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Multi-stage Sensitivity Analysis of Distributed Energy Systems: A Variance-based Sobol Method

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Journal of Modern Power Systems and Clean Energy 2020年第5期8卷 895-905页

作者： Shangshang Wei Yiguo Li Xianhua Gao Kwang Y.Lee Li Sun Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education and Department of Energy and Environment Southeast UniversityNanjing 210096China IEEE Department of Electrical&Computer Engineering Baylor UniversityWacoTX 76798USA

In the face of the pressing environmental issues,the past decade witnessed the booming development of the distributed energy systems(DESs).A notable problem of DESs is the inevitable uncertainty that may make DESs deviate significantly from the deterministically obtained expectations,in both aspects of optimal design and economic *** thus necessitates the sensitivity analysis to quantify the impacts of the massive parametric *** paper aims to give a comprehensive quantification,and carries out a multi-stage sensitivity analysis on DESs from the perspectives of evaluation criteria,optimal design and economic ***,a mathematical model of a DES is developed to present the solutions to the three stages of the ***,the Monte-Carlo simulation is carried out subject to the probabilistic distributions of the energy,technical and economic *** on the simulation results,the variance-based Sobol method is applied to calculate the individual importance,interactional importance and total importance of various *** comparison of the multi-stage results shows that only a few parameters play critical roles while the uncertainty of most of the massive parameters has little impact on the system *** addition,the influence of parameter interactions in the optimal design stage are much stronger than that in the evaluation criteria and operation strategy stages.

关键词： Sensitivity analysis uncertainty operation design optimization parameter characteristic distributed energy system(DES)

HFT-ONLSTM: Hierarchical and Fine-Tuning Multi-label Text Classification

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arXiv 2022年

作者： Gao, Pengfei Zhao, Jingpeng Ma, Yinglong Ahmad, Tanvir Jin, Beihong School of Control and Computer Engineering North China Electric Power University Beijing102206 China Institute of Software Chinese Academy of Sciences Beijing100190 China

Many important classification problems in the real-world consist of a large number of closely related categories in a hierarchical structure or taxonomy. Hierarchical multilabel text classification (HMTC) with higher accuracy over large sets of closely related categories organized in a hierarchy or taxonomy has become a challenging problem. In this paper, we present a hierarchical and fine-tuning approach based on the Ordered Neural LSTM neural network, abbreviated as HFT-ONLSTM, for more accurate level-by-level HMTC. First, we present a novel approach to learning the joint embeddings based on parent category labels and textual data for accurately capturing the joint features of both category labels and texts. Second, a fine tuning technique is adopted for training parameters such that the text classification results in the upper level should contribute to the classification in the lower one. At last, the comprehensive analysis is made based on extensive experiments in comparison with the state-of-the-art hierarchical and flat multi-label text classification approaches over two benchmark datasets, and the experimental results show that our HFT-ONLSTM approach outperforms these approaches, in particular reducing computational costs while achieving superior *** Codes 68T07 Copyright © 2022, The Authors. All rights reserved.

关键词： Embeddings

An Automatic Ridge Estimation Method for Tacholess Order Tracking of Wind Turbine Gearbox Under Varying-Speed Operation

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SSRN

SSRN 2023年

作者： Liu, Changliang Liu, Shaokang Wu, Yingjie Liu, Weiliang Liu, Shuai Control and Computer Engineering Department University of North China Electric Power Beijing102200 China Baoding key Laboratory of State Detection and Optimization Regulation for Integrated Energy System Baoding071000 China Automation Engineering Department University of Northeast Electric Power Jinlin132000 China

The instantaneous shaft speed estimation method of wind turbine gearbox based on time-frequency ridge estimation is the most widely used method, but it requires parameter adjustment and expert knowledge to ensure the accuracy of ridge estimation, which significantly reduces the effectiveness of such methods in practice. In this paper, an end-to-end automated ridge estimating (ARE) method is proposed. ARE uses the inherent harmonic relationship in the vibration signal of wind turbine (WT) gearbox to construct a selection index for automatically selecting the target ridge with clear physical meaning. Then, a sub-region division strategy is proposed to avoid the interference of other components and improve computational efficiency. Finally, a parameter-free objective function considering both the amplitude and smoothness of the ridge is proposed to achieve target ridge estimation. The vibration signals of different WT gearboxes collected on-site were applied to verify the performance of ARE. The result shows that ARE realizes the automatic estimation of a ridge. It outperforms other methods in terms of accuracy and computational efficiency. © 2023, The Authors. All rights reserved.

关键词： Computational efficiency

Convergence Analysis of the Best Response Algorithm for Time-Varying Games

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Convergence Analysis of the Best Response Algorithm for Time...

IEEE Conference on Decision and control

作者： Zifan Wang Yi Shen Michael M. Zavlanos Karl H. Johansson Division of Decision and Control Systems School of Electrical Enginnering and Computer Science KTH Royal Institute of Technology and also with Digital Futures Stockholm Sweden Department of Mechanical Engineering and Materials Science Duke University Durham NC USA

This paper studies a class of strongly monotone games involving non-cooperative agents that optimize their own time-varying cost functions. We assume that the agents can observe other agents' historical actions and choose actions that best respond to other agents' previous actions; we call this a best response scheme. We start by analyzing the convergence rate of this best response scheme for standard time-invariant games. Specifically, we provide a sufficient condition on the strong monotonicity parameter of the time-invariant games under which the proposed best response algorithm achieves exponential convergence to the static Nash equilibrium. We further illustrate that this best response algorithm may oscillate when the proposed sufficient condition fails to hold, which indicates that this condition is tight. Next, we analyze this best response algorithm for time-varying games where the cost functions of each agent change over time. Under similar conditions as for time-invariant games, we show that the proposed best response algorithm stays asymptotically close to the evolving equilibrium. We do so by analyzing both the equilibrium tracking error and the dynamic regret. Numerical experiments on economic market problems are presented to validate our analysis.

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Model predictive control for tracking using artificial references: Fundamentals, recent results and practical implementation

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Model predictive control for tracking using artificial refer...

IEEE Conference on Decision and control

作者： P. Krupa J. Köhler A. Ferramosca I. Alvarado M.N. Zeilinger T. Alamo D. Limon Computer Science Group Gran Sasso Science Institute (GSSI) L’Aquila Italy ETH Zürich Institute for Dynamic Systems and Control Zürich Switzerland Department of Management Information and Production Engineering University of Bergamo Via Marconi 5 Dalmine (BG) Italy Department of Systems Engineering and Automation Universidad de Sevilla Seville Spain

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper provides a comprehensive tutorial on a family of Model Predictive control (MPC) formulations, known as MPC for tracking, which are characterized by including an artificial reference as part of the decision variables in the optimization problem. These formulations have several benefits with respect to the classical MPC formulations, including guaranteed recursive feasibility under online reference changes, as well as asymptotic stability and an increased domain of attraction. This tutorial paper introduces the concept of using an artificial reference in MPC, presenting the benefits and theoretical guarantees obtained by its use. We then provide a survey of the main advances and extensions of the original linear MPC for tracking, including its non-linear extension. Additionally, we discuss its application to learning-based MPC, and discuss optimization aspects related to its implementation.

关键词： Surveys Asymptotic stability Costs Tutorials Optimization Predictive control

Modeling and Analysis of a Coupled SIS Bi-Virus Model

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arXiv 2022年

作者： Gracy, Sebin Paré, Philip E. Liu, Ji Sandberg, Henrik Beck, Carolyn L. Johansson, Karl Henrik Başar, Tamer Department of Electrical Engineering and Computer Science South Dakota School of Mines and Technology SD United States School of Electrical and Computer Engineering Purdue University IN United States Department of Electrical and Computer Engineering Stony Brook University United States Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology and Digital Futures Stockholm Sweden Coordinated Science Laboratory University of Illinois at Urbana-Champaign United States

The paper deals with the setting where two viruses (say virus 1 and virus 2) coexist in a population, and they are not necessarily mutually exclusive, in the sense that infection due to one virus does not preclude the possibility of simultaneous infection due to the other. We develop a coupled bi-virus susceptible-infected-susceptible (SIS) model from a 4n-state Markov process, where n is the number of agents (i.e., individuals or subpopulation) in the population. We identify a sufficient condition for both viruses to eventually die out, and a sufficient condition for the existence, uniqueness and asymptotic stability of the endemic equilibrium of each virus. We establish a sufficient condition and multiple necessary conditions for local exponential convergence to the boundary equilibrium (i.e., one virus persists, the other one dies out) of each virus. Under mild assumptions on the healing rate, we show that there cannot exist a coexisting equilibrium where for each node there is a nonzero fraction infected only by virus 1;a nonzero fraction infected only by virus 2;but no fraction that is infected by both viruses 1 and 2. Likewise, assuming that healing rates are strictly positive, a coexisting equilibrium where for each node there is a nonzero fraction infected by both viruses 1 and 2, but no fraction is infected only by virus 1 (resp. virus 2) does not exist. Further, we provide a necessary condition for the existence of certain other kinds of coexisting equilibria. We show that, unlike the competitive bivirus model, the coupled bivirus model is not monotone. Finally, we illustrate our theoretical findings using an extensive set of simulations. © 2022, CC0.

关键词： Coronavirus

Partially Double-Pass Structure in Serial Hybrid Fiber Amplifier

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Partially Double-Pass Structure in Serial Hybrid Fiber Ampli...

engineering, Science and Advanced Technology (ICESAT), International Conference on

作者： Ali Yaseen Ali Mohammed Kamil Salh Al-Mashhadani Thamer Fahad Al-Mashhadani Rabi Noori Hammudi Yassine Bouteraa Control and Energy Management Laboratory (CEM Lab)Ecole Nationaled Ingenieurs de Sfax (ENIS) Institut Superieur de Biotechnologie de Sfax (ISBS) University of Sfax Tunisia Department of Petroleum Systems Control Engineering Tikrit University Saladdin Iraq Department of Electrical Engineering Tikrit University Saladdin Iraq Department of Laser Engineering and optoelectronics Kut Univeristy College Alkut Wasit Iraq Department of Computer Engineering Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia

In this paper, a partially double pass configuration in serial hybrid fiber amplifier is experimentally demonstrated. In the proposed design, a double pass erbium gain and single pass Raman gain are achieved serially. A total pump power of 450 mW (400 mW for 1495 nm Raman amplifier and 50 mW for1480 nm in erbium amplifier) were used. At -30 dBm input signal power and optimum pumps conditions, the achieved flatness bandwidth is 80 nm (1530–1610 nm) in the conventional and long bands (C+L) bands. In addition, the obtained average gain level is 33 dB. While the obtained flatness gain is 85 nm (1525–1610 nm) within the large input signal power region at -5 dBm. By choosing a proper pump wavelength that avoid the overlapping between Raman and erbium peaks gain, a wide flatness gain is obtained.

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Distract Your Attention: Multi-head Cross Attention Network for Facial Expression Recognition

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arXiv 2021年

作者： Wen, Zhengyao Lin, Wenzhong Wang, Tao Xu, Ge Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China

This paper presents a novel facial expression recognition network, called Distract your Attention Network (DAN). Our method is based on two key observations in biological visual perception. Firstly, multiple facial expression classes share inherently similar underlying facial appearance, and their differences could be subtle. Secondly, facial expressions simultaneously exhibit themselves through multiple facial regions, and for recognition, a holistic approach by encoding high-order interactions among local features is required. To address these issues, this work proposes DAN with three key components: Feature Clustering Network (FCN), Multi-head Attention Network (MAN), and Attention Fusion Network (AFN). Specifically, FCN extracts robust features by adopting a large-margin learning objective to maximize class separability. In addition, MAN instantiates a number of attention heads to simultaneously attend to multiple facial areas and build attention maps on these regions. Further, AFN distracts these attentions to multiple locations before fusing the feature maps to a comprehensive one. Extensive experiments on three public datasets (including AffectNet, RAF-DB, and SFEW 2.0) verified that the proposed method consistently achieves state-of-the-art facial expression recognition performance. The DAN code is publicly available. Copyright © 2021, The Authors. All rights reserved.

关键词： Face recognition

Rethinking Guidance Information to Utilize Unlabeled Samples: A Label Encoding Perspective

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arXiv 2024年

作者： Zhang, Yulong Yao, Yuan Chen, Shuhao Jin, Pengrong Zhang, Yu Jin, Jian Lu, Jiangang Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China College of Control Science and Engineering Zhejiang University Hangzhou China Beijing Teleinfo Technology Company Ltd. China Academy of Information and Communications Technology Beijing China Research Institute of Industrial Internet of Things China Academy of Information and Communications Technology Beijing China

Empirical Risk Minimization (ERM) is fragile in scenarios with insufficient labeled samples. A vanilla extension of ERM to unlabeled samples is Entropy Minimization (EntMin), which employs the soft-labels of unlabeled samples to guide their learning. However, EntMin emphasizes prediction discriminability while neglecting prediction diversity. To alleviate this issue, in this paper, we rethink the guidance information to utilize unlabeled samples. By analyzing the learning objective of ERM, we find that the guidance information for labeled samples in a specific category is the corresponding label encoding. Inspired by this finding, we propose a Label-Encoding Risk Minimization (LERM). It first estimates the label encodings through prediction means of unlabeled samples and then aligns them with their corresponding ground-truth label encodings. As a result, the LERM ensures both prediction discriminability and diversity, and it can be integrated into existing methods as a plugin. Theoretically, we analyze the relationships between LERM and ERM as well as EntMin. Empirically, we verify the superiority of the LERM under several label insufficient scenarios. The codes are available at https://***/zhangyl660/LERM. Copyright © 2024, The Authors. All rights reserved.

关键词： Forecasting