NREL U.S. Solar Photovoltaic System Cost Benchmark Q1 2016 Report
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Excel data file for the U.S. Solar Photovoltaic System Cost Benchmark Q1 2016 Report
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The proposal had outlined a year for program conversion, a year for testing and debugging, and two years for numerical experiments. We kept to that schedule. In first (partial) year, author designed a finite element for isostatic thin-shell deformation on a sphere, derived all of its algebraic and stiffness properties, and embedded it in a new finite element code which derives its basic solution strategy (and some critical subroutines) from earlier flat-Earth codes. Also designed and programmed a new fault element to represent faults along plate boundaries. Wrote a preliminary version of a spherical graphics program for the display of output. Tested this new code for accuracy on individual model plates. Made estimates of the computer-time/cost efficiency of the code for whole-earth grids, which were reasonable. Finally, converted an interactive graphical grid-designer program from Cartesian to spherical geometry to permit the beginning of serious modeling. For reasons of cost efficiency, models are isostatic, and do not consider the local effects of unsupported loads or bending stresses. The requirements are: (1) ability to represent rigid rotation on a sphere; (2) ability to represent a spatially uniform strain-rate tensor in the limit of small elements; and (3) continuity of velocity across all element boundaries. Author designed a 3-node triangle shell element which has two different sets of basis functions to represent (vector) velocity and all other (scalar) variables. Such elements can be shown to converge to the formulas for plane triangles in the limit of small size, but can also applied to cover any area smaller than a hemisphere. The difficult volume integrals involved in computing the stiffness of such elements are performed numerically using 7 Gauss integration points on the surface of the sphere, beneath each of which a vertical integral is performed using about 100 points.
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Demand response may be a valuable flexible resource for low-carbon electric power grids. However, there are as many types of possible demand response as there are ways to use electricity, making demand response difficult to study at scale in realistic settings. This talk reviews our state of knowledge regarding the potential value of demand response in several example systems as a function of increasing levels of wind and solar power, sometimes drawing on the analogy between demand response and storage. Overall, we find demand response to be promising, but its potential value is very system dependent. Furthermore, demand response, like storage, can easily saturate ancillary service markets.
An analytical cost-performance model for a ground-based optical communications receiving telescope is presented. The model considers costs of existing telescopes as a function of diameter and field of view. This, coupled with communication performance as a function of receiver diameter and field of view, yields the appropriate telescope cost versus communication performance curve.
In March 2018, Lawrence Berkeley National Laboratory (LBNL) and Nexant released a significant upgrade of the Interruption Cost Estimate (ICE) Calculator. While most of the improvements involved a modernization of the user interface, there are two notable modifications to the underlying econometric models. LBNL and Nexant documented the original models and customer interruption cost meta-analysis in a 2009 report. They subsequently revised the meta-analysis and econometric models for the ICE Calculator in 2015, as documented in an updated report. The models for the current version of the ICE Calculator are based on two additional modifications summarized in this update.
The peculiar nature of whole slide imaging (WSI), digitizing conventional glass slides to obtain multiple high resolution images which capture microscopic details of a patient’s histopathological features, has garnered increased interest from the computer vision research community over the last two decades. Given the unique computational space and time complexity inherent to gigapixel-size whole slide image data, researchers have proposed novel machine learning algorithms to aid in the performance of diagnostic tasks in clinical pathology. One effective algorithm represents a Whole slide image as a bag of smaller image patches, which can be represented as low-dimension image patch embeddings. Weakly supervised deep-learning methods, such as cluster-constrained-attention multiple instance learning (CLAM), have shown promising results when combined with image patch embeddings. While traditional ensemble classifiers yield improved task performance, such methods come with a steep cost in model complexity. Through knowledge distillation, it is possible to retain some performance improvements from an ensemble, while minimizing costs to model complexity. In this work, we implement a weakly supervised ensemble using clustering-constrained-attention multiple-instance learners (CLAM), which uses attention and instance-level clustering to identify task salient regions and feature extraction in whole slides. By applying logit-based and attention-based knowledge distillation, we show it is possible to retain some performance improvements resulting from the ensemble at zero cost to model complexity.
Underlying each of the Department of Energy's (DOE's) federal appliance and equipment standards are a set of complex analyses of the projected costs and benefits of regulation. Any new or amended standard must be designed to achieve significant additional energy conservation, provided that it is technologically feasible and economically justified (42 U.S.C. 6295(o)(2)(A)). A proposed standard is considered economically justified when its benefits exceed its burdens, as represented by the projected net present value of costs and benefits. DOE performs multiple analyses to evaluate the balance of costs and benefits of commercial appliance and equipment e efficiency standards, at the national and individual building or business level, each framed to capture different nuances of the complex impact of standards on the commercial end user population. The Life-Cycle Cost (LCC) analysis models the combined impact of appliance first cost and operating cost changes on a representative commercial building sample in order to identify the fraction of customers achieving LCC savings or incurring net cost at the considered efficiency levels.1 Thus, the choice of commercial discount rate value(s) used to calculate the present value of energy cost savings within the Life-Cycle Cost model implicitly plays a key role in estimating the economic impact of potential standard levels.2 This report is intended to provide a more in-depth discussion of the commercial discount rate estimation process than can be readily included in standard rulemaking Technical Support Documents (TSDs).
“The cost for blower testing is high, because it is labor intensive, and it may disrupt occupants in multiple units. This high cost and disruption deter program participants, and dissuade them from pursuing energy improvements that would trigger air leakage testing, such as improvements to the building envelope.” This statement found in a 2012 report by Heschong Mahone Group for several California interests emphasizes the importance of reducing the cost and complexity of blower testing in multifamily buildings. Energy efficiency opportunities are being bypassed. The cost of single blower testing is on the order of $300. The cost for guarded blower door testing—the more appropriate test for assessing energy savings opportunities—could easily be six times that, and that’s only if you have the equipment and simultaneous access to multiple apartments. Thus, the proper test is simply not performed. This research seeks to provide an algorithm for predicting the guarded blower door test result based upon a single, total blower door test.
Delta launch vehicle capabilities, constraints and costs for Straight 8 model 2914 series
This analysis evaluated integrated CCS costs (i.e., capture, transport, and storage) from the perspective of a CO 2 source. Capture costs for sources with annual CO 2 capture rates from 0.65 to 3.90 Mt were based on two NETL reports. Transportation costs from source to storage reservoir were modeled for two pipelines systems (dedicated and trunkline) using the FE/NETL CO 2 Transport Cost Model. Storage costs were modeled in dome and regional dip structural settings for two reservoirs in the Rose Run Formation, three within the Mt. Simon, one in the Lower Tuscaloosa, and one in the Frio using the FE/NETL CO 2 Saline Storage Cost Model. A paper with the same name and information as well as additional details on this analysis was published in The International Journal of Greenhouse Gas Control along with a supplementary document that provides additional material (i.e., key parameters used in the models for obtaining transport and storage costs and CCS cost and pipeline results).
A useful perspective on the economic value of simulation in engineering comes from considering the role simulation plays in constructing a system. We propose a conceptual model that combines an embryonic concept of the value of an information bit with cost estimation tools used in software engineering. The model provides an economic justification for the common conception that models should be built to address specific questions rather than to comprehensively represent a referent system. Extending these ideas, we offer a model for the incremental value of parallel execution to explain why simulation applications that take advantage of sophisticated parallel discrete event simulation tools form a relatively narrow niche despite the ubiquity of parallel computing hardware. The proposed model enables us to bring value of information criteria into model development and to make predictions about the future of parallel simulation applications.
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The cost and effectiveness of developing land cover information derived from Landsat imagery for hydrologic studies are compared with the cost and effectiveness of conventional sources. The analysis shows that the conventional and Landsat methods are nearly equally effective in providing adequate land cover data for hydrologic studies. The total cost effectiveness analysis demonstrates that the conventional method is cost effective for a study area of less than 26 sq km and that the Landsat method is to be preferred for areas of more than 26 sq km.
Energy modeling of decarbonized scenarios in integrated energy systems requires nuclear energy parameters that are critical for forecasting, modeling and cost structure analysis. Using updated real-world data has always been a challenge to estimate current nuclear reactors costs and deployment scenarios. Given this, an updated set of parameters for overnight capital costs and operation and maintenance costs are estimated for the Net Zero World initiative using recent reports that provided a vast set of open sources data inputs. This paper follows the methodology developed in the Net Zero World report and applies the new ranges estimated in the Gateway for Accelerated Innovation in Nuclear report that address many of the current challenges in obtaining accurate cost data for advanced nuclear concepts. The final goal is to provide new estimates of the overnight capital costs and operational costs for different countries. The present paper improves the earlier capital cost estimations, building on recent literature that aims to obtain accurate data for modeling and simulation to enhance energy system evaluations and support decision-making in areas like de-carbonization and capacity expansion. Finally, the paper compares the new cost estimates with the old cost results.
This report benchmarks U.S. solar photovoltaic (PV) system installed costs as of the first quarter of 2017 (Q1 2017). We use a bottom-up methodology, accounting for all system and projectdevelopment costs incurred during the installation to model the costs for residential, commercial, and utility-scale systems. In general, we attempt to model the typical installation techniques and business operations from an installed-cost perspective. Costs are represented from the perspective of the developer/installer; thus, all hardware costs represent the price at which components are purchased by the developer/installer, not accounting for preexisting supply agreements or other contracts. Importantly, the benchmark also represents the sales price paid to the installer; therefore, it includes profit in the cost of the hardware, 1 along with the profit the installer/developer receives, as a separate cost category. However, it does not include any additional net profit, such as a developer fee or price gross-up, which is common in the marketplace. We adopt this approach owing to the wide variation in developer profits in all three sectors, where project pricing is highly dependent on region and project specifics such as local retail electricity rate structures, local rebate and incentive structures, competitive environment, and overall project or deal structures. Finally, our benchmarks are national averages weighted by state installed capacities.