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At least 1,009 records · Page 56

Control and Management of Multiple Converters in a Residential Smart Grid

Power electronic systems are becoming a staple building block for electric grid networks. However, these systems have been largely designed to grid integrate in ad hoc configurations with little or no coordination of control. This work proposes a central controller and power electronic system hardware and software design for a residential system (photovoltaic, energy storage and residential building). This system supports auto-integration, plug and play capabilities, and optimal energy management to meet different use cases. Modelling and multi-day testing of the system have been conducted in a controller hardware-in-the-loop (C-HIL) testbed. Multiple use cases and pricing options have been considered as part of the simulation and testing. Results are presented of these systems as a proof of principle.

Starke, Michael↗

Software for Transformative Remedial Action Scheme Tool (TRAST)

The transformative remedial action scheme tool (TRAST) can be applied to improve and validate the power system remedial action scheme (RAS), and further improve the performance of power system operation and control. This tool provides a full suite of advanced functionalities, which are given as follows: 1. Advanced statistical data analysis; 2. OPF-based automated power flow case generation; 3. Customized dynamic simulation in HPC/cloud platform; 4. Machine learning based RAS coefficient prediction; 5. A reliable RAS validation strategy in multiple commercial platforms.

Fan, Xiaoyuan↗

Closed-Loop Wind Turbine Controllers for Active Wake Mixing Strategies

Wind turbine active wake mixing (AWM) is an exciting new field of research where dynamic actuation, usually on the blade pitch angles, is used to increase wind farm-wide power production. From a controls perspective, the current state-of-the-art AWM strategies are very simple: a dynamic, usually periodic, reference signal is prescribed to actuators in an open-loop (OL) fashion. The actuation is then presumed to have a certain desired effect on the system, i.e., the wind turbine and the flow it affects. However, this system is highly nonlinear and experiences disturbances in the form of wind variations that are not known a priori. As a result, the OL approach might not yield optimal results. In this article, a novel approach is presented, which closes the loop on AWM controllers. A feedback loop is implemented, which uses measurements of the individual blade bending moments that are widely available on modern wind turbines to determine the individual blade pitch angles. A proof of concept of this implementation is presented in this article, and a thorough comparison with the OL method is executed using high-fidelity flow simulations. These simulations show that the novel closed-loop controller does not substantially increase wake mixing but achieves similar performance as the OL controller while reducing fatigue loads on the controlled turbine.

17 WIND ENERGY↗

Data-Driven Linear Parameter-Varying Modeling and Control of Flexible Loads for Grid Services: Preprint

Flexible loads have great potential to improve the power grid's flexibility and stability. To effectively control large ensembles of heterogeneous loads, reliable models thereof are required. The paper presents a data-driven modeling and control approach to manage flexible loads for providing grid services. We leverage a linear parameter-varying autoregressive moving average (LPV-ARMA) model to describe the aggregate load response, where the parameters in the model are used to capture external environment impacts (e.g., weather). A gain-scheduling feedback controller is then developed to adapt to environmental variations. This data-driven approach can be easily applied to different types of loads in various environmental conditions. In addition to the ensemble controller, distributed load controllers are designed to deliver grid services, while maintaining the quality of service of inherent load tasks. We demonstrate the work on the IEEE 37-node distribution system for real-time power regulation services through control of thermostatically controlled loads.

control↗

Cyber-Physical Smart Light Control System Integration with Smart Grid using Zigbee

This paper presents a hardware-in-the-loop cyber-physical system architecture design to monitor and control smart lights connected to the active distribution grid. The architecture uses Zigbee-based (IEEE 802.15.4) wireless sensor networks and publish-subscribe architecture to exchange monitoring and control signals between smart-light actuators (SLAs) and a smart-light central controller (SLCC). Each SLA integrated into a smart light consists of a Zigbee-based endpoint module to send and receive signals to and from the SLCC. The SLCC consists of a Zigbee-based coordinator module, which further exchanges the monitoring and control signals with the active distribution management system over the TCP/IP communication network. The monitoring signals from the SLAs include light status, brightness level, voltage, current, and power data, whereas, the control signals to the SLAs include light intensity, turn ON, turn OFF, standby, and default settings. We have used our existing hardware-in-the-loop (HIL) cyber-physical system (CPS) security SCADA testbed to process signals received from the SLCC and respond suitable control signals based on the smart light schedule requirements, system operation, and active distribution grid dynamic characteristics. We have integrated the proposed cyber-physical smart light control system (CPSLCS) testbed to our existing HIL CPS SCADA testbed. We use the integrated testbed to demonstrate the efficacy of the proposed algorithm by real-time performance and latency between the SLCC and SLAs. The experiments demonstrated significant results by 100% realtime performance and low latency while exchanging data between the SLCC and SLAs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Model-Free Voltage Control Approach to Mitigate Motor Stalling and FIDVR for Smart Grids

Electric power networks are large and highly nonlinear dynamical systems that present unique challenges to control design. Though there is a large number of dynamic models for power system stability and control, many models are only useful with right assumptions and wrong for other tasks. Moreover, the dynamic behavior of the grid is increasingly complex under the banner of smart grids. These lead to the difficulty of developing appropriate dynamic modeling, and thus an efficient control strategy. To avoid such modeling challenges, here we present a novel dynamic voltage control strategy based on a model-free control (MFC) approach, requiring no modeling procedure. In particular, it focuses on fault-induced delayed voltage recovery (FIDVR) events, which require complex and accurate dynamic load models to replicate such events. This work utilizes MFC as an online controller to achieve the desired voltage stability under the FIDVR event. The proposed MFC strategy allows simple implementation and low computational cost for efficient mitigation of FIDVR. For benchmarking, a reasonably accurate dynamic performance model is explored. Simulation results with the IEEE 57 bus test network demonstrate the enhanced dynamic voltage profile for load buses having induction motors with the support of reactive power resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Agent-Supervisor Coordination for Decentralized Event-Triggered Optimization

This letter proposes decentralized resource-aware coordination schemes for solving network optimization problems defined by objective functions that combine locally evaluable costs with network-wide coupling components. These methods are well suited for a group of supervised agents trying to solve an optimization problem under mild coordination requirements. Each agent has information on its local cost and coordinates with the network supervisor for information about the coupling term of the cost. The proposed approach is feedback-based and asynchronous by design, guarantees anytime feasibility, and ensures the asymptotic convergence of the network state to the desired optimizer. Numerical simulations on a power system example illustrate our results.

decentralized algorithms↗

Modeling Needs to Support the Reconstruction Strategy of Ukraine

Ukraine has been facing difficult times. Russia started a full-scale invasion on February 24, 2022, and has caused huge human and infrastructure losses. As a result of the invasion, more than 8 million people left their homes. The Russian army has targeted Ukrainian energy sources, destroying or damaging over 50% of thermal power generation capacity (coal and gas), 30% of solar generation, and 90% of wind generation. The Russians are also threatening Ukrainian energy security, as they currently control the Zaporizhzhia nuclear power plant – Europe’s largest. In addition, Russia has destroyed 121,000 buildings, including 5,300 multistory buildings - more buildings than Ukraine built during the past five years. The occupiers destroyed or damaged 343 district heat boiler stations (destroyed 12 / damaged 331) and 8 CHPs (destroyed 4/ damaged 4). There is no doubt that Ukraine will be able to protect its sovereignty and restore its territorial integrity; however, this will be a long process. The Government of Ukraine needs to simultaneously focus on many issues, from waging war to the restoration of electricity, water, and heat supply in the territories close to the front line. In addition to these time-sensitive issues, the government also needs to plan a long term multi-sector strategy for the reconstruction of Ukraine’s economy. Ukraine initiated a broad-based political process for recovery at the International Ukraine Recovery Conference (URC 2022) in Lugano, Switzerland. Prior to URC 2022, Ukraine applied for EU membership on February 28 and was granted the status of candidate country by the European Council on June 23, 2022. More than 40 nations are fully committed to supporting Ukraine throughout its path from early to long-term recovery. In addition, these countries link a successful recovery to Ukraine’s European future (URC, 2022a). The reconstruction process will be long. The government also recognizes that it is not enough to build energy infrastructure back – it should be built back better. The government is committed to building a more sustainable and cleaner energy sector. Energy modeling can provide important insights into paths to decarbonize Ukraine’s economy while rebuilding it after the war. Pacific Northwest National Laboratory (PNNL) and the Institute for Economics and Forecasting of the National Academy of Sciences of Ukraine (IEF) work on modeling decarbonization scenarios in the energy sector of Ukraine. The teams focus on the heat sector, which includes district heat, autonomous and individual heating, and energy consumption by final energy consumption sectors, including buildings. Since the teams use world-class integrated assessment models, other sectors will be analyzed as well. The purpose of the document is to describe the needs of key Ukrainian ministries in modeling the reconstruction process. The scope of this document is limited to modeling energy consumption by the power and heat sectors, final energy consumption by buildings, and GHG emissions from these two sectors. The rest of this policy memo is organized as follows. After this introduction, Chapter 2 discusses key provisions of the reconstruction strategy with a focus on energy, buildings, heat supply, environment, and European integration aspirations. Section 3 provides an overview of recent developments and key decisions of the Government of Ukraine in the area of energy efficiency and decarbonization. Finally, Section 4 provides key suggestions on how PNNL and IEF can help the Government of Ukraine in developing strategic documents.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Fully integrated multi-phase buck converter with coupled air core inductors

A multi-phase buck switching converter having grouped pairs of phases, each phase using two magnetically coupled air-core inductors. For each group, a first driver circuit controlling switching of a first power transistor switching circuit coupled to a first air-core inductor output for driving an output load at the first phase. A second driver circuit controlling switching of a second power transistor switching circuit coupled to a second air-core inductor output for driving said output load at the second phase. The first and second phases are spaced 180° apart. The coupled air-core inductors per group of such orientation, separation distance and mutual inductance polarity relative to each other such that magnetic coupling between the two or more inductors at each phase results in a net increase in effective inductance per unit volume. Each air-core inductor is a metal slab of defined length, height and thickness formed using back-end-of-line semiconductor manufacturing process.

Zhang, Xin↗

Frequency Response Improvement in a Standalone Small Hydropower Plant Using Battery Storage

This paper proposes a control architecture for frequency, current, and voltage control that facilitates using battery storage to improve the response of standalone small hydropower plants. The frequency controller uses rate-of-change of frequency and frequency-Watt-based generations to produce active power commands. The distinctive feature of the controller design is that it nicely integrates response to frequency change with constraints on frequency and state of battery to enable power injections. The current and voltage control scheme allows incorporating the frequency controller. The distinctive feature of this controller is that it incorporates a bounded integral control strategy that guarantees stability. Results on the stability of the hydropower plant with proposed scheme are presented and robust ways to choose the controller gains are investigated via root locus analysis. In conclusion, simulations performed show that: the hydropower plant response is significantly improved with battery storage using the proposed scheme; the load carrying capability of the hydropower plant is significantly improved with battery storage; the proposed scheme has the capability to recharge the battery; and the proposed control scheme gives improved performance.

13 HYDRO ENERGY↗

Droop-Free Distributed Control for AC Microgrids

In this chapter, droop-free distributed control for AC microgrids is discussed. The hierarchical structure of microgrid control is first introduced. Secondary level controls both with and without droop are discussed. Then two droop-free distributed controls are presented: one achieves average voltage regulation and perfect power sharing, and the other one achieves average voltage regulation, voltage variance regulation, and relaxed reactive power sharing. For the latter droop-free control, the relaxed reactive power sharing is achieved through a special distributed generator (DG) that will not participate in reactive power sharing.

Mohiuddin, Sheik Mohammad↗

5G Securely Energized and Resilient: (5G-SER) (Final Report)

NREL's work on 5G integration with physical power systems (versus simulated systems demonstrated in task 3) under 5G-Securely Energized and Resilient (5G-SER) achieved a major milestone in with the completion of Task 4 activities. After many months (6+) of planning and development along with scaling challenges along the way, a full 5G end-to-end network with physical hardware components (physical inverter, physical power panel, physical battery, etc.) was deployed in a containerized environment. In parallel, a distributed controls architecture for a microgrid powering 5G resources was also successfully modified from its previous instantiation for a simulated environment to work with these physical components. These accomplishments set the stage to use newly setup 5G technology with physical microgrid components to test the feasibility of 5G wireless with physical systems to enable resilient communications between controls and distributed solar and storage resources while exploring ways to configure 5G components to survive power disturbances. The results detailed in the report below show that even utilizing physical components, 5G wireless systems were able to provide resilient results that were similar to the results from the simulated environment Task 3).

24 POWER TRANSMISSION AND DISTRIBUTION↗

Efficient data-driven models for prediction and optimization of geothermal power plant operations

Increasing the capacity of geothermal energy as a renewable resource calls for development and deployment of efficient control and optimization technologies for geothermal power plants. A data-driven prediction and optimization model is presented as a cost-effective and efficient alternative to physics-based approach. The model predicts power output and operational cost by propagating the influence of control and disturbance variables within an artificial neural network (ANN). Numerical experiments with simulated and field data from a real geothermal power plant are first used to demonstrate the prediction performance of the ANN model. The model is then adopted to maximize the net predicted power production by automatically adjusting the working fluid circulation rate. The optimization performance of the model in evaluated using a thermodynamic flowsheet simulation model. The workflow is applied to model and control the effect of ambient temperature on an air-cooled binary cycle power plant, which is complex and costly to perform using a physics-based predictive model. As a result, the performance of the method is demonstrated by applying it to both simulated and field datasets from a binary cycle geothermal power plant.

15 GEOTHERMAL ENERGY↗

Precise Timing Based on Pulsar Observation for Grid Synchronization

While Global Positioning System signals are widely used as the synchronized timing Sources for wide-area measurement systems for power grid monitoring and control, they are vulnerable to failures and malicious attacks. To address this Problem, an alternative kind of timing sources, the millisecond pulsars, were proposed to serve the power grid as they are more precise and physically indestructible. Millisecond pulsars are a kind of neutron stars that emit radio pulse signals that have extremely stable periods of milliseconds. However, the observed pulse Signals from pulsars cannot be directly used for timing because of their low signal-to-noise ratio and the dispersion effects of interstellar medium. In this paper, the precise timing method based on pulsar observation data is proposed to interpret the pulsar observation data and therefrom to generate precise timing signal for the power grid synchronization. In our proposed method,. incoherent de-dispersion is used on the observation data to mitigate the effect of interstellar medium. dispersion. Then spectrum analysis and segment folding are used to precisely estimate the local pulsar period. Finally the standard pulse per second signal is generated from. the estimated pulsar period and its precision. is analyzed. Experiments with the observation data of the pulsar based timing signal can be more accurate compared to GPS timing signals.

Luo, Xiqian↗

Modernizing to an AI-Ready Control System

The Accelerator Controls Operations Research Network (ACORN) project will modernize the accelerator control system and upgrade power supplies to enable future operations of the Fermilab Accelerator Complex with megawatt proton beams. By focusing on MLOps, ACORN enables full integration of AI into the control system to allow safe and reliable improvements to accelerator beam operations.

43 PARTICLE ACCELERATORS↗

Methane Emissions Produced by Pneumatic Devices and Produced Water Tanks on Natural Gas Wellsites

In recent years, more scrutiny has been placed on the release of greenhouse gasses (GHGs) by the oil and gas industry in North America as climate concerns increase. In the coming years, stricter regulations proposed by the Environmental Protection Agency (EPA) concerning the release of GHGs will further direct attention to GHG emissions quantification, modeling, and overall reduction. Active natural gas wellsites employ production equipment that routinely emits methane during normal operation. Production equipment often includes, but is not limited to, gas production units (GPUs), pneumatic controllers (PCs) and actuators powered by produced natural gas, and produced water storage tanks. This work details direct methane emission measurements taken at active natural gas wellsites originating from intermittent pneumatic controllers and produced water storage tanks. Efforts to model methane flows originating from these sources are also detailed, and those results are compared to direct measurement. The direct methane emissions measurement campaign collected flow data from two active dry wellsites in the Marcellus shale region. These measurement campaigns captured, in total, several weeks of continuous data from these sites. Data included multiple pneumatic device vent flowrate channels, a single channel monitoring total emissions vented from the produced water storage tanks, and corresponding site weather data. Periodic composition measurements were taken from flows vented from produced water tanks. Computational modeling efforts attempted to mimic a given site’s methane emissions behavior given limited input parameters. Direct measurement data and simulation data yielded, through reduction and analysis, apparent methane emissions factors, statistics on pneumatic device actuation events, important relationships between GPU parameters and pneumatic device actuation events, produced water storage tank vent flows and flow compositions, and parameters most contributing to the magnitude and frequency of these fugitive methane emissions. Measurements, considering data from a 72hr period, produced PC emissions factors from 0.008 to 0.03 SCFH per device with an average device emitting 0.026 SCFH at the first site. The second site produced PC emissions factors spanning from 0.05 to 25.47 SCFH with an average device emitting 1.93 SCFH not including the 25.47 SCFH device, which was assumed to be malfunctioning. Two unique water tank emission measurements were made, 618 g CH4 per hour and 32.6 g CH4 per hour. On a water basis, the water tank emissions factors were 0.66 and 0.042 kg CH4 per bbl of water, respectively.

03 NATURAL GAS↗

Active control of laser beam pointing for the Zettawatt-Equivalent Ultrashort pulse laser System: a proof-of-principle study with 16-inch optics

We present a proof-of-principle study of active beam-pointing control for the Zettawatt-Equivalent Ultrashort pulse laser System (ZEUS) using a piezo-actuated 16-inch mirror. To the best of our knowledge, this is the largest actively controlled mirror reported in a high-power laser system. A simple proportional feedback control was implemented based on a field-programmable gate array, which reduced the standard deviation of beam-pointing fluctuations by 91% to 0.075 μrad in the horizontal direction and by 78% to 0.25 μrad in the vertical direction. We also demonstrated the elimination of long-term pointing jitter caused by temperature drift using the same apparatus.

laser pointing control↗

Laser Plasma Interaction in the MG Magnetic Field (Final Report)

Strong magnetic fields change properties of plasma. Employment of the magnetic fields can improve conditions for inertial confinement fusion. Compression and heating of the magnetized plasma is a base of the MagLIF pulsed power approach to the controlled fusion. Study of expansion and heating of plasma in the external magnetic fields, development of plasma instabilities, parametric and other effects are important for basic physics and applications. The main goal of the research for the grant was experimental investigation of laser produced plasma in the well characterized and controlled MG magnetic fields. We developed a platform for investigation of high intensity laser-plasma interaction (LPI) in the MG fields using a university-scale pulsed power machine. A Zebra machine at UNR generated transverse magnetic fields of 3 MG on the surface of the rod load and longitudinal fields of 1.4 MG in the coil loads. The magnetic fields were characterized with two-color Faraday rotation diagnostics. The pulsed power machine provided almost static magnetic fields for LPI compared to the much faster laser driven magnetic fields. We found that eddy currents in the rising magnetic field generate plasma on the metal targets. Eddy currents did not impact Si and CH dielectric targets. A Leopard laser with intensity in the focus up to 10 19 W/cm 2 produced plasma in the MG magnetic fields. The modified reflected Faraday diagnostics was used to study laser driven B-field at the MTW laser at Laboratory for Laser Energetics, UR. We demonstrated a slow dependence of the magnetic field in the coil on the applied laser intensity. The magnetic field increased by a factor of 2 if laser intensity increased by a factor of 30. This scaling is important for comparison of experiments at different laser facilities. Expansion of the plasma in the 2-3 MG external B-field was studied. Laser-produced plasma in the azimuthal magnetic field took the unique form of a thin disc expanding radially with a velocity of 250 km/s and confined in the vertical direction. A HYDRA MHD program at the University of Rochester was applied for simulations of LPI in the magnetic field B >3 MG. Simulations for the plasma disc parameters and the expansion dynamics were in a good agreement with experiments. Generation of narrow dense plasma jets in the longitudinal magnetic field of 0.6-0.8 MG was studied. Narrow plasma jets reached a length of 3-4 mm with the electron plasma density of (0.2-1.2)x10 20 cm -3 . A jet tip propagated with the velocity of 160-200 km/s. MHD simulations showed a good agreement of the dynamics of the formation of plasma jets with experiments. These jets are relevant to astrophysical jets. Simulations of K-shell spectra of Si plasma was performed for LPI in the B-field. The laser prepulse generated plasma near the laser target. A PrismSPECT model with a MeV electron beam produced by the laser was used. The spectral modelling showed the increased plasma density by a factor by 2-3 in the magnetic field. This was in agreement with the observed dynamics of the plasma plume confined by the axial magnetic field. The two-plasmon decay was studied in the 2.5-3 MG transversal magnetic fields. Strong 2-3.5 nm spectral widening and a 2-4 nm shifts of “red” and “blue” 3/2ω 0 spectral components were observed. The large shift and widening exceed the expected temperature and magnetic shift. PIC simulations are performing to clarify physics of this effect. The experimental research program for the grant is completed. New plasma effects in the MG fields were studied at the university-scale pulsed power generator. Two graduate and two undergraduate UNR and UR students carried experiments at the Zebra generator, supported and developed plasma diagnostics, provided data processing, and performed MHD simulations of LPI in the strong magnetic field. Research results are published in 9 referred papers and presented in 12 conferences. Program manager: Kramer U. Akli; Collaborators: R. C. Mancini and H. Sawada, University of Nevada, Reno (UNR); R. Betti and A. V. Maximov, University of Rochester (UR).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗