automatically and adaptively tuned step sizes provides higher-quality grid services than a DERMS with a manually tuned step size.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Overvoltage Prevention and Curtailment Reduction Using Adaptive Droop-Based Supplementary Control in Smart Inverters

Recent developments in the renewable energy sector have seen an unprecedented growth in residential photovoltaic (PV) installations. However, high PV penetration levels often lead to overvoltage problems in low-voltage (LV) distribution feeders. Smart inverter control such as active power curtailment (APC)-based overvoltage control can be implemented to overcome these challenges. The APC technique utilizes a constant droop-based approach which curtails power rigidly, which can lead to significant energy curtailment in the LV distribution feeders. In this paper, different variations of the APC technique with linear, quadratic, and exponential droops have been analyzed from the point-of-view of energy curtailment for a LV distribution network in North America. Further, a combinatorial approach using various droop-based APC methods in conjunction with adaptive dynamic programming (ADP) as a supplementary control scheme has also been proposed. The proposed approach minimizes energy curtailment in the LV distribution network by adjusting the droop gains. Simulation results depict that ADP in conjunction with exponential droop reduces the energy curtailment to approximately 50% compared to using the standard linear droop.

42 ENGINEERING↗
DOE OSTI2025

A Cost-Effective Wave Energy Harvesting System with Maximum Power Point Tracking Capability

In this paper, we propose a low-cost bidirectional four-switch inverter that transfers three-phase energy between a permanent magnet synchronous generator (PMSG) driven by a wave energy collector and the power grid or a local ac load. To achieve high control performance, the machine-side inverter uses a high-gain observer for rotor position estimation and a Lyapunov-based approach for torque control. For the gridside inverter control, we estimate the filter capacitor voltage with a model reference adaptive system and control the dc-link voltage with a Lyapunov-based energy function. We also track the maximum power point from the sea waves with an integral control law that actively matches the generator impedance with that of the wave collection device. The proposed system supports both grid-following/forming modes. We validate our control design with simulation results on a 3-kW hardware setup.

wave energy, power systems integration, control de↗
DOE OSTI2024

A Measurement-Based Adaptive Voltage Regulation Method Considering Topology Changes

This paper proposes an online adaptive data-driven distributed energy resource (DER) dispatch optimization method for voltage control considering topology changes. By using a local sensitivity factor (LSF)-enabled voltage control, traditional DER control can be reformulated into a linear programming (LP) problem, leading to faster computation speeds. Power injection alteration and topology changes are two common operational changes in the distribution network that can affect the LSF and voltage control performance. To address this issue, a robust estimation method is developed to adjust the sensitivity matrix at each time step for the time-varying power injection changes. When topology changes occur, only the allocated predominant LSF submatrices are updated based on measurement data, allowing for a fast adaptation to the system reconfiguration. Results obtained from a real distribution feeder in Southern California demonstrate its robustness as compared to traditional volt-var control and constant LSF matrix dispatch control methods.

DERs↗
DOE OSTI2024

Deep Learning-Based Dynamic Modeling of Three-Phase Voltage Source Inverters

Inverter-based resource (IBR) models are necessary to analyze modern power system stability and create effective control strategies. Modeling IBRs in converter-rich power systems is crucial, yet challenging due to the lack of commercial information on converter topologies and control parameters. This paper proposes novel convolutional neural network (CNN)–based data-driven techniques for modeling IBRs, addressing adaptability and proprietary concerns without requiring internal system physics knowledge. The proposed method is tested using real grid-tied commercial IBR transient data and demonstrates effectiveness and accuracy. Furthermore, the developed modeling approach is integrated and implemented in the open-source power distribution simulation and analysis tool, GridLAB-D, to illustrate the potentiality of dynamic analysis of large-scale power systems with high IBRs.

deep learning, artificial intelligence↗
DOE OSTI2023

Control systems and data management for high-power laser facilities

The next generation of high-power lasers enables repetition of experiments at orders of magnitude higher frequency than what was possible using the prior generation. Facilities requiring human intervention between laser repetitions need to adapt in order to keep pace with the new laser technology. A distributed networked control system can enable laboratory-wide automation and feedback control loops. These higher-repetition-rate experiments will create enormous quantities of data. A consistent approach to managing data can increase data accessibility, reduce repetitive data-software development and mitigate poorly organized metadata. An opportunity arises to share knowledge of improvements to control and data infrastructure currently being undertaken. We compare platforms and approaches to state-of-the-art control systems and data management at high-power laser facilities, and we illustrate these topics with case studies from our community

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Collaborative Distribution System Restoration Planning and Real-Time Dispatch Considering Behind-the-Meter DERs

Modern distribution systems are becoming more resilient against power outages thanks to the flexible generation capacity provided by the increasing integration of distributed energy resources (DERs). Compared to utility-scale DERs, which can be directly controlled by system operators, small-scale, behind-the-meter DERs are much more difficult to coordinate despite being the vast majority. Two major obstacles to the implementation of DERs for service restoration are the coordination of behind-the-meter DERs and the management of uncertainty. In this paper, a novel distribution system restoration strategy is proposed to overcome these two obstacles. The flexibility of be-hind-the-meter DERs is quantified and integrated into the restoration planning models within a hierarchical structure. The model predictive control technique is employed to enable adaptive restoration planning solution adjustments to accommodate fault scenarios and forecast errors. Besides, real-time power dispatch models are proposed to maintain power balance using available DER capability. Comprehensive integration of adaptive restoration planning schemes and real-time dispatch results are achieved through a collaborative restoration framework. Finally, the effectiveness of the proposed restoration strategy is verified through a modified IEEE 123-bus system and a real-world utility system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Adaptive Control Algorithm to Adjust Settings in Photovoltaic Inverters for Electric Grid Cybersecurity (DERAC) v0.1

Volt-VAR and Volt-Watt functionality in photovoltaic (PV) smart inverters provide mechanisms to ensure system voltage magnitudes and power factors remain within acceptable limits. However, these control functions can become unstable, introducing oscillations in system voltages when not appropriately configured or maliciously altered during a cyberattack. In the event that Volt-VAR and Volt-Watt control functions in a portion of PV smart inverters in a distribution grid are unstable, the proposed adaptation scheme utilizes the remaining and stably-behaving PV smart inverters and other Distributed Energy Resources to mitigate the effect of the instability in real-time. The adaptation mechanism is entirely decentralized, model-free, communication-free, and requires virtually no external configuration. This repository provides code to simulate the algorithm in experiments on the IEEE 37 node test feeder.

Arnold, Daniel↗
DOE OSTI2021

Design and analysis of a wake model for spatially heterogeneous flow

Abstract. Methods of turbine wake modeling are being developed to more accurately account for spatially variant atmospheric conditions within wind farms. Most current wake modeling utilities are designed to apply a uniform flow field to the entire domain of a wind farm. When this method is used, the accuracy of power prediction and wind farm controls can be compromised depending on the flow-field characteristics of a particular area. In an effort to improve strategies of wind farm wake modeling and power prediction, FLOw Redirection and Induction in Steady State (FLORIS) was developed to implement sophisticated methods of atmospheric characterization and power output calculation. In this paper, we describe an adapted FLORIS model that features spatial heterogeneity in flow-field characterization. This model approximates an observed flow field by interpolating from a set of atmospheric measurements that represent local weather conditions. The objective of this method is to capture heterogeneous atmospheric effects caused by site-specific terrain features, without explicitly modeling the geometry of the wind farm terrain. The implemented adaptations were validated by comparing the simulated power predictions generated from FLORIS to the actual recorded wind farm output from the supervisory control and data acquisition (SCADA) recordings and large eddy simulations (LESs). When comparing the performance of the proposed heterogeneous model to homogeneous FLORIS simulations, the results show a 14.6 % decrease for mean absolute error (MAE) in wind farm power output predictions for cases using wind farm SCADA data and a 18.9 % decrease in LES case studies. The results of these studies also indicate that the efficacy of the proposed modeling techniques may vary with differing site-specific operational conditions. This work quantifies the accuracy of wind plant power predictions under heterogeneous flow conditions and establishes best practices for atmospheric surveying for wake modeling.

17 WIND ENERGY↗
DOE OSTI2020

PV-Fed Smart Inverters for Mitigation of Voltage and Frequency Fluctuations in Islanded Microgrids

The presence of low-inertia distributed generation (DG) units makes islanded microgrids vulnerable to voltage and frequency variations. Besides, the considerable difference between the inertia of synchronous-based and inverter-based DGs results in a power imbalance between supply and demand during abnormal conditions. As a result, both voltage and frequency of microgrid ac-bus start oscillating which might have severe consequences such as blackouts. This paper deploys the traditional controller of photovoltaic (PV) units to improve the dynamic behavior of islanded microgrids by suppressing the voltage and frequency fluctuations. To this end, an adaptive piecewise droop (APD) characteristic is proposed and employed in PV units to attain a faster balance between generation and consumption during transients, leading to an enhanced frequency response. Besides, the reactive-power control loop is equipped with a droop characteristic which enables the PV units to inject/absorb reactive power during transients and participate in voltage-profile enhancement of the system. Case study results are presented using PSCAD/EMTDC to confirm the validity of proposed method in improving the dynamics of islanded microgrids.

Pilehvar, Mohsen S.↗
DOE OSTI2021

Adaptive critic design-based reinforcement learning approach in controlling virtual inertia-based grid-connected inverters

In this report, an adaptive critic design (ACD) approach is proposed to control the phase and voltage of a grid-connected virtual synchronous generator (VSG). The penetration of fast responding inertia-less power converters significantly affect the stability of the power system, especially weak systems such as micro grids. The concept of virtual inertia addresses this concern by virtually emulating the behavior of a synchronous generator. However, the conventional VSG is designed based on two conditions: (i) fixed operating point and (ii) inductive grid connections. The performance of VSGs in low-voltage semi-resistive microgrids is far from optimal. To overcome the aforementioned concerns, a heuristic dynamic programing (HDP) approach is proposed to optimally control grid-connected VSGs. The neural-network-based inherence of the HDP enables the proposed technique to adapt to any impedance angle. The HDP controller includes two subnetworks: (i) the action network that controls the system optimally and (ii) the critic network, which evaluates the effectiveness of the action network. The simulation and experimental results are provided to evaluate the effectiveness of the proposed technique. As shown, the HDP-based approach illustrates a better performance in comparison with the conventional PI-based VSG in various operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Virtual Cable Impedance based Load Sharing in a Microgrid for Parallel Connected Grid Forming Converters

This paper presents a novel approach to power sharing between direct connected grid-forming converters, utilizing virtual cable impedance and droop-based outer loop control. To enhance stability, resistive droop is implemented, while virtual cable impedance with non-zero resistive and inductive components ensures improved power sharing. The inner loop controller employs a Lyapunov energy function to achieve superior dynamic performance. The proposed control architecture is validated through comprehensive modeling and real-time processor-in-the-loop simulations, demonstrating its robustness and efficiency under various operating conditions. The results highlight the potential of this control strategy to improve the reliability and efficiency of renewable energy systems. Additionally, a comparative analysis with traditional methods underscores the advantages of the proposed approach in terms of stability and performance. The proposed control architecture offers a scalable and flexible solution for grid-forming converters, enabling seamless integration of renewable energy sources. Its robustness and adaptability make it an attractive solution for real-world applications. Furthermore, the approach can be extended to other power electronic systems, enhancing overall system performance and efficiency. By providing a reliable and efficient control strategy, this paper contributes to the advancement of renewable energy systems and their adoption in the energy sector. The proposed control strategy has far-reaching implications for the widespread adoption of renewable energy sources, enabling a more sustainable and efficient energy future. The overall system is modeled in MATLAB/Simulink and PLECS software domain.

grid forming converters (GFM)↗
DOE OSTI2023

Adaptive controller for forced oscillation suppression in the grid

A control system and method for an inverter-based resource device provided in a synchronous power grid. The control system includes at least one inverter based resource device connected to an electrical power system, and a controller module. The inverter based resource device includes a reference power Pref, a combination module and a transfer function. The inverter based resource device injects modulated power into the power system. The power system (which is represented by a transfer function in the control system) receives an undesirable forced oscillation, which is connected to a measuring device. A controller module processes the measured output and provides a control signal to the inverter based resource device. The controller is arranged to suppress a forced oscillation detected in the power system.

Guttromson, Ross↗
DOE OSTI2022

Integration of Control Methods and Digital Twins for Advanced Nuclear Reactors

Advanced nuclear reactors offer a new set of features to energy generation, due to their ability to adapt to variable energy demand, operate autonomously, be deployed in rural locations and monitored remotely, afford compact size and lower power ratings, and rely on novel technologies to achieve safer operations. Thus, a requirement for the success of these reactors is the use of intelligent forms of control to track changing power demands, make autonomous decisions, and reduce the need for human involvement. Regulatory requirements pertaining to control of nuclear reactors could be met via historical means of control; however, these are not expected to enable the level of highly autonomous operations desired in advanced nuclear reactors. Historical control methods rely on both logical and high-performance (HP) control. These two types of control are usually used separately, with a human element being introduced whenever decisions are cascaded from one science to another. AI/ML control, on the other hand, can replace the human element in the current U.S. fleet of nuclear power plants (NPPs) by acting as a supervisory optimizer that understands the plant internal/external variables in order to make control decisions, and can easily handle non-linear and multi-input/multi out (MIMO) decisions—another requirement for advanced nuclear reactors that could be difficult to handle via logical and HP control. Because of the harsh operating environments produced in advanced reactors, resulting in the frequent failure of sensors and other types of equipment, and considering the lack of operating history for advanced nuclear reactors, control of advanced nuclear reactors would necessitate relying on a model that can track and adapt to the actual process (i.e., a digital twin). This digital twin can make approximations when knowledge and data are unavailable and would evolve as more knowledge is gained. The reactor control must also be risk-informed to account for the high-consequence nature of advanced reactors. This report introduces a high-level (i.e., not method- or process-specific) integration of the three different control and digital twinning methods able to meet the requirements for advanced nuclear reactors. These methods could be applied during both the operational and design stages of these reactors. The aim is to demonstrate how each method interfaces with and highlights enabling solutions necessitated by the unique features of advanced nuclear reactors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Fault-Tolerant Decentralized Control for Large-Scale Inverter-Based Resources for Active Power Tracking

Integration of inverter-based resources (IBRs) which lack the intrinsic characteristics such as the inertial response of the traditional synchronous-generator (SG)-based sources presents a new challenge in the form of analyzing the grid stability under their presence. While the dynamic composition of IBRs differs from that of the SGs, the control objective remains similar in terms of tracking the desired active power. This letter presents a decentralized primal-dual-based fault-tolerant control framework for the power allocation in IBRs. Overall, a hierarchical control algorithm is developed with a lower level addressing the current control and the parameter estimation for the IBRs and the higher level acting as the reference power generator to the low level based on the desired active power profile. The decentralized network-based algorithm adaptively splits the desired power between the IBRs taking into consideration the health of the IBRs transmission lines. The proposed framework is tested through a simulation on the network of IBRs and the high-level controller performance is compared against the existing framework in the literature. The proposed algorithm shows significant performance improvement in the magnitude of power deviation and settling time to the nominal value under faulty conditions as compared to the algorithm in the literature.

24 POWER TRANSMISSION AND DISTRIBUTION↗