Modeling the Real-Time Use of Reserves in the Joint Energy and Reserve Hourly Scheduling of a Pumped Storage Plant

This paper studies the impact that different approaches of modeling the real-time use of the secondary regulation reserves have in the joint energy and reserve hourly scheduling of a price-taker pumped-storage hydropower plant. The unexpected imbalance costs due to the error between the forecasted real-time use of the reserves and the actual value are also studied and evaluated for the different approaches. The proposed methodology is applied to a daily-cycle and closed-loop pumped-storage hydropower plant. Preliminary results show that the deviations in the water volume at the end of the day are important when the percentage of the real-time use of reserves is unknown in advance, and also that the total income in all approaches after correcting these deviations is significantly lower than the maximum theoretical income.

A contribution on modeling methodologies for multibody systems.

Multibody System Dynamics has been responsible for revolutionizing Mechanical Engineering Design by using mathematical models to simulate and optimize the dynamic behavior of a wide range of mechanical systems. These mathematical models not only can provide valuable informations about a system that could otherwise be obtained only by experiments with prototypes, but also have been responsible for the development of many model-based control systems. This work represents a contribution for dynamic modeling of multibody mechanical systems by developing a novel recursive modular methodology that unifies the main contributions of several Classical Mechanics formalisms. The reason for proposing such a methodology is to motivate the implementation of computational routines for modeling complex multibody mechanical systems without being dependent on closed source software and, consequently, to contribute for the teaching of Multibody System Dynamics in undergraduate and graduate levels. All the theoretical developments are based on and motivated by a critical literature review, leading to a general matrix form of the dynamic equations of motion of a multibody mechanical system (that can be expressed in terms of any set of variables adopted for the description of motions performed by the system, even if such a set includes redundant variables) and to a general recursive methodology for obtaining mathematical models of complex systems given a set of equations describing the dynamics of each of its uncoupled subsystems and another set describing the constraints among these subsystems in the assembled system. This work also includes some discussions on the description of motion (using any possible set of motion variables and admitting any kind of constraint that can be expressed by an invariant), and on the conditions for solving forward and inverse dynamics problems given a mathematical model of a multibody system. Finally, some examples of computational packages based on the novel methodology, along with some case studies, are presented, highlighting the contributions that can be achieved by using the proposed methodology.

A GIS-based methodology to quantitatively define an Adjacent Protected Area in a shallow karst cavity: The case of Altamira cave

Different types of land use are usually present in the areas adjacent to many shallow karst cavities. Over time, the increasing amount of potentially harmful matter and energy, of mainly anthropic origin or influence, that reaches the interior of a shallow karst cavity can modify the hypogeal ecosystem and increase the risk of damage to the Palaeolithic rock art often preserved within the cavity. This study proposes a new Protected Area status based on the geological processes that control these matter and energy fluxes into the Altamira cave karst system. Analysis of the geological characteristics of the shallow karst system shows that direct and lateral infiltration, internal water circulation, ventilation, gas exchange and transmission of vibrations are the processes that control these matter and energy fluxes into the cave. This study applies a comprehensive methodological approach based on Geographic Information Systems (GIS) to establish the area of influence of each transfer process. The stratigraphic and structural characteristics of the interior of the cave were determined using 3D Laser Scanning topography combined with classical field work, data gathering, cartography and a porosity–permeability analysis of host rock samples. As a result, it was possible to determine the hydrogeological behavior of the cave. In addition, by mapping and modeling the surface parameters it was possible to identify the main features restricting hydrological behavior and hence direct and lateral infiltration into the cave. These surface parameters included the shape of the drainage network and a geomorphological and structural characterization via digital terrain models. Geological and geomorphological maps and models integrated into the GIS environment defined the areas involved in gas exchange and ventilation processes. Likewise, areas that could potentially transmit vibrations directly into the cave were identified. This study shows that it is possible to define a Protected Area by quantifying the area of influence related to each transfer process. The combined maximum area of influence of all the processes will result in the new Protected Area. This area will thus encompass all the processes that account for most of the matter and energy carried into the cave and will fulfill the criteria used to define the Protected Area. This methodology is based on the spatial quantification of processes and entities of geological origin and can therefore be applied to any shallow karst system that requires protection.

Dispersivity Determination Through a Modeling Approach From a Tracer Test Based on Total Br Concentration in Soil Samples

Determination of reliable solute transport parameters is an essential aspect for the characterization of the mechanisms and processes involved in solute transport (e.g., pesticides, fertilizers, contaminants) through the unsaturated zone. A rapid inexpensive method to estimate the dispersivity parameter at the field scale is presented herein. It is based on the quantification by the X-ray fluorescence solid-state technique of total bromine in soil, along with an inverse numerical modeling approach. The results show that this methodology is a good alternative to the classic Br− determination in soil water by ion chromatography. A good agreement between the observed and simulated total soil Br is reported. The results highlight the potential applicability of both combined techniques to infer readily solute transport parameters under field conditions.

Development of a systems risk methodology for single and multi-modal transportation systems. Final report.

Transportation Department, Research and Special Programs Administration, Washington, D.C.

Modeling Seasonal and Weather Impacts on Cycling Count

Thesis (Master's)--University of Washington, 2016-06

An advanced regularization methodology for use in watershed model calibration

A calibration methodology based on an efficient and stable mathematical regularization scheme is described. This scheme is a variant of so-called Tikhonov regularization in which the parameter estimation process is formulated as a constrained minimization problem. Use of the methodology eliminates the need for a modeler to formulate a parsimonious inverse problem in which a handful of parameters are designated for estimation prior to initiating the calibration process. Instead, the level of parameter parsimony required to achieve a stable solution to the inverse problem is determined by the inversion algorithm itself. Where parameters, or combinations of parameters, cannot be uniquely estimated, they are provided with values, or assigned relationships with other parameters, that are decreed to be realistic by the modeler. Conversely, where the information content of a calibration dataset is sufficient to allow estimates to be made of the values of many parameters, the making of such estimates is not precluded by preemptive parsimonizing ahead of the calibration process. White Tikhonov schemes are very attractive and hence widely used, problems with numerical stability can sometimes arise because the strength with which regularization constraints are applied throughout the regularized inversion process cannot be guaranteed to exactly complement inadequacies in the information content of a given calibration dataset. A new technique overcomes this problem by allowing relative regularization weights to be estimated as parameters through the calibration process itself. The technique is applied to the simultaneous calibration of five subwatershed models, and it is demonstrated that the new scheme results in a more efficient inversion, and better enforcement of regularization constraints than traditional Tikhonov regularization methodologies. Moreover, it is argued that a joint calibration exercise of this type results in a more meaningful set of parameters than can be achieved by individual subwatershed model calibration. (c) 2005 Elsevier B.V. All rights reserved.

Patterns in complex systems modeling

The design, development, and use of complex systems models raises a unique class of challenges and potential pitfalls, many of which are commonly recurring problems. Over time, researchers gain experience in this form of modeling, choosing algorithms, techniques, and frameworks that improve the quality, confidence level, and speed of development of their models. This increasing collective experience of complex systems modellers is a resource that should be captured. Fields such as software engineering and architecture have benefited from the development of generic solutions to recurring problems, called patterns. Using pattern development techniques from these fields, insights from communities such as learning and information processing, data mining, bioinformatics, and agent-based modeling can be identified and captured. Collections of such 'pattern languages' would allow knowledge gained through experience to be readily accessible to less-experienced practitioners and to other domains. This paper proposes a methodology for capturing the wisdom of computational modelers by introducing example visualization patterns, and a pattern classification system for analyzing the relationship between micro and macro behaviour in complex systems models. We anticipate that a new field of complex systems patterns will provide an invaluable resource for both practicing and future generations of modelers.

Conditional distribution modeling for estimating and exploiting uncertainty in control systems

This paper presents a general methodology for estimating and incorporating uncertainty in the controller and forward models for noisy nonlinear control problems. Conditional distribution modeling in a neural network context is used to estimate uncertainty around the prediction of neural network outputs. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localize the possible control solutions to consider. A nonlinear multivariable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non Gaussian distributions of control signal as well as processes with hysteresis.

Three-dimensional modeling of the human eye based on magnetic resonance imaging

PURPOSE. A methodology for noninvasively characterizing the three-dimensional (3-D) shape of the complete human eye is not currently available for research into ocular diseases that have a structural substrate, such as myopia. A novel application of a magnetic resonance imaging (MRI) acquisition and analysis technique is presented that, for the first time, allows the 3-D shape of the eye to be investigated fully. METHODS. The technique involves the acquisition of a T2-weighted MRI, which is optimized to reveal the fluid-filled chambers of the eye. Automatic segmentation and meshing algorithms generate a 3-D surface model, which can be shaded with morphologic parameters such as distance from the posterior corneal pole and deviation from sphericity. Full details of the method are illustrated with data from 14 eyes of seven individuals. The spatial accuracy of the calculated models is demonstrated by comparing the MRI-derived axial lengths with values measured in the same eyes using interferometry. RESULTS. The color-coded eye models showed substantial variation in the absolute size of the 14 eyes. Variations in the sphericity of the eyes were also evident, with some appearing approximately spherical whereas others were clearly oblate and one was slightly prolate. Nasal-temporal asymmetries were noted in some subjects. CONCLUSIONS. The MRI acquisition and analysis technique allows a novel way of examining 3-D ocular shape. The ability to stratify and analyze eye shape, ocular volume, and sphericity will further extend the understanding of which specific biometric parameters predispose emmetropic children subsequently to develop myopia. Copyright © Association for Research in Vision and Ophthalmology.

Early marketing matters:a time-varying parameter approach to persistence modeling

Are persistent marketing effects most likely to appear right after the introduction of a product? The authors give an affirmative answer to this question by developing a model that explicitly reports how persistent and transient marketing effects evolve over time. The proposed model provides managers with a valuable tool to evaluate their allocation of marketing expenditures over time. An application of the model to many pharmaceutical products, estimated through (exact initial) Kalman filtering, indicates that both persistent and transient effects occur predominantly immediately after a brand's introduction. Subsequently, the size of the effects declines. The authors theoretically and empirically compare their methodology with methodology based on unit root testing and demonstrate that the need for unit root tests creates difficulties in applying conventional persistence modeling. The authors recommend that marketing models should either accommodate persistent effects that change over time or be applied to mature brands or limited time windows only.

Distribution modeling of nonlinear inverse controllers under a Bayesian framework

The inverse controller is traditionally assumed to be a deterministic function. This paper presents a pedagogical methodology for estimating the stochastic model of the inverse controller. The proposed method is based on Bayes' theorem. Using Bayes' rule to obtain the stochastic model of the inverse controller allows the use of knowledge of uncertainty from both the inverse and the forward model in estimating the optimal control signal. The paper presents the methodology for general nonlinear systems and is demonstrated on nonlinear single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) examples. © 2006 IEEE.

A Bayesian approach to modeling the conditional density of the inverse controller

The inverse controller is traditionally assumed to be a deterministic function. This paper presents a pedagogical methodology for estimating the stochastic model of the inverse controller. The proposed method is based on Bayes' theorem. Using Bayes' rule to obtain the stochastic model of the inverse controller allows the use of knowledge of uncertainty from both the inverse and the forward model in estimating the optimal control signal. The paper presents the methodology for general nonlinear systems. For illustration purposes, the proposed methodology is applied to linear Gaussian systems. © 2004 IEEE.

Bioactive sol-gel glasses at the atomic scale:the complementary use of advanced probe and computer modeling methods

Sol-gel-synthesized bioactive glasses may be formed via a hydrolysis condensation reaction, silica being introduced in the form of tetraethyl orthosilicate (TEOS), and calcium is typically added in the form of calcium nitrate. The synthesis reaction proceeds in an aqueous environment; the resultant gel is dried, before stabilization by heat treatment. These materials, being amorphous, are complex at the level of their atomic-scale structure, but their bulk properties may only be properly understood on the basis of that structural insight. Thus, a full understanding of their structure-property relationship may only be achieved through the application of a coherent suite of leading-edge experimental probes, coupled with the cogent use of advanced computer simulation methods. Using as an exemplar a calcia-silica sol-gel glass of the kind developed by Larry Hench, in the memory of whom this paper is dedicated, we illustrate the successful use of high-energy X-ray and neutron scattering (diffraction) methods, magic-angle spinning solid-state NMR, and molecular dynamics simulation as components to a powerful methodology for the study of amorphous materials.

Modeling the fiscal impacts caused by climate change

Aim of the paper: The purpose is to gather the practices and to model the impacts of climate change on fiscal spending and revenues, responsibilities and opportunities, balance and debt related to climate change (CC). Methodology of the paper: The methodology will distinguish fiscal cost of mitigation and adaptation, besides direct and indirect costs. It will also introduce cost benefit analyses to evaluate the propensity of policy makers for action or passivity. Several scenarios will be drafted to see the different outcomes. The scenarios shall contain the possible losses in the natural and artificial environment and resources. Impacts on public budget are based on damage of income opportunities and capital/wealth/natural assets. There will be a list of actions when the fiscal correction of market failures will be necessary. Findings: There will be a summary and synthesis of estimation models on CC impacts on public finances, and morals of existing/existed budgeting practices on mitigation. The model will be based on damages (and maybe benefits) from CC, adjusted with probabilities of scenarios and policy making propensity for action. Findings will cover the way of funding of fiscal costs. Practical use, value added: From the synthesis of model, the fiscal cost of mitigation and adaptation can be estimated for any developed, emerging and developing countries. The paper will try to reply, also, for the challenge how to harmonize fiscal and developmental sustainability.