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At least 181 records · Page 10

Comparison of wind farm control strategies under realistic offshore wind conditions: turbine quantities of interest

Abstract. Wind farm flow control is a strategy to increase the efficiency and therefore lower the levelized cost of energy of a wind farm. This is done using turbine settings such as the yaw angle, blade pitch angles, or generator torque to manipulate the flow behind the turbine, affecting downstream turbines in the farm. Two inherently different wind farm flow control methods have been identified in the literature: wake steering and wake mixing. This paper focuses on comparing the turbine quantities of interest between these methods for a simple two-turbine wind farm setup, while a companion article (Brown et al., 2025) focuses on the wake quantities of interest for a single wind turbine setup. Both papers use the same set of wind farm simulations based on high-fidelity large-eddy simulations (LESs) coupled with OpenFAST turbine models. First, precursor simulations are executed in order to match wind conditions measured with lidars in an offshore wind farm off the east coast of the USA. These measurements show general wind conditions that exhibit substantially higher vertical wind shear and veer than any of the LES studies performed with wind farm flow control strategies currently available in the literature. The precursors are used to evaluate the effectiveness of the control methods. In the LES, the wind veer leads to highly skewed wakes, which have considerable influence on the power uplift of wind farm flow control strategies. In addition to a baseline controller, four different control strategies, each of which uses either pitch or yaw control, are performed on the upstream turbine of a simple two-turbine wind farm. Assuming that the wind direction is known and constant over time, the simulations show that wake steering is generally the superior wind farm flow control strategy, considering both wind farm power production and turbine damage equivalent loads when substantial wind veer is present. This result is consistent over different wind speeds and wind directions. On the other hand, for similar wind conditions with lower veer, wake mixing was found to yield the highest power production, although at the expense of generally higher loads. This leads us to conclude that the effect of wind veer, which has so far not usually been considered, can not be neglected when determining the optimal wind farm flow control strategy.

17 WIND ENERGY↗

Equivalent-Circuit Models for Grid-Forming Inverters under Unbalanced Steady-State Operating Conditions: Preprint

Positive- and negative-sequence equivalent-circuit models are put forth to capture the operation of grid-forming (GFM) inverters in unbalanced steady-state operating conditions acknowledging the impact of current limiting. The particular control architecture examined adopts droop control (for primary control), nested inner-current and outer-voltage control (in the stationary reference frame), and it is adaptable to two different types of current limiting (current-reference saturation and virtual-impedance limiting). We anticipate the proposed models to be of interest in modeling, analysis, and simulation of GFM inverters in unbalanced settings that may arise, e.g., in the face of faults. Validation of the equivalent-circuit models is pursued via comparison with full-order electromagnetic-transient (EMT) simulations for representative balanced and unbalanced faults.

equivalent-circuit models↗

Positive-Sequence Phasor Modeling of Droop-Controlled, Grid-Forming Inverters with Fault Current Limiting Function

Traditional positive-sequence phasor models of droop-controlled, grid-forming inverters do not have the fault current limiting function. During a short-circuit fault the model generates unrealistic high fault current making the simulation results less practical. This paper develops a fault current limiting function for the positive-sequence phasor model of droop-controlled, grid-forming inverters, which can effectively limit the inverter output current at the predefined maximum during faults. A user-written model has been developed for the commercially-available software Siemens/PTI PSS/E. Fault studies on a modified IEEE 39-bus system with all grid-forming inverters verify the effectiveness of the developed fault current limiting function. The proposed model can be used to evaluate how the limited fault currents of droop-controlled, grid-forming inverters impact the bulk power system transient stability under fault conditions.

Du, Wei↗

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↗

Chalcogenide phase-change material advances programmable terahertz metamaterials: a non-volatile perspective for reconfigurable intelligent surfaces

Terahertz (THz) waves have gained considerable attention in the rising 6G communication due to their large bandwidth. However, the cost and power consumption become the major constraints for the commercialization of 6G THz systems as the frequency increases. Reconfigurable intelligent surface (RIS) comprising active metasurfaces and digital controllers has been proposed for beamforming in the 6G multiple-input-multiple-output systems, showing good potential to suppress the system size, weight, and power consumption (SWaP). Currently, their controlling diodes can hardly work up to THz frequencies. Therefore, several active stimuli have been investigated as alternatives. Among them, chalcogenide phase-change material Ge 2 Sb 2 Te 5 (GST) addresses large modulation depth, picosecond switching speed, and non-volatile properties. Notably, the non-volatile GST may enable RIS systems with memory and low control power. This work briefly reviews the advances of GST-tuned THz metamaterials (MTMs), discusses the current obstacles to overcome, and gives a perspective of GST applications in the rising 6G communications.

6G↗

A Reinforcement Learning Approach to Augment Conventional PID Control in Nuclear Power Plant Transient Operation

The ability of nuclear reactors to operate their power conversion cycles more flexibly will enhance their value to energy grids with variable pricing. Current nuclear control systems are typically classical controllers that are often based on proportional-integral-derivative (PID) control. This paper presents a method of augmenting the existing PID control for difficult transient operations in nuclear power plants using a reinforcement learning–derived feedforward signal applied in real time. The agents, which are trained on a test thermal load-following problem, are designed to improve steam generator outlet temperature control for a range of fast load-following scenarios covering ramp rates from 9%/min to 15%/min. Several reinforcement learning algorithms were initially investigated for the training of the feedforward agents with deep Q-learning (DQN) and proximal policy optimization (PPO) networks, which were found to be the most promising. The DQN controllers utilize discrete actions, giving them a better disturbance rejection at steady state but inconsistent response to initial temperature deviations. In contrast, PPO-trained agents, which take continuous actions except for a dead zone around zero, were shown to have the best combination of high disturbance rejection at steady state and good tracking of the desired temperature value. The ability of the PPO agent was also examined, with the average time of decision making found to be on the order of 1 ms. The fault properties of the controller under the loss of the reinforcement learning agent feedforward signal were also examined. The controller showed strong performance in situations of “no-signal” faults. but was less good at handling “stuck-at” faults, where the feedforward signal remains at a set value. In both cases, however, the PID was able to successfully maintain stability, eventually returning the system to a steady state. It is hoped that this work will allow for the proposed control architecture to be examined for more difficult control problems such that it may eventually be used to adapt existing nuclear plants for more aggressive load-following on grids of the future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Purification and expression of a novel bacteriocin, JUQZ-1, against Pseudomonas syringae pv. Actinidiae (PSA), secreted by Brevibacillus laterosporus Wq-1, isolated from the rhizosphere soil of healthy kiwifruit

Kiwifruit canker, caused by Pseudomonas syringae pv. actinidiae (PSA), has led to significant losses in the kiwifruit industry each year. Due to the drug resistance feature of PSA, biological control is currently the most promising method. Developing biocontrol bacteria against PSA could help solve the issue of drug resistance generated during the chemical control of PSA to a certain extent. In this research, a Wq-1 strain that demonstrated excellent inhibitory activity against PSA was isolated from the rhizosphere soil of healthy kiwifruit. Based on the morphological characteristics and phylogenetic analysis of the 16S rRNA gene sequence, the isolated strain was identified as Brevibacillus laterosporus Wq-1. Bacteriostatic proteins were isolated from the cell-free culture filtrate of strain Wq-1 and were found to have a molecular weight of approximately 12 kDa, as determined by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Liquid chromatography–tandem mass spectrometry (LC–MS/MS) detection revealed that there were several peptides in the target band that were consistent with protein 01021 in the genome. The gene of the 01021 protein was cloned into the plasmid pPICZa, and the recombinant bacteriocin was successfully expressed using the Pichia pastoris X33 expression system. The recombinant protein 01021 effectively inhibited the growth of PSA. This is the first report of the protein’s antimicrobial activity, distinguishing it from previously identified bacteriocins. Therefore, we named this bacteriocin JUQZ-1. In addition, our results showed that the protein JUQZ-1 not only exhibited a broad bacteriostatic spectrum but also high thermal and pH stability suitable for harsh environmental conditions., JUQZ-1, a protein with antimicrobial properties and strong environmental tolerance, may serve as a promising alternative to antibiotics.

Shuai, Yang↗

Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e

We introduce a novel Proximal Policy Optimization (PPO) algorithm aimed at addressing the challenge of maintaining a uniform proton beam intensity delivery in the Muon to Electron Conversion Experiment (Mu2e) at Fermi National Accelerator Laboratory (Fermilab). Our primary objective is to regulate the spill process to ensure a consistent intensity profile, with the ultimate goal of creating an automated controller capable of providing real-time feedback and calibration of the Spill Regulation System (SRS) parameters on a millisecond timescale. We treat the Mu2e accelerator system as a Markov Decision Process suitable for Reinforcement Learning (RL), utilizing PPO to reduce bias and enhance training stability. A key innovation in our approach is the integration of a neuralized Proportional-Integral-Derivative (PID) controller into the policy function, resulting in a significant improvement in the Spill Duty Factor (SDF) by 13.6%, surpassing the performance of the current PID controller baseline by an additional 1.6%. This paper presents the preliminary offline results based on a differentiable simulator of the Mu2e accelerator. It paves the groundwork for real-time implementations and applications, representing a crucial step towards automated proton beam intensity control for the Mu2e experiment.

43 PARTICLE ACCELERATORS↗

CRADA Final Report: Open Microgrid Platform

Current microgrid control technology is mostly proprietary, expensive, and inflexible. An open-source, vendor-neutral, publish-subscribe controller will significantly lower the barrier to entry for new technologies and market entrants: inverter, battery, and load control manufacturers; cloud and services providers; and energy aggregators. An OpenFMB controller can significantly reduce the acquisition, integration, and ongoing operating and maintenance costs and increase revenue opportunities for energy producers and consumers. It allows distributed energy resource (DER) owners to replace individual DER components as richer-function, lower-cost devices become available or to incorporate new forecast and optimization algorithms as they are developed. A standard, secure, full-function DER field controller will also provide a low-cost means for grid operators to effectively manage the variability and uncertainty of solar photovoltaics (PV). Under the terms of this CRADA, ORNL has worked with Open Energy Solutions (OES) to advance the transition of ORNL’s existing open-source microgrid controller into a platform geared toward mainstream implementation. Using a more prevalent and memory-safe programming language, Rust, OES has converted ORNL’s current generation on-grid optimization into an application more suitable for industry use. The results of the ported optimization were analyzed by inputting the same arguments in both the current-generation and next-generation optimizers and verifying that the results were equivalent.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Low- n stability and plasma response to RMP in various STEP scenarios

The low-n (n is the toroidal mode number) magnetohydrodynamic (MHD) stability and plasma response are numerically investigated for various scenarios designed for STEP, that are relevant for the H-mode pedestal analysis. Control of the edge-localized modes (ELMs) with externally applied resonant magnetic perturbations (RMPs) is considered. Optimization of the ELM control coil current configuration, based on the computed plasma MHD response and well-established figures of merit validated on present-day experiments, finds reasonable robustness of a fixed coil phasing (for a given n-number) to control ELMs in all five STEP plasmas considered. Based on certain semi-empirical criteria, the required coil current to achieve ELM suppression is estimated to be about 10–20 kAt with the n = 1 or 2 RMP configuration and about 100–200 kAt for the n = 4 RMP. Systematic linear stability calculations are used to map out stability windows for the low-n kink-peeling modes, in terms of the ideal-wall location and variation of the edge safety factor q 95 with respect to the target design. The kink-peeling stability boundary is found to be generally sensitive to the q 95 variation, which has implications for achieving the quiescent H-mode regime in STEP. Full toroidal quasilinear initial-value simulations for these STEP plasmas find that generation of the edge-harmonic oscillations (EHOs) depends sensitively on the plasma scenario, the initial linear stability of the kink-peeling modes, the initial plasma toroidal flow and q 95 . In general, it is easier (more robust) to access the EHO-regime for two of the cases considered with smaller plasma volume and higher on-axis safety factor. Finally, quasilinear simulations find robust density pumpout due to applied RMPs in these STEP plasmas, but the effect on the plasma toroidal flow varies among different cases.

EHO↗

A Universal Controller for Grid-Forming Inverters in Microgrid during Islanding for Low Transient Current

This paper presents a universal controller to reduce the transient current during islanding of microgrid. In the proposed universal controller, two sets of semi-parallel paths are formed, where one set produces voltage and phase-angle references for the grid-following (GFL) mode, and the other set produces the voltage and phase-angle references for the grid-forming (GFM) mode of operation for the inverters. Herein, the controller enables an inverter to universally operate in GFL and GFM mode, whereas, only one set of voltage and phase-angle reference is engaged for PWM signal generation. When the microgrid is disconnected from the grid, the universal controller switches the voltage and phase-angle references from GFL to GFM mode. The proposed controller ensures lower transient current by keeping the two sets of semi-parallel paths synchronized throughout the operation of the inverter and enabling seamless transition between the modes. The proposed controller is verified through hardware experiments under different scenarios in a laboratory scale microgrid for inverters transitioning from GFL to GFM mode after islanding.

Sadeque, Fahmid↗

Accelerating Nuclear Facility Mission Completion Through an Improved Chemical Hazard Control Strategy - 20460

Code of Federal Regulation (CFR) 10 CFR 830, Nuclear Safety Management [1], explicitly identifies hazardous materials in addition to radioactive materials when establishing the scope of materials that must be evaluated in Hazard Category (HC) 1, 2, and 3 nuclear facilities. This inclusion has led to a near decade-long progression of more and more rigorous application of chemical hazard controls in these facilities. The progressive addition of more rigorous chemical hazard controls has occurred across the Department of Energy (DOE) Complex, having been driven by contractors and regulators alike. However, chemical hazards in other DOE facilities have been, and continue to be, controlled using traditional industrial safety centered strategies. Thus, identical chemical hazards are controlled using dramatically different approaches based solely on the facility type. Not only are the controls different, the analysis and derivation rigor and requirements are also significantly different. In particular, chemical control derivation and application in non-nuclear facilities are much less onerous than the comprehensive hazard analysis process used in nuclear facilities, even in circumstances in which chemicals are not initiators to, or do not exacerbate a nuclear event. While the derivation and control approaches used in these two types of facilities are disparate, the safety results are similarly effective based on a review of reported chemical events from 2014 through 2018. While both approaches achieve comparable safety outcomes, the approach used in nuclear facilities results in significantly greater preparation costs and implementation costs. Furthermore, the problem with the differing approach is not relegated to the control preparation and implementation burden. The operational impact of potentially unnecessary controls slows mission completion without a corresponding increase in safety, not to mention the dilution of the importance of Technical Safety Requirements. The proposed solution must first include a critical and thorough examination of DOE Complex and top-tier chemical industry chemical hazard control practices, coupled with a similar examination of the driving facility regulatory requirements. Results from the examination can then be used to fuel a bold departure from current chemical control practices in Hazard Category 1, 2, and 3 nuclear facilities. Development of an improved and consistent chemical hazard control process would follow, one that continues to ensure safety while accelerating mission completion and significantly reducing the burden associated with chemical hazard control development and implementation. The improved process must establish a hierarchy where radiological hazards are addressed using safety class and safety significant controls and chemical hazards are addressed using overarching safety management programs (with limited unique exceptions). The improved Hazard Category 1,2, and 3 nuclear facility chemical hazard control strategy, while compliant with 10 CFR 830 [1], would be founded on the requirements in 10 CFR 851, Worker Safety and Health Program [2], and the complementary DOE O 151.1D, Comprehensive Emergency Management System [3]. In this way, the Hazard Category 1, 2, and 3 nuclear facility chemical hazard control strategy would, wherever appropriate, be the same process used at other DOE Complex facilities. Ultimately, the improved process will maintain safety and significantly reduce costs and life cycle risk through faster mission completion. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

MARS-F/K modeling of plasma response and fast ion losses due to RMP in KSTAR

Abstract The toroidal single-fluid magnetohydrodynamic (MHD) code MARS-F (Liu et al 2000 Phys. Plasmas 7 3681) and the MHD-kinetic hybrid code MARS-K (Liu et al 2008 Phys. Plasmas 15 112503) are utilized to study the plasma response to the n = 1 ( n is the toroidal mode number) resonant magnetic perturbation (RMP), applied to suppress the type-I edge localized mode (ELM) in a KSTAR discharge. Both the resistive-rotating and ideal-static plasma models identify strong screening of the resonant radial field harmonics of the applied RMP due to the plasma response, and predict a strong edge-peeling response of the plasma which is consistent with the optimal ELM control coil current configuration adopted in experiment. The RMP-induced radial displacement of the plasma, computed by the resistive-rotating plasma model, agrees reasonably well with that reconstructed from the measured data in the plasma core. Taking into account the drift kinetic response of fast ions, MARS-K hybrid modeling also finds quantitative agreement of the plasma core fluid pressure perturbation with experiment. Based on the MARS-F computed plasma response, a guiding-center orbit-tracing simulation finds about 0.3% of fast ion losses due the n = 1 RMP in the KSTAR ELM control experiment considered. Most losses are associated with counter-current fast ions located near the plasma edge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Distributed Quantum Computing with Photons and Atomic Memories

The promise of universal quantum computing requires scalable single- and inter-qubit control interactions. Currently, three of the leading candidate platforms for quantum computing are based on superconducting circuits, trapped ions, and neutral atom arrays. However, these systems have strong interaction with environmental and control noises that introduce decoherence of qubit states and gate operations. Alternatively, photons are well decoupled from the environment and have advantages of speed and timing for quantum computing. Photonic systems have already demonstrated capability for solving specific intractable problems like Boson sampling, but face challenges for practically scalable universal quantum computing solutions because it is extremely difficult for a single photon to “talk” to another deterministically. Here, a universal distributed quantum computing scheme based on photons and atomic-ensemble-based quantum memories is proposed. Taking the established photonic advantages, two-qubit nonlinear interaction is mediated by converting photonic qubits into quantum memory states and employing Rydberg blockade for the controlled gate operation. Spatial and temporal scalability of this scheme is demonstrated further. Furthermore, these results show photon-atom network hybrid approach can be a potential solution to universal distributed quantum computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Stable compression of a spherical tokamak plasma

In this study, an analysis of toroidal plasma compression by a collapsing flux conserver reveals linearly stable scenarios of operation to high compression ratios. The resistive and ideal MHD stability is calculated in full toroidal geometry using the asymptotic matching method in realistic conditions. A time dependent MHD simulation of the compression is conducted to confirm the conservation principles used to calculate the equilibrium states for the analysis. The near edge current profile, controlled by toroidal field ramping during compression, is shown to be critical to stability due to coupling between poloidal components of the least stable mode. Two cases with slight differences in edge current are examined, one with a stable corridor to high compression and one without.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Evaluating Named Data Networking for Industrial Control System [Slides]

Current proposed work is: See if the inherent security that comes with Named Networking (NDN) can be applied to Industrial Control Systems; and, Every packet is required to be cryptographically signed which makes every single piece of data communicated in the system secure and authenticated.

42 ENGINEERING↗

Hybrid model predictive control techniques for safety factor profile and stored energy regulation while incorporating NBI constraints

Abstract A novel hybrid Model Predictive Control (MPC) algorithm has been designed for simultaneous safety factor ( q ) profile and stored energy ( w ) control while incorporating the pulse-width-modulation constraints associated with the neutral beam injection (NBI) system. Regulation of the q -profile has been extensively shown to be a key factor for improved confinement as well as non-inductive sustainment of the plasma current. Simultaneous control of w is necessary to prevent the triggering of pressure-driven magnetohydrodynamic instabilities as the controller shapes the q profile. Conventional MPC schemes proposed for q -profile control have considered the NBI powers as continuous-time signals, ignoring the discrete-time nature of these actuators and leading in some cases to performance loss. The hybrid MPC scheme in this work has the capability of incorporating the discrete-time actuator dynamics as additional constraints. In nonlinear simulations, the proposed hybrid MPC scheme demonstrates improved q -profile+ w control performance for NSTX-U operating scenarios.

Physics↗

Control of a Three-Phase Grid-Connected Voltage-Sourced Converter Using Long Short-Term Memory Networks

With the rise of inverter-based resources (IBRs) within the power system, the control of grid-connected converters (GCCs) has become pertinent due to the fact they interface IBRs to the grid. The conventional method of control for a GCC such as the voltage-sourced converter (VSC) is through a decoupled control loop in the synchronous reference frame. However, this model-based control method is sensitive to parameter changes causing deterioration in controller performance. Data-driven approaches such as machine learning can be utilized to design controllers that are capable of operating GCCs in various system conditions. This work explores a deep learning-based control method for a three-phase grid-connected VSC, specifically utilizing a long short-term memory (LSTM) network for robust control. Simulations of a conventional controlled VSC are conducted using Simulink to collect data for training the LSTM-based controller. The LSTM model is built and trained using the Keras and TensorFlow libraries in Python and tested in Simulink. The performance of the LSTM-based controller is evaluated under different case studies and compared to the conventional method of control. Simulation results demonstrate the effectiveness of this approach by outperforming the conventional controller and maintaining stability under different system parameter changes.

24 POWER TRANSMISSION AND DISTRIBUTION↗