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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8

Methods for Translating ReEDS Solutions to Production Cost Modeling Tools

Capacity expansion modeling tools are increasingly being utilized to investigate a wide range of potential future scenarios, particularly with high penetrations of variable and energy-constrained resources that may be operated differently than current dispatch paradigms. While capacity expansion models are particularly adept at making investment decisions for future years, they must make compromises in operational aspects to maintain computational tractability. However, it is of high interest to determine if such future systems would be able to maintain reliability during a variety of grid conditions, and to identify any potential operational challenges for these systems at finer temporal resolution than is typically captured in CEMs. As such, there is value in having an automated tool that can convert many CEM investment pathways into inputs for a more detailed production cost model, in this case the PLEXOS commercial software package. This paper describes the methodology used to make that translation for the NREL-developed ReEDS model, making use of two internally developed tools - PIDG and beetle - along with a set of processing scripts. We describe the current assumptions, data sets, and important operational characteristics of these translations along with an example of the extended analyses that may be done through this connection.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

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↗

FECM/NETL CO2 Saline Storage Cost Model CO2_S_COM 2024 (v4)

The U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management (FECM), in collaboration with the National Energy Technology Laboratory (NETL), has developed the FECM/NETL CO2 Saline Storage Cost Model (CO2_S_COM). This Excel-based tool provides a comprehensive framework for estimating the costs and breakeven prices associated with storing carbon dioxide (CO2) in deep saline formations. Designed from the perspective of a CO2 storage site owner, the CO2_S_COM incorporates four integrated modules—project management, financial analysis, activity cost estimation, and geological evaluation—to deliver fast, robust and actionable insights for screening project finances.

CO2 storage↗

PV O&M Cost Model [SWR-21-14]

This tool presents a method for calculating costs associated with the operation and maintenance (O&M) of photovoltaic (PV) systems. The tool compiles details regarding the cost and frequency of multiple O&M services to estimate annual O&M costs ($/year) for each year of an analysis period, the net present value ($) of life cycle costs accumulated over the analysis period, and the reserve account amount ($) that might be required to fund unexpected repairs. The reserve account includes parts inventory and is important for providing a source of funds to make repairs quickly and avoid lost production. This method allows a detailed selection of services to perform based on system size, market served (e.g., residential, commercial, or utility), type and configuration of system components (e.g., micro-, string, or central inverter), and site and environmental conditions (e.g., pollen, bird populations) which is an improvement over simple per unit valuations of O&M costs ($/kW/year). This model also distinguishes costs that vary from year to year and increase at different rates over time as modeled by heuristic failure distributions (e.g., Weibull or Lognormal distribution) based on actuarial data for many of the services.

Walker, Andy↗

Updated Oregon Floating Offshore Wind Cost Modeling [Slides]

The study provides heat maps showing updated estimates of the levelized cost of energy (LCOE) for floating offshore wind energy off the coast of Oregon. This project builds on a 2019 National Renewable Energy Laboratory (NREL) floating offshore wind power cost study in Oregon (Musial et al. 2019) and a recent NREL California cost analysis (Beiter et al. 2020). Floating wind power cost data, modeling methodology, and resource data are updated and LCOE is estimated through 2032 using 2019 as a reference year. Comparisons are made to the previous offshore wind energy cost studies (Musial et al. 2019; Beiter et al. 2020). The study does not prioritize specific sites or make judgments about marine spatial planning viability.

17 WIND ENERGY↗

Greening the Grid: Advances in Production Cost Modeling for India Renewable Energy Grid Integration Study

The Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid study uses advanced weather and power system modeling to explore the operational impacts of meeting India's 2022 renewable energy targets and identify actions that may be favorable for integrating high levels of renewable energy into the Indian grid. The study relies primarily on a production cost model that simulates optimal scheduling and dispatch of available generation in a future year (2022) by minimizing total production costs subject to physical, operational, and market constraints. This fact sheet provides a detailed look at each of these models, including their common assumptions and the insights provided by each.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Automation life-cycle cost model

The problem domain being addressed by this contractual effort can be summarized by the following list: Automation and Robotics (A&R) technologies appear to be viable alternatives to current, manual operations; Life-cycle cost models are typically judged with suspicion due to implicit assumptions and little associated documentation; and Uncertainty is a reality for increasingly complex problems and few models explicitly account for its affect on the solution space. The objectives for this effort range from the near-term (1-2 years) to far-term (3-5 years). In the near-term, the envisioned capabilities of the modeling tool are annotated. In addition, a framework is defined and developed in the Decision Modelling System (DEMOS) environment. Our approach is summarized as follows: Assess desirable capabilities (structure into near- and far-term); Identify useful existing models/data; Identify parameters for utility analysis; Define tool framework; Encode scenario thread for model validation; and Provide transition path for tool development. This report contains all relevant, technical progress made on this contractual effort.

Gathmann, Thomas P.↗

Designers' unified cost model

The Structures Technology Program Office (STPO) at NASA LaRC has initiated development of a conceptual and preliminary designers' cost prediction model. The model will provide a technically sound method for evaluating the relative cost of different composite structural designs, fabrication processes, and assembly methods that can be compared to equivalent metallic parts or assemblies. The feasibility of developing cost prediction software in a modular form for interfacing with state-of-the-art preliminary design tools and computer aided design programs is being evaluated. The goal of this task is to establish theoretical cost functions that relate geometric design features to summed material cost and labor content in terms of process mechanics and physics. The output of the designers' present analytical tools will be input for the designers' cost prediction model to provide the designer with a database and deterministic cost methodology that allows one to trade and synthesize designs with both cost and weight as objective functions for optimization. This paper presents the team members, approach, goals, plans, and progress to date for development of COSTADE (Cost Optimization Software for Transport Aircraft Design Evaluation).

Freeman, W.↗

On the Inclusion of Energy-Shifting Demand Response in Production Cost Models: Methodology and a Case Study

In the context of future power system requirements for additional flexibility, demand response (DR) is an attractive potential resource. Its proponents widely laud its prospective benefits, which include enabling higher penetrations of variable renewable generation at lower cost than alternative storage technologies, and improving economic efficiency. In practice, DR from the commercial and residential sectors is largely an emerging, not a mature, resource, and its actual costs and benefits need to be studied to determine promising combinations of physical DR resource, enabling controls and communications, power system characteristics, regulatory environments, market structures, and business models. The work described in this report focuses on the enablement of such analysis from the production cost modeling perspective. In particular, we contribute a bottom-up methodology for modeling load-shifting DR in production cost models. The resulting model is sufficiently detailed to reflect the physical characteristics and constraints of the underlying flexible load, and includes the possibility of capturing diurnal and seasonal variations in the resource. Nonetheless, the model is of low complexity and thus suitable for inclusion in conventional unit commitment and market clearing algorithms. The ability to simulate DR as an operational resource on a power system over a year facilitates an assessment of its time-varying value to the power system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Life Cycle Cost Modeling of High-speed Commercial Aircraft - Final Report

SpaceWorks has concluded a 9-month research and development project aimed at addressing key questions in NASA’s effort to anticipate, understand, and ultimately support the emerging high-speed commercial flight market. The current project is a continuation of the Life Cycle Cost Modeling of High-Speed Commercial Aircraft1 , which is a follow-on to a 2021 study led by Deloitte and SpaceWorks entitled Commercial Hypersonic Transportation Market Study2 . Based in part on the recommendations of these prior studies, the objectives of this current effort were to expand the trade space to include Mach 1.5 aircraft and conduct additional trade studies. These included utilizing tech stops to extend serviceable range between city pairs, mixed aircraft fleets based on market size, flight scheduling to maximize value of the travel opportunity, and scenarios with multiple service operators. Additionally, SpaceWorks conducted new market surveys and research to update air passengers’ willingness-to-pay for highspeed flights given the changes in macroeconomic conditions since the start of the Commercial Hypersonic Transportation Market Study with Deloitte. Ultimately, the new data and capability to evaluate all the trade studies were implemented in a new simulation environment called MIDAS (Multi-market Integrated Dynamic Aerospace Simulation). This sophisticated tool, implemented using AnyLogic software, utilizes agent-based and discrete event simulation (DES) techniques to provide highly detailed analysis and assessment of the high-speed aircraft market problem.

high-speed↗

Simulation Planning Using Component Based Cost Model

Successful simulations for scientific discovery on high-performance computing platforms require careful planning, including verification of specific application configuration and runtime parameters, estimation of resource requirements, and steering and monitoring of the simulation. However, simulation planning is an aspect of scientific computing that is extremely sparse in available literature or training. In this paper we focus on the resource management aspect of such planning through formulation of a component-based cost model. We illustrate the methodology and formulation through FLASH, a highly configurable simulation code used in multiple scientific domains.

Dubey, Anshu↗

Proposed reliability cost model

The research investigations which were involved in the study include: cost analysis/allocation, reliability and product assurance, forecasting methodology, systems analysis, and model-building. This is a classic example of an interdisciplinary problem, since the model-building requirements include the need for understanding and communication between technical disciplines on one hand, and the financial/accounting skill categories on the other. The systems approach is utilized within this context to establish a clearer and more objective relationship between reliability assurance and the subcategories (or subelements) that provide, or reenforce, the reliability assurance for a system. Subcategories are further subdivided as illustrated by a tree diagram. The reliability assurance elements can be seen to be potential alternative strategies, or approaches, depending on the specific goals/objectives of the trade studies. The scope was limited to the establishment of a proposed reliability cost-model format. The model format/approach is dependent upon the use of a series of subsystem-oriented CER's and sometimes possible CTR's, in devising a suitable cost-effective policy.

Delionback, L. M.↗

Framework for Unified Systems Engineering and Design of Wind Plants (FUSED-Wind) cost models and case analyzer [SWR-14-25]

Framework for Unified Systems Engineering and Design of Wind Plants ( FUSED-Wind) is an open-source framework for multi-disciplinary optimisation and analysis (MDAO) of wind energy systems, developed jointly by DTU and NREL. The framework is designed as an extension to the NASA developed OpenMDAO, and defines key I/O elements and methods necessary for wiring together different simulation codes in order to achieve a system level analysis capability of wind turbine plants with multiple levels of fidelity. NREL and DTU have developed independent interfaces to their respective simulation codes and cost models (e.g. FAST/CCBlade, HAWC2/BECAS) with the aim of offering an environment where these codes can be used interchangeably. The open source nature of the framework enables third parties to develop interfaces to their own tools, either replacing or extending those offered by DTU and NREL.

Dykes, Katherine↗

NASA's X-Plane Database and Parametric Cost Model v 2.0

The NASA Armstrong Cost Engineering Team with technical assistance from NASA HQ (SID)has gone through the full process in developing new CERs from Version #1 to Version #2 CERs. We took a step backward and reexamined all of the data collected, such as dependent and independent variables, cost, dry weight, length, wingspan, manned versus unmanned, altitude, Mach number, thrust, and skin. We used a well- known statistical analysis tool called CO$TAT instead of using "R" multiple linear or the "Regression" tool found in Microsoft Excel(TradeMark). We setup an "array of data" by adding 21" dummy variables;" we analyzed the standard error (SE) and then determined the "best fit." We have parametrically priced-out several future X-planes and compared our results to those of other resources. More work needs to be done in getting "accurate and traceable cost data" from historical X-plane records!

life cycle cost↗