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DOE OSTI2022

Roadmap for IES Modeling and Simulation Activities

Since inception of the DOE-NE Integrated Energy Systems (IES) program, several program and modeling visions and roadmaps have been published. In 2017, the last modeling and simulation capability development plan was published. In 2020, a comprehensive roadmap for the DOE-NE Integrated Energy Systems program has been published. The current report is meant to update the 2017 modeling and simulation capability roadmap and complement the IES overall program roadmap published in 2020. The role of modeling and simulation within IES is to support the demonstration of new coupled integrated technologies along every step of the technology maturation from the strategic analysis of preferred system architecture to preliminary design, to laboratory testing, up to full commercial testing and integration. To achieve this role, modeling and simulation must be able to assess the technical performance and the economic viability of potential IES. Also, modeling and simulation must provide support for experimental evaluations, i.e., support component design and real time operations of experimental demonstration systems. Finally, modeling and simulation can help scale-up experimental systems to the final commercial systems. This report details the current state of the modeling and simulation efforts within IES for the above-mentioned areas, provides a gap analysis and proposes next steps for a time horizon over the next 4 to 5 years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

ANSI/ASHRAE/IES Standard 90.1-2010 Performance Rating Method Reference Manual

This document is intended to be a reference manual for the Appendix G Performance Rating Method (PRM) of ANSI/ASHRAE/IES Standard 90.1- 2010 (Standard 90.1-2010).The PRM is used for rating the energy efficiency of commercial and high-rise residential buildings with designs that exceed the requirements of Standard 90.1. The procedures and processes described in this manual are designed to provide consistency and accuracy by filling in gaps and providing additional details needed by users of the PRM. It should be noted that this document is created independently from ASHRAE and SSPC 90.1 and is not sanctioned nor approved by either of those entities . Potential users of this manual include energy modelers, software developers and implementers of “beyond code” energy programs. Energy modelers using ASHRAE Standard 90.1-2010 for beyond code programs can use this document as a reference manual for interpreting requirements of the Performance Rating method. Software developers, developing tools for automated creation of the baseline model can use this reference manual as a guideline for developing the rules for the baseline model.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Potential Cooling Energy Savings of Economizer Control and Artificial-Neural-Network-Based Air-Handling Unit Discharge Air Temperature Control for Commercial Building

Heating, ventilation, and air-conditioning (HVAC) systems play a significant role in building energy consumption, accounting for around 50% of total energy usage. As a result, it is essential to explore ways to conserve energy and improve HVAC system efficiency. One such solution is the use of economizer controls, which can reduce cooling energy consumption by using the free-cooling effect. However, there are various types of economizer controls available, and their effectiveness may vary depending on the specific climate conditions. To investigate the cooling energy-saving potential of economizer controls, this study employs a dry-bulb temperature-based economizer control approach. The dry-bulb temperature-based control strategy uses the outdoor air temperature as an indicator of whether free cooling can be used instead of mechanical cooling. This study also introduces an artificial neural network (ANN) prediction model to optimize the control of the HVAC system, which can lead to additional cooling energy savings. To develop the ANN prediction model, the EnergyPlus program is used for simulation modeling, and the Python programming language is employed for model development. The results show that implementing a temperature-based economizer control strategy can lead to a reduction of 7.6% in annual cooling energy consumption. Moreover, by employing an ANN-based optimal control of discharge air temperature in air-handling units, an additional 22.1% of cooling energy savings can be achieved. In conclusion, the findings of this study demonstrate that the implementation of economizer controls, especially the dry-bulb temperature-based approach, can be an effective strategy for reducing cooling energy consumption in HVAC systems. Additionally, using ANN prediction models to optimize HVAC system controls can further increase energy savings, resulting in improved energy efficiency and reduced operating costs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Could a bioenergy program stimulate electric vehicle market penetration? Potential impacts of biogas to electricity annual rebate program

Abstract The biogas‐to‐electricity pathway under the Renewable Fuel Standard (RFS) allows for Renewable Identification Number (RIN) credits to be generated when electricity produced from biogas is used in the transportation sector. Though approved as a general pathway, EPA has proposed multiple credit allocation methods to functionalize this pathway. This study describes and evaluates a potential credit allocation framework where vehicle manufacturers generate electricity RIN (E‐RIN) credits and use these credits to increase the sales of plug‐in electric vehicles (PEVs). Under this framework, manufacturers use part of the credit value to reimburse electricity generators, offsetting potential higher biogas electricity generation cost. The remaining credit value is passed on to consumers as an annual PEV rebate to stimulate PEV sales. An iterative simulation framework is developed to fulfill two tasks: (a) to estimate the annual rebate amounts and their upfront value to consumers based on various factors, such as vehicle mileage, E‐RIN equivalence value, and biogas capacity, and (b) to evaluate potential impacts of the E‐RIN program on electrification of the future light‐duty vehicles (LDVs) and energy use. The annual rebate amount varies by vehicle technology and could be up to $870/year for battery electric vehicles (BEVs) and range between $230 and 825/year for plug‐in hybrid electric vehicles (PHEVs) depending on the electric range. These per vehicle rebates decrease when demand for electricity exceeds biogas electricity availability. The effectiveness of the program as modeled here is subject to different factors, such as the E‐RIN equivalence value, biogas electricity generation cost, biogas electricity generation capacity, and consumers’ valuation of the E‐RIN rebate. Our modeling results indicate that an E‐RIN program has the potential to produce nearly $12 billion in E‐RIN credits annually and to significantly increase PEV annual sales by up to 2.3 million and the PEV population by about 19.7 million in 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Summary and Assessment of Metal Fuel Capabilities in Bison

The work described in this report was performed under funding from the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. This report is issued in satisfaction of the level 2 milestone M2MS-18IN0201012 on Release Bison with Initial Metallic Fuel Performance Capability. Metallic fuel development began in Bison a few years after light water reactor development began (~ 2009). The initial development was funded by the Advanced Fuels Campaign. With recent interest from industry, the Nuclear Regulatory Commission, and the Versatile Test Reactor program, the Nuclear Energy Modeling Simulation Program has increased funding for metallic fuel development and validation in FY18. The material models with the most mature development are binary uranium-zirconium and ternary uranium-plutonium-zirconium alloys for fuel and HT9 for cladding. The first material models were incorporated from open literature sources, which include mechanical and thermal material properties that are functions of temperature, porosity, and zirconium concentration, swelling, fission gas release, zirconium diffusion, creep, and sodium coolant channel boundary conditions. These material models have been utilized to simulate ERB-II fuel pins and the results compared to measurements. The EBR-II experiment measurements mostly consist of cladding strain and zirconium redistribution. As such, comparisons to EBR-II measurements are currently limited to these two figures of merit. Simulations and comparisons to experiment measurements have also been done for transient testing of EBR- II fuel pins in TREAT, which included temperature measurements. Preliminary comparisons between Bison calculations and experiment measurements are favorable. These comparisons have also highlighted the importance of the fuel swelling and fission gas release models on cladding strain. Also, Bison metallic fuel simulations are currently being run in support of ATR experiments and VTR exploratory design calculations. Further development and evaluation of individual material models and fuel system models are planned for FY19.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Groundwater monitoring program plan and conceptual site model for the Al-Tuwaitha Nuclear Research Center in Iraq.

The Radiation Protection Center of the Iraqi Ministry of Environment is developing a groundwater monitoring program (GMP) for the Al-Tuwaitha Nuclear Research Center located near Baghdad, Iraq. The Al-Tuwaitha Nuclear Research Center was established in about 1960 and is currently being cleaned-up and decommissioned by Iraq s Ministry of Science and Technology. This Groundwater Monitoring Program Plan (GMPP) and Conceptual Site Model (CSM) support the Radiation Protection Center by providing: A CSM describing the hydrogeologic regime and contaminant issues, recommendations for future groundwater characterization activities, and descriptions of the organizational elements of a groundwater monitoring program. The Conceptual Site Model identifies a number of potential sources of groundwater contamination at Al-Tuwaitha. The model also identifies two water-bearing zones (a shallow groundwater zone and a regional aquifer). The depth to the shallow groundwater zone varies from approximately 7 to 10 meters (m) across the facility. The shallow groundwater zone is composed of a layer of silty sand and fine sand that does not extend laterally across the entire facility. An approximately 4-m thick layer of clay underlies the shallow groundwater zone. The depth to the regional aquifer varies from approximately 14 to 17 m across the facility. The regional aquifer is composed of interfingering layers of silty sand, fine-grained sand, and medium-grained sand. Based on the limited analyses described in this report, there is no severe contamination of the groundwater at Al-Tuwaitha with radioactive constituents. However, significant data gaps exist and this plan recommends the installation of additional groundwater monitoring wells and conducting additional types of radiological and chemical analyses.

Copland, John Robin↗
DOE OSTI2025

Method of Test for Evaluating Building Performance Simulation Software

ANSI/ASHRAE Standard 140 Method of Test for Evaluating Building Performance Simulation Software specifies the method to test the core competency of building performance simulation (BPS) software, a broad class of software which includes building energy modeling (BEM) software. Standard 140 has been widely used by BEM software vendors to help diagnose and compare the results from the program with other modeling programs. The Standard is also referenced by codes, standards, government programs, and other incentive programs as a part of minimum requirements for qualifying BEM software. The explanatory information, summary tables and figures in this 140 User’s Manual (referred to as “this Manual”) are provided to help users in implementing various suites of tests specified in Standard 140-2023 (referred to in this manual as “Standard 140” or “the Standard”).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Multi-Model, Multi-Scale Research Program in Stressors, Responses, and Coupled Systems Dynamics at the Energy-Water-Land Nexus and for Concentrated, Interdependent Infrastructures: Toward Next Generation Capabilities in Integrated Impacts, Adaptation, and Vulnerability (I-IAV) Modeling and a Community of Practice

The goal of this research program was to build a next generation integrated suite of science-driven modeling and analytic capabilities, and a more expanded and connected community of practice, for analyses of the stressors, impacts, adaptations and vulnerabilities of global and regional change. The emphasis was on understanding energy-water-land interactions and feedbacks and interdependent infrastructures at appropriate regional and temporal scales. Although the scope spans many complex facets of data, modeling, and analysis, as well as scales appropriate for integrated impacts and adaptation research, the focus of this effort was the development of multi-model, multi-scale capabilities spanning the domains of Multi-Sector Dynamics (MSD) models; Impact, Adaptation, and Vulnerability (IAV) models; and Earth System Models (ESMs).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]

The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.

Guerra Fernandez, Omar Jose↗
DOE OSTI2011

IMIGO: An Optimal Adaptive Nonlinear Program for Accelerator Optics Modeling and Other Applications

Model-based electron accelerator control is the maintenance of optimal parameters of an electron beam such as its orbit, size, and shape, as well as machine parameters such as tunes. It works well when the model reflects reality. SLAC pioneered this technique in SPEAR about thirty decades ago. Similar techniques are now employed in particle accelerator and synchrotron laboratories around the world. There is still an inherently complex problem related to the employment of such techniques to manage the operation and analysis of accelerators and storage rings. The problem arises from the use by those techniques of complex numerical algorithms commonly known as nonlinear solvers that are difficult to control and operate. Lessons learned at SLAC have led to the development of a new, simple-to-use, and iterative nonlinear solver that holds much promise not only in advancing the derivation of errors in accelerators and storage rings at SLAC, but also in its ability to tackle a range of complex engineering problems. A CRADA project was recently completed to build on this experience at SLAC, and to collaborate with an outside company GO AI Services to further develop and validate this nonlinear solver for robust SLAC accelerator. In this report, we present the project report submitted to DOE and SLAC.

Accelerators↗
DOE OSTI2018

Transactive System Program Communication System Cost Model

Transactive energy is an economics and controls technique that aims to dynamically manage the generation and consumption of electricity within the power system. Much research has been done in the area of demonstrating the capability and performance of transactive systems, as well as valuing the benefits a transactive system can provide. Significantly less research has been done in the area of estimating the costs of a transactive system. This work aimed to build a model that would estimate the costs of the communications system that would be necessary to support a transactive system and be realized by a local utility. Dynamic pricing, and a customer’s response to this pricing, is a key aspect of a transactive system; this would require a two-way communication system between utilities and customers. Since the system will vary based on many factors, the cost model was consequently designed for use in a wide variety of applications. The cost model requires some basic user inputs regarding the system being analyzed, such as location and size. The user also identifies one or more generic circuit models that best represent the system. Additionally, a user can, but is not required to, change assumed equipment and installation costs and equipment lifetime within the model. These inputs will result in 20 year cost estimates for three different communication technologies that are capable of supporting the bandwidth needs of a transactive energy system. The three communication systems included in the model are cellular, fiber optic and wireless mesh. Each vary significantly from one another and offer unique advantages and barriers. A cellular network avoids high upfront costs, but is limited to areas where there is coverage by the service provider and subject to the ongoing rate established with the service provider. A fiber optic system requires a large up-front cost, but it will provide a reliable system to areas where cellular and mesh may be unable to do so. Additionally, fiber provides more bandwidth than necessary for transactive systems and can offer additional business opportunities. A mesh system can be installed for less upfront costs than fiber and offers enough bandwidth to support a transactive system, but the ability to model this technology is done with less certainty than the other two options. The estimated costs include the communication system that connects the customers to their nearest substation, in addition to the smart meter and radio that would be required for each customer. The communications from the substation to the utility are not included in estimates, as the need for upgrading that system would be assessed on a case-by-case basis. Although the cost of the smart meter and radio is included, no other appliance specific cost is included in the estimate provided by the model. The communication system is a key aspect of the development of a transactive system. This work resulted in easily being able to estimate the costs of a communication system specific to the system being studied. This cost model will aid ongoing valuation and simulation work in the field of transactive energy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Development and Porting of Nuclear Reactor Computational Models for the NRIC Virtual Test Bed in FY23

The U.S. DOE’s National Reactor Innovation Center (NRIC) hosts an open-source website and associated GitHub repository called the Virtual Test Bed (VTB) on which computational models for advanced reactors are documented and shared with the reactor community. In FY23 under the NRIC program, computational models for nuclear reactor analysis were developed and contributed to the VTB Github repository during FY23 by contributors at Argonne National Laboratory. Other models developed outside of NRIC were also ported to the VTB as part of this work, serving a broader mission to make computational reactor analysis models more widely available to the reactor community. The model development activities focused on demonstration of gas-cooled microreactor models including computational fluid dynamics simulations of flow through an industry-inspired air jacket design, and simulation of multiphysics transients for a gas-cooled microreactor assembly. Additionally, development of a molten salt reactor (led at Idaho National Laboratory) was supported through Argonne’s expertise in multigroup cross sections generation. Models for these two reactor types were targeted due to their relevancy to NRIC’s Demonstration of Microreactor Experiments (DOME) and Laboratory for Operation and Testing in the U.S. (LOTUS) physical test beds, which are slated to host microreactor and molten salt reactor experiments. The model porting activities consisted of developing detailed documentation for several physics models which originate from the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. We include only contributions from Argonne National Laboratory in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Simulation of Thermal Spectrum MSR using PROTEUS

In recent years, there has been renewed interest in Molten Salter Reactors (MSRs) for their potential advantages compared to reactors that rely on solid fuel. Given the current interest for MSRs, it is a good opportunity to demonstrate that the advanced tools developed in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program are useful for modeling MSRs. In addition, one objective of the program is to develop modeling and simulation capabilities to predict the performance and safety of all types of advanced nuclear reactor. For this study, PROTEUS [1], the primary reactor physics tool within the program, was assessed and used to model one of the preliminary core designs provided by ThorCon, one of the leading MSR companies from industry. The focus of this first step in the modeling and simulation work is to predict the core design’s steady state performance.

Fei, T.↗
DOE OSTI2017

An enhanced SOCP-based method for feeder load balancing using the multi-terminal soft open point in active distribution networks

The integration of distributed generators (DGs) exacerbates the feeder power flow fluctuation and load unbalanced condition in active distribution networks (ADNs). The unbalanced feeder load causes inefficient use of network assets and network congestion during system operation. The flexible interconnection based on the multi-terminal soft open point (SOP) significantly benefits the operation of ADNs. The multi-terminal SOP, which is a controllable power electronic device installed to replace the normally open point, provides accurate active and reactive power flow control to enable the flexible connection of feeders. An enhanced SOCP-based method for feeder load balancing using the multi-terminal SOP is proposed in this paper. Furthermore, by regulating the operation of the multi-terminal SOP, the proposed method can mitigate the unbalanced condition of feeder load and simultaneously reduce the power losses of ADNs. Then, the original non-convex model is converted into a second-order cone programming (SOCP) model using convex relaxation. In order to tighten the SOCP relaxation and improve the computation efficiency, an enhanced SOCP-based approach is developed to solve the proposed model. Finally, case studies are performed on the modified IEEE 33-node system to verify the effectiveness and efficiency of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A mixed formulation of the plane-stress problem to facilitate reuse of constitutive models in finite-element programs

Here, the plane-stress assumption can be challenging to support in a finite element program because it traditionally requires separate implementations of constitutive models than those intended for three-dimensional or two-dimensional plane-strain simulations. As a solution to this issue, this paper presents a method to solve the plane-stress problem using a mixed formulation. In this formulation, the out-of-plane strain is treated as a field variable that is solved for in addition to the standard in-plane displacement variables, in a manner that weakly enforces the condition that the out-of-plane stress is zero. The proposed formulation is non-intrusive, requiring no modifications to the constitutive models in contrast to the conventional plane-stress formulation. The proposed mixed formulation has been benchmarked against analytical solutions and numerical solutions, with good performance and accuracy.

97 MATHEMATICS AND COMPUTING↗