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At least 37 records · Page 2

Autonomous Closed-Loop Experimental Characterization and Dynamic Model Validation of a Scaled Underwater Kite

This paper presents the closed-loop experimental framework and dynamic model validation for a 1/12-scale underwater kite design. The pool-based tow testing framework described herein, which involves a fully actuated, closed-loop controlled kite and flexible tether, significantly expands upon the capabilities of any previously developed open-source framework for experimental underwater kite characterization. Specifically, the framework has allowed for the validation of three closed-loop flight control strategies, along with a critical comparison between dynamic model predictions and experimental results. In this paper, we provide a detailed presentation of the experimental tow system and kite setup, describe the control algorithms implemented and tested, and quantify the level of agreement between our multi-degree-of-freedom kite dynamic model and experimental data. Finally, we also present a sensitivity analysis that helps to identify the most influential parameters to kite performance and further explain the remaining mismatches between the model and data.

42 ENGINEERING↗

Dynamic modelling and control strategy of a temperature-driven metal hydride cooling system for buildings

A temperature-driven coupled metal hydride (MH) based thermal energy storage (TES) system can allow to shave and shift the peak energy demand in buildings. The high energy density and long-term (seasonal) energy storage capability are its major advantages over other energy storage methods. The dynamic nature of the MH operation, however, requires controlled hydrogen transfer between the coupled MHs at a rate needed to meet the building's transient load. While temperature-driven MH systems are studied in the literature, their application in buildings and control are scarcely reported. Here, this paper presents a control-based dynamic modeling of the temperature-driven coupled MH-TES system for building cooling applications. The dynamic model is developed in MATLAB(R) Simulink environment, considering the thermodynamic and kinetic behaviors of the MH systems. Based on a preliminary analysis of a property database of over 337 hydrides, we select around 1600 MH pairs suitable for building cooling applications. Each of these MH pairs is studied for their performance using the dynamic model, and among all, Zr 0.76 Ti 0.24 Ni 1.16 Mn 0.63 V 0.14 Fe 0.18 -Ti 0.85 Zr 0.15 Cr 1.2 Mn 0.8 MH pair showed fast dynamics along with high coefficient of performance (COP) of 0.71. A parametric investigation is performed on this MH pair to understand the effect of operating temperatures. Finally, three proportional-integral (PI) feedback controllers are investigated to regulate the temperature, pressure and mass exchange between the coupled MH pairs. The developed PI controller is sufficiently capable of rejecting the signal noise from the hydrogen flow and internal heat exchange processes with root mean square error of 5.78 W between reference and actual cooling load.

08 HYDROGEN↗

Heat Integration Optimization and Dynamic Modeling Investigation for Advancing the Coal-Direct Chemical Looping Process

The purpose of the project is to address the optimization and startup operation of a modular coal direct chemical looping (CDCL) combustion system integrated with a steam cycle for power generation to reduce the risks involved in further scale-up of the technology. The modular reactor design of the CDCL process provides flexibility in the fabrication of the reactor and in its operating capacity (i.e. turndown ratio) at the cost of a more complex heat exchange network (HEN) design and integration. To address the technology gaps and advance the efficiency and economic feasibility of the CDCL technology, the project will perform a detailed and comprehensive analysis of the integration of a modular CDCL reactor system and a steam cycle system under both static and transient conditions via HEN process performance simulations and system dynamic modeling, respectively. The scope of work consists of 1) Experimental and computational studies of the CDCL combustor reactor 2) Comprehensive static (i.e. steady-state) system HEN design analysis in CDCL 550 MWe commercial unit for power generation and 3) Dynamic modeling of site specific design of 10MWe CDCL large pilot plant. The project team has successfully developed and validated a kinetic model for the oxidation of oxygen carriers in the combustor using the unreacted shrinking core model (UCSM). The model is capable of capturing the oxidation kinetics of fully or partially reduced oxygen carrier particles. A computational fluid dynamics (CFD) model is developed to simulate the hydrodynamics, heat transfer, and chemical reaction occurring in the CDCL combustor. The model is developed in MFIX and ANSYS Fluent. Key aspects of CDCL combustor operation, including heat transfer, oxygen carrier oxidation, and the transport of oxygen carrier particles, are simulated using this CFD model. The HEN for a commercial scale 550 MWe CDCL power plant is simulated and optimized using ASPEN Plus. Practical design considerations are incorporated based on industrial experiences. The performance and cost for the commercial CDCL plant is updated based on these analyses. A dynamic model for the 10 MWe CDCL pilot plant is developed in ProTRAX simulation software. The model is based on the pilot plant design developed in project DE-FE0027654 “10 MWe CDCL Large Pilot Plang – Pre-FEED Study” and the steam cycle data obtained from Dover Light & Power plant. The transient behaviors during pilot plant load variation are simulated using the dynamic model.

01 COAL, LIGNITE, AND PEAT↗

Data-Driven Dynamic Modeling in Power Systems: A Fresh Look on Inverter-Based Resource Modeling

Here, this article introduces ways to identify dynamic system models using measurement data. In power system analysis, a static model represents the time-invariant input-output relationship of a system, while a dynamic model describes the behavior of the system over time. For example, how will a system transit from one steady-state operation point to another?

24 POWER TRANSMISSION AND DISTRIBUTION↗

Dynamic Modeling and Simulation of a Subcritical Coal-Fired Power Plant under Load-Following Conditions

Dynamic models for power plants that capture realistic general process trends and effects of manipulated variables are needed to improve load-following, while minimizing carbon footprint. In this work, a dynamic modeling approach and simulation results for subcritical coal-fired power plant components are presented. These encompass simulation of the dynamics in the fireside, including the effects of fuel, air combustion, and the dynamics of the entire waterside and power generation sections. This model development enables the simulation and analysis of the important short and long-time scale dynamics of components such as heaters, evaporative loop, and power generation units. Furthermore, additional variables in the power generation section are introduced to improve model accuracy, extending the prediction capability of subcritical power plant models and opening new opportunities for research in operator training, optimization, and advanced model-based controller design that are based on these models. The change in process gain for different ramp rates associated with disturbance signals that affect process variables is also explored and a correlation developed. This provides opportunities to study disturbance rejection control implementation and adaptation for scenarios with such variations in ramp rates. The prediction capabilities of selected components are compared to data available in literature, with the obtained root mean squared error ranges that reflect the model performance and quality of predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observability Analysis of a Power System Stochastic Dynamic Model Using a Derivative-Free Approach

Serving as a prerequisite to power system dynamic state estimation, the observability analysis of a power system dynamic model has recently attracted the attention of many power engineers. However, because this model is typically nonlinear and large-scale, the analysis of its observability is a challenge to the traditional derivative-based methods. Indeed, the linear-approximation-based approach may provide unreliable results while the nonlinear-technique-based approach inevitably faces extremely complicated derivations. Furthermore, because power systems are intrinsically stochastic, the traditional deterministic approaches may lead to inaccurate observability analyses. In this work, facing these challenges, we propose a novel polynomial-chaos-based derivative-free observability analysis approach that not only is free of any linear approximations, but also accounts for the stochasticity of the dynamic model while bringing a low implementation complexity. Furthermore, this approach enables us to quantify the degree of observability of a stochastic model, what conventional deterministic methods cannot do. The excellent performance of the proposed method has been demonstrated by performing extensive simulations using a synchronous generator model with IEEE-DC1A exciter and the TGOV1 turbine governor.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies

Abstract Electric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model.

42 ENGINEERING↗

Dynamic modelling of slip in a wind turbine spherical roller main bearing

This paper considers the problem of the dynamic modelling of macro slip in spherical roller bearings. By revisiting the fundamental physics which drive these systems, potential issues in existing models have been identified. Furthermore, in pure rolling conditions it was found that governing differential equations become "stiff", requiring the use of implicit methods of time integration. The problem of individual roller macro slip in a wind turbine main bearing is then investigated using a simplified representation of system dynamics. Model results indicate clear links between slip/friction and the operational strategy of the wind turbine, as well as significantly higher frictional effects in the downwind main bearing row. Due to modelling simplifications, these results should not yet be considered conclusive, with further work required.

17 WIND ENERGY↗

Building Model Calibration: Validation of GridLAB-D Thermal Dynamics Modeling

This report investigates how well GridLAB-D’s house model characterizes the thermal dynamics of buildings given the overpredicted diurnal electric load swing observed in the Distribution System Operation with Transactive (DSO+T) study. This study seeks to validate GridLAB-D’s house model by calibrating it to data from the well-instrumented Pacific Northwest National Laboratory Lab Homes in Richland, WA. The datasets chosen included multiple pre-cooling and pre-heating testing periods where the indoor air temperature was allowed to float over a multi-hour length of time to mimic diurnal behavior. The multi-season calibrations were evaluated by comparing the heating/cooling electric power, indoor air temperature, and the rise/decay time during temperature float periods with Lab Homes data. The default GridLAB-D assumptions for latent load fraction, air heat capacity, mass heat capacity, window-to-wall-ratio, overall envelope conductance (assumed as NORMAL thermal integrity level), and solar heat gain coefficient were compared with the calibrated model to confirm when the default assumptions were adequate and the impact of calibration on the accuracy of modeling the thermal dynamics of homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

What is (quantitative) system dynamics modeling? Defining characteristics and the opportunities they create

A clear definition of system dynamics modeling can provide shared understanding and clarify the impact of the field. We introduce a set of characteristics that define quantitative system dynamics, selected to capture core philosophy, describe theoretical and practical principles, and apply to historical work but be flexible enough to remain relevant as the field progresses. The defining characteristics are: (1) models are based on causal feedback structure, (2) accumulations and delays are foundational, (3) models are equation-based, (4) concept of time is continuous, and (5) analysis focuses on feedback dynamics. We discuss the implications of these principles and use them to identify research opportunities in which the system dynamics field can advance. These research opportunities include causality, disaggregation, data science and AI, and contributing to scientific advancement. Progress in these areas has the potential to improve both the science and practice of system dynamics.

97 MATHEMATICS AND COMPUTING↗

Dynamic Modeling and Analysis for Large-Scale Renewable Energy Integration

Lina He will present dynamic modeling techniques for the integration of large-scale renewable energy systems. The presentation will address the challenges associated with high renewable penetration and provide frameworks for ensuring smooth and reliable grid operations.

Dynamic modeling, large-scale renewable integratio↗

A hierarchical gray-box dynamic modeling methodology for direct-expansion cooling systems to support control stability analysis; Méthodologie de modélisation dynamique hiérarchique de type boîte grise pour les systèmes de refroidissement à détente directe afin de soutenir l'analyse de stabilité de la commande

In this paper, a gray-box dynamic modeling approach for direct-expansion cooling systems is presented. The overall approach incorporates a multi-stage training procedure that consists of 1) identification of component sub-models from quasi-steady-state performance data, 2) system model integration with estimation of refrigerant charge and 3) fine tuning of thermal capacitances of the evaporator and condenser to capture the system dynamic responses. Compared to traditional physics-based models, the proposed modeling approach has advantages including reduced engineering efforts in the model development phase, improved computational efficiency and enhanced prediction accuracy. The modeling method was validated using a 3-ton variable-speed heat pump and proved to be capable of accurately predicting the system transient behaviors over a wide range of operating conditions. The established dynamic model was then applied for control stability analysis, with a specific goal of determining a proper control execution time step. The case study results showed that the stable control execution time step could change significantly, from 3 sec to 19 sec, as the operating conditions and control settings vary, and a proper selection of the execution time step is critical to ensure stable and reliable operations.

42 ENGINEERING↗

Rigid-flexible coupling multi-body dynamics modeling of a semi-submersible floating offshore wind turbine

A 14-degree-of-freedom (14-DOF) flexible multibody dynamics model is developed and verified for a semi-submersible floating offshore wind turbine (FOWT). The model considers the coupled dynamics of the platform, tower, nacelle, blades, and mooring subjected to external wind and wave loads. The platform is simplified as a rigid body connected to the seabed by the mooring system. The tower and blade are modeled as flexible cantilever beams. The energy method is used to derive the governing equations of motion, where the kinetic energy, potential energy, and work done by external wind-wave forces are all deduced in a global coordinate system. The 5-MW baseline semi-submersible FOWT is used to verify the derived model against the results simulated from FAST developed by the US National Renewable Energy Laboratory (NREL) at two scenarios: free decay state and different wind-wave load cases. Results show that the established FOWT model can well reflect the vibration characteristics of FAST model. The application of the model to the control of platform pitch with a tuned mass damper is studied. Furthermore, the simplified model could provide a low-order method for the structural dynamics analysis and advanced vibration control design for the multi-body components of the semi-submersible FOWT in the future.

17 WIND ENERGY↗