检索结果-内蒙古大学图书馆

A stochastic MPEC approach for grid tariff design with demand-side flexibility

ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS 2023年第3期14卷 707-729页

作者： Askeland, Magnus Burandt, Thorsten Gabriel, Steven A. Energy Systems SINTEF Energy Research Trondheim Norway Department of Electric Power Engineering Norwegian University of Science and Technology Trondheim Norway Workgroup for Infrastructure Policy Technical University of Berlin Berlin Germany The Energy Transportation Environment Department German Institute for Economic Research (DIW Berlin) Berlin Germany Department of Industrial Economics and Technology Management Norwegian University of Science and Technology Trondheim Norway Department of Mechanical Engineering Applied Math and Statistics Scientific Computation Program University of Maryland College Park MD USA

As the end-users increasingly can provide flexibility to the power system, it is important to consider how this flexibility can be activated as a resource for the grid. Electricity network tariffs is one option that can be used to activate this flexibility. Therefore, by designing efficient grid tariffs, it might be possible to reduce the total costs in the power system by incentivizing a change in consumption patterns. This paper provides a methodology for optimal grid tariff design under decentralized decision-making and uncertainty in demand, power prices, and renewable generation. A bilevel model is formulated to adequately describe the interaction between the end-users and a distribution system operator. In addition, a centralized decision-making model is provided for benchmarking purposes. The bilevel model is reformulated as a mixed-integer linear problem solvable by branch-and-cut techniques. Results based on both deterministic and stochastic settings are presented and discussed. The findings suggest how electricity grid tariffs should be designed to provide an efficient price signal for reducing aggregate network peaks.

关键词： Bilevel problem Grid tariffs Mathematical program with equilibrium constraints (MPEC) Uncertainty

来源：评论

学校读者我要写书评

暂无评论

An Assessment of the Supremizer and Aggregation Methods of Stabilization for Reduced-Order Models

arXiv

引用

arXiv 2023年

作者： Davie, Kayla D. Elman, Howard C. Applied Mathematics & Statistics Scientific Computation Program University of Maryland College ParkMD20742 United States Department of Computer Science Institute for Advanced Computer Studies University of Maryland College ParkMD20742 United States

MSC Codes 65N22, 65K10, 65F45We explore the features of two methods of stabilization, aggregation and supremizer methods, for reduced-order modeling of parametrized optimal control problems. In both methods, the reduced basis spaces are augmented to guarantee stability. For the aggregation method, the reduced basis approximation spaces for the state and adjoint variables are augmented in such a way that the spaces are identical. For the supremizer method, the reduced basis approximation space for the state-control product space is augmented with the solutions of a supremizer equation. We implement both of these methods for solving several parametrized control problems and assess their performance. Results indicate that the number of reduced basis vectors needed to approximate the solution space to some tolerance with the supremizer method is much larger, possibly double, that for aggregation. There are also some cases where the supremizer method fails to produce a converged solution. We present results to compare the accuracy, efficiency, and computational costs associated with both methods of stabilization which suggest that stabilization by aggregation is a superior stabilization method for control problems. © 2023, CC BY.

关键词： Stabilization

来源：评论

学校读者我要写书评

暂无评论

Estimation of Parameter Distributions for Reaction-Diffusion Equations with Competition using Aggregate Spatiotemporal Data

arXiv

引用

arXiv 2023年

作者： Nguyen, Kyle Rutter, Erica M. Flores, Kevin Biomathematics Graduate Program North Carolina State University RaleighNC United States Center for Research in Scientific Computation North Carolina State University RaleighNC United States Department of Applied Mathematics University of California Merced MercedCA United States Department of Mathematics North Carolina State University RaleighNC United States

Reaction diffusion equations have been used to model a wide range of biological phenomenon related to population spread and proliferation from ecology to cancer. It is commonly assumed that individuals in a population have homogeneous diffusion and growth rates, however, this assumption can be inaccurate when the population is intrinsically divided into many distinct subpopulations that compete with each other. In previous work, the task of inferring the degree of phenotypic heterogeneity between subpopulations from total population density has been performed within a framework that combines parameter distribution estimation with reaction-diffusion models. Here, we extend this approach so that it is compatible with reaction-diffusion models that include competition between subpopulations. We use a reaction-diffusion model of Glioblastoma multiforme, an aggressive type of brain cancer, to test our approach on simulated data that are similar to measurements that could be collected in practice. We use Prokhorov metric framework and convert the reaction-diffusion model to a random differential equation model to estimate joint distributions of diffusion and growth rates among heterogeneous subpopulations. We then compare the new random differential equation model performance against other partial differential equation models’ performance. We find that the random differential equation is more capable at predicting the cell density compared to other models while being more time efficient. Finally, we use k-means clustering to predict the number of subpopulations based on the recovered distributions. © 2023, CC BY.

关键词： Parameter estimation

来源：评论

学校读者我要写书评

暂无评论

PERMUTATION INVARIANT REPRESENTATIONS with APPLICATIONS to GRAPH DEEP LEARNING

arXiv

引用

arXiv 2022年

作者： Balan, Radu Haghani, Naveed Singh, Maneesh Department of Mathematics University of Maryland College ParkMD20742 United States Applied Mathematics and Statistics and Scientific Computation Program University of Maryland College ParkMD20742 United States Verisk Analytics Jersey CityNJ07310 United States

This paper presents primarily two Euclidean embeddings of the quotient space generated by matrices that are identified modulo arbitrary row permutations. The original application is in deep learning on graphs where the learning task is invariant to node relabeling. Two embedding schemes are introduced, one based on sorting and the other based on algebras of multivariate polynomials. While both embeddings exhibit a computational complexity exponential in problem size, the sorting based embedding is globally bi-Lipschitz and admits a low dimensional target space. Additionally, an almost everywhere injective scheme can be implemented with minimal redundancy and low computational cost. In turn, this proves that almost any classifier can be implemented with an arbitrary small loss of performance. Numerical experiments are carried out on two data sets, a chemical compound data set (QM9) and a proteins data set (PROTEINS FULL).MSC Codes 05C62, 20C32, 68R12 © 2022, CC BY.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

Neglected tropical diseases risk correlates with poverty and early ecosystem destruction

引用

Infectious Diseases of Poverty 2023年第2期12卷 129-129页

作者： Arthur Ramalho Magalhães Cláudia Torres Codeço Jens-Christian Svenning Luis E.Escobar Paige Van de Vuurst Thiago Gonçalves-Souza Laboratory of Ecological Synthesis and Biodiversity Conservation (ECOFUN) Federal Rural University of Pernambuco Recife Brazil Scientific Computation Program (PROCC) Oswaldo Cruz Foundation (Fiocruz) Rio de Janeiro Brazil Center for Ecological Dynamics in a Novel Biosphere (ECONOVO) & Center for Biodiversity Dynamics in a Changing World (BIOCHANGE) Department of Biology. Aarhus University Aarhus Denmark Department of Fish and Wildlife Conservation Virginia Tech Blacksburg USA Center for Emerging Zoonotic and Arthropod-Borne Pathogens Virginia Tech Blacksburg USA Translational Biology Medicine and Health Program Virginia Tech Graduate School Blacksburg USA

Background Neglected tropical diseases affect the most vulnerable populations and cause chronic and debilitating *** vulnerability is a well-known and important determinant of neglected tropical *** example,poverty and sanitation could influence parasite ***,the quantitative impact of socioeconomic conditions on disease transmission risk remains poorly *** This study investigated the role of socioeconomic variables in the predictive capacity of risk models of neglected tropical zoonoses using a decade of epidemiological data(2007–2018)from ***-borne diseases investigated in this study included dengue,malaria,Chagas disease,leishmaniasis,and Brazilian spotted fever,while directly-transmitted zoonotic diseases included schistosomiasis,leptospirosis,and *** and socioeconomic predictors were combined with infectious disease data to build environmental and socioenvironmental sets of ecological niche models and their performances were *** Socioeconomic variables were found to be as important as environmental variables in influencing the estimated likelihood of disease transmission across large spatial *** combination of socioeconomic and environmental variables improved overall model accuracy(or predictive power)by 10%on average(P<0.01),reaching a maximum of 18%in the case of dengue *** domestic product was the most important socioeconomic variable(37%relative variable importance,all individual models exhibited P<0.00),showing a decreasing relationship with disease indicating poverty as a major factor for disease *** of natural vegetation cover between 2008 and 2018 was the most important environmental variable(42%relative variable importance,P<0.05)among environmental models,exhibiting a decreasing relationship with disease probability,showing that these diseases are especially prevalent in areas where natural ecosystem destruction is

关键词： Disease ecology Ecological niche model Socioecological system Vector-borne diseases Zoonosis Brazil

来源：评论

学校读者我要写书评

暂无评论

Singularities, mixing, and non-Markovianity of Pauli dynamical maps

引用

Physical Review A 2021年第4期103卷 042610-042610页

作者： Shrikant Utagi Vinod N. Rao R. Srikanth Subhashish Banerjee Theoretical Sciences Division Poornaprajna Institute of Scientific Research Bidalur Bengaluru-562164 India Graduate Studies Manipal Academy of Higher Education Manipal-576104 India Interdisciplinary Program on Quantum Information and Computation (IDRP-QIC) Indian Institute of Technology Jodhpur-342037 India

Quantum non-Markovianity of channels can be produced by mixing Markovian channels, as observed recently by various authors. We consider an analogous question of whether singularities of the channel can be produced by mixing nonsingular channels, i.e., ones that lack them. Here we answer the question in the negative in the context of qubit Pauli channels. On the other hand, mixing channels with a singularity can lead to the elimination of singularities in the resultant channel. We distinguish between two types of singular channels, which lead under mixing to broadly quite different properties of the singularity in the resultant channel. The connection to non-Markovianity (in the sense of completely positive indivisibility) is pointed out. These results impose nontrivial restrictions on the experimental realization of noninvertible quantum channels by a process of channel mixing.

关键词： Quantum channels Quantum memories

来源：评论

学校读者我要写书评

暂无评论

Estimation of mask effectiveness perception for small domains using multiple data sources

arXiv

引用

arXiv 2021年

作者： Sen, Aditi Lahiri, Partha Applied Mathematics & Statistics and Scientific Computation University of Maryland College Park United States The Joint Program in Survey Methodology Department of Mathematics University of Maryland College ParkMD20742 United States

All pandemics are local;so learning about the impacts of pandemics on public health and related societal issues at granular levels is of great interest. COVID-19 is affecting everyone in the globe and mask wearing is one of the few precautions against it. To quantify people's perception of mask effectiveness and to prevent the spread of COVID-19 for small areas, we use Understanding America Study's (UAS) survey data on COVID-19 as our primary data source. Our data analysis shows that direct survey-weighted estimates for small areas could be highly unreliable. In this paper, we develop a synthetic estimation method to estimate proportions of mask effectiveness for small area using a logistic model that combines information from multiple data sources. We select our working model using an extensive data analysis facilitated by a new variable selection criterion for survey data and benchmarking ratios. We propose a jackknife method to estimate variance of our proposed estimator. From our data analysis, it is evident that our proposed synthetic method outperforms direct survey-weighted estimator with respect to commonly used evaluation measures. Copyright © 2021, The Authors. All rights reserved.

关键词： Data handling

来源：评论

学校读者我要写书评

暂无评论

Enhanced optical nonlinearities under collective strong light-matter coupling

引用

Physical Review A 2021年第6期103卷 063111-063111页

作者： Raphael F. Ribeiro Jorge A. Campos-Gonzalez-Angulo Noel C. Giebink Wei Xiong Joel Yuen-Zhou Department of Chemistry and Cherry Emerson Center for Scientific Computation Emory University Atlanta Georgia 30322 USA Department of Chemistry and Biochemistry University of California San Diego La Jolla California 92093 USA Department of Electrical Engineering The Pennsylvania State University University Park Pennsylvania 16802 USA Materials Science and Engineering Program University of California San Diego La Jolla California 92093 USA

Optical microcavities and metallic nanostructures have been shown to significantly modulate the dynamics and spectroscopic response of molecular systems. We present a study of the nonlinear optics of a model consisting of N anharmonic multilevel systems (e.g., Morse oscillators) undergoing collective strong coupling with a resonant infrared microcavity. We find that, under experimentally accessible conditions, molecular systems in microcavities may have nonlinear phenomena significantly intensified due to the high quality of polariton resonances and the enhanced microcavity electromagnetic energy density relative to free space. Particularly large enhancement of multiphoton absorption happens when multipolariton states are resonant with bare molecule multiphoton transitions. In particular, our model predicts two-photon absorption cross-section enhancements by several orders of magnitude relative to free space when the Rabi splitting ΩR is approximately equal to the molecular anharmonic shift 2Δ. Our results provide rough upper bounds to resonant nonlinear-response enhancement factors as relaxation to dark states is treated phenomenologically. Notably, ensembles of two-level systems undergoing strong coupling with a cavity (described by the Tavis-Cummings model) show no such optical nonlinearity enhancements, highlighting the rich phenomenology afforded by multilevel anharmonic systems. Similar conclusions are expected to hold for excitonic systems that share features with our model (e.g., molecular dyes with accessible S0→S1→S2 transitions) and strongly interact with a UV-visible cavity.

关键词： Chemical Physics & Physical Chemistry Photonics Polaritons Green's function methods Quantum master equation

来源：评论

学校读者我要写书评

暂无评论

Using Cluster Analysis and Dynamic programming for Demand Response Applied to Electricity Load in Residential Homes

引用

Journal of Engineering for Sustainable Buildings and Cities 2020年第1期1卷 011006页

作者： Chanpiwat, Pattanun Gabriel, Steven A. Moglen, Rachel L. Siemann, Michael J. Department of Mechanical Engineering University of Maryland College Park 20742 MD United States Department of Mechanical Engineering and the Applied Mathematics Statistics and Scientific Computation Program University of Maryland College Park 20742 MD United States Department of Industrial Economics and Technology Management Norwegian University of Science and Technology Trondheim NO-7491 Norway Operations Research and Industrial Engineering The University of Texas at Austin Austin 78712 TX United States Resideo Technologies Austin 78702 TX United States

This paper develops means to analyze and cluster residential households into homogeneous groups based on the electricity load. Classifying customers by electricity load profiles is a top priority for retail electric providers (REPs), so they can plan and conduct demand response (DR) effectively. We present a practical method to identify the most DR-profitable customer groups as opposed to tailoring DR programs for each separate household, which may be computationally prohibitive. Electricity load data of 10,000 residential households from 2017 located in Texas was used. The study proposed the clustered load-profile method (CLPM) to classify residential customers based on their electricity load profiles in combination with a dynamic program for DR scheduling to optimize DR profits. The main conclusions are that the proposed approach has an average 2.3% profitability improvement over a business-as-usual heuristic. In addition, the proposed method on average is approximately 70 times faster than running the DR dynamic programming separately for each household. Thus, our method not only is an important application to provide computational business insights for REPs and other power market participants but also enhances resilience for power grid with an advanced DR scheduling tool. Copyright © 2020 by ASME.

关键词： cluster analysis customer classification demand response dynamic programming energy efficiency integrated systems occupant behavior optimization residential household

来源：评论

学校读者我要写书评

暂无评论

A Low-rank solver for the stochastic unsteady navier-stokes problem

arXiv

引用

arXiv 2019年

作者： Elman, Howard Su, Tengfei Department of Computer Science Institute for Advanced Computer Studies University of Maryland College ParkMD20742 United States Applied Mathematics & Statistics and Scientific Computation Program University of Maryland College ParkMD20742 United States

We study a low-rank iterative solver for the unsteady Navier–Stokes equations for incompressible flows with a stochastic viscosity. The equations are discretized using the stochastic Galerkin method, and we consider an all-at-once formulation where the algebraic systems at all the time steps are collected and solved simultaneously. The problem is linearized with Picard’s method. To efficiently solve the linear systems at each step, we use low-rank tensor representations within the Krylov subspace method, which leads to significant reductions in storage requirements and computational costs. Combined with effective mean-based preconditioners and the idea of inexact solve, we show that only a small number of linear iterations are needed at each Picard step. The proposed algorithm is tested with a model of flow in a two-dimensional symmetric step domain with different settings to demonstrate the computational efficiency. Copyright © 2019, The Authors. All rights reserved.

关键词： Navier Stokes equations

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：