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At least 37 records · Page 2

Validation and Verification for INL Modelica-based TEDS models Via Experimental Results

This report provides an overview on the verification and validation (V&V) of the Thermal Energy Distribution System (TEDS) model developed in the Modelica process modeling ecosystem using experimental data. Model development has led to the creation of a dynamic process model of the experimental TEDS facility housed within the Energy Systems Laboratory (ESL) at Idaho National Laboratory (INL). The model was then used during the preconstruction phase of the experimental effort to inform experimental design (e.g., insulation requirements, bypass line placement, expected performance of components) and to test innovative control schemes prior to the initial operation. The TEDS model developed in Modelica includes the primary components of the TEDS experimental unit: a 200kW Chromalox heater; a single-tank packed-bed thermal energy storage system filled with 0.125-inch alumina (Al2O3) beads; an ethylene-glycol-to-Therminol-66 heat exchanger; system piping; five control valves; and all associated temperature, pressure, and volumetric flow sensors. Using the Institute of Electrical and Electronics Engineers (IEEE) V&V methodologies, considered the gold standard in the engineering field, the model was verified using a combination of static analysis, spatial convergence, and regression tests. Then using dynamic time warping (DTW) initial runs to validate and tune the TEDS model versus the experiment were conducted. This tuning method was accomplished using the INL Risk Analysis Virtual ENvironment (RAVEN) software package. Tuning is required to account for physical phenomena that are less understood within the empirical heat transfer correlations. Through the commencement of this work, a systems-level model of TEDS with associated control systems, sensors, piping diameters, and component capabilities has been created. This model was utilized in the pre-experimental phase to inform system design, insulation thicknesses, and potential control schemes to operate the system effectively and safely. Then, initial experimental startup and operational data were used to demonstrate the validation and tuning methodology. This process demonstrates the classical two-step approach of a model informing experimental design followed by the experiment validation and tuning the model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modelica IBPSA Library v1

The Modelica IBPSA library is a free open-source library with basic models that codify best practices for the implementation of models for building and community energy and control systems. The development of the IBPSA library is organized through the IBPSA Project 1 (https://ibpsa.github.io/project1) of the International Building Performance Simulation Association (IBPSA). This library is typically not used directly by end-users. Rather, it is integrated by developers of other Modelica libraries for building and community energy systems, who then distribute it to end-users as part of their respective library.

Wetter, Michael↗

Modelica IBPSA MPC Library v0.1

The Modelica IBPSA MPC Library is a free open-source library with basic models that codify best practices for the implementation of models to be used in Nonlinear Model Predictive Control of building and community energy systems. The development of the Modelica IBPSA MPC Library is organized through the IBPSA Project 1 (https://ibpsa.github.io/project1) of the International Building Performance Simulation Association (IBPSA).

Blum, David↗

Status on the Component Models Developed in the Modelica Framework: High-Temperature Steam Electrolysis Plant & Gas Turbine Power Plant

This report has been prepared as part of an effort to design and build a modeling and simulation (M&S) framework to assess the economic viability of a nuclear-renewable hybrid energy system (N-R HES). In order to facilitate dynamic M&S of such an integrated system, research groups in multiple national laboratories have been developing various subsystems as dynamic physics-based components using the Modelica programming language. In fiscal year (FY) 2015, Idaho National Laboratory (INL) performed a dynamic analysis of two region-specific N-R HES configurations, including the gas-to-liquid (natural gas to Fischer-Tropsch synthetic fuel) and brackish water reverse osmosis desalination plants as industrial processes. In FY 2016, INL has developed two additional subsystems in the Modelica framework: a high-temperature steam electrolysis (HTSE) plant and a gas turbine power plant (GTPP). HTSE has been proposed as a high priority industrial process to be integrated with a light water reactor (LWR) in an N-R HES. This integrated energy system would be capable of dynamically apportioning thermal and electrical energy (1) to provide responsive generation to the power grid and (2) to produce alternative industrial products (i.e., hydrogen and oxygen) without generating any greenhouse gases. A dynamic performance analysis of the LWR/HTSE integration case was carried out to evaluate the technical feasibility (load-following capability) and safety of such a system operating under highly variable conditions requiring flexible output. To support the dynamic analysis, the detailed dynamic model and control design of the HTSE process, which employs solid oxide electrolysis cells, have been developed to predict the process behavior over a large range of operating conditions. As first-generation N-R HES technology will be based on LWRs, which provide thermal energy at a relatively low temperature, complementary temperature-boosting technology was suggested for integration with the HTSE process that requires higher temperature input. Simulation results involving several case studies show that the suggested control scheme could maintain the controlled variables (including the steam utilization factor, cathode stream inlet composition, and temperatures of the process streams at various locations) within desired limits under various plant operating conditions. The results also indicate that the proposed HTSE plant could provide operational flexibility to participate in energy management at the utility scale by dynamically optimizing the use of excess plant capacity within an N-R HES. A natural-gas fired GTPP has been proposed as a secondary energy supply to be included in an N-R HES. This auxiliary generator could be used to cover rapid dynamics in grid demand that cannot be met by the remainder of the N-R HES. To evaluate the operability and controllability of the proposed process during transients between load (demand) levels, the dynamic model and control design were developed. Special attention was given to the design of feedback controllers to regulate the power frequency, and exhaust gas and turbine firing temperatures. Several case studies were performed to investigate the system responses to the major disturbance (power load demand) in such a control system. The simulation results show that the performance of the proposed control strategies was satisfactory under each test when the GTPP experienced high rapid variations in the load.

08 HYDROGEN↗

Status Report on the High-Temperature Steam Electrolysis Plant Model Developed in the Modelica Framework (FY17)

This report has been prepared as part of an effort to design and build a modeling and simulation (M&S) framework to assess the economic viability of a nuclear-renewable hybrid energy system (N-R HES). In order to facilitate dynamic M&S of such an integrated system, research groups in multiple national laboratories have been developing various subsystems as dynamic physics-based components using the Modelica programming language. In fiscal year 2015 (FY15), Idaho National Laboratory (INL) performed a dynamic analysis of two region-specific N-R HES configurations, including the gas-to-liquid (natural gas to Fischer-Tropsch synthetic fuel) and brackish water reverse osmosis desalination plants as industrial processes. In FY16, INL developed two additional subsystems in the Modelica framework: (1) a high-temperature steam electrolysis (HTSE) plant as a high priority industrial plant to be integrated with a light water reactor (LWR) within an N-R HES and (2) a gas turbine power plant as a secondary energy supply. In FY17, five new components (i.e., a feedwater pump, a multi-stage compression system, a sweep-gas turbine, flow control valves, and pressure control valves) have been incorporated into the HTSE system proposed in FY16, aiming to better realistically characterize all key components of concern. Special attention has been given to the controller settings based on process models (i.e., direct synthesis method), aiming to improve process dynamics and controllability. A dynamic performance analysis of the improved LWR/HTSE integration case was carried out to evaluate the technical feasibility (load-following capability) and safety of such a system operating under highly variable conditions requiring flexible output. The analysis (evaluated in terms of the step response) clearly shows that the FY17 model resulted in superior output responses with much smaller settling times and less oscillatory behavior in response to disturbances in the electric load than those observed with the FY16 model. Simulation results involving several case studies show that the suggested control scheme could maintain the controlled variables (including the steam utilization factor, cathode stream inlet composition, and temperatures and pressures of the process streams at various locations) within desired limits under various plant operating conditions. The results also indicate that the proposed HTSE plant could provide operational flexibility to participate in energy management at the utility scale by dynamically optimizing the use of excess plant capacity within an N-R HES.

08 HYDROGEN↗

A Templated Approach for Multi-Physics Modeling of Hybrid Energy Systems in Modelica

A prototypical hybrid energy system (HES) couples a primary thermal power generator (i.e., nuclear power plant) with one or more additional subsystems beyond the traditional balance of plant electricity generation system. The definition and architecture of an HES can be adapted based on the needs and opportunities of a given local market. For example, locations in need of potable water may be best served by coupling a desalination plant to the HES. A location near an oil refinery may have a need for emission-free hydrogen production. The flexible, multidomain capabilities of Modelica are being used to investigate the dynamics (e.g., thermal hydraulics and electrical generation/consumption) of such a hybrid system. This paper examines the simulation infrastructure created to enable the coupling of multiphysics subsystem models for HES studies. A demonstration of a tightly coupled nuclear hybrid energy system implemented using the Modelica based infrastructure is presented for two representative cases. An appendix is also included providing a step-by-step procedure for using the template-based infrastructure.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Simulation Speed Analysis and Improvements of Modelica Models for Building Energy Simulation

This paper presents an approach for speeding up Modelica models. Insight is provided into how Modelica models are solved and what determines the tool’s computational speed. Aspects such as algebraic loops, code efficiency and integrator choice are discussed. This is illustrated using simple building simulation examples and Dymola. The generality of the work is in some cases verified using OpenModelica. Using this approach, a medium sized office building including building envelope, heating ventilation and air conditioning (HVAC) systems and control strategy can be simulated at a speed five hundred times faster than real time.

Jorissen, Filip↗

Modelica Models for Data Center Cooling Systems

This paper presents a package of Modelica models, which are dedicated to data center cooling systems and recently added to the Modelica Buildings library. To demonstrate the usage of this package, we modeled a chilled water system with an integrated wateside economizer, and an air-cooled direct expansion system with an airside economizer. These models are then applied to evaluate the control performance. After that we performed a detailed comparison in terms of system-level energy efficiency, economizing hours and supply air conditions for the two cooling systems. The advantages and disadvantages of this package are finally summarized and discussed.

Fu, Yangyang↗

Flexible Reinforcement Learning Framework for Building Control using EnergyPlus-Modelica Energy Models

In recent years, reinforcement learning (RL) methods have been greatly enhanced by leveraging deep learning approaches. RL methods applied to building control have shown potential in many applications due to their ability to complement or replace conventional methods such as model-based or rule-based controls. However, RL-based building control software is likely tailored either to one target building system or to a specific RL method so that significant additional effort would be required to customize the RL-based controller for use in other building systems or with other RL approaches. Also, RL-based building controls usually depend on building energy simulations to train controllers, so emulating building dynamics (i.e., thermal dynamics and control dynamics) and capturing sub-hourly dynamic profiles are crucial to further the development of effective RL-based building control methods. To address these challenges, we present an open source RL-based control software employing a high-fidelity hybrid EnergyPlus-Modelica building energy model which emulates building dynamics at 1-minute resolution. This software consists of decoupled components (environment, building emulator, control agent, and RL algorithm), which allows for quick prototyping and benchmarking of standard RL algorithms in different systems; for example, a single component can be replaced without revising all of the software. To demonstrate this software framework, we conducted a benchmark study using an EnergyPlus-Modelica building energy model for a Chicago office building with an RL-based controller to dynamically control the chilled water temperature setpoint and the air handling unit supply air temperature setpoint on selected floors.

Lee, Joon-Yong↗

Creation of Multiple Effect Evaporator and Combined Cycle Modelica Modules, and Optimization of Potable Water Generation from Saltwater Sources (Final Technical Report)

Modelica models for a Heat Recovery Steam Generator (HRSG) and Multiple Effect Evaporator have been developed. These models have been validated against results from literature and from an actual cogeneration system on the campus of NC State University. The models are capable of connecting to other components to create multi-input, multi-output energy systems with storage, also known as integrated energy systems. An existing 35 MW gas turbine model is connected to the HRSG model created for this project to produce 9 bar steam. The high pressure steam feeds a backpressure steam turbine from the library to generate additional electric power. 2 bar steam leaves the turbine to supply an 8 effect MEE to generate water for a community. As part of the effort, three research papers were submitted (two published in ANS Proceedings and one submitted to Applied Energy).

20 FOSSIL-FUELED POWER PLANTS↗

Hybrid Energy System Modeling in Modelica

In this paper, a Hybrid Energy System (HES) configuration is modeled in Modelica. Hybrid Energy Systems (HES) have as their defining characteristic the use of one or more energy inputs, combined with the potential for multiple energy outputs. Compared to traditional energy systems, HES provide additional operational flexibility so that high variability in both energy production and consumption levels can be absorbed more effectively. This is particularly important when including renewable energy sources, whose output levels are inherently variable, determined by nature. The specific HES configuration modeled in this paper include two energy inputs: a nuclear plant, and a series of wind turbines. In addition, the system produces two energy outputs: electricity and synthetic fuel. The models are verified through simulations of the individual components, and the system as a whole. The simulations are performed for a range of component sizes, operating conditions, and control schemes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Verification of Modelica-Based Models with Analytical Solutions for Tritium Diffusion

Here, tritium transport in metal and molten salt fluids combined with diffusion through high-temperature structural materials is an important phenomenon in both magnetic confinement fusion (MCF) and molten salt reactor (MSR) applications. For MCF, tritium is desirable to capture for fusion fuel. For MSRs, uncaptured tritium potentially can be released to the environment. In either application, quantifying the time- and space-dependent tritium concentration in the working fluid(s) and structural components is necessary.Whereas capability exists specifically for calculating tritium transport in such systems (e.g., using TMAP for fusion reactors), it is desirable to unify the calculation of tritium transport with other system variables such as dynamic fluid and structure temperature combined with control systems such as those that might be found in a system code. Some capability for radioactive trace substance transport exists in thermal-hydraulic systems codes (e.g., RELAP5-3D); however, this capability is not coupled to species diffusion through solids. Combined calculations of tritium transport and thermal-hydraulic solution have been demonstrated with TRIDENT but only for a specific type of MSR.Researchers at Oak Ridge National Laboratory have developed a set of Modelica-based dynamic system modeling tools called TRANsient Simulation Framework Of Reconfigurable Models (TRANSFORM) that were used previously to model advanced fission reactors and associated systems. In this system, the augmented TRANSFORM library includes dynamically coupled fluid and solid trace substance transport and diffusion. Results from simulations are compared against analytical solutions for verification.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simplifications for hydronic system models in modelica

Building systems and their heating, ventilation and air conditioning flow networks, are becoming increasingly complex. Some building energy simulation tools simulate these flow networks using pressure drop equations. These flow network models typically generate coupled algebraic nonlinear systems of equations, which become increasingly more difficult to solve as their sizes increase. This leads to longer computation times and can cause the solver to fail. These problems also arise when using the equation-based modelling language Modelica and Annex 60-based libraries. This may limit the applicability of the library to relatively small problems unless problems are restructured. This paper discusses two algebraic loop types and presents an approach that decouples algebraic loops into smaller parts, or removes them completely. The approach is applied to a case study model where an algebraic loop of 86 iteration variables is decoupled into smaller parts with a maximum of five iteration variables.

42 ENGINEERING↗

Modelica Buildings Library

The Building Informatics Environment is a modeling environment based on the Modelica language. The environment allows users to create a computer model of a building and its energy systems with various time scales and physical resolutions. The environment can be used for rapid development of e.g. demand controls algorithms new HVAC system solutions and new operational strategies. Models for building energy and control systems are made available in the environment. The models can be used as provided or they can be changed or linked with each other in order to model the effects that a particular user is interested in.

Wetter, Michael↗

An extension of the OpenModelica compiler for using Modelica models in a discrete event simulation

In this article, a new back-end and run-time system is described for the OpenModelica compiler. This new back-end transforms a Modelica model into a module for the adevs discrete event simulation package, thereby extending adevs to encompass complex, hybrid dynamical systems. The new run-time system that has been built within the adevs simulation package supports models with state-events and time-events and that comprise differential-algebraic systems with high index. Finally, although the procedure for effecting this transformation is based on adevs and the Discrete Event System Specification, it can be adapted to any discrete event simulation package.

97 MATHEMATICS AND COMPUTING↗

A Modelica Implementation of an Organic Rankine Cycle

Organic Rankine cycle (ORC) systems generate power from low-grade heat sources, such as geothermal sources and industrial waste heat. A key feature is that a working fluid is selected to match the temperature of the source. With the vast pool of candidate working fluids comes the challenge of developing a large number of robust thermodynamic media models. We implemented a subcritical ORC model in Modelica that uses working fluid data records and interpolation schemes in lieu of thermodynamic medium evaluation for energy recovery estimation. This is a component model that can be integrated into a larger energy system model. It does not require detailed thermodynamic, heat transfer, or machine analysis. Our ORC model fills a gap where working fluids are ready to choose or easy to add, and at the same time can be integrated into an energy system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Fan and Pump Efficiency in Modelica based on the Euler Number

Simulation programs often assume constant hydraulic efficiency for fan or pump models when performance curves are unavailable. This is inaccurate because the hydraulic efficiency varies with the operation condition. It therefore consistently underestimates the power draw at off-design conditions at which the hydraulic efficiency drops. Use of a modified Euler number allows computing the hydraulic efficiency and shaft power with limited data. Others showed the validity of the modified Euler number for fan efficiency calculations. We show that it is also applicable for pumps, and present its implementation in Modelica for a fan or pump model. Here, the only input required from the user is one data point at which the hydraulic efficiency is at its maximum. The reported method is applicable regardless of the type, size, or operational region of the fan or pump. Across a sample of eighteen sets of pump data and seven sets of fan data, the errors of the computed power from interpolated data were within 15% for the range of 20% - 70% of maximum flow rate and 40% - 90% of maximum pressure rise, excluding outliers.

component model↗

Nuclear Thermal Propulsion Dynamic Modeling with Modelica

Oak Ridge National Laboratory (ORNL) is participating in the nuclear thermal propulsion (NTP) research and development effort supported by the National Aeronautics and Space Administration (NASA). This effort involves collaboration between multiple research groups, representing various government agencies and industry partners. ORNL has developed a Modelica-based modeling package for dynamic system modeling of nuclear reactors called the Transient Simulation Framework of Reconfigurable Models (TRANSFORM). While this software has been successfully demonstrated in simulations of traditional pressurized-water reactors, boiling-water reactors, liquid-metal reactors and molten-salt reactors, it has also been adapted for non-traditional use in modeling hybrid energy systems, and tritium transport. This versatility is being applied to the current NTP project, where specific modules within TRANSFORM are being developed for and applied to transient modeling of the NASA NTP design. This paper presents the current state of the ORNL-NTP model, the utility of TRANSFORM methodologies in NTP transient simulations, the ability to develop NTP-specific modules, and future work for the model.

Rader, Jordan↗