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At least 1,621 records · Page 90

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↗

Development of a Practical Secondary Control for Hardware Microgrids: Preprint

Practical vendor-agnostic interoperability guidelines for the secondary control architecture of microgrids (MGs) with multiple grid-forming (GFM) inverter-based resources (IBRs) have not yet been developed. Therefore, this paper proposes a generic and vendor-agnostic secondary control architecture that works with all GFM IBRs and synchronous generators. This secondary control does not need to employ any additional measurement devices in the MG and uses the inherent communication systems of the GFM units, such as Modbus TCP/IP. The practical challenges of Modbus holding registers such as packet loss, quantization error, etc. and their deteriorating impacts on the secondary control action are investigated. The proposed three-stage modification of any secondary control architecture to eliminate these impacts includes 1) averaging the data read, 2) situational event-triggering of the controller, and 3) the finite iteration of the controlling action. The proposed method is validated using a laboratory hardware MG with commercial GFM units.

inverter based resources↗

Enhancing Autonomous Control of Microreactors Using Multi-Agent Reinforcement Learning

In order for microreactors to be economically competitive, operation costs will need to be minimized through some degree of autonomous control. Previous work has demonstrated the effectiveness of reinforcement learning (RL) for load-following control in a drum-controlled microreactor. This study extends that work by exploring the potential of RL to independently control each of the reactor’s drums. We compare a single-agent RL approach with a multi-agent RL (MARL) framework, testing them for generalization across different load-following power profiles and control timescales, and for robustness in cases of randomly disabled control drums. Since the point kinetics simulation environment used in this study cannot resolve spatial effects, we assume that in the absence of spatially localized disturbances, optimal drum movements should be symmetrical. We demonstrate that single-agent RL is able to achieve accurate performance only when symmetric actions are ignored; otherwise, it fails to train a useful controller. Meanwhile, the MARL framework performs symmetric actions by design and trains a robust, accurate agent, as evidenced by mean absolute errors in power matching of 0.41% for the training power profile, 0.68% for a profile with half the drums disabled, and 0.21% for a profile on a realistic load-following time horizon.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Development of microheaters for gas sensor with an AT-Mega 8535 temperature controller using a PWM (pulse width modulation) method

Microheater is the main component in gas sensor characterized by their sensitivity, selectivity, and time response of gas sensor which is depend on the microheater temperature stability. A Cu microheater was developed and utilized AT-Mega 8535 controller using a PWM (pulse width modulation) method. This control system is interfaced to the PC to observe the real time temperature response of the microheater. Three initial resistance (R0) variations of microheater were developed in an open loop control system. The power characteristic of designed microheater depends on the specified microheater initial resistance. The smaller R0, the less power required to reach a temperature setting value. The developed microheater was designed to reach a temperature setting value of 250°C having resistance 0.531 Ω for 1.979 Watt and 0.265 Ω for 1.072 Watt respectively. The results of the investigation on the control performances shows microheater-control system achieved operating temperature up to 250°C. The response of the temperature control shows smallest R0 resulted in a high stability with short settling time, short delay time and small ripple for temperature setting values higher than 150°C. The obtained error of microheater temperature with R0 = 0.265 is 8.596 %. It is concluded that the developed microheater can be utilized as a component of a gas sensor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Combined magnetic and kinetic control of advanced tokamak steady state scenarios based on semi-empirical modelling

Our paper shows that semi-empirical data-driven models based on a two-time-scale approximation for the magnetic and kinetic control of advanced tokamak (AT) scenarios can be advantageously identified from simulated rather than real data, and used for control design. The method is applied to the combined control of the safety factor profile, q(x), and normalized pressure parameter, beta(N), using DIII-D parameters and actuators (on-axis co-current neutral beam injection (NBI) power, off-axis co-current NBI power, electron cyclotron current drive power, and ohmic coil). The approximate plasma response model was identified from simulated open-loop data obtained using a rapidly converging plasma transport code, METIS, which includes an MHD equilibrium and current diffusion solver, and combines plasma transport nonlinearity with 0D scaling laws and 1.5D ordinary differential equations. The paper discusses the results of closed-loop METIS simulations, using the near-optimal ARTAEMIS control algorithm (MoreauDet al 2013 Nucl. Fusion 53 063020) for steady stateAT operation. With feedforward plus feedback control, the steady state target q-profile and beta(N) are satisfactorily tracked with a time scale of about 10 s, despite large disturbances applied to the feedforward powers and plasma parameters. We also show the robustness of the control algorithm with respect to disturbances of the H&CD actuators and of plasma parameters such as the H-factor, plasma density and effective charge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Multiobjective Optimization Framework for Online Stochastic Optimal Control in Hybrid Electric Vehicles

The increasing urgency to extract additional efficiency from hybrid propulsion systems has led to the development of advanced power management control algorithms. In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain and we show that the control policy yielding the Pareto optimal solution minimizes online the long-run expected average cost per unit time criterion. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion. Both solutions achieved the same cumulative fuel consumption demonstrating that the online Pareto control policy is an optimal control policy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Integrated Coordination of Voltage Regulators with Distributed Cooperative Inverter Control in Systems with High Penetration of DGs

Increased penetration of distributed generation (DG) in recent years has a significant impact on operation and control of power systems. One of the main issues with the increased penetration of DGs is the effect of voltage rise. This paper investigates integration of coordinated voltage regulator (VRs) operation with cooperative distributed inverter control to maintain voltages in appropriate limits in distribution systems with high penetration of DGs. The coordinated VR control is used to optimize the settings of multiple nested VRs while the cooperative distributed control optimally dispatches reactive power of the DGs. The integrated approach is compared with the case without coordinated VRs control (uncoordinated local control). Simulation results illustrate the effective performance of the proposed method to achieve unified voltage profile.

coordinated voltage regulator control↗

Coordinated Control Strategy of a Battery Energy Storage System to Support a Wind Power Plant Providing Multi-Timescale Frequency Ancillary Services

With increasing penetrations of wind generation on electric grids, wind power plants (WPPs) are encouraged to provide frequency ancillary services (FAS); however, it is a challenge to ensure that variable wind generation can reliably provide these ancillary services. This paper proposes using a battery energy storage system (BESS) to ensure the WPPs' commitment to FAS. This method also focuses on reducing the BESS's size and extending its lifetime. In this paper, a state-machine-based coordinated control strategy is developed to utilize a BESS to support the obliged FAS of a WPP (including both primary and secondary frequency control). This method takes into account the operational constraints of the WPP (e.g., real-time reserve) and the BESS (e.g., state of charge [SOC], charge and discharge rate) to provide reliable FAS. Meanwhile, an adaptive SOC-feedback control is designed to maintain SOC at the optimal value as much as possible and thus reduce the size and extend the lifetime of the BESS. In conclusion, the effectiveness of the control strategy is validated with an innovative, multi-area, interconnected power system simulation platform that can mimic realistic power systems operation and control by simulating real-time economic dispatch, regulating reserve scheduling, multi-area automatic generation control, and generators' dynamic response.

25 ENERGY STORAGE↗

A Methodology for Robust Load Reduction in Wind Turbine Blades Using Flow Control Devices

Decades of wind turbine research, development and installation have demonstrated reductions in levelized cost of energy (LCOE) resulting from turbines with larger rotor diameters and increased hub heights. Further reductions in LCOE by up-scaling turbine size can be challenged by practical limitations such as the square-cube law: where the power scales with the square of the blade length and the added mass scales with the volume (the cube). Active blade load control can disrupt this trend, allowing longer blades with less mass. This paper presents the details of the development of a robust load control system to reduce blade fatigue loads. The control system, which we coined sectional lift control or SLC, uses a lift actuator model to emulate an active flow control device. The main contributions of this paper are: (1) Methodology for SLC design to reduce dynamic blade root moments in a neighborhood of the rotor angular frequency (1P). (2) Analysis and numerical evidence supporting the use of a single robust SLC for all wind speeds, without the need for scheduling on wind speed or readily available measurements such as collective pitch or generator angular speed. (3) Intuition and numerical evidence to demonstrate that the SLC and the turbine controller do not interact. (4) Evaluation of the SLC using a full suite of fatigue and turbine performance metrics.

17 WIND ENERGY↗

Integrated Synchronization Control of Grid-Forming Inverters for Smooth Microgrid Transition: Preprint

This paper develops an integrated synchronization control technique for a grid-forming inverter operating within a microgrid that can improve the microgrid's transients during microgrid transition operation. This integrated synchronization control includes the disconnection synchronization control and the reconnection synchronization control. The simulation results show that the developed synchronization control works effectively to smooth the angle change of the grid-forming inverter during microgrid transition operation. Thus, the microgrid's transients are significantly improved compared to the case without synchronization control.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Commercial Building Sensors and Controls Systems: Barriers and Drivers: Preprint

Building sensors and controls systems, including building automation systems, comprise the sensor-based devices installed in buildings as well as the control and automation of those devices. Optimized sensors and controls systems could lead to 29% annual energy savings in commercial buildings and are integral to the growth of grid-interactive efficient buildings. Only 13% of small commercial buildings, however, have installed sensors and controls systems, largely because of cost barriers. To accelerate adoption, this work seeks to increase the transparency of system costs and identify specific barriers and drivers. To gather industry insights, the team reached out to building owners, vendors, and contractors and conducted 21 interviews with the goal of collecting cost data and market characteristics regarding building sensors and controls. We collected the cost data in the form of invoices and used it to develop a percentage-based cost category breakdown. The interview data were analyzed using grounded theory to identify overarching concepts such as barriers, drivers, and future directions. From this analysis, we found the primary barriers to be complex and confusing systems, lack of user skills, and financial concerns, and the primary drivers to be operational benefits, insight into operations, and remote access to data. The future directions analysis highlighted the potential technological solutions to address gaps and barriers, as well as predicted drivers to increase adoption. This greater understanding of the costs, barriers, and drivers associated with commercial building sensors and controls systems lays the groundwork for increasing system adoption, reducing energy consumption, and transforming the market.

building automation system↗

Reinforcement Learning for Intelligent Building Energy Management System Control *

A building energy management system (BEMS) is a computer-based system designed to monitor and control a building's energy needs. Modern BEMS rely on the sensing and connectivity capabilities of Internet of Things (IoT) technology to intelligently adjust the energy consumption to reduce cost while respecting the consumers' preferences. Increasingly, control decisions are made based on predictions by models trained using supervised machine learning methods, which still requires control policies to be formulated in a rule-based fashion. When using reinforcement learning (RL) instead, control policies are learned by observing the utility in terms of cost and comfort associated with actions such as a change in the heating system's setpoint. The resulting RL-based controllers can capture not only the dynamics of the building and the associated electrical devices, but also fluctuations in electricity prices and user demand, avoiding the need to combine multiple predictive models with tailored control policies. This chapter will provide an overview of RL-based approaches for BEMS. After sketching the taxonomy of general RL methods, we discuss the implications of relying on the individual methods in a BEMS context. Existing work applying RL is presented along the key devices controlled by BEMS systems. Finally, we summarize the state-of-the-art and sketch limitations and open research directions.

Kotevska, Olivera↗

Adaptive changes in sexual behavior in the high–risk population in response to human monkeypox transmission in Canada can help control the outbreak: Insights from a two–group, two–route epidemic model

Monkeypox, a zoonotic disease, is emerging as a potential sexually transmitted infection/disease, with underlying transmission mechanisms still unclear. We devised a risk-structured, compartmental model, incorporating sexual behavior dynamics. We compared different strategies targeting the high-risk population: a scenario of control policies geared toward the use of condoms and/or sexual abstinence (robust control strategy) with risk compensation behavior change, and a scenario of control strategies with behavior change in response to the doubling rate (adaptive control strategy). Monkeypox's basic reproduction number is 1.464, 0.0066, and 1.461 in the high-risk, low-risk, and total populations, respectively, with the high-risk group being the major driver of monkeypox spread. Policies imposing condom use or sexual abstinence need to achieve a 35% minimum compliance rate to stop further transmission, while a combination of both can curb the spread with 10% compliance to abstinence and 25% to condom use. With risk compensation, the only option is to impose sexual abstinence by at least 35%. Adaptive control is more effective than robust control where the daily sexual contact number is reduced proportionally and remains constant thereafter, shortening the time to epidemic peak, lowering its size, facilitating disease attenuation, and playing a key role in controlling the current outbreak.

60 APPLIED LIFE SCIENCES↗

Wave tank and bench-top control testing of a wave energy converter

An increasing number of experiments are being conducted to study the design and performance of wave energy converters. Often in these tests, a real-time realization of prospective control algorithms is applied in order to assess and optimize energy absorption as well as other factors. This paper details the design and execution of an experiment for evaluating the capability of a model-scale WEC to execute basic control algorithms. Model-scale hardware, system, and experimental design are considered, with a focus on providing an experimental setup capable of meeting the dynamic requirements of a control system. To more efficiently execute such tests, a dry bench testing method is proposed and utilized to allow for controller tuning and to give an initial assessment of controller performance; this is followed by wave tank testing. The trends from the dry bench test and wave tank test results show good agreement with theory and confirm the ability of a relatively simple feedback controller to substantially improve energy absorption. Additionally, the dry bench testing approach is shown to be an effective and efficient means of designing and testing both controllers and actuator systems for wave energy converters.

16 TIDAL AND WAVE POWER↗

Testing and demonstration of model predictive control applied to a radiant slab cooling system in a building test facility

Radiant slab systems have the potential to significantly reduce energy consumption in buildings. However, control of radiant slab systems is challenging. Classical feedback control is inadequate due to the large thermal inertia of the systems and heuristic feed-forward control often leads to unacceptable indoor comfort and may not achieve the full energy savings potential. Model predictive control (MPC) is now attracting increasing interest in the building industry and holds promise for radiant systems. However, an often-cited barrier to its implementation in the building industry is the high computational cost and complexity relative to the feedback controls used in conventional systems. The objectives of this study were to (i) verify the correct operation of an open source MPC toolchain developed for radiant slab systems, and (ii) demonstrate its efficacy in a test facility. A matched pair of cells in the FLEXLAB building test facility at the Lawrence Berkeley National Laboratory was used in the study. The proposed MPC toolchain was implemented in one cell and the performance compared to that of the other cell, which used a conventional heuristic control strategy. Finally, the results showed that the simplified MPC approach applied in the toolchain worked as expected and realized energy savings over the conventional control strategy. The MPC yielded 42% chilled water pump power reduction and 16% cooling thermal energy savings, while maintaining equal or better indoor comfort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Deciphering Reaction Mechanisms of Molecular Proton Reduction Catalysts with Cyclic Voltammetry: Kinetic vs Thermodynamic Control

The kinetics and thermodynamics of elementary reaction steps involved in the catalytic reduction of protons to hydrogen define the reaction landscape for catalysis. The mechanisms can differ in the order of the elementary proton transfer, electron transfer, and bond-forming steps and can be further differentiated by the sites at which protons and electrons localize. Access to fully elucidated mechanistic, kinetic, and thermochemical details of molecular catalysts is crucial to facilitate the development of new catalysts that operate with optimal efficiency, selectivity, and durability. The mechanism by which a catalyst operates, as well as the kinetics and thermodynamics associated with the individual steps, can often be accessed through electroanalytical studies. Here, this Account details the application of cyclic voltammetry to interrogate reaction mechanisms and quantify the kinetics and thermodynamics of elementary reaction steps for a series of molecular catalysts that mediate electrochemical proton reduction. I distinguish the limiting scenarios wherein a catalyst operates under kinetic control vs thermodynamic control, with a focus on detecting how cyclic voltammetry features shift with proton source strength and concentration, as well as scan rate. For systems that operate under kinetic control, catalytic currents are observed at, or slightly positive toward, the formal potential for the redox process that triggers catalysis. Under thermodynamic control, catalytic responses shift as a function of the proton source pKa and effective pH of the solution. After drawing this distinction, we introduce the appropriate voltammetry experiments and accompanying analytical expressions for extracting key metrics from the data. To illustrate analytical strategies to quantify elementary reaction steps of catalysts operating under kinetic control, I describe our studies of proton reduction catalysts Co(dmgBF 2 ) 2 (CH 3 CN) 2 (dmgBF 2 = difluoroboryl-dimethylglyoxime) and [Ni(P 2 Ph N 2 Ph ) 2 ] 2+ (P 2 Ph N 2 Ph = 1,5-phenyl-3,7-phenyl-1,5-diaza-3,7-diphosphacyclooctane). Here, peak shift analysis, foot-of-the-wave analysis, and plateau current analysis are applied to data sets wherein voltammetric response are recorded as a function of catalyst concentration, proton source concentration, proton source strength, and scan rate to quantify rate constants for elementary proton transfer and bond-forming steps in a catalytic cycle. Further, the case study of [Ni(P 2 Ph N 2 Ph ) 2 ] 2+ illustrates how complementary spectroscopic methods can bolster the mechanistic assignment. Collectively, these two studies showcase how detailed mechanistic studies inform on rate-limiting elementary steps in catalysis and other key processes underpinning catalysis. Second, I present analytical strategies to interrogate catalysts operating under thermodynamic control, centered on the case study of [Ni II (P 2 Ph N 2 Bn ) 2 ] 2+ (P 2 Ph N 2 Bn = 1,5-dibenzyl-3,7-diphenyl-1,5-diaza-3,7-diphosphacyclooctane). Here, the application of nonaqueous Pourbaix theory to extract thermodynamic information is introduced, and the construction of a coupled Pourbaix diagram is detailed. This study identifies ligand-based protonation as the key process that places catalysis under thermodynamic control and influences the reaction mechanism. Together, the work detailed in this Account showcases the utility of electroanalytical methods to disentangle complex reaction mechanisms and extract key thermochemical and kinetic parameters for elementary steps of catalysis. Through detailed presentation of the key analytical expressions that underpin these analyses, this Account seeks to facilitate the adoption of cyclic voltammetry by the community to fully extract kinetic, thermochemical, and mechanistic information on electrochemical small-molecule activation.

catalysts↗

Redox-enabled electronic interrogation and feedback control of hierarchical and networked biological systems

Abstract Microelectronic devices can directly communicate with biology, as electronic information can be transmitted via redox reactions within biological systems. By engineering biology’s native redox networks, we enable electronic interrogation and control of biological systems at several hierarchical levels: proteins, cells, and cell consortia. First, electro-biofabrication facilitates on-device biological component assembly. Then, electrode-actuated redox data transmission and redox-linked synthetic biology allows programming of enzyme activity and closed-loop electrogenetic control of cellular function. Specifically, horseradish peroxidase is assembled onto interdigitated electrodes where electrode-generated hydrogen peroxide controls its activity. E. coli ’s stress response regulon, oxyRS , is rewired to enable algorithm-based feedback control of gene expression, including an eCRISPR module that switches cell-cell quorum sensing communication from one autoinducer to another—creating an electronically controlled ‘bilingual’ cell. Then, these disparate redox-guided devices are wirelessly connected, enabling real-time communication and user-based control. We suggest these methodologies will help us to better understand and develop sophisticated control for biology.

59 BASIC BIOLOGICAL SCIENCES↗

Data-driven optimized control of the COVID-19 epidemics

Optimizing the impact on the economy of control strategies aiming at containing the spread of COVID-19 is a critical challenge. We use daily new case counts of COVID-19 patients reported by local health administrations from different Metropolitan Statistical Areas (MSAs) within the US to parametrize a model that well describes the propagation of the disease in each area. We then introduce a time-varying control input that represents the level of social distancing imposed on the population of a given area and solve an optimal control problem with the goal of minimizing the impact of social distancing on the economy in the presence of relevant constraints, such as a desired level of suppression for the epidemics at a terminal time. We find that with the exception of the initial time and of the final time, the optimal control input is well approximated by a constant, specific to each area, which contrasts with the implemented system of reopening ‘in phases’. For all the areas considered, this optimal level corresponds to stricter social distancing than the level estimated from data. Proper selection of the time period for application of the control action optimally is important: depending on the particular MSA this period should be either short or long or intermediate. We also consider the case that the transmissibility increases in time (due e.g. to increasingly colder weather), for which we find that the optimal control solution yields progressively stricter measures of social distancing. We finally compute the optimal control solution for a model modified to incorporate the effects of vaccinations on the population and we see that depending on a number of factors, social distancing measures could be optimally reduced during the period over which vaccines are administered to the population.

60 APPLIED LIFE SCIENCES↗