Four approaches to modeling multi-junction concentrating photovoltaic system performance are assessed by comparing modeled performance to measured performance. Measured weather, irradiance, and system performance data were collected on two systems over a one month period. Residual analysis is used to assess the models and to identify opportunities for model improvement. Large photovoltaic systems are typically developed as projects which supply electricity to a utility and are owned by independent power producers. Obtaining financing at favorable rates and attracting investors requires confidence in the projected energy yield from the plant. In this paper, various performance models for projecting annual energy yield from Concentrating Photovoltaic (CPV) systems are assessed by comparing measured system output to model predictions based on measured weather and irradiance data. The results are statistically analyzed to identify systematic error sources.
Four approaches to modeling multi-junction concentrating photovoltaic system performance are assessed by comparing modeled performance to measured performance. Measured weather, irradiance, and system performance data were collected on two systems over a one month period. Residual analysis is used to assess the models and to identify opportunities for model improvement.
Problem Statement: (1) Uncertainties in PV system performance and reliability impact business decisions - Project cost and financing estimates, Pricing service contracts and guarantees, Developing deployment and O&M strategies; (2) Understanding and reducing these uncertainties will help make the PV industry more competitive (3) Performance has typically been estimated without much attention to reliability of components; and (4) Tools are needed to assess all inputs to the value proposition (e.g., LCOE, cash flow, reputation, etc.). Goals and objectives are: (1) Develop a stochastic simulation model (in GoldSim) that can represent PV system performance as a function of system design, weather, reliability, and O&M policies; (2) Evaluate performance for an example system to quantify sources of uncertainty and identify dominant parameters via a sensitivity study; and (3) Example System - 1 inverter, 225 kW DC Array latitude tilt (90 strings of 12 modules {l_brace}1080 modules{r_brace}), Weather from Tucumcari, NM (TMY2 with annual uncertainty).
The Fracture-Matrix Transport (FMT) code developed at Sandia National Laboratories solves chemical equilibrium problems using the Pitzer activity coefficient model with a database containing actinide species. The code is capable of predicting actinide solubilities at 25 C in various ionic-strength solutions from dilute groundwaters to high-ionic-strength brines. The code uses oxidation state analogies, i.e., Am(III) is used to predict solubilities of actinides in the +III oxidation state; Th(IV) is used to predict solubilities of actinides in the +IV state; Np(V) is utilized to predict solubilities of actinides in the +V state. This code has been qualified for predicting actinide solubilities for the Waste Isolation Pilot Plant (WIPP) Compliance Certification Application in 1996, and Compliance Re-Certification Applications in 2004 and 2009. We have established revised actinide-solubility uncertainty ranges and probability distributions for Performance Assessment (PA) by comparing actinide solubilities predicted by the FMT code with solubility data in various solutions from the open literature. The literature data used in this study include solubilities in simple solutions (NaCl, NaHCO{sub 3}, Na{sub 2}CO{sub 3}, NaClO{sub 4}, KCl, K{sub 2}CO{sub 3}, etc.), binary mixing solutions (NaCl+NaHCO{sub 3}, NaCl+Na{sub 2}CO{sub 3}, KCl+K{sub 2}CO{sub 3}, etc.), ternary mixing solutions (NaCl+Na{sub 2}CO{sub 3}+KCl, NaHCO{sub 3}+Na{sub 2}CO{sub 3}+NaClO{sub 4}, etc.), and multi-component synthetic brines relevant to the WIPP.
The need for the engineering analysis of systems in which the transport of thermal energy occurs primarily through a conduction process is a common situation. For all but the simplest geometries and boundary conditions, analytic solutions to heat conduction problems are unavailable, thus forcing the analyst to call upon some type of approximate numerical procedure. A wide variety of numerical packages currently exist for such applications, ranging in sophistication from the large, general purpose, commercial codes, such as COMSOL, COSMOSWorks, ABAQUS and TSS to codes written by individuals for specific problem applications. The original purpose for developing the finite element code described here, COYOTE, was to bridge the gap between the complex commercial codes and the more simplistic, individual application programs. COYOTE was designed to treat most of the standard conduction problems of interest with a user-oriented input structure and format that was easily learned and remembered. Because of its architecture, the code has also proved useful for research in numerical algorithms and development of thermal analysis capabilities. This general philosophy has been retained in the current version of the program, COYOTE, Version 5.0, though the capabilities of the code have been significantly expanded. A major change in the code is its availability on parallel computer architectures and the increase in problem complexity and size that this implies. The present document describes the theoretical and numerical background for the COYOTE program. This volume is intended as a background document for the user's manual. Potential users of COYOTE are encouraged to become familiar with the present report and the simple example analyses reported in before using the program. The theoretical and numerical background for the finite element computer program, COYOTE, is presented in detail. COYOTE is designed for the multi-dimensional analysis of nonlinear heat conduction problems. A general description of the boundary value problems treated by the program is presented. The finite element formulation and the associated numerical methods used in COYOTE are also outlined. Instructions for use of the code are documented in SAND2010-0714.
The viscosity of molten salts comprising ternary and quaternary mixtures of the nitrates of sodium, potassium, lithium and calcium was determined experimentally. Viscosity was measured over the temperature range from near the relatively low liquidus temperatures of he individual mixtures to 200C. Molten salt mixtures that do not contain calcium nitrate exhibited relatively low viscosity and an Arrhenius temperature dependence. Molten salt mixtures that contained calcium nitrate were relatively more viscous and viscosity increased as the roportion of calcium nitrate increased. The temperature dependence of viscosity of molten salts containing calcium nitrate displayed curvature, rather than linearity, when plotted in Arrhenius format. Viscosity data for these mixtures were correlated by the Vogel-Fulcher- ammann-Hesse equation.
In a multiyear research agreement with Tenix Investments Pty. Ltd., Sandia has been developing field deployable technologies for detection of biotoxins in water supply systems. The unattended water sensor or UWS employs microfluidic chip based gel electrophoresis for monitoring biological analytes in a small integrated sensor platform. This instrument collects, prepares, and analyzes water samples in an automated manner. Sample analysis is done using the {mu}ChemLab{trademark} analysis module. This report uses analysis results of two datasets collected using the UWS to estimate performance of the device. The first dataset is made up of samples containing ricin at varying concentrations and is used for assessing instrument response and detection probability. The second dataset is comprised of analyses of water samples collected at a water utility which are used to assess the false positive probability. The analyses of the two sets are used to estimate the Receiver Operating Characteristic or ROC curves for the device at one set of operational and detection algorithm parameters. For these parameters and based on a statistical estimate, the ricin probability of detection is about 0.9 at a concentration of 5 nM for a false positive probability of 1 x 10{sup -6}.
The Sierra Toolkit computational mesh is a software library intended to support massively parallel multi-physics computations on dynamically changing unstructured meshes. This domain of intended use is inherently complex due to distributed memory parallelism, parallel scalability, heterogeneity of physics, heterogeneous discretization of an unstructured mesh, and runtime adaptation of the mesh. Management of this inherent complexity begins with a conceptual analysis and modeling of this domain of intended use; i.e., development of a domain model. The Sierra Toolkit computational mesh software library is designed and implemented based upon this domain model. Software developers using, maintaining, or extending the Sierra Toolkit computational mesh library must be familiar with the concepts/domain model presented in this report.