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Valuing Electricity Storage with Production Cost Modeling Presentation.
Abstract not provided.
Analysis Modeling Cost of Energy and Policy Impact: Wind Vision 2014.
Abstract not provided.
Development of an Obsolescence Cost Model for Nuclear Power Plants
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Gen 3 Particle Pilot Plant (G3P3): Quantifying System Benefits through Production Cost Modeling (full paper).
Abstract not provided.
Satellite servicing mission preliminary cost estimation model
The cost model presented is a preliminary methodology for determining a rough order-of-magnitude cost for implementing a satellite servicing mission. Mission implementation, in this context, encompassess all activities associated with mission design and planning, including both flight and ground crew training and systems integration (payload processing) of servicing hardward with the Shuttle. A basic assumption made in developing this cost model is that a generic set of servicing hardware was developed and flight tested, is inventoried, and is maintained by NASA. This implies that all hardware physical and functional interfaces are well known and therefore recurring CITE testing is not required. The development of the cost model algorithms and examples of their use are discussed.
Optical Telescope Assembly Cost Estimating Model
Parametric cost models can be used by designers and project managers to compare cost between major architectural cost drivers and allow high-level design trades; enable cost-benefit analysis for technology development investment; and, provide a basis for estimating total project cost between related concepts. The NASA Marshall Space Flight Center has developed a 5- parameter cost model that explains 93% (Adjusted R2) of the cost variation in a database of 46 total ground and space telescope assemblies. This model can be used to estimate the most probably cost for the Habitable Exoplanet Telescope Assembly.
Modeling the Cost of CO2 Saline Storage on a Regional and National Level
This poster presents the results of using the FECM/NETL CO2 Saline Storage Cost Model (CO2_S_COM) to evaluate the cost of saline storage in potential storage formations in the lower 48 U.S. states. Costs were calculated for 314 saline storage formations in the CO2_S_COM geologic property database. These results were used to generate national and regional cost-supply curves. In addition, a sensitivity analysis was performed that quantified how modifying several input variables in CO2_S_COM affected the costs. Poster presented (virtual) at the 2024 AGU Conference, December 9-13, 2024, Washington, D.C.
Software Cost-Estimation Model
Software Cost Estimation Model SOFTCOST provides automated resource and schedule model for software development. Combines several cost models found in open literature into one comprehensive set of algorithms. Compensates for nearly fifty implementation factors relative to size of task, inherited baseline, organizational and system environment and difficulty of task.
The Application of Architecture Frameworks to Modelling Exploration Operations Costs
Developments in architectural frameworks and system-of-systems thinking have provided useful constructs for systems engineering. DoDAF concepts, language, and formalisms, in particular, provide a natural way of conceptualizing an operations cost model applicable to NASA's space exploration vision. Not all DoDAF products have meaning or apply to a DoDAF inspired operations cost model, but this paper describes how such DoDAF concepts as nodes, systems, and operational activities relate to the development of a model to estimate exploration operations costs. The paper discusses the specific implementation to the Mission Operations Directorate (MOD) operational functions/activities currently being developed and presents an overview of how this powerful representation can apply to robotic space missions as well.
NASA Software Cost Estimation Model: An Analogy Based Estimation Model
The cost estimation of software development activities is increasingly critical for large scale integrated projects such as those at DOD and NASA especially as the software systems become larger and more complex. As an example MSL (Mars Scientific Laboratory) developed at the Jet Propulsion Laboratory launched with over 2 million lines of code making it the largest robotic spacecraft ever flown (Based on the size of the software). Software development activities are also notorious for their cost growth, with NASA flight software averaging over 50% cost growth. All across the agency, estimators and analysts are increasingly being tasked to develop reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods there is very little focus on the use of models based on analogy and clustering algorithms. In this paper we summarize our findings on effort/cost model estimation and model development based on ten years of software effort estimation research using data mining and machine learning methods to develop estimation models based on analogy and clustering. The NASA Software Cost Model performance is evaluated by comparing it to COCOMO II, linear regression, and K- nearest neighbor prediction model performance on the same data set.
Development and validation of chemistry agnostic flow battery cost performance model and application to nonaqueous electrolyte systems: Chemistry agnostic flow battery cost performance model
A chemistry agnostic cost performance model is described for a nonaqueous flow battery. The model predicts flow battery performance by estimating the active reaction zone thickness at each electrode as a function of current density, state of charge, and flow rate using measured data for electrode kinetics, electrolyte conductivity, and electrode-specific surface area. Validation of the model is conducted using a 4kW stack data at various current densities and flow rates. This model is used to estimate the performance of a nonaqueous flow battery with electrode and electrolyte properties used from the literature. The optimized cost for this system is estimated for various power and energy levels using component costs provided by vendors. The model allows optimization of design parameters such as electrode thickness, area, flow path design, and operating parameters such as power density, flow rate, and operating SOC range for various application duty cycles. A parametric analysis is done to identify components and electrode/electrolyte properties with the highest impact on system cost for various application durations. A pathway to 100$kWh -1 for the storage system is identified.
Data Management Technology Survey and Recommendation
The Data Management Plan (DMP) document already released describes the architecture and plan for developing the data management framework needed by the Carbon Capture Simulation Initiative (CCSI) toolset. The CCSI toolset includes: experimental data, physical property methods and parameters, empirical correlations, validation data set, models, simulation inputs and outputs, reduced-order models, cost models, risk models, uncertainty estimation, etc. Each tool in the toolset requires and generates data, and the data management system organizes and stores the data. The data management framework will be driven by end-users and interact with CCSI workflow components such as Turbine. This document reports on the technology survey completed as the first step in the Data Management Plan. It also provides recommendations for a path forward based on the survey results.
Comparative analysis for various redox flow batteries chemistries using a cost performance model
A robust performance-based cost model is developed for all-vanadium, iron-vanadium and iron chromium redox flow batteries. Systems aspects such as shunt current losses, pumping losses and thermal management are accounted for. The objective function, set to minimize system cost, allows determination of stack design and operating parameters such as current density, flow rate and depth of discharge (DOD). Component costs obtained from vendors are used to calculate system costs for various time frames. A 2 kW stack data was used to estimate unit energy costs and compared with model estimates for the same size electrodes. The tool has been shared with the redox flow battery community to both validate their stack data and guide future direction.
Software cost/resource modeling: Deep space network software cost estimation model
A parametric software cost estimation model prepared for JPL deep space network (DSN) data systems implementation tasks is presented. The resource estimation model incorporates principles and data from a number of existing models, such as those of the General Research Corporation, Doty Associates, IBM (Walston-Felix), Rome Air Force Development Center, University of Maryland, and Rayleigh-Norden-Putnam. The model calibrates task magnitude and difficulty, development environment, and software technology effects through prompted responses to a set of approximately 50 questions. Parameters in the model are adjusted to fit JPL software lifecycle statistics. The estimation model output scales a standard DSN work breakdown structure skeleton, which is then input to a PERT/CPM system, producing a detailed schedule and resource budget for the project being planned.
Photovoltaic Manufacturing Consortium (PVMC) – Enabling America’s Solar Revolution
The U.S. Photovoltaic Manufacturing Consortium (US-PVMC) is an industry-led consortium which was created with the mission to accelerate the research, development, manufacturing, field testing, commercialization, and deployment of next-generation solar photovoltaic technologies. Formed as part of the U.S. Department of Energy's (DOE) SunShot initiative, and headquartered in New York State, PVMC is managed by the State University of New York Polytechnic Institute (SUNY Poly) at the Colleges of Nanoscale Science and Engineering. PVMC is a hybrid of industry-led consortium and manufacturing development facility, with capabilities for collaborative and proprietary industry engagement. Through its technology development programs, advanced manufacturing development facilities, system demonstrations, and reliability and testing capabilities, PVMC has demonstrated itself to be a recognized proving ground for innovative solar technologies and system designs. PVMC comprises multiple locations, with the core manufacturing and deployment support activities conducted at the Solar Energy Development Center (SEDC), and the core Si wafering and metrology technologies being headed out of the University of Central Florida. The SEDC provides a pilot line for proof-of-concept prototyping, offering critical opportunities to demonstrate emerging concepts in PV manufacturing, such as evaluations of innovative materials, system components, and PV system designs. The facility, located in Halfmoon NY, encompasses 40,000 square feet of dedicated PV development space. The infrastructure and capabilities housed at PVMC includes PV system level testing at the Prototype Demonstration Facility (PDF), manufacturing scale cell & module fabrication at the Manufacturing Development Facility (MDF), cell and module testing, reliability equipment on its PV pilot line, all integrated with a PV performance database and analytical characterizations for PVMC and its partners test and commercial arrays. Additional development and deployment support are also housed at the SEDC, such as cost modeling and cost model based development activities for PV and thin film modules, components, and system level designs for reduced LCOE through lower installation hardware costs, labor reductions, soft costs and reduced operations and maintenance costs. The progression of the consortium activities started with infrastructure and capabilities build out focused on CIGS thin film photovoltaics, with a particular focus on flexible cell and module production. As marketplace changes and partners objectives shifted, the consortium shifted heavily towards deployment and market pull activities including Balance of System, cost modeling, and installation cost reduction efforts along with impacts to performance and DER operational costs. The consortium consisted of a wide array of PV supply chain companies from equipment and component suppliers through national developers and installers with a particular focus on commercial scale deployments (typically 25 to 2MW installations). With DOE funding ending after the fifth budget period, the advantages and disadvantages of such a consortium is detailed along with potential avenues for self-sustainability is reviewed.
Developing a New Model to Estimate the Costs to Decommission DOE's Active Facilities - 16368
The Active Facilities Data Collection System (AFDCS) is a major means the U.S. Department of Energy (DOE or Department) uses to estimate its out-year environmental liability for the active and surplus facilities across the Department. The previous AFDCS cost model was based on cost assumptions that date back to the mid-1990s. The model is being replaced with a model that reflects more recent facility disposition experience and costs. DOE's Office of Environmental Management's (DOE-EM) historical cost collection database provides the basis for the new AFDCS cost model. This paper describes the process that was used to update the AFDCS facility data inputs, analyze this data, and formulate historical costs and parameters. This process created a robust and reliable cost model that will provide DOE with a valid estimate of the facilities' disposition costs. (authors)
Cost estimation for solid waste management in industrialising regions - Precedents, problems and prospects
Highlights: Black-Right-Pointing-Pointer We review cost estimation approaches for solid waste management. Black-Right-Pointing-Pointer Unit cost method and benchmarking techniques used in industrialising regions (IR). Black-Right-Pointing-Pointer Variety in scope, quality and stakeholders makes cost estimation challenging in IR. Black-Right-Pointing-Pointer Integrate waste flow and cost models using cost functions to improve cost planning. - Abstract: The importance of cost planning for solid waste management (SWM) in industrialising regions (IR) is not well recognised. The approaches used to estimate costs of SWM can broadly be classified into three categories - the unit cost method, benchmarking techniques and developing cost models using sub-approaches such as cost and production function analysis. These methods have been developed into computer programmes with varying functionality and utility. IR mostly use the unit cost and benchmarking approach to estimate their SWM costs. The models for cost estimation, on the other hand, are used at times in industrialised countries, but not in IR. Taken together, these approaches could be viewed as precedents that can be modified appropriately to suit waste management systems in IR. The main challenges (or problems) one might face while attempting to do so are a lack of cost data, and a lack of quality for what data do exist. There are practical benefits to planners in IR where solid waste problems are critical and budgets are limited.