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A Novel Methodology to Determine the Maximum PV Penetration in Distribution Networks 2

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A Novel Methodology to Determine the Maximum PV Penetration ...

2nd International Conference on Smart Grid and Renewable Energy, SGRE 2019

作者： Ul Abideen, Mohammad Zain Ellabban, Omar Refaat, Shady S. Abu-Rub, Haitham Al-Fagih, Luluwah College of Science and Engineering Hamad Bin Khalifa University Division of Engineering Management and Decision Sciences Doha Qatar Iberdrola Innovation Middle East Qatar Science Technology Park Doha Qatar Texas A and M University at Qatar Electrical and Computer Engineering Department Doha Qatar School of Computer Science and Mathematics Kingston University London Kingston upon Thames United Kingdom

ISBN: (纸本)9781728129600

Recently, there has been an increase in the interest surrounding the integration of solar photovoltaic (PV) systems in the low voltage (LV) distribution network. This is due to many benefits, such as low generation costs, high efficiency, scalability, etc. However, large PV penetration at the distribution network can cause voltage levels to rise beyond the acceptable limits of the grid codes. Large amount of losses can also occur due to the reverse power flow resulting from the high penetration level of distributed PV generation units integrated into the distribution network. In this paper, a novel methodology based on a gradual increase in the PV penetration level is presented to determine the maximum PV penetration level in the LV distribution networks. PV penetration is defined as the ratio of the peak PV active generation to the peak active demand of the load. The IEEE European LV test feeder has been used as a test case to validate the proposed methodology. Real PV and load data, from residential customers in Ausgrid's electricity network, New South Wales (NSW), Australia, has been used to generate seasonal and worst-case PV generation and load profiles. The PV penetration in the network is increased to find the levels at which the voltage violations occur. PV penetration level with the minimum losses throughout the year is considered as the maximum acceptable level. Various analyses of real data have been used to find the optimal maximum level of PV penetration at the distribution network level. © 2019 IEEE.

关键词： Solar power generation

Event-triggered add-on safety for connected and automated vehicles using road-side network infrastructure

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arXiv 2019年

作者： Mamduhi, Mohammad H. Hashemi, Ehsan Baras, John S. Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science Royal Institute of Technology Stockholm10044 Sweden Mechanical and Mechatronics Engineering Department University of Waterloo ON Canada Institute of Systems Research Department of Electrical and Computer Engineering University of Maryland College ParkMD20742 United States

This paper proposes an event-triggered add-on safety mechanism to adjust the control parameters for timely braking in a networked vehicular system while maintaining maneuverability. Passenger vehicle maneuverability is significantly affected by the combined-slip friction effect, in which larger longitudinal tire slips result in considerable drop in lateral tire forces. This is of higher importance when unexpected dangerous situations occur on the road and immediate actions, such as braking, need to be taken to avoid collision. Harsh braking can lead to high-slip and loss of maneuverability;hence, timely braking is essential to reduce high-slip scenarios. In addition to the vehicles own active safety systems, the proposed event-triggered add-on safety is activated upon being informed about dangers by the road-side infrastructure. The aim is to incorporate the add-on safety feature to adjust the automatic control parameters for smooth and timely braking such that a collision is avoided while vehicle's maneuverability is maintained. We study two different wireless technologies for communication between the infrastructure and the vehicles, the Long-Term Evolution (LTE) and the fifth generation (5G) schemes. The framework is validated through high-fidelity software simulations and the advantages of including the add-on feature to augment the safety margins for each communication technology is evaluated. Copyright © 2019, The Authors. All rights reserved.

关键词： 5G mobile communication systems

Finite impulse response models: A non-asymptotic analysis of the least squares estimator

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arXiv 2019年

作者： Djehiche, Boualem Mazhar, Othmane Rojas, Cristian R. Department of Mathematics School of Engineering Sciences Kth Royal Institute of Technology Stockholm100 44 Division of Decision and Control Systems School of Electrical Engineering and Computer Science Kth Royal Institute of Technology StockholmSE-100 44

We consider a finite impulse response system with centered independent sub-Gaussian design covariates and noise components that are not necessarily iden-tically distributed. We derive non-asymptotic near-optimal estimation and prediction bounds for the least squares estimator of the parameters. Our results are based on two concentration inequalities on the norm of sums of dependent covariate vectors and on the singular values of their covariance operator that are of independent value on their own and where the dependence arises from the time shift structure of the time series. These results generalize the known bounds for the independent case. Copyright © 2019, The Authors. All rights reserved.

关键词： Covariance matrix

OER: Six Perspectives on Global Misconceptions and Challenges

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OER: Six Perspectives on Global Misconceptions and Challenge...

2019 IEEE International Conference on engineering, Technology and Education, TALE 2019

作者： Towey, Dave Reisman, Sorel Chan, Henry Demartini, Claudio Tovar, Edmundo Margaria, Tiziana University of Nottingham Ningbo China School of Computer Science Ningbo China California State University Fullerton Department of Information Systems and Decision Sciences Fullerton United States Hong Kong Polytechnic University Department of Computing Hong Kong Hong Kong Politecnico di Torino Control Computer Engineering Department Turin Italy Universidad Politécnica de Madrid School of Computer Engineers Madrid Spain University of Limerick Department of Computer Science and Information Systems Limerick Ireland

ISBN: (纸本)9781728126654

Open Educational Resources (OERs) are freely accessible materials for teaching, learning, and research that have been made available such that they can be freely used, modified, and shared. Prompted by the potential positive impact that OERs can have, a growing community of OER enthusiasts has been advocating for their adoption in higher education, and elsewhere. The growing demand for computer science education and training (especially in areas related to artificial intelligence, machine learning, and big data) has led to speculation as to how OERs may be best leveraged to support such teaching and learning. The recent occasion of an international OER workshop at the 2019 IEEE Conference on computers, Software and Applications (COMPSAC) allowed for six OER enthusiasts, all with extensive OER experience, to reflect on the status of OER adoption and understanding. These reflections, addressing misconceptions and challenges, form the basis for this paper. © 2019 IEEE.

关键词： Application programs

A Hierarchical Approach For The Stochastic Stability Analysis Of Evolutionary Dynamics

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A Hierarchical Approach For The Stochastic Stability Analysi...

IEEE Conference on decision and control

作者： Hassan Jaleel Jeff S. Shamma Intelligent Machines & Sociotechnical Systems (iMaSS) Lab Syed Babar Ali School of Science & Engineering at Lahore University of Management Science (LUMS) Lahore Pakistan Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE) King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

ISBN: (数字)9781728174471

ISBN: (纸本)9781728174488

We propose a hierarchical approach for the stochastic stability analysis of evolutionary dynamics. Each layer in the hierarchy represents a compromise between computational effort and the resolution of information about the long-run behavior of evolutionary dynamics. Previously, we proposed a graphical reformulation of Evolutionarily Sable Strategy (ESS) analysis through which we identified a set of strategies that cannot be ESS. Moreover, we also computed a set of strategies that was guaranteed to contain the set of stochastically stable strategies. The previous analysis was developed by considering transitions resulting from single mutations only. We extend the graphical approach to higher order analysis by incorporating mutations of higher order and show that we can refine our solution estimate by identifying smaller subsets of strategies that contain the set of stochastically stable strategies. However, this refinement comes at a cost of increase in computational budget.

关键词： Statistics Sociology Stability analysis Resistance Standards Game theory Wireless networks

RFBLS: A robust rough fuzzy broad learning system with local neighborhood structure

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Neurocomputing 2025年 647卷

作者： Yonghe Chu Yanlong Guo Peng Li Weiping Ding Witold Pedrycz Heling Cao School of Artificial Intelligence and Computer Science Nantong University Nantong 226019 China College of Information Science and Engineering Henan University of Technology Zhengzhou 450001 China Key Laboratory of Grain Information Processing and Control(Henan University of Technology) Ministry of Education Zhengzhou 450001 China Centre for Complexity Science Henan University of Technology Zhengzhou 450001 China Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6G 2R3 Canada Institute of Systems Engineering Macau University of Science and Technology Macau SAR Taipa 999078 China Research Center of Performance and Productivity Analysis Istinye University Istanbul Turkiye

As an extension of random vector functional link neural network (RVFLNN), the broad learning system (BLS) has gradually been applied in various fields due to its advantages of simple network structure, rapid training, and fast model updating. Despite its remarkable achievements, there are still some difficulties and challenges that restrict its further application in practical tasks. In BLS, all samples equally contribute to constructing the optimal classification boundary. However, when training samples contain noise or outliers, it will result in the obtained classification boundary not being the true optimal classification boundary. In other words, BLS is sensitive to noise points or outliers. To address it, we propose a robust rough fuzzy broad learning system with local neighborhood structure (RFBLS). In RFBLS, fuzzy sets are utilized by associating a membership degree with each sample. This incorporation ensures diverse contributions of different samples during the minimization of the objective function. Samples with noise or outliers are assigned smaller weights, effectively eliminating the influence of noise and outlier samples in the learning process. We employ the rough set theory to explore the influence-decision degree of each conditional attribute on the decision attribute, aiming to eliminate the impact of redundant or interfering features. Subsequently, we comprehensively consider the distance between samples and class centers, as well as the local neighborhood structure relationship between samples. Initially, we calculate the initial membership degree of each sample based on the distance to class centers. Then, utilizing fuzzy K-nearest neighbors, we calculate and rank the membership degrees of K nearest neighbors for each sample. These rankings are then weighted with the initial membership degree, achieving the fusion of relationships and membership degree calculations between samples. Finally, extensive comparative experiments are conducted on var

关键词： Broad learning system Fuzzy theory K-nearest neighbors Neighborhood rough sets

Affinely Parametrized State-space Models: Ways to Maximize the Likelihood Function

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IFAC-PapersOnLine 2018年第15期51卷 718-723页

作者： Wills, Adrian Yu, Chengpu Ljung, Lennart Verhaegen, Michel School of Electrical Engineering and Computer Science University of Newcastle Australia School iof Automation Beijing Institute of Technology China Division of Automatic Control Department of Electrical Engineering Linkoping University Sweden Delft Center for Systems and Control Delft University Delft2628CD Netherlands

Using Maximum Likelihood (or Prediction Error) methods to identify linear state space model is a prime technique. The likelihood function is a nonconvex function and care must be exercised in the numerical maximization. Here the focus will be on affine parameterizations which allow some special techniques and algorithms. Three approaches to formulate and perform the maximization are described in this contribution: (1) The standard and well known Gauss-Newton iterative search, (2) a scheme based on the EM (expectation-maximization) technique, which becomes especially simple in the affine parameterization case, and (3) a new approach based on lifting the problem to a higher dimension in the parameter space and introducing rank constraints. © 2018

关键词： Maximum likelihood estimation

Recursive network estimation from binary-valued observation data

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arXiv 2019年

作者： Xing, Yu He, Xingkang Fang, Haitao Johansson, Karl Henrik Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-10044 Sweden

This paper studies the problem of recursively estimating the weighted adjacency matrix of a network out of a temporal sequence of binary-valued observations. The observation sequence is generated from nonlinear networked dynamics in which agents exchange and display binary outputs. Sufficient conditions are given to ensure stability of the observation sequence and identifiability of the system parameters. It is shown that stability and identifiability can be guaranteed under the assumption of independent standard Gaussian disturbances. Via a maximum likelihood approach, the estimation problem is transformed into an optimization problem, and it is verified that its solution is the true parameter vector under the independent standard Gaussian assumption. A recursive algorithm for the estimation problem is then proposed based on stochastic approximation techniques. Its strong consistency is established and convergence rate analyzed. Finally, numerical simulations are conducted to illustrate the results and to show that the proposed algorithm is insensitive to small unmodeled factors. Copyright © 2019, The Authors. All rights reserved.

关键词： Approximation theory

Network weight estimation for binary-valued observation models

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arXiv 2019年

作者： Xing, Yu He, Xingkang Fang, Haitao Johansson, Karl Henrik Key Lab of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-10044 Sweden

This paper studies the estimation of network weights for a class of systems with binary-valued observations. In these systems only quantized observations are available for the network estimation. Furthermore, system states are coupled with observations, and the quantization parts are unknown inherent components, which hinder the design of inputs and quantizers. To fulfill the estimation, we propose a recursive algorithm based on stochastic approximation techniques. More precisely, to deal with the temporal dependency of observations and achieve the recursive estimation of network weights, a deterministic objective function is constructed based on the likelihood function by extending the dimension of observations and applying ergodic properties of Markov chains. It is shown that this function is strictly concave and has unique maximum identical to the true parameter vector. Finally, the strong consistency of the algorithm is established. Our recursive algorithm can be applied to online tasks like real-time decision-making and surveillance for networked systems. This work also provides a new scheme for the identification of systems with quantized observations. Copyright © 2019, The Authors. All rights reserved.

关键词： Stochastic systems