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At least 631 records · Page 35

2018 Research Highlight in Manufacturing: Global Value Chain and Manufacturing Analysis on Geothermal Power Plant Turbines

Currently, geothermal project developers customize the size of the power plant to fit the resource being developed. The turbine is designed and sized to optimize efficiency and resource utilization for electricity production; most often, other power plant components are then chosen to complement the turbine design. These custom turbine designs demand one-off manufacturing processes, which result in higher manufacturing setup costs, longer lead-times, and higher capital costs overall in comparison to larger-volume line manufacturing processes. In contrast, turbines produced in standard increments, manufactured in larger volumes, could result in lower costs per turbine. In this study, we developed a manufacturing cost model to identify requirements for equipment, facilities, raw materials, and labor. Then we used discounted cash flow (DCF) analysis to calculate the minimum sustainable price (MSP). We analyzed three different cases 1) 1 MWe geothermal ORC turboexpander 2) 5 MWe ORC turboexpander and 3) 20 MWe geothermal steam turbine, and calculated the cost of manufacturing the major components, such as the impellers/blades, shaft/rotor, nozzles, inlet guide lanes, disks, and casings. The results showed that MSP could highly vary between 893 $/kW and 30 $/kW based on turbine size, standardization and volume of manufacturing. The analysis also showed that the economy of scale applies both to the size of the turbine and the number manufactured in a single run. As an example, the unit price of a 5 MW standard design turbine could be 150 $/W cheaper than the custom design. Sensitivity analysis indicated that these savings come largely from reduced labor costs for design and engineering and manufacturing setup. In addition to manufacturing cost savings, there is a delivery time saving up to 10 months, which could have a positive effect to construction financing operation time. Another advantage of these standard turbines is their adaptability to different geothermal systems by operating at off-design conditions. We also modeled off-design turbine efficiencies within the commercially-favorable operating range of a standard ORC compared to custom-designed ORC equipment. Than we used these performance calculations and power output capacities in a discounted cash flow (DCF) analysis of plant operations and financing, thereby creating representative techno economic models of a total geothermal power plant. I this scope we used NREL's System Advisor model (SAM) and performed DCF analysis of standard and custom design turbines using results from IPSEpro over range of temperatures of interest. In this scope 63 different off-design cases were analyzed. This helped us to answer the question; 'Can today`s capital cost savings compensate the future revenue losses due to lower electricity generation?' The results showed that, the net capital cost savings for the modeled 5 MW case study may reach up to +$1,298,672. Also, the difference between NPV of standard design and custom design turbine could reach up to +$733,940. To sum up, when all the things mentioned above are taken into consideration, it can be said that, the standard turbines are competitive over a wide range of temperatures and flow rates and the give positive NPV differences for certain cases near their design point.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Development of a funding, cost, and spending model for satellite projects

The need for a predictive budget/funging model is obvious. The current models used by the Resource Analysis Office (RAO) are used to predict the total costs of satellite projects. An effort to extend the modeling capabilities from total budget analysis to total budget and budget outlays over time analysis was conducted. A statistical based and data driven methodology was used to derive and develop the model. Th budget data for the last 18 GSFC-sponsored satellite projects were analyzed and used to build a funding model which would describe the historical spending patterns. This raw data consisted of dollars spent in that specific year and their 1989 dollar equivalent. This data was converted to the standard format used by the RAO group and placed in a database. A simple statistical analysis was performed to calculate the gross statistics associated with project length and project cost ant the conditional statistics on project length and project cost. The modeling approach used is derived form the theory of embedded statistics which states that properly analyzed data will produce the underlying generating function. The process of funding large scale projects over extended periods of time is described by Life Cycle Cost Models (LCCM). The data was analyzed to find a model in the generic form of a LCCM. The model developed is based on a Weibull function whose parameters are found by both nonlinear optimization and nonlinear regression. In order to use this model it is necessary to transform the problem from a dollar/time space to a percentage of total budget/time space. This transformation is equivalent to moving to a probability space. By using the basic rules of probability, the validity of both the optimization and the regression steps are insured. This statistically significant model is then integrated and inverted. The resulting output represents a project schedule which relates the amount of money spent to the percentage of project completion.

Johnson, Jesse P.↗

Planning Optimization for Inductively Charged On-demand Automated Electric Shuttles Project at Greenville, South Carolina

Wireless charging technology presents an ideal fit for autonomous electric vehicles for realizing a fully automated system (vehicle and charger). This paper presents a planning optimization analysis for a pilot project of in-route wireless charging infrastructure serving fixed-route on-demand shared automated electric shuttles (SAESs) at Greenville, South Carolina, USA. A single-objective non-linear mixed integer system planning optimization problem is formulated. A comprehensive cost model representing the overall inductively charged SAESs system is developed, considering road construction, power electronics and materials, traction battery, and installation costs. The optimization problem is solved to determine the best combination of the system key design parameters (number and allocations of wireless chargers, charging power level, track length and on-board battery capacity) that show the most cost-effective solution and allow the SAESs to achieve charge-sustaining operation. The planning platform incorporates representative simulated traffic data (driving speed and routes) for four SAESs in the Greenville using the Simulation of Urban Mobility tool. These data are fed to a vehicle powertrain model and a wireless charger power model to predict the battery power, energy and state-of-charge profiles, which are provided to the search algorithm to assess the design objectives under specific constraints. Finally, the results indicate that implementing high-power (100 kW) wireless charger at a few designated stops for fixed-route SAESs with the proper track length allows the vehicles to realize charge-sustaining operation, infinite range, and zero recharge downtime, with a significant reduction in the on-board battery (36%) and road coverage (69%), at minimum cost.

33 ADVANCED PROPULSION SYSTEMS↗

FLOW BATTERY COST AND COMMERCIALIZATION TOOL (FlowBaCC) v.1.0

The Flow Battery Cost and Commercialization Tool (FlowBaCC) is a python-based framework used to project the costs and commercialization timelines for redox flow batteries. FlowBaCC combines learning curves for component costs and performance with adoption curves for market diffusion to project future system costs. The tool uses the bottom-up, spreadsheet-based Battery Performance and Cost Model for Flow Batteries (BatPaC-Flow) as the engine to translate learning curve inputs into full system costs. FlowBaCC provides capital costs and levelized costs of energy storage. The tool enables scenario analysis, sensitivity analysis, and uncertainty quantification (via grid and Monte Carlo methods).

Fu, Xiaoxu [Argonne National Laboratory (ANL), Arg↗

Industry survey of space system cost benefits from New Ways Of Doing Business

The cost of designing, building and operating space system hardware has always been expensive. Small quantities of specialty parts escalate engineering design, production and operations cost. Funding cutbacks and shrinking revenues dictate aggressive cost saving programs. NASA's highest priority is providing economical transportation to and from space. Over the past three decades NASA has seen technological advances that provide grater efficiencies in designing, building, and operating of space system hardware. As future programs such as NLS, LUTE and SEI begin, these greater efficiencies and cost savings should be reflected in the cost models. There are several New Ways Of Doing Business (NWODB) which, when fully implemented will reduce space system costs. These philosophies and/or culture changes are integrated in five areas: (1) More Extensive Pre-Phase C/D & E, (2) Multi Year Funding Stability, (3) Improved Quality, Management and Procurement Processes, (4) Advanced Design Methods, and (5) Advanced Production Methods. Following is an overview of NWODB and the Cost Quantification Analysis results using an industry survey, one of the four quantification techniques used in the study. The NWODB Cost Quantification Analysis is a study performed at Marshall Space Flight Center by the Engineering Cost Group, Applied Research Incorporated and Pittsburg State University. This study took place over a period of four months in mid 1992. The purpose of the study was to identify potential NWODB which could lead to improved cost effectiveness within NASA and to quantify potential cost benefits that might accrue if these NWODB were implemented.

Rosmait, Russell L.↗

Novel evaporator architecture with entrance-length crossflow-paths for supercritical Organic Rankine Cycles

Here in this article, a novel geometry is proposed for evaporators that are used in Supercritical Organic Rankine Cycles. The proposed geometry consists of successive plenums at several length-scale levels, creating a multi-scale heat exchanger (HX). The channels at the lowest length-scale levels were considered to have their length determined by the thermal entrance-length. Numerical simulations based on turbulent flow correlations for supercritical R134a and water were used to evaluate the performance of heat exchangers. Using the data on pumping power and area of heat exchange, the total present cost was evaluated using a cost model for shell-and-tube heat exchangers. With respect to the shell-and-tube baseline case, the cost per heat load and total costs of new HXs is lowered by approximately 20–26% and 15–30%, respectively. This reduction in present costs of the new HXs were found to be attributed to higher operational costs for the shell-and-tube HXs, as evidenced by the higher pumping power, as well their capital investment costs. The cost savings in the new HX designs compared to those of the shell-and-tube HXs, at similar heat load performance, indicate that the new HX architectures proposed in this paper are valid alternatives to traditional HX designs.

42 ENGINEERING↗

How Can Probabilistic Solar Power Forecasts Be Used to Lower Costs and Improve Reliability in Power Spot Markets? A Review and Application to Flexiramp Requirements

Net load uncertainty in electricity spot markets is rapidly growing. There are five general approaches by which system operators and market participants can use probabilistic forecasts of wind, solar, and load to help manage this uncertainty. These include operator situation awareness, resource risk hedging, reserves procurement, definition of contingencies, and explicit stochastic optimization. We review these approaches, and then provide a case study in which a method for using probabilistic solar forecasts to define needs for reserves is developed and evaluated. The case study has three parts. First, we describe building blocks for enhancing the Watt-Sun solar forecasting system to produce probabilistic irradiance and power forecasts. Second, relationships between Watt-Sun forecasts for multiple sites in California and the system's need for flexible ramp capability (flexiramp) are defined by machine learning and statistical methods. Third, the performance of present methods to defining flexiramp requirements, which are not conditioned on weather and renewables forecasts, is compared with that of probabilistic solar forecast-based requirements, using a multi-timescale production costing model with an 1820-bus representation of the WECC power system. Significant potential savings in fuel and flexiramp procurement costs from using solar-informed reserve requirements are found.

14 SOLAR ENERGY↗

Selective Area Growth of GaAs on Si Patterned Using Nanoimprint Lithography

Heteroepitaxial selective area growth (SAG) of GaAs on patterned Si substrates is a potential low-cost approach to integrate III-V and Si materials for tandem or multijunction solar cells. The use of nanoscale openings in a dielectric material can minimize nucleation-related defects and allow thinner buffer layers to be used to accommodate lattice mismatch between Si and an epitaxial III-V layer. For photovoltaic applications, the cost of patterning and growth, as well as the impact on the performance of the Si bottom cell must be considered. We present preliminary results on the use of soft nanoimprint lithography (SNIL) to create patterned nucleation templates for the heteroepitaxial SAG of GaAs on Si. We demonstrate that SNIL patterning of passivating layers on the Si substrate improves measured minority carrier properties relative to unprotected Si. Cost modeling of the SNIL process shows that adding a patterning step only adds a minor contribution to the overall cost of a tandem III-V/Si solar cell, and can enable significant savings if it enables thinner buffer layers.

14 SOLAR ENERGY↗

Power System Operational Impacts of Electric Vehicle Dynamic Wireless Charging

The electrification of the transportation sector poses an opportunity for reducing greenhouse gas (GHG) emissions from passenger vehicles. Electric vehicle (EV) charging through dynamic wireless power transfer (DWPT), known as roadway electrification, could shift EV demand profiles to better coincide with renewable electricity generation. However, this would be a very large new load and few studies evaluate the regional impacts of DWPT charging in a power transmission system. This paper defines methods that address dataset generation for passenger vehicle trips and models to evaluate regional impacts for this emerging technology. Household vehicle miles traveled (VMT) data form localized EV demand profiles through discrete-event simulation. This data serves as exogenous inputs for a Production Cost Model (PCM) of a synthetic transmission system based on the Electric Reliability Council of Texas's (ERCOT) network. EV charging methods are compared for both a 2018 baseline generation mixture and a high-renewable generation case incorporating 20 GW of installed solar photovoltaic (PV) capacity. The PCM employs unit commitment and economic dispatch (UC&ED) models to compare financial, environmental, and grid reliability impacts from EV charging across passenger EV adoption levels. In-transit charging could reduce grid operational costs by as much as 1.49%, with up to $13.7B saved in annual vehicle operational costs for consumers compared to gas-powered vehicles. Health impacts analysis from power plant and vehicle tailpipe emissions from this study show net health benefits increase by 40% for in-transit charging coupled with high renewable generation. Renewable resources provide an avenue for cost-effective in-transit charging with reduced emissions. The combination of dataset generation and open-source power system modeling establish a foundation for the holistic evaluation of regional DWPT impacts.

dynamic wireless power transfer↗

On-board processing for future satellite communications systems: Satellite-Routed FDMA

A frequency division multiple access (FDMA) 30/20 GHz satellite communications architecture without on-board baseband processing is investigated. Conceptual system designs are suggested for domestic traffic models totaling 4 Gb/s of customer premises service (CPS) traffic and 6 Gb/s of trunking traffic. Emphasis is given to the CPS portion of the system which includes thousands of earth terminals with digital traffic ranging from a single 64 kb/s voice channel to hundreds of channels of voice, data, and video with an aggregate data rate of 33 Mb/s. A unique regional design concept that effectively smooths the non-uniform traffic distribution and greatly simplifies the satellite design is employed. The satellite antenna system forms thirty-two 0.33 deg beam on both the uplinks and the downlinks in one design. In another design matched to a traffic model with more dispersed users, there are twenty-four 0.33 deg beams and twenty-one 0.7 deg beams. Detailed system design techniques show that a single satellite producing approximately 5 kW of dc power is capable of handling at least 75% of the postulated traffic. A detailed cost model of the ground segment and estimated system costs based on current information from manufacturers are presented.

Berk, G.↗

2022 Standard Scenarios Report: A U.S. Electricity Sector Outlook

This report documents the eighth edition of the annual Standard Scenarios. It summarizes 70 forward-looking scenarios of the U.S. electricity sector that have been designed to capture a wide range of possible futures. In August 2022, the United States Congress passed the Inflation Reduction Act (IRA), a law aimed at accelerating U.S. decarbonization, clean energy manufacturing, and deployment of new power and end-use technologies. This year’s scenarios include representations of the main electricity-sector provisions from IRA and the potential impact on electricity demand. The Standard Scenarios are simulated using the Regional Energy Deployment System (ReEDS) model, which projects utility-scale electricity sector evolution for the contiguous United States using a system-wide, least-cost approach subject to policy and operational constraints. A subset of the scenarios are simulated in the PLEXOS production cost model to obtain a broader suite of metrics at the hourly resolution, which are made available through the National Renewable Energy Laboratory’s (NREL’s) annual Cambium data sets. The scenarios can be viewed and downloaded from NREL’s Scenario Viewer. Annual results are available for the full suite of scenarios in the Standard Scenarios projects in the viewer, whereas the Cambium projects contain hourly data for a subset of scenarios. The Standard Scenarios includes a scenario called the Mid-case, which has central or median values for core inputs such as technology costs and fuel prices, moderately paced demand growth averaging 1.3% per year, and electricity sector policies as they existed in September 2022 (including IRA). The remaining 69 scenarios are created by varying inputs such as technology and fuel prices, resource availability, demand growth, whether nascent generation technologies are allowed, and by introducing national decarbonization constraints.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quantifying the Economic and Grid Reliability Impacts of Improved Wind Power Forecasting

Wind power forecasting is an important tool in power system operations to address variability and uncertainty. Accurately doing so is important to reducing the occurrence and length of curtailment, enhancing market efficiency, and improving the operational reliability of the bulk power system. This research quantifies the value of wind power forecasting improvements in the IEEE 118-bus test system as modified to emulate the generation mixes of Midcontinent, California, and New England independent system operator balancing authority areas. To measure the economic value, a commercially available production cost modeling tool was used to simulate the multi-timescale unit commitment (UC) and economic dispatch process for calculating the cost savings and curtailment reductions. To measure the reliability improvements, an in-house tool, FESTIV, was used to calculate the system's area control error and the North American Electric Reliability Corporation Control Performance Standard 2. The approach allowed scientific reproducibility of results and cross-validation of the tools. A total of 270 scenarios were evaluated to accommodate the variation of three factors: generation mix, wind penetration level, and wind fore-casting improvements. The modified IEEE 118-bus systems utilized 1 year of data at multiple timescales, including the day-ahead UC, 4-hour-ahead UC, and 5-min real-time dispatch. The value of improved wind power forecasting was found to be strongly tied to the conventional generation mix, existence of energy storage devices, and the penetration level of wind energy. The simulation results demonstrate that wind power forecasting brings clear benefits to power system operations.

17 WIND ENERGY↗

Operating Reserves in ReEDS

This presentation provides an overview of the formulation for operating reserves in the Regional Energy Deployment System (ReEDS), a capacity expansion model. It describes the three reserve products modeled in ReEDS--regulation, spinning (contingency), and flexibility--and highlights recent updates to the modeling approach, including modifications to how storage provides reserves, the constraints on commitment for generators that provide reserves, and the costs for thermal units to provide spinning reserve. The presentation benchmarks operating reserve provision in ReEDS against comparable simulations in PLEXOS, finding that the improved formulation is different but yields results that are holistically similar to those in production cost modeling. In this presentation we also investigate the impact of different reserve options in the model (e.g., allowing wind and solar to provide operating reserves) on the solution. The results thus far indicate that most switches related to operating reserves exert little influence on the outcome on the results. Future work will continue to explore operating reserves in capacity expansion models, particularly for models with different temporal resolution.

14 SOLAR ENERGY↗

Integrated Computational Materials Engineering (ICME) for Third Generation Advanced High-Strength Steel Development

This paper presents an overview of a four-year project focused on development of an integrated computational materials engineering (ICME) toolset for third generation advanced high-strength steels (3GAHSS). Following a brief look at ICME as an emerging discipline within the Materials Genome Initiative, technical tasks in the ICME project will be discussed. Specific aims of the individual tasks are multi-scale, microstructure-based material model development using state-of-the-art computational and experimental techniques, forming, toolset assembly, design optimization, integration and technical cost modeling. The integrated approach is initially illustrated using a 980 grade transformation induced plasticity (TRIP) steel, subject to a two-step quenching and partitioning (Q&P) heat treatment, as an example.

Savic, Vesna↗

Space power distribution system technology. Volume 1: Reference EPS design

The multihundred kilowatt electrical power aspects of a mannable space platform in low Earth orbit is analyzed from a cost and technology viewpoint. At the projected orbital altitudes, Shuttle launch and servicing are technically and economically viable. Power generation is specified as photovoltaic consistent with projected planning. The cost models and trades are based upon a zero interest rate (the government taxes concurrently as required), constant dollars (1980), and costs derived in the first half of 1980. Space platform utilization of up to 30 years is evaluated to fully understand the impact of resupply and replacement as satellite missions are extended. Such lifetimes are potentially realizable with Shuttle servicing capability and are economically desirable.

Decker, D. K.↗

Trade Study: Storing NASA HDF5/netCDF-4 Data in the Amazon Cloud and Retrieving Data Via Hyrax Server Data Server

This study explored three candidate architectures with different types of objects and access paths for serving NASA Earth Science HDF5 data via Hyrax running on Amazon Web Services (AWS). We studied the cost and performance for each architecture using several representative Use-Cases. The objectives of the study were: Conduct a trade study to identify one or more high performance integrated solutions for storing and retrieving NASA HDF5 and netCDF4 data in a cloud (web object store) environment. The target environment is Amazon Web Services (AWS) Simple Storage Service (S3). Conduct needed level of software development to properly evaluate solutions in the trade study and to obtain required benchmarking metrics for input into government decision of potential follow-on prototyping. Develop a cloud cost model for the preferred data storage solution (or solutions) that accounts for different granulation and aggregation schemes as well as cost and performance trades.We will describe the three architectures and the use cases along with performance results and recommendations for further work.

AWS cost↗