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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Sodium Void Worth and Control Rod Worth Measurements in ZPPR 15

Sodium void worth and control rod worth were measured in Phases A, B, C and D of the ZPPR15 experimental program. Sodium voiding was simulated by replacing stainless steel cans containing sodium by empty stainless steel cans of the same sizes. The control rod worth measurements were measurements of simulated control rods (CRs) and simulated empty control rod positions (CRPs). A CRP consisted of a 2 x 2 array of drawers filled with sodium plates. A CR consisted of a 2 x 2 array of drawers containing alternating columns of boron carbide plates and sodium plates in the front 18 inches and just sodium plates in the back 18 inches. The ZPPR staff published the measured sodium void worths and control rod worths and the statistical uncertainties in the measured values. In reality, the published uncertainty for each of these measurements is only one component of the total uncertainty. There are additional contributions from uncertainties related to measurement technique, plate compositions and reproducibility. However, the dominant uncertainty for the sodium void worth and control rod worth measurements is the uncertainty in βeff which is required to convert from the natural measurement units, cents, to the calculation units, pcm or Δ/k 1 k 2 . A full uncertainty analysis was performed for the sodium void worth and control rod worth measurements. The significant uncertainties were quantified, and a total uncertainty was derived for each sodium void worth or control rod worth measurement. The ZPPR-15 experimental records were used to create detailed as-built Monte Carlo models of the sodium void worth and control rod worth configurations. These models were used to compute the sodium void worths and control rod worths. (C/E – 1) and the related uncertainty in (C/E – 1) were derived for the measured worths.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Static actuator-sharing algorithm for concurrent control of multiple plasma properties

Simultaneous regulation of multiple properties in next-generation tokamaks like ITER and fusion pilot plant may require the integration of different plasma control algorithms. Such integration requires the conversion of individual controller commands into physical actuator requests while accounting for the coupling between different plasma properties. This work proposes a tokamak and scenario-agnostic actuator-sharing algorithm (ASA) to perform the above-mentioned command-request conversion and, hence, integrate multiple plasma controllers. The proposed algorithm implicitly solves a quadratic programming (QP) problem formulated to account for the saturation limits and the relation between the controller commands and physical actuator requests. Since the constraints arising in the QP program are linear, the proposed ASA is highly computationally efficient and can be implemented in the tokamak plasma control system in real time. Furthermore, the proposed algorithm is designed to handle real-time changes in the control objectives and actuators’ availability. Nonlinear simulations carried out using the Control Oriented Transport SIMulator illustrate the effectiveness of the proposed algorithm in achieving multiple control objectives simultaneously.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Self-consistent equilibrium and transport simulations for NSTX-U plasmas enhanced via machine learning surrogate models

The Control-Oriented Transport SIMulator (COTSIM) is an advanced equilibrium and transport code designed for simulating tokamak discharges at computational speeds suitable for control applications. COTSIM’s modular framework enables users to select models that balance accuracy with speed according to specific needs, allowing the code to operate from fast to faster-than-real-time performance levels. This work presents recent enhancements to COTSIM’s predictive accuracy for NSTX-U scenarios, achieved by integrating neural-network-based surrogate models and self-consistent equilibrium calculations. To improve source deposition predictions, a surrogate model for NUBEAM has been incorporated. Additionally, a surrogate model for the Multi-Mode Module (MMM) now supports predictions of anomalous thermal, momentum, and particle diffusivities—key factors for modeling the evolution of temperature and rotation. Each surrogate model was specifically trained for the NSTX-U operational regime to enhance COTSIM’s accuracy while maintaining computational efficiency. Moreover, COTSIM now couples fixed-boundary equilibrium solvers with its transport solvers, enabling self-consistent predictions of plasma profiles and equilibrium evolution over the discharge. Simulation results demonstrate strong agreement between COTSIM and TRANSP predictions for NSTX-U discharges. These substantial advancements expand COTSIM’s utility in model-based control applications for NSTX-U. Potential applications include simultaneous optimization of equilibrium and transport scenarios, integration into digital twins, real-time profile estimation (e.g., temperature and rotation) from limited or noisy measurements, and advanced feedback-based scenario control.

Equilibrium and transport modeling↗
DOE OSTI2025

Benefits of Dual Fuel Heat Pump Grid-responsive Control: A Model-based Control Optimization Approach Using Building and Equipment Co-simulation

Conventional dual fuel heat pumps lack the intelligent control mechanisms to efficiently manage the switch between heat pump and furnace, leading to sub-optimal energy usage and, in some cases, increased operating costs. To resolve this gap, this study applies optimized control on hybrid heat pumps. With a focus on equipment control strategies, we compare the performances of five spacing heating equipment, including a conventional heat pump (HP), a conventional furnace, a dual fuel heat pump (DFHP) with conventional control, a dual fuel heat pump with smart control, and a novel seamlessly fuel flexible heat pump (SFFHP). While DFHP runs on either gas or electricity at any given moment, SFFHP concurrently consumes gas and electricity by continuously optimizing the proportion of each. In this research, a co-simulation framework is developed by integrating a building envelope model with a physics-based heat pump simulation model to analyze the benefits of grid-responsive controls of DFHP and SFFHP. The model-based optimal controls adjust the operation of the heat pump and gas furnace based on utility price signals and marginal grid emission to minimize utility cost and CO 2 emissions for multiple climate zones, different utility tariffs, and marginal grid emission scenarios. Case studies in Chicago and Los Angeles demonstrate that SFFHP and DFHP, with model-based optimal control, can deliver significant reductions in peak demand, utility cost, and CO 2 emission. In Chicago, SFFHP and smart controlled DFHP yield up to 64.7% and 61.7% utility cost reduction and up to 15.7% and 8.5% CO 2 emission reduction compared to the gas furnace. In Los Angeles, SFFHP and smart controlled DFHP achieve up to 43.6% and 40.1% utility cost reduction and up to 13.8% and 14.1% CO2 emission reduction compared to conventional heat pumps. In conclusion, by leveraging the fuel flexibility nature of dual fuel heat pumps, the model-based control optimization approach makes dual fuel heat pump an attractive option for demand response programs.

Control↗
DOE OSTI2022

Simulating the non-monotonic strain response of nanoporous multiferroic composites under electric field control

In this work, we simulate and analyze the mechanical response of a class of multiferroic materials consisting of a templated porous nanostructure made out of cobalt ferrite (CFO) partially filled by atomic layer deposition (ALD) with a ferroelectric phase of lead zirconate titanate (PZT). The strain in the device is measured when an electric field is applied for varying ALD thicknesses, displaying a non-monotonic dependence with a maximum strain achieved for a coating thickness of 3 nm. To understand this behavior, we apply finite element modeling to the smallest repeatable unit of the nanoporous template and simulate the mechanical response as a function of PZT coating thickness. We find that this non-monotonic response is caused by the interplay between two driving forces opposing one another. First, increased porosity works toward increasing the strain due to a reduced system stiffness. Second, decreased porosity involves a larger mass fraction of PZT, which drives the electro-mechanical response of the structure, thus leading to a larger strain. The balance between these two driving forces is controlled by the shear coupling at the CFO/PZT interface and the effective PZT cross section along the direction of the applied electric field. Here, our numerical results show that considering a nonlinear piezoelectric response for PZT leads to an improved agreement with the experimental data, consistent with ex situ poling of the nanostructure prior to magnetic measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Thermal Reservoir Networks for Modularly Expandable Thermal Microgrids

The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among which the TEN emerged as the most promising solution. The selected TEN design integrates geothermal borefields, heat recovery heat pumps, photovoltaic (PV) arrays, and battery storage. Compared to the baseline system – gas heating combined with air-source chillers – the proposed TEN reduces annual imported energy by 74% and peak electricity demand by 45%, achieves a levelized cost of energy of $\$0.210$/kWh, and substantially enhances resilience. Life-cycle costs increase by approximately 6%, and initial investment costs are about 2.5 times higher than the baseline. However, if central plant infrastructure, district loops, and utility-scale PV and battery systems are privately funded and operated, the initial investment would fall below the baseline system cost. Critical to achieving these significant performance improvements were detailed nonlinear dynamic simulations coupling geothermal heat transfer, energy system operation, and realistic feedback control logic. These simulations identified essential design modifications and control strategy refinements that substantially reduced energy use, peak demand, and compressor shortcycling, thereby improving durability and reliability—issues that would have been significantly more expensive to resolve during operation. Additionally, the verification step highlighted sensitivities to key design parameters that could reduce initial investment by approximately $\$2$ million and reduce annual life-cycle costs more than $\$300,000$. We recommend adopting the PBD methodology for future feasibility studies and TEN pilot projects to gain valuable operational experience. Furthermore, we recommend that DoD invest in transferring and scaling the PBD methodology to other installations. This entails developing standardized computational frameworks and component libraries as well as training industry in conducting PBD. Such investments would enable rapid, robust, reliable, and cost-effective retrofits, supporting DoD’s ambitious energy system modernization goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Modelica-json: Transforming energy models to digitize the control delivery process

Building simulation models are typically not used to generate the documentation required for bidding and project delivery of commercial building systems, or for their semantic modeling and commissioning. This paper presents a software tool that aids in digitizing the control delivery process, spanning simulation during design to implementation and formal verification during commissioning. The tool can generate from Modelica models digital documentation of control sequences. This digital documentation, along with other project drawings and specifications can be used for project bidding. It can also be used for implementation of control sequences through machineto-machine translation to commercial legacy control products, for which we are currently developing the proposed ASHRAE Standard 231P based on the presented work. Moreover, as-installed control sequences can be formally verified against the design specification, and a semantic model in Brick can be exported to aid in configuration of building analytics and fault detection. The paper presents what we believe is the first translation of a Modelica-implemented control sequence to a native implementation on a commercial control platform, using the webCTRL product line from Automated Logic. The paper also shows how a webCTRL implementation can be formally verified against its Modelica specification. These use cases have all been demonstrated with a prototype implementation that is now being further developed.

Wetter, Michael↗
DOE OSTI2026

Flying focus with arbitrary directionality for spatiotemporal control of laser intensity

Flying focus techniques produce laser pulses whose focal points travel at arbitrary, controllable velocities. While this flexibility can enhance a broad range of laser-based applications, existing techniques constrain the motion of the focal point to the propagation direction of the pulse. Here, we introduce a flying focus configuration that decouples the motion of the focus from the propagation direction. Here, a chirped laser pulse focused and diffracted by a diffractive lens and grating creates a focal point that can move both along and transverse to the propagation direction. The focal length of the lens, grating period, and chirp can be tuned to control the direction and velocity of the focus. Simulations demonstrate this control for a holographic configuration suited to high-power pulses, in which two off-axis pump beams with different focal lengths encode the equivalent phase of a chromatic lens and grating in a gas or plasma. For low-power pulses, conventional solid-state or adaptive optics can be used instead. Multi-dimensional control over the focal trajectory enables new configurations for applications, including laser wakefield acceleration of ions, nonlinear Thomson scattering, and surface-plasmon emission of THz radiation.

Classical optics↗
DOE OSTI2023

OC6 project Phase III: validation of the aerodynamic loading on a wind turbine rotor undergoing large motion caused by a floating support structure

Abstract. This paper provides a summary of the work done within Phase III of the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) project, under the International Energy Agency Wind Technology Collaboration Programme Task 30. This phase focused on validating the aerodynamic loading on a wind turbine rotor undergoing large motion caused by a floating support structure. Numerical models of the Technical University of Denmark 10 MW reference wind turbine were validated using measurement data from a 1:75 scale test performed during the UNsteady Aerodynamics for FLOating Wind (UNAFLOW) project and a follow-on experimental campaign, both performed at the Politecnico di Milano wind tunnel. Validation of the models was performed by comparing the loads for steady (fixed platform) and unsteady (harmonic motion of the platform) wind conditions. For the unsteady wind conditions, the platform was forced to oscillate in the surge and pitch directions under several frequencies and amplitudes. These oscillations result in a wind variation that impacts the rotor loads (e.g., thrust and torque). For the conditions studied in these tests, the system aerodynamic response was almost steady. Only a small hysteresis in airfoil performance undergoing angle of attack variations in attached flow was observed. During the experiments, the rotor speed and blade pitch angle were held constant. However, in real wind turbine operating conditions, the surge and pitch variations would result in rotor speed variations and/or blade pitch actuations, depending on the wind turbine controller region that the system is operating. Additional simulations with these control parameters were conducted to verify the fidelity of different models. Participant results showed, in general, a good agreement with the experimental measurements and the need to account for dynamic inflow when there are changes in the flow conditions due to the rotor speed variations or blade pitch actuations in response to surge and pitch motion. Numerical models not accounting for dynamic inflow effects predicted rotor loads that were 9 % lower in amplitude during rotor speed variations and 18 % higher in amplitude during blade pitch actuations.

17 WIND ENERGY↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2023

Creating a Simulation Platform for Research and Development of Advanced Control Methods

Advanced nuclear reactors are essential to meet the changing energy requirements throughout both the United States and the rest of world. In addition to other features, they are designed to enable deployment in remote locations and operate in a fully (or near-fully) autonomous manner, which will require a new control paradigm. To realize autonomously operating reactors, the U.S. Department of Energy’s Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program conducts research and development into the enabling technologies and methods needed, including digital twins, machine learning, and risk modeling, in addition to various types of control methods. These technologies and methods are the key foundations needed to achieve fully autonomous systems. To develop and evaluate the technologies and methods necessary for achieving autonomous operations, it is critical to identify a software tool capable of integrating all the required elements. In surveying the available solutions, no software platforms were identified that could accomplish what was needed without introducing drawbacks. This challenge was the motivation for the current effort: to develop a software platform that can seamlessly integrate autonomouscontrol-enabling technologies and methods, allowing for accelerated research and development and transfer of ideas. The resulting platform, known as the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND), is Python-based, and leverages open-source tools to provide flexibility and facilitate building upon prior research. It is designed to enable advanced reactor developers to deploy and test advanced control technologies and methods coupled with their own models, solutions, and hardware. Given the substantial undertaking of developing such a platform, the current effort focused on laying down scalable, flexible software foundations and infrastructure, then demonstrating the platform via a use case. These foundations included developing generic modules, which contain the base variable and system blocks (the information and functional building blocks, respectively, that can be used to design a simulation) and the data handling and storage blocks needed to exchange information between the various blocks; as well as enablingtechnology-specific modules. This platform was evaluated via a use case, which was to simulate and control a process for the Microreactor Automated Control System (MACS) test bed. While MACS is not currently directly coupled to any specific microreactor physics, it was initially developed in concert with the Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and so the MARVEL physics are used here. As part of this use case, several enabling-technology-specific blocks within COMMAND were integrated, including a proportional integral derivative (PID) control block, a Reactor Excursion and Leak Analysis Program (RELAP5-3D) block, and an anomaly detection block. The COMMAND software platform was successfully demonstrated to achieve the scalability and flexibility objectives of this effort and will be leveraged by the program’s research efforts to advance state of the art control methodologies towards autonomous operations of advanced reactors. As new use cases are created and implemented, it is anticipated that COMMAND will continue to grow and evolve to meet new requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Autonomous Controls For Reactor Technologies (acorn)

ACORN (Autonomous Controls fOr Reactor techNologies) software utilizes data, obtained from an experimental test bed and/or simulation, to implement a control command for microreactor operation. Command examples include a change to the temperature profile, power profiles, heat fluxes, etc. The control command recommended by the code is derived based on future predicted states of a microreactor, allowing proactive optimal and autonomous microreactor operation. The software is written in Python languages. The current software supports autonomous temperature controls of heat pipe simulator and autonomous heat flux controls of a 37 heat pipe non-nuclear testbed simulator (or its surrogate models).

Lin, Linyu [Idaho National Laboratory (INL), Idaho↗
DOE OSTI2023

Fast model-based scenario optimization in NSTX-U enabled by analytic gradient computation

Model-based optimization offers a systematic approach to advanced scenario planning. In this case, the feedforward-control inputs (actuator trajectories) that are needed to attain and sustain a desired scenario are obtained by solving a nonlinear constrained optimization problem. This class of problems generally minimize a cost function that measures the difference between desired and actual plasma states. Several numerical optimization algorithms, such as sequential quadratic programming, require repeated calculation of the cost function gradients with respect to the input trajectories. Calculating these gradients numerically can be computationally intensive, increasing the time needed to solve the feedforward-control optimization problem. Here, this work introduces a method to analytically calculate these cost function gradients from the current profile evolution model. This can significantly reduce the computational time and allow for fast feedforward-control optimization, which would eventually enable optimal scenario planning between discharges. The performance of the feedforward optimizer with analytical gradients is compared to a traditional optimization algorithm based on numerical gradients for different NSTX-U scenarios. The plasma dynamics in the optimization algorithm are simulated using the Control Oriented Transport SIMulator (COTSIM). Results of the work show that analytical gradients consistently reduce the computation time while achieving trajectories that are comparable to those obtained by traditional optimization algorithms based on numerical gradients.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

A Photovoltaic MPPT Charge Controller Real-Time Testbed for Cybersecurity Applications

The increasing deployment of distributed energy resources (DER) over the last decade is a great ally to combat climate change and strengthen the grid during increasingly common extreme weather events. However, DER systems, combined with the ongoing transition to a digital power grid, also pose substantial cybersecurity threats. One of the most common communication protocols used in DER integration is the Distributed Network Protocol 3 (DNP3), which is known to have many security vulnerabilities. Thus, it is essential to investigate cyberattack behaviors and mitigation on power systems using DNP3. In this paper, we designed and implemented a cybersecurity testbed for a simulated photovoltaic (PV) maximum power point tracking (MPPT) charge controller. Our testbed uses an MPPT charge controller simulated on a Typhoon HIL602+ real-time simulator with a real DNP3 communication connection over TCP/IP, allowing for safe and efficient monitoring and manipulation of data traffic between the simulated hardware and supervisory control and data acquisition (SCADA) systems.

14 SOLAR ENERGY↗
DOE OSTI2026

Neural-Network-Enhanced COTSIM: Advancing Predictive Capabilities for Fast DIII-D Simulations

Sustaining fusion reactions in tokamaks requires heating plasma to thermonuclear temperatures while maintaining confinement and stability. Neutral beam injection (NBI) provides heating, current drive, torque, and fueling, while electron cyclotron (EC) waves are widely used for heating and current drive; together, these actuators shape the plasma current, temperature, and density profiles. The control-oriented tokamak simulator (COTSIM), a predictive, control-oriented code, has been enhanced with neural-network surrogates for transport and sources. Turbulent transport is predicted by MMMnet—a neural-network version of the updated multimode model (MMM 9.0.10)—with significantly reduced computation time relative to MMM; neoclassical transport follows the Chang–Hinton model. NUBEAMnet, a surrogate of the Monte Carlo NUBEAM module, predicts beam-driven heating, current, and torque. EC heating and current drive use a control-oriented, empirically scaled source model; plasma resistivity follows the Spitzer formulation; bootstrap current uses the Sauter model. Equilibrium is computed using both prescribed and fixed-boundary solvers (FBSs), and the pedestal structure is modeled with an empirical pedestal model. For a representative DIII-D discharge, COTSIM predicts electron and ion temperature and safety-factor profiles in close agreement with TRANSP predictive and interpretive simulations while extending predictions through the pedestal region to the plasma edge (versus 80% of the minor radius in TRANSP). Furthermore, the equivalent COTSIM simulation runs in under 3 min compared to about 2 h for TRANSP, enabling rapid scenario planning, optimization of tokamak operation, and between-pulse control design.

Control-oriented tokamak simulator (COTSIM)↗
DOE OSTI2026

SCALE HTR-PROTEUS Benchmark Model

This dataset contains input and result files of computational simulations of HTR-PROTEUS benchmark with the latest version of SCALE code system. The simulations cover criticality control rod worth calculations as well as sensitivity analysis and uncertainty quantification. Users wanting to reproduce results from this dataset are required to obtain a license to the SCALE code system for which details on the distribution can be found here: https://www.ornl.gov/scale/releases

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Adaptive PID Gain Scheduling Control for Hydropower Turbine Using Neural CDE and Stochastic Distribution Shaping

This paper introduces a gain-scheduling PID controller design strategy for hydroturbine frequency control mode. This scheme first uses real data to learn the nonlinear dynamics of the hydroturbine using neural controlled differential equations and then perturbs the obtained nonlinear system at different equilibrium points, based on which a static output feedback adaptive dynamic programming algorithm is then used to optimize the PID gains for each equilibrium point. Moreover, a continuous-time version of stochastic distribution control is proposed to further fine-tune the optimized PID gains. Finally, the controller is obtained by implementing linear interpolation between the optimized PID control gains. The simulation results show that the proposed gain-scheduling PID controller can control a larger range of operation points compared with the given fixed PID controller and the baseline method. Compared with the given fixed PID controller, the proposed gain-scheduling PID controller can regulate hydroturbine frequency against disturbances induced by power-load variation with over 50% less overshoot for some operation points.

13 HYDRO ENERGY↗
DOE OSTI2024

Positive-Sequence Modeling of Droop-Controlled Grid-Forming Inverters for Transient Stability Simulation of Transmission Systems

Here, this paper describes a positive-sequence model to represent two widely reported droop-controlled grid-forming inverters for bulk power systems simulation study. Methods of how to develop the equivalent voltage source behind impedance to represent inverters with and without inner control loops, modeling of P-f and Q-V droop controls, active and reactive power limiting modeling, and modeling of fault current limiting controls are described in detail. The model is implemented in commercially available positive-sequence simulation tools and compared with detailed electromagnetic transient models in both a single-grid-forming-inverter infinite-bus system and a modified IEEE 39-bus system. Finally, the model is tested on the full US Western Electricity Coordinating Council (WECC) system. Study results show that the model has a good level of accuracy compared to the detailed EMT models, and at the same time also achieves a high computational efficiency, which is suitable for the bulk power system simulation study.

42 ENGINEERING↗