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At least 649 records · Page 36

Roadmap for IES Modeling and Simulation Activities: Update 2023

Since inception of the DOE-NE Integrated Energy Systems (IES) program, several program and modeling visions and roadmaps have been published. In 2020, a last comprehensive roadmap for the DOE-NE Integrated Energy Systems program was published. In 2017, a separate modeling and simulation capability development plan was published that was extensively updated in 2022. The current report incrementally updates the 2022 modeling and simulation capability roadmap. This is not a new report, but individual sections have been updated to reflect recent accomplishments and new directions of the program. 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 years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

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↗

Global Market and Economic Welfare Implications of Changes in Agricultural Yields Due to Climate Change

The economic welfare effects of climate change on global agriculture will be mediated by several complex biophysical and economic processes. For a given emissions scenario, these include: (1) the response of the climate system to anthropogenic forcing, (2) the response of crop yields to climate system and carbon dioxide changes, given baseline improvements in crop yields, (3) the response of agricultural markets to crop yield changes, and (4) the economic welfare implications of such market responses. In this paper, we use information about the first two processes from available climate-crop model comparison studies to analyze implications for the third and fourth processes. Applying the range of crop yield changes in a Global Integrated Assessment Model (GCAM) highlights several important economic relationships. First, we find a consistent relationship between global cropland area and yield change that is approximately orthogonal to the relationship between regional cropland area and yield change. Second, we find that the change in economic welfare, expressed as total surplus change per unit economic output, peaks during the 21st century. Third, we find that, at the global level, changes in yield affect both producer surplus and consumer surplus. Specifically, surplus changes to producers and consumers are always opposite in sign, although which economic actors gain or lose varies with the sign of yield change for any given commodity. Taken together, these results contribute to a growing body of research on climate-induced changes on agriculture by highlighting several economic relationships that are robust to differences in the underlying biophysical responses.

54 ENVIRONMENTAL SCIENCES↗

Assessment of CASL VERA for BWR analysis and application to accident tolerant SiC/SiC channel box

Application of the Virtual Environment for Reactor Applications (VERA) to BWR analysis is assessed in this paper by comparing results to those calculated using other widely-used modeling tools, namely the U.S. Nuclear Regulatory Commission’s PARCS/PATHS and the Serpent Monte Carlo particle transport code. Additionally, VERA is used to calculate 3-D temperature and fast neutron flux distributions in silicon carbide (SiC) fiber-reinforced, SiC matrix composite (SiC/SiC) BWR channel boxes, which are being studied as an Accident Tolerant Fuel core structural material concept. We found that the code-to-code comparisons were favorable, and the SiC/SiC channel box evaluation demonstrates the many advanced modeling features VERA provides while also highlighting the non-uniformity in fast neutron flux distributions that can play a role in potential SiC/SiC channel box deformation. Traditional BWR analysis tools do not have the calculation fidelity necessary for coupled assessment of flux and temperature gradients in a SiC/SiC channel box. VERA is a state-of-the-art modeling environment that was developed to increase the safety and economic competitiveness of nuclear power through improved modeling accuracy. While VERA has already been deployed in the nuclear industry for PWR applications, the current study is a vital initial step in the extensive development, validation, and verification that VERA must go through to be useful for BWR applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Building a better framework for evaluating human well-being impacts in global change analysis: The example of energy security

Human well-being can be greatly impacted by the global environmental and socio-economic change captured in Integrated Models of Global Change (IMGCs). Though most IMGCs address some aspects of well-being, their underlying modeling approach and ‘philosophy’ differ widely, and some key elements – like energy security – are omitted. In this report, we describe a project in which we set out to a create a framework through which the well-being dimensions of the household are connected to key drivers of socio-economic and environmental change – and how the needed metrics, data and modeling methods can be brought to bear. We focus on the well-being dimensions of energy, and lay out the necessary elements to capturing household energy security – using household energy burden as the relevant metric. We begin by showing the conceptual linkage of energy burden to environmental drivers like temperature change, using a simple and straightforward conceptual framework. We then go further to use the example of GCAM-USA to show how some key analytical features of the model can provide insight into how energy security across different groups can change along alternative pathways to sustainability. We compare our preliminary assessment of household energy burden to existing data and suggest further steps to improve and refine this analysis in future research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

On a numerical sufficiency test for monotonic convergence of finite element models

Finite element analyses characterized by monotonic convergence include the discipline for meaningful measurements of convergence rate and consequently economical extrapolation. Few proposers of element models guarantee monotonic convergence for their elements. Thus, a need exists for an automatic test to classify available element models. This paper describes such a test - a test can be performed using a digital computer to guarantee that a particular element model imbues monotonicity. It describes the test and its basis. It examines seven element models for a rectangular membrane to illustrate the value of the tests. Besides confirming results already known, the application yields new data. It 'proves' monotonicity for two improved models, defines the range of element proportions for which another element can be guaranteed to exhibit monotonicity, and suggests that another element is deficient. In the special case of absolutely convergent membrane displacement models, proof of monotonicity is a necessary and sufficient condition to insure that upper bound estimates of strain energy are developed. Accordingly, the test furnishes a proof of bound solutions independently of requirements on displacement continuity the element basis may or may not satisfy.

Melosh, R. J.↗

Organic Rankine Cycle Integration and Optimization for High Efficiency CHP Genset Systems (Final Technical Report)

This project successfully advanced the integration of Organic Rankine Cycle (ORC) technology with reciprocating engine–based combined heat and power (CHP) systems to improve electrical efficiency, total CHP efficiency, and grid-responsive operation. Over three budget periods, the work progressed from high-temperature ORC component development and thermodynamic model validation to next-generation system design, working fluid transition, and techno-economic analysis. Key technical accomplishments include development and validation of a thermodynamic model capable of accurately predicting ORC performance across an expanded temperature and pressure envelope; successful identification and validation of low-global-warming-potential (GWP) working fluids—most notably R1233zd(E)—as viable replacements for R245fa; and demonstration of scalable ORC architectures suitable for integration with 1–20 MW class reciprocating engines. These advances enable flexible CHP configurations that can increase electrical output while maintaining high overall utilization of available thermal energy. The project also produced a clean-sheet design for a next-generation ORC system targeting substantially higher power output per unit, supported by detailed component selection, heat exchanger evaluation, and system-level modeling. Techno-economic analyses indicate that ORC-enabled flexible CHP systems can meet or exceed Department of Energy (DOE) efficiency targets while providing value to both facility operators and the electric grid.. Late-stage testing of the largest next-generation ORC prototype identified limitations related to pump net positive suction head (NPSH) requirements and condenser flooding under certain operating conditions. Although these issues constrained full validation of that configuration within the project timeframe, they provided clear and actionable design guidance for future system refinements. Importantly, validated modeling, smaller-scale testing, and working fluid evaluations confirmed the technical viability of the overall approach. In aggregate, this project met its core objectives by establishing validated design tools, de-risking key ORC technologies for CHP applications, and defining a credible pathway toward commercialization of flexible, high-efficiency CHP systems. The results form a strong foundation for continued development and deployment beyond the conclusion of the DOE-funded effort.

20 FOSSIL-FUELED POWER PLANTS↗

Storage Enabled Flexibility of Conventional Generation Assets (StorFlex)

The power systems have faced progressively more demanding operational requirements over the last two decades. Several factors contribute to these challenging operating conditions, including load growth, aging infrastructure, increasing penetrations of distributed energy resources (DERs), electrification of the economy, and policy initiatives such as decarbonization. The power system and its components must provide high operational flexibility to mitigate these challenges. For example, the proliferation of intermittent DERs such as wind and solar has increased the need for conventional generation assets like hydropower plants to respond to sudden load-generation imbalances. The higher flexibility requirements for hydropower plants cause more wear and tear, potentially shortening the useful lifespan of hydropower turbines. To reduce the need for hydropower plants to follow sudden changes in the dispatch signal, we investigate their combined operation with the energy storage systems (ESSs; “ESS-based hybridization”). Our analyses focuses on improving the lifespan of hydropower plants through ESS-based hybridization. Wear and tear on hydropower turbines (particularly Francis turbines) is modeled using a loss-of-life concept that is based on damage experienced by the turbine due to various cycles of operation. Then, we show that using ESSs to offset some of the high variation increases the remaining life of the hydropower plants. To demonstrate this, a few modeling tools were developed for this work: (1) a dynamic model for various components of the turbine and its governor; (2) a control strategy that assigns a slow-varying dispatch signal to a hydropower unit versus a fastmoving signal to ESS, such that the overall power request remains the same; and (3) models for the financial analysis to quantify the economic merits of such a framework. We used the models we developed to analyze the dispatch pattern of an actual hydropower plant with a power output of 50 MW and a head height of 152 m. This work showed that ESS-based hybridization could extend the life of the hydropower plant by 5% on average. This extension in life was then used to estimate the economic benefit in terms of cost deferrals associated with hydropower plant maintenance and replacement: on average, $3.6 million. Sensitivity analysis with respect to the size of ESS and cost of turbines was performed to show the variation in benefits over the range of turbine costs and ESS sizes. Crucially, stacking damage reduction and lifetime extension with other ESS value streams such as providing ancillary services could substantially increase the financial benefits of ESS-based hybridization. The higher costs associated with ESS of appropriate size would make more financial sense when multiple value streams are stacked and co-optimized to extract the maximum benefit. This dimension will be explored in future work.

13 HYDRO ENERGY↗

Life-cycle analysis of greenhouse gas emissions from hydrogen delivery: A cost-guided analysis

The cost of hydrogen delivery for transportation accounts for most of the current H 2 selling price; delivery also requires substantial amounts of energy. In this work, we developed harmonized techno-economic and life-cycle emissions models of current and future H 2 production and delivery pathways. Our techno-economic analysis of dispensed H 2 costs guided our selection of pathways for the life-cycle analysis. In this paper, we present the results of market expansion scenarios using existing capabilities (for example, those that use H 2 from steam methane reforming, chlor-alkali, and natural gas liquid cracker plants), as well as results for future electrolysis plants that use nuclear, solar, and hydroelectric power. Reductions in greenhouse gas emissions for fuel cell electric vehicles compared to conventional gasoline pathways vary from 40% reduction for fossil-derived H 2 to 20-fold for clean H 2 . Supplemental tables with greenhouse gas emissions data for each step in the H 2 pathways enable readers to evaluate additional scenarios.

08 HYDROGEN↗

Energy Northwest — Advanced Grid Interactive Load Efficiency (AGILE) : A Techno-economic Assessment

The Advanced Grid Interactive Load Efficiency project team, led by Energy Northwest, was awarded funding as part of the fourth round of the Clean Energy Fund program to investigate, co-create, and complete a preliminary design for grid-interactive efficient buildings (GEBs) for a number of schools served by Grays Harbor PUD. The project team has evaluated different combinations of systems at selected school buildings and the potential to respond to grid and customer needs, and develop a preliminary system technical design, including specifying desired GEB technology options, determining communication and electrical interface requirements, assessing control software sensor requirements, and interfacing with building management systems. PNNL led the techno-economic assessment efforts, leveraging its advanced modeling and analytical methods and tools developed for building-to-grid integration. This report documents the economic assessment for different GEB design options, encompassing an in-depth examination of use cases and value propositions, assumptions and inputs, models, methods, case studies, as well as key findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Case Study on Condenser Water Supply Temperature Optimization with a District Cooling Plant

District cooling (DC) continues to proliferate due to increasing global cooling demands and economies of scale benefits; however, most district-scale modeling has focused on heating, and to the best of our knowledge, researchers have yet to model cooling plants featuring waterside economizers in DC settings. With the popular Modelica Buildings library expanding its capabilities to district scale, this study is one of the first to demonstrate how the open-source models can be used for detailed energy and control analysis of a DC plant. For a real-world case study, we developed and calibrated high-fidelity models for a DC system central plant at a college campus in Colorado, USA, and we optimized the condenser water supply temperature (CWST) setpoint for a DC plant across multiple time horizons using the Optimization library in Dymola. Results indicate that annual CWST optimization saves 4.7% annual plant energy, with less than 1% of additional energy savings gained through daily optimization. This confirms previous studies' findings that high frequency CWST optimizations are not necessary for the studied system.

chiller plant↗

Nonlinear Multiobjective MPC-Based Optimal Operation of a High Consistency Refining System in Papermaking

As one of the most important unit in the papermaking industry, the high consistency (HC) refining system is confronted with challenges such as improving pulp quality, energy saving, and emissions reduction in its operation processes. Here in this correspondence, an optimal operation of HC refining system is presented using nonlinear multiobjective model predictive control strategies that aim at set-point tracking objective of pulp quality, economic objective, and specific energy (SE) consumption objective, respectively. First, a set of input and output data at different times are employed to construct the subprocess model of the state process model for the HC refining system, and then the Wiener-type model can be obtained through combining the mechanism model of Canadian Standard Freeness and the state process model that determines their structures based on Akaike information criterion. Second, the multiobjective optimization strategy that optimizes both the set-point tracking objective of pulp quality and SE consumption is proposed simultaneously, which uses NSGA-II approach to obtain the Pareto optimal set. Furthermore, targeting at the set-point tracking objective of pulp quality, economic objective, and SE consumption objective, the sequential quadratic programming method is utilized to produce the optimal predictive controllers. In conclusion, the simulation results demonstrate that the proposed methods can make the HC refining system provide a better performance of set-point tracking of pulp quality when these predictive controllers are employed. In addition, while the optimal predictive controllers orienting with comprehensive economic objective and SE consumption objective, it has been shown that they have significantly reduced the energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluating the regional risks to food availability and access from land-based climate policies in an Integrated Assessment Model

Mitigating greenhouse gas (GHG) emissions is necessary to reduce the overall negative climate change impacts on crop yields and agricultural production. However, certain mitigation measures may generate unintended consequences to food availability and food access due to both land use competition and economic burden of mitigation. Integrated assessment models (IAM) are generally used to evaluate these policies; however, currently these models may not capture the importance of income and food prices for hunger and overall economic wellbeing. Here, we implement a measure of food security that captures the nutritional and economic aspects as the total expenditures on staple foods divided by income and weighted by total caloric consumption in an IAM, the Global Change Analysis Model (GCAM4.0). We then project consumer prices and our measure of food security along the Shared Socioeconomic Pathways (SSPs). Sustained economic growth underpins increases in caloric consumption and lowering expenditures on staple foods. Strict conservation policies affect food accessibility in a larger number of developing countries, whereas the negative effects of pricing terrestrial emissions is more concentrated on the poor in Sub-Saharan Africa, by substantially replacing their cropland with forests and affecting the production of key staples.

Cui, Ryna↗

Visualization of Multi-Fidelity Approximations of Stochastic Economic Dispatch

As renewable energy generation deployment increases, the operation of electrical grids becomes more complex. Economic dispatch is part of a grid operator's regular decision process where the amount of energy to generate is determined based on the number of available generators and the actual level of energy demand. Renewable generators are inherently stochastic due to the chaotic nature of weather patterns, and thus, real-time decisions of economic dispatch become increasingly complex. Modeling efforts to assist in these decisions in the highest fidelity typically take hours to days to solve on leadership-class computers; too long for the 5-minute operational time-frame demanded of operators. Alternatively, multi-fidelity approximations can be used to predict generation levels quickly and with sufficient accuracy to be used for real-time operations. We have developed a visualization tool to demonstrate the utility of multi-fidelity approximations by displaying contextual results of economic dispatch approximations, comparisons across fidelity levels of generation levels and possible failures to meet demand, and meta-data on the modeling setup.

interactive visualization↗

BETO 2021 Peer Review - Feasibility Study of Utilizing Electricity to Produce Intermediates from CO2 and Biomass

Capturing and converting CO2 generated from bioethanol facilities into valuable products, leveraging renewable electricity as the primary energy input, could increase overall biorefinery carbon utilization by as much as 40% and provide a means to decarbonize fuels and chemicals production. However, significant uncertainty exists around the costs, carbon intensity, risks, and technical challenges associated with electron-driven CO2 reduction. Thus, the overarching objective of this project is to guide existing and future research and development efforts by addressing these knowledge gaps for utilizing renewable electricity and CO2 to improve biorefinery economics and carbon utilization. By September 2023, this project will develop and publish a comprehensive design report for the integration of CO2 utilization into two existing conceptual biorefinery designs, which will include conceptual process models, pioneer and nth plant economics, identification and quantification of technological risks, and projections for future cost reductions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Process design tools and techno-economic analysis for capacitive deionization

Capacitive deionization (CDI) devices use cyclical electrosorption on porous electrode surfaces to achieve water desalination. Process modeling and design of CDI systems requires accurate treatment of the coupling among input electrical forcing, input flow rates, and system responses including salt removal dynamics, water recovery, energy storage, and dissipation. Techno-economic analyses of CDI further require a method to calculate and compare between a produced commodity (e.g. desalted water) versus capital and operational costs of the system. In this work, we demonstrate a new modeling and analysis tool for CDI developed as an installable Matlab program that allows direct numerical simulation of CDI dynamics and calculation of key performance and cost parameters. The program is provided for free and is used to run open-source Simulink models. The Simulink environment sends information to the program and allows for a drag and drop design space where users can connect CDI cells to relevant periphery blocks such as grid energy, battery, solar panel, waste disposal, and maintenance/labor cost streams. The program allows for simulation of arbitrary current forcing and arbitrary flow rate forcing of one or more CDI cells. We employ validated well-mixed reactor formulations together with a non-linear circuit model formulation that can accommodate a variety of electric double layer sub-models (e.g. for charge efficiency). The program includes a graphical user interface (GUI) to specify CDI plant parameters, specify operating conditions, run individual tests or parameter batch-mode simulations, and plot relevant results. The techno-economic models convert among dimensional streams of species (e.g. feed, desalted water, and brine), energy, and cost and enable a variety of economic estimates including levelized water costs.

42 ENGINEERING↗

Techno-Economic Optimization of Fixed Bed and Moving Bed Contactors for CO2 Capture from NGCC Plants Using a Functionalized Metal-Organic Framework

Amine-appended metal–organic frameworks (MOFs) have strong potential for post-combustion CO2 capture from NGCC plants. In this work, a specific tetramine-appended MOF, Mg2(dobpdc)(3-4-3) (dobpdc4− = 4,4′-dioxidobiphenyl-3,3′dicarboxylate; 3-4-3 = N,N′bis(3-aminopropyl)-1,4-diaminobutane), is evaluated due to its superior performance compared to other candidate diamine-appended and tetraamine-appended MOFs. Techno-economic optimization is performed to minimize the cost of capture by using the Framework for Optimization, Quantification of Uncertainty, and Surrogates (FOQUS), which is capable of optimizing systems by using derivative-free optimization solvers where process models are built using numerous modeling platforms. The technical and economic performances of both fixed bed and moving bed processes are compared with state-of-the-art amine-based solvent systems.

Hughes, Ryan↗

Techno-Economic Analysis and Global Warming Potential of a Novel Offshore Macroalgae Biorefinery

The success of a large scale macroalgae-based biorefinery is dependent on the demonstration of favorable system economics and environmental sustainability. This study uses detailed process modeling to quantify the mass and energy flows through the various unit operations required for a novel free-floating macroalgae biorefinery concept. The modular process model served as the foundation for the techno-economic and global warming potential analyses used to quantify the sustainability of the proposed concept. This work includes detailed techno-economic results for a complete macroalgae cultivation and conversion system with multiple hatchery configurations and several emerging technologies. System optimization was achieved through the evaluation of various technology options for each unit operation. Technologies considered include traditional twine and textile substrate hatchery configurations, drone assisted seeding and biomass transport, mechanized line seeding and harvesting, adhesive spore mixtures that simplify seeding operations and improve hatchery energetics, and hydrothermal liquefaction to produce upgradable biocrude. Outputs from the system include renewable diesel (R100), naphtha, biochar, nitrogen and phosphorus fertilizers, and aqueous/solid waste streams. Three different system pathways were explored, yielding a biomass production cost ranging from $210 to $565 per dry metric ton and a minimum fuel selling price from $1.35 to $2.91 per liter of gasoline equivalent. Stochastic manipulation of the process model and sensitivity analyses support these results. The global warming potential analysis shows net greenhouse gas emissions ranging from 14 to 29 gCO2-eq MJ-1, supported by stochastic and sensitivity analyses. The recommendations from this work highlight critical areas for research and development investment such that a sustainable macroalgae cultivation and conversion system can be realized.

NOMAD seaweed cultivation, techno-economic analysi↗