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Mesoscale Wind Farm Placement via Linear Optimization Constrained by Power System and Techno-economics

Journal of Modern Power Systems and Clean Energy 2021年第2期9卷 356-366页

作者： Ali Erduman Bahri Uzunoglu Bedri Kekezoglu Ali Durusu the Electrical Engineering Department Hakkari UniversityHakkari30000 Turkey Department of Engineering Sciences Department of Electrical EngineeringComputational and Data-enabled Science and Engineering in Energy SystemsUppsala University75121 UppsalaSweden Department of Mathematics Florida State UniversityTallahasseeFL 32310USA the Electrical Engineering Department Yildiz Technical UniversityIstanbul34220 Turkey

The objective of this study is to develop a wind farm placement and investment methodology based on a linear optimization *** problem has a major significance for the investment success for the projects of renewable energy such as wind *** this study,a mesoscale approach is adopted whereby the wind farm location is investigated in comparison with a microscale approach where the location of each individual turbine is *** study focuses on the placement of a wind farm by economical optimization constrained by the power system,wind resources,and *** optimization is introduced in this context at the power system which is constrained by wind farm planning.

关键词： Generation expansion grid integration mesoscale wind farm linear optimization wind power

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Enabling the statistical calibration of active nitridation of graphite by atomic nitrogen 45

Enabling the statistical calibration of active nitridation o...

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45th AIAA Thermophysics Conference, 2015

作者： Bauman, Paul T. University at Buffalo State University of New York BuffaloNY14260-4400 United States Department of Mechanical and Aerospace Engineering Computational and Data-Enabled Science and Engineering United States

ISBN: (数字)9781624103612

ISBN: (纸本)9781624103612

A workow is presented for using PDE-based models to simulate an experimental setup for inferring properties associated with carbon nitridation. The eventual goal is the statistical calibration of the parameters associated with the active nitridation of graphite carbon;this work is a stepping stone in this direction. Simple catalycity models are used to illustrate the the calibration workow. This study builds from previous work where it was determined that a one-dimensional model used was inadequate to represent the physical mechanisms at work. The experimental work is briey recapitulated and the mathematical model used for data reduction is presented. Details of the statistical calibration procedure and all assumptions are discussed. Results of the calibration procedure for the simple catalytic model will be presented and discussed. Extensions underway are highlighted. © 2015, American Institute of Aeronautics and Astronautics Inc. All Rights Reserved.

关键词： Aluminum nitride

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GRINS: A multiphysics framework based on the libMesh finite element library

GRINS: A multiphysics framework based on the libMesh finite ...

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作者： Bauman, Paul T. Stogner, Roy H. Mechanical and Aerospace Engineering Computational and Data-Enabled Science and Engineering University at Buffalo State University of New York BuffaloNY14260-4400 United States Institute for Computational Engineering and Sciences University of Texas at Austin AustinTX78712 United States

This paper describes a flexible C++ software framework, called GRINS, for simulating complex multiphysics systems of partial differential equations using the finite element method. GRINS is designed to facilitate the rapid development and reuse of finite element formulation code as well as other features of complex simulations, including quantity-of-interest functionals, solvers, boundary conditions, initial conditions, and postprocessing. GRINS is built on the FEMSystem framework that is part of the libMesh finite element library. GRINS, through FEMSystem and libMesh, supports a number of contemporary algorithms and computing features including hybrid distributed and shared memory parallelism, parallel adaptive mesh refinement on unstructured grids, goal-oriented refinement driven by dual-weighted residual error estimates in quantities of interest, and adjoint-based parameter sensitivities. GRINS is deployed both as an application binary, allowing immediate use of existing features, and as a library to which the user may build and link a stand-alone application, extending the framework to their needs. Several examples demonstrate the effectiveness of the design, including uncertainty quantification applications. Planned developments are also discussed. © 2016 Society for Industrial and Applied Mathematics.

关键词： Multiphysics

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Emergency Care Patient Prediction using Electronic Health Records (EHR) data: An End-to-End Machine Learning Pipeline 10

Emergency Care Patient Prediction using Electronic Health Re...

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10th International Conference on Future Internet of Things and Cloud, FiCloud 2023

作者： Sumon, Maruful Abedin Kwemebe, Tor A. Melapu, Venkata K. Hasan, Md Mohiuddin Jackson State University Computational Data-Enabled Science and Engineering Jackson United States Jackson State University Department of Mathematics and Computer Science Jackson United States Jackson State University Computer Science and Engineering Jackson United States

ISBN: (纸本)9798350316353

Using electronic health records (EHR) data for predicting the condition of patients who are in need of emergency care is a promising application of machine learning. With the help of machine learning, complex problems of identification of patterns can be solved with ease and accuracy when proper machine learning model is implemented. This paper uses EHR data to build an end-to-end machine learning pipeline for predicting the outcome of emergency care patients. As a machine learning process, the pipeline includes data preprocessing, feature engineering, model selection, data set training and testing, evaluation, and deployment. By using EHR data in this pipeline, the model has been trained and tested on a large dataset of many patients information with different types of machine learning algorithms to improve and get the best prediction accuracy. This pipeline can aid in managing primary care patients efficiently and effectively with the implementation of best suitable machine learning algorithm at the time of urgency. By implementing the model on the EHR dataset, an accuracy of more than 75\% is obtained which indicates the efficiency of the machine learning process in the process of identifying patients who need the emergency care more than the general patients when taken to the primary care or emergency. © 2023 IEEE.

关键词： Forecasting

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A numerical study of bayesian inference of surface catalycity in low speed reacting flow using laser absorption spectroscopy 12th

A numerical study of bayesian inference of surface catalycit...

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12th AIAA/ASME Joint Thermophysics and Heat Transfer Conference, 2018

作者： Adowski, Timothy R. Bauman, Paul T. Department of Mechanical and Aerospace Engineering University at Buffalo BuffaloNY14260-4400 United States Department of Mechanical and Aerospace Engineering Computational and Data-Enabled Science and Engineering University at Buffalo BuffaloNY14260-4400 United States

ISBN: (数字)9781624105524

ISBN: (纸本)9781624105524

In this work, we investigate the statistical inference of surface chemistry parameters from noisy data stemming from tunable diode laser absorption spectroscopy (TDLAS). We leverage previous work whereby TDLAS is simulated in two-dimensional finite element simulations of low speed reacting flow. In particular, we compute the attenuation of laser intensity along an optical path that passes through carbon monoxide CO gas generated by a reacting specimen. The goal is to be able to infer parameters related to the surface chemistry based on the laser attenuation data. Using baseline values from the literature, we numerically simulate TDLAS data and add statistical noise. We then use this synthetic data to infer parameters in various surface chemistry models to demonstrate the feasibility of the methodology. © 2018 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： Surface chemistry

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Implicit Asymptotic Preserving Method for Linear Transport Equations

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Communications in computational Physics 2017年第6期22卷 157-181页

作者： Qin Li Li Wang Mathematics Department University of Wisconsin-Madison480 Lincoln Dr.MadisonWI 53705USA Departments of Mathematics and Computational Data-Enabled Science and Engineering Program State University of New York at Buffalo244 Mathematics BuildingBuffaloNY 14260USA The Optimization Group TheWisconsin Institute ofDiscoveryMadisonWI 53715USA

The computation of the radiative transfer equation is expensive mainly due to two stiff terms:the transport term and the collision *** stiffness in the former comes from the fact that particles(such as photons)travel at the speed of light,while that in the latter is due to the strong scattering in the optically thick *** study the fully implicit scheme for this equation to account for the *** main challenge in the implicit treatment is the coupling between the spacial and angular coordinates that requires the large size of the to-be-inverted matrix,which is also ill-conditioned and not necessarily *** main idea is to utilize the spectral structure of the ill-conditioned matrix to construct a pre-conditioner,which,along with an exquisite split of the spatial and angular dependence,significantly improve the condition number and allows a matrix-free *** also design a fast solver to compute this pre-conditioner explicitly in *** method is shown to be efficient in both diffusive and free streaming limit,and the computational cost is comparable to the state-of-the-art *** examples including anisotropic scattering and two-dimensional problems are provided to validate the effectiveness of our method.

关键词： Implicitmethod asymptotic preserving pre-conditioner diffusive regime free streaming limit

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Modeling laser attenuation in reacting flows using adaptive finite elements 55

Modeling laser attenuation in reacting flows using adaptive ...

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55th AIAA Aerospace sciences Meeting

作者： Bauman, Paul T. Adowski, Timothy R. Department of Mechanical and Aerospace Engineering Computational and Data-Enabled Science and Engineering University at Buffalo State University of New York BuffaloNY14260-4400 United States Department of Mechanical and Aerospace Engineering University at Buffalo State University of New York BuffaloNY14260-4400 United States

ISBN: (数字)9781624104473

ISBN: (纸本)9781624104473

In this work, we demonstrate the use of adaptive finite element analysis in low speed chemically reacting flows to compute the attenuation of laser intensity through an arbitrary path in the domain. We use adjoint-based error estimates to estimate the error in the computed intensity and drive adaptive mesh refinement. We discuss details of the implementation with the GRINS multiphysics framework, built on the libMesh finite element library. We present an example illustrating the adjoint solution and resulting adapted mesh for a laser attenuation quantity-of-interest in a two-dimensional reacting flow with heterogeneous carbon surface chemistry. © 2017 by Paul T. Bauman.

关键词： Chemically Reacting Flow Diode Lasers Adaptive Mesh Refinement Finite Element Formulation Doppler Broadening Beer Lambert Law Computing Thermal Boundary Condition Navier Stokes Equations Mathematical Models

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A Comparison of Global Sensitivity Methods for Power Systems

A Comparison of Global Sensitivity Methods for Power Systems

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International Conference on System Reliability and science (ICSRS)

作者： Ruilong Yue Hui Duan Giray Ökten Bahri Uzunoğlu Department of Mathematics Florida State University USA Department of Electrical Engineering Computational and Data-Enabled Science and Engineering in Energy Systems Uppsala University Sweden

The sensitivity of power system operations uncertainties that originate from distributed renewable generation, natural disasters like hurricanes, and changing loads such as vehicle charging needs careful engineering for reliable, resilient and robust power systems. The power system is a global sensitivity problem since each input uncertainty varies the output and all the variables simultaneously that have higher order interactions between inputs, unlike local sensitivity. The article assesses and compares the global sensitivity methods of Sobol’ sensitivity indices, the activity scores of the active subspace method, and Shapley values, to assess the importance of input parameters in the IEEE 14-bus modified test system. The limitations and advantages of each approach are illustrated to reduce the complexity of the model by performing uncertainty quantification for the output by global sensitivity indices in the IEEE 14-bus modified test system.

关键词： Renewable energy sources Sensitivity Uncertainty Wind power generation Reliability engineering Hurricanes Safety

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Ensemble Filter Scenario Based Control on Linearized Power System Manifold

Ensemble Filter Scenario Based Control on Linearized Power S...

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International Conference on System Reliability and science (ICSRS)

作者： Bahri Uzunoğlu Department of Electrical Engineering Computational and data-enabled science and engineering in energy systems Uppsala University Sweden Department of Mathematics Florida State University USA

ISBN: (数字)9798350354508

ISBN: (纸本)9798350354515

This article integrates the widely recognised ensemble filters that are employed for power system state estimation and their ensemble scenarios to controls for power systems linearised on manifolds. The approach has the effect of directly providing constraint scenarios for any optimal real-time fast power system management for any ensemble-based state estimator used in the power system, thereby reducing the computational task for both radial and meshed power systems and addressing the computational needs of stochastic external state parameter that is not controlled by the grid operator. New and unparalleled obstacles have surfaced in the recent past for power systems. Tighter guidelines for grid reliability and service quality, the growing spread of electric mobility that has given rise to a new class of intermittent loads with distinct spatiotemporal patterns, and the growing use of distributed microgenerators from renewable power sources-which are frequently characterised by unpredictable behavior-are some of these challenges. For proof of concept, the method is shown on a simple example.

关键词： Manifolds Renewable energy sources Uncertainty Decision making Transforms Power systems Spatiotemporal phenomena Kalman filters Reliability State estimation

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Droplet formation simulation using mixed finite elements

arXiv

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arXiv 2023年

作者： Nathawani, Darsh K. Knepley, Matthew G. Computational and Data-Enabled Science and Engineering University at Buffalo BuffaloNY14260 United States Department of Computer Science and Engineering University at Buffalo BuffaloNY14260 United States

Droplet formation happens in finite time due to the surface tension force. The linear stability analysis is useful to estimate droplet size but fails to approximate droplet shape. This is due to a highly non-linear flow description near the point where the first pinch-off happens. A one-dimensional axisymmetric mathematical model was first developed by Eggers and Dupont[2] using asymptotic analysis. This asymptotic approach to the Navier-Stokes equations leads to a universal scaling explaining the self-similar nature of the solution. Numerical models for the one-dimensional model were developed using the finite difference[2] and finite element method[3]. The focus of this study is to provide a robust computational model for one-dimensional axisymmetric droplet formation using the Portable, Extensible Toolkit for Scientific Computation (PETSc). The code is verified using the Method of Manufactured Solutions (MMS) and validated using previous experimental studies done by Zhang and Basaran[4]. The present model is used for simulating pendant drops of water, glycerol, and paraffin wax, with an aspiration of extending the application to simulate more complex pinch-off phenomena. © 2023, CC BY.

关键词： Linear stability analysis

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