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Compensation Mechanisms for Double Auctions in Peer-to-Peer Local Energy Markets

Current Sustainable/Renewable Energy Reports 2020年第4期7卷 165-175页

作者： Gerwin, Christoph Mieth, Robert Dvorkin, Yury Workgroup for Infrastructure Policy Technische Universität Berlin Straße des 17. Juni 135 Berlin10623 Germany Tandon School of Engineering Department of Electrical and Computer Engineering NYU BrooklynNY11201 United States Control Systems Group Technische Universität Berlin Einsteinufer 17 Berlin10587 Germany

Purpose of Review: This paper compares different double-auction pricing mechanisms in the context of peer-to-peer trading in local electricity markets. Benchmarking against the traditional system marginal price (SMP) approach, we analyze the outcomes of the Vickrey-Clarke-Groves (VCG) and Pay-as-bid (PAB) approaches, which lead to a revenue imbalance in the market. To mitigate this imbalance, we propose a set of mechanisms that impose trading fees or subsidies with different fairness policies and discuss their impact on the behavior of market participants. Recent Findings: Proliferation of small-scale and distributed energy resources in low-voltage distribution systems has spurred the development of platforms for peer-to-peer local electricity trading. While recent studies prove that local electricity trading can be beneficial to both the peers and system, implementation of local energy markets is still in the early stages and there is no consensus on an optimal market design. Summary: This paper provides a detailed description of market properties for a competitive LEM that is cleared using the SMP, VCG, and PAB approaches. We show that the proposed compensation mechanisms effectively enforce predefined fairness policies and derive exact payments for each peer depending on market results and individual peer characteristics. The case study uses real-world data to illustrate that different compensation mechanisms can be used to incentivize desirable peer behavior, e.g., installation of new distributed energy resources, investment in grid supportive generation, or flexible energy usage. © 2020, Springer Nature Switzerland AG.

关键词： Power markets

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A Guide to Image and Video based Small Object Detection using Deep Learning: Case Study of Maritime Surveillance

arXiv

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arXiv 2022年

作者： Rekavandi, Aref Miri Xu, Lian Boussaid, Farid Seghouane, Abd-Krim Hoefs, Stephen Bennamoun, Mohammed The Department of Computer Science and Software Engineering The University of Western Australia 35 Stirling Highway CrawleyWA6009 Australia The Department of Electrical Electronics and Computer Engineering The University of Western Australia 35 Stirling Highway CrawleyWA6009 Australia The School of Mathematics and Statistics The University of Melbourne Melbourne Australia submarine optronics undersea combat systems and undersea command and control maritime division Defence Science and Technology Group Australia

Small object detection (SOD) in optical images and videos is a challenging problem that even state-of-the-art generic object detection methods fail to accurately localize and identify such objects. Typically, small objects appear in real-world due to large camera-object distance. Because small objects occupy only a small area in the input image (e.g., less than 10%), the information extracted from such a small area is not always rich enough to support decision making. Multidisciplinary strategies are being developed by researchers working at the interface of deep learning and computer vision to enhance the performance of SOD deep learning based methods. In this paper, we provide a comprehensive review of over 160 research papers published between 2017 and 2022 in order to survey this growing subject. This paper summarizes the existing literature and provide a taxonomy that illustrates the broad picture of current research. We investigate how to improve the performance of small object detection in maritime environments, where increasing performance is critical. By establishing a connection between generic and maritime SOD research, future directions have been identified. In addition, the popular datasets that have been used for SOD for generic and maritime applications are discussed, and also well-known evaluation metrics for the state-of-the-art methods on some of the datasets are provided. © 2022, CC BY-NC-SA.

关键词： Object recognition

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A survey on security and privacy issues of UAVs

arXiv

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arXiv 2021年

作者： Mekdad, Yassine Aris, Ahmet Babun, Leonardo Fergougui, Abdeslam E.L. Conti, Mauro Lazzeretti, Riccardo Uluagac, A. Selcuk Laboratory of Computer Networks and Systems Moulay Ismail University of Meknes Zitoune Meknes11201 Morocco Cyber-Physical Systems Security Lab Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States Department of Mathematics University of Padua Padua35121 Italy Department of Computer Control and Management Engineering "Antonio Ruberti" Sapienza University of Rome Rome00185 Italy

In the 21st century, the industry of drones, also known as Unmanned Aerial Vehicles (UAVs), has witnessed a rapid increase with its large number of airspace users. The tremendous benefits of this technology in civilian applications such as hostage rescue and parcel delivery will integrate smart cities in the future. Nowadays, the affordability of commercial drones expands its usage at a large scale. However, the development of drone technology is associated with vulnerabilities and threats due to the lack of efficient security implementations. Moreover, the complexity of UAVs in software and hardware triggers potential security and privacy issues. Thus, posing significant challenges for the industry, academia, and governments. In this paper, we extensively survey the security and privacy issues of UAVs by providing a systematic classification at four levels: Hardware-level, Software-level, Communication-level, and Sensor-level. In particular, for each level, we thoroughly investigate (1) common vulnerabilities affecting UAVs for potential attacks from malicious actors, (2) existing threats that are jeopardizing the civilian application of UAVs, (3) active and passive attacks performed by the adversaries to compromise the security and privacy of UAVs, (4) possible countermeasures and mitigation techniques to protect UAVs from such malicious activities. In addition, we summarize the takeaways that highlight lessons learned about UAVs’ security and privacy issues. Finally, we conclude our survey by presenting the critical pitfalls and suggesting promising future research directions for security and privacy of UAVs. © 2021, CC BY.

关键词： Drones

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Secure State Estimation against Sparse Attacks on a Time-varying Set of Sensors

arXiv

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arXiv 2022年

作者： Li, Zishuo Niazi, Muhammad Umar B. Liu, Changxin Mo, Yilin Johansson, Karl H. Department of Automation Tsinghua University Beijing100084 China Division of Decision and Control Systems Digital Futures School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden Laboratory for Information and Decision Systems Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States

This paper studies the problem of secure state estimation of a linear time-invariant (LTI) system with bounded noise in the presence of sparse attacks on an unknown, time-varying set of sensors. In other words, at each time, the attacker has the freedom to choose an arbitrary set of no more that p sensors and manipulate their measurements without restraint. To this end, we propose a secure state estimation scheme and guarantee a bounded estimation error subject to 2p-sparse observability and a mild, technical assumption that the system matrix has no degenerate eigenvalues. The proposed scheme comprises a design of decentralized observer for each sensor based on the local observable subspace decomposition. At each time step, the local estimates of sensors are fused by a median operator to obtain a secure estimation, which is then followed by a local detection-and-resetting process of the decentralized observers. The estimation error is shown to be upper-bounded by a constant which is determined only by the system parameters and noise magnitudes. Moreover, we design the detector threshold to ensure that the benign sensors never trigger the detector. The efficacy of the proposed algorithm is demonstrated by its application on a benchmark example of IEEE 14-bus system. © 2022, CC BY-NC-ND.

关键词： Fault detection

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Multimodal Emotion Recognition Based on Multi-Scale Facial Features and Cross-Modal Attention 26

Multimodal Emotion Recognition Based on Multi-Scale Facial F...

引用

26th International Conference on Industrial Technology, ICIT 2025

作者： Bao, Chengao Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru School of Automation China University of Geosciences Wuhan430074 China School of Automation Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2G7 Canada Tokyo Institute of Technology Yokohama226-8502 Japan Tokyo Institute of Technology Tokyo226-8502 Japan

ISBN: (纸本)9798331521950

A multi-modal emotion recognition method based on facial multi-scale features and cross-modal attention (MS-FCA) network is proposed. The MSFCA model improves the traditional single-branch ViT network into a two-branch ViT architecture by using classification tokens in each branch to interact with picture embeddings in the other branch, which facilitates effective interactions between different scales of information. Subsequently, audio features are extracted using ResNet18 network. The cross-modal attention mechanism is used to obtain the weight matrices between different modal features, making full use of inter-modal correlation and effectively fusing visual and audio features for more accurate emotion recognition. Two datasets are used for the experiments: eNTERFACE'05 and REDVESS dataset. The experimental results show that the accuracy of the proposed method on the eNTERFACE'05 and REDVESS datasets is 85.42% and 83.84% respectively, which proves the effectiveness of the proposed method. © 2025 IEEE.

关键词： Modal analysis

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LMI stability analysis for a micro RNA - Messenger RNA interaction mathematical model

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2019年第4期81卷 3-10页

作者： Olteanu, Mircea Ştefan, Radu Department of Mathematical Methods and Models Faculty of Applied Sciences University "Politehnica" of Bucharest Romania Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharest Romania

The micro RNA-messenger RNA dynamics is a topic of constant interest. In this paper we analyze the stability of equilibria of a mathematical model associated to this interaction. After proving the existence and uniqueness of an equilibrium point in the positive ortant, we provide numerically tractable conditions (by using Linear Matrix Inequalities techniques) to check the asymptotic stability of the equilibrium point. An illustrative numerical example is closing the paper along with some conclusions. © 2019, Politechnica University of Bucharest. All rights reserved.

关键词： RNA

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Covariance estimation from compressive data partitions using a projected gradient-based algorithm

arXiv

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arXiv 2021年

作者： Monsalve, Jonathan Ramirez, Juan Esnaola, Iñaki Arguello, Henry Department of Electrical Engineering Universidad Industrial de Santander Bucaramanga680002 Colombia Department of Computer Science Universidad Rey Juan Carlos Madrid28933 Spain Department of Automatic Control and Systems Engineering The University of Sheffield Western Bank Sheffield United Kingdom Department Systems Engineering and Informatics Universidad Industrial de Santander Bucaramanga680002 Colombia

Covariance matrix estimation techniques require high acquisition costs that challenge the sampling systems’ storing and transmission capabilities. For this reason, various acquisition approaches have been developed to simultaneously sense and compress the relevant information of the signal using random projections. However, estimating the covariance matrix from the random projections is an ill-posed problem that requires further information about the data, such as sparsity, low rank, or stationary behavior. Furthermore, this approach fails using high compression ratios. Therefore, this paper proposes an algorithm based on the projected gradient method to recover a low-rank or Toeplitz approximation of the covariance matrix. The proposed algorithm divides the data into subsets projected onto different subspaces, assuming that each subset contains an approximation of the signal statistics, improving the inverse problem’s condition. The error induced by this assumption is analytically derived along with the convergence guarantees of the proposed method. Extensive simulations show that the proposed algorithm can effectively recover the covariance matrix of hyperspectral images with high compression ratios (8 − 15% approx) in noisy scenarios. Additionally, simulations and theoretical results show that filtering the gradient reduces the estimator’s error recovering up to twice the number of eigenvectors. © 2021, CC BY-NC-ND.

关键词： Covariance matrix

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Design of the PID temperature controller for an alkaline electrolysis system with time delays

arXiv

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arXiv 2022年

作者： Qi, Ruomei Li, Jiarong Lin, Jin Song, Yonghua Wang, Jiepeng Cui, Qiangqiang Qiu, Yiwei Tang, Ming Wang, Jian State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing China Tsinghua-Sichuan Energy Internet Research Institute Chengdu China Department of Electrical and Computer Engineering University of Macau China School of Materials Science and Engineering Shanghai University Shanghai China Purification Equipment Research Institute of CSIC Handan China College of Electrical Engineering Sichuan University Chengdu China

Electrolysis systems use proportional-integral-derivative (PID) temperature controllers to maintain stack temperatures around set points. However, heat transfer delays in electrolysis systems cause manual tuning of PID temperature controllers to be time-consuming, and temperature oscillations often occur. This paper focuses on the design of the PID temperature controller for an alkaline electrolysis system to achieve fast and stable temperature control. A thermal dynamic model of an electrolysis system is established in the frequency-domain for controller designs. Based on this model, the temperature stability is analysed by the root distribution, and the PID parameters are optimized considering both the temperature overshoot and the settling time. The performance of the optimal PID controllers is verified through experiments. Furthermore, the simulation results show that the before-stack temperature should be used as the feedback variable for small lab-scale systems to suppress stack temperature fluctuations, and the after-stack temperature should be used for larger systems to improve the economy. This study is helpful in ensuring the temperature stability and control of electrolysis systems. Copyright © 2022, The Authors. All rights reserved.

关键词： Three term control systems

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Thermal Modelling and controller Design of an Alkaline Electrolysis System under Dynamic Operating Conditions

arXiv

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arXiv 2022年

Thermal management is vital for the efficient and safe operation of alkaline electrolysis systems. Traditional alkaline electrolysis systems use simple proportional-integral-differentiation (PID) controllers to maintain the stack temperature near the rated value. However, in renewable-to-hydrogen scenarios, the stack temperature is disturbed by load fluctuations, and the temperature overshoot phenomenon occurs which can exceed the upper limit and harm the stack. This paper focuses on the thermal modelling and controller design of an alkaline electrolysis system under dynamic operating conditions. A control-oriented thermal model is established in the form of a third-order time-delay process, which is used for simulation and controller design. Based on this model, we propose two novel controllers to reduce temperature overshoot: one is a current feed-forward PID controller (PID-I), the other is a model predictive controller (MPC). Their performances are tested on a lab-scale system and the experimental results are satisfying: the temperature overshoot is reduced by 2.2◦C with the PID-I controller, and no obvious overshoot is observed with the MPC controller. Furthermore, the thermal dynamic performance of an MW-scale alkaline electrolysis system is analyzed by simulation, which shows that the temperature overshoot phenomenon is more general in large systems. The proposed method allows for higher temperature set points which can improve system efficiency by 1%. © 2022, CC BY.

关键词： controllers

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Optimal Sizing and Pricing of Renewable Power to Ammonia systems Considering the Limited Flexibility of Ammonia Synthesis

arXiv

引用

arXiv 2022年

作者： Yu, Zhipeng Lin, Jin Liu, Feng Li, Jiarong Zhao, Yuxuan Song, Yonghua Song, Yanhua Zhang, XinZhen The State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100087 China Sichuan Energy Internet Reasearch Institute Tsinghua University Chengdu610213 China The Department of Electrical and Computer Engineering University of Macau 999078 China The Department of Electrical Engineering Tsinghua University Beijing100087 China Shenzhen Edo Renewable Co. Ltd Shenzhen518067 China

Converting renewable energy into ammonia has been recognized as a promising way to realize "green hydrogen substitution" in the chemical industry. However, renewable power to ammonia (RePtA) requires an essential investment in facilities to provide a buffer against the strong volatility of renewable energy and the limited flexibility of ammonia synthesis, which involves the three main stakeholders, namely, power, hydrogen, and ammonia. Therefore, the sizing and pricing of RePtA play a core role in balancing the interest demands of investors. This paper proposes an optimal sizing and pricing method for RePtA system planning. First, power to ammonia (P2A) is modeled as a flexible load, especially considering the limited flexibility of ammonia synthesis, which has been verified using real dynamic regulation data. Second, the multi-investor economic (MIE) model is established considering both external and internal trading modes. Then, a two-stage decomposed sizing and pricing method is proposed to solve the problem caused by the strong coupling of planning, operation, and trading, and information gap decision theory (IGDT) method is utilized to handle the uncertainty of renewable generation. Finally, real data from a real-life system in Inner Mongolia are utilized to verify the proposed approach. The results show that the system proposed has a yield of 8.15%. Copyright © 2022, The Authors. All rights reserved.

关键词： Costs

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