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Bi-level Optimal Planning of Voltage Regulator in Distribution Systems Considering Maximization of Incentive-based Photovoltaic Energy Integration

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CSEE Journal of Power and Energy Systems 2023年第6期9卷 2008-2017页

作者： Xu Xu Youwei Jia Chun Sing Lai Minghao Wang Zhao Xu Department of Electrical and Electronic Engineering Southern University of Science and TechnologyShenzhenChina Department of Electrical Engineering The Hong Kong Polytechnic UniversityHung HomHong Kong SARChina Department of Electrical and Electronic Engineering University Key Laboratory of Advanced Wireless Communications of Guangdong ProvinceSouthern University of Science and TechnologyShenzhen 515100China Department of Electronic and Computer Engineering Brunel Institute of Power SystemsBrunel University LondonLondonUB83PH United Kingdom Department of Electrical Engineering Shenzhen Research InstituteThe Hong Kong Polytechnic UniversityHung HomHong Kong SARChina

This paper focuses on optimal voltage regulator(VR)planning to maximize the photovoltaic(PV)energy integration in distribution *** describe the amount of dynamic PV energy that can be integrated into the power system,the concept of PV accommodation capability(PVAC)is introduced and modeled with *** proposed planning model is formulated as a Benders decomposition based bi-level stochastic optimization *** the upper-level problem,VR planning decisions and PVAC are determined via mixed integer linear programming(MILP)before considering *** in the lower-level problem,the feasibility of first-level results is checked by critical network constraints(*** magnitude constraints and line capacity constraints)under uncertainties considered by time-varying loads and PV *** this paper,these uncertainties are represented in the form of operational scenarios,which are generated by the Gaussian copula theory and reduced by a well-studied backward-reduction *** modified IEEE 33-node distribution grid is utilized to verify the effectiveness of the proposed *** results demonstrate that a PV energy integration can be significantly enhanced after optimal voltage regulator planning.

关键词： Bi-level stochastic optimization problem critical network constraints photovoltaic energy integration uncertainties voltage regulator planning

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System Design and Validation of a Decentralized Automated Vehicle Compute System for Energy Efficiency

System Design and Validation of a Decentralized Automated Ve...

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2023 IEEE International Automated Vehicle Validation Conference, IAVVC 2023

作者： Kothari, Aadi Gerdes, Ryan Billington, Thomas Jaggannagari, Rohan Virginia Polytechnic Institute and State University Department of Electrical and Computer Engineering Blacksburg United States Virginia Polytechnic Institute and State University Department of Electrical and Computer Engineering Arlington United States Virginia Polytechnic Institute and State University Department of Computer Science Blacksburg United States

ISBN: (纸本)9798350322538

With the rise of Artificial Intelligence (AI), Connected and Automated Vehicles (CAVs) have made significant strides towards improving road safety. These advancements have also made driving easier and more energy efficient. With the advanced perception capabilities provided by Vehicle-To-Everything (V2X) radios, vision, LiDAR, and radar sensors, CA V s can detect potential hazards earlier than traditional vehicles. However, advanced sensing requires greater computational resources, increasing power consumption and straining the vehicle's compute device(s). As the demand for power increases, electric vehicles (EV s) lose their valuable range, reducing their appeal to customers. As the High Voltage (HV) system powers the compute, the inclusion of powerful Graphical Processing Units (GPUs) can take away from the valuable range and may not fully warrant their utilization for most automated vehicle systems. We propose a technique to identify microcontroller boards that are powered by the system's Low Voltage (LV) battery, supporting efficient hardware acceleration on the edge. This would enable EV s to support advanced computing capabilities without compromising the range. © 2023 IEEE.

关键词： Energy efficiency

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Towards Implementation of a Small-Scale Prototype Model of a Smart Grid

Towards Implementation of a Small-Scale Prototype Model of a...

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2023 IEEE Conference on Technologies for Sustainability, SusTech 2023

作者： Monemi, Sean Aviles, Jonathan Oliver, Eric Prajapati, Dhruv Nava, Michael Brown, Jon-Michael Robinson, Spencer California State Polytechnic University Electrical and Computer Engineering PomonaCA United States

ISBN: (纸本)9798350345483

Smart Grid technology is progressing rapidly and being implemented into power systems worldwide. Smart grids are essential for today's modern era and constantly changing technology. They are typically made up of four key categories: generation, transmission, distribution, and control. Various hardware and software components were utilized to design and create a Smart Grid model that demonstrated the aforementioned categories. Efforts are being made all over the United States to improve energy consumption efficiency to modernize the power grid to correct the power supply problem caused by increased power demand. This paper provides an experimental study that includes a comprehensive design and implementation of a small-scale prototype model of a Smart Grid. A set of analysis and calculations will be performed to improve the power factor and efficiency as a whole. © 2023 IEEE.

关键词： Smart power grids

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Design of Multi-Robotic System for Navigation in a Tomato Crop Field Using Human Robot Interaction, Robot Operating System and Gazebo

Design of Multi-Robotic System for Navigation in a Tomato Cr...

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2023 IEEE International Conference on electrical, computer and Energy Technologies, ICECET 2023

作者： Chandrasekaran, Balasubramaniyan Florida Polytechnic University Department of Electrical and Computer Engineering LakelandFL United States

ISBN: (纸本)9798350327816

Robotics is an emerging field and finds application in various areas. For applications such as navigation and collecting information in a large agricultural field, it is important to use more than one robot for timely and efficient information gathering. In this paper, an architecture for multi-robot navigation in an agricultural field is presented and the system uses Robot Operating System and Gazebo. This is a work in progress. © 2023 IEEE.

关键词： complementary sensors multi-robotics navigation sensor fusion sensors

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A Protection Scheme in RTDS Model of an IEEE 16-Bus System

A Protection Scheme in RTDS Model of an IEEE 16-Bus System

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2023 IEEE Conference on Technologies for Sustainability, SusTech 2023

作者： Monemi, Sean Boghzian, Angine California State Polytechnic University Electrical and Computer Engineering PomonaCA United States

ISBN: (纸本)9798350345483

This paper demonstrates a protection scheme and relay settings needed to protect a model of power grid system designed using IEEE 16-Bus system. Simulation is done in real time using Real Time Digital Simulator (RTDS). Distance protection is the scheme implemented in the settings using Quickset software for two relays to communicate and therefore detect the faults in different zones. A fault bus is placed between two different buses and their length can be modified to locate the fault in different zones. © 2023 IEEE.

关键词： Electric circuit breakers

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Knowledge-Empowered,Collaborative,and Co-Evolving AI Models:The Post-LLM Roadmap

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工程（英文） 2025年第1期44卷 87-100页

作者： Fei Wu Tao Shen Thomas Bäck Jingyuan Chen Gang Huang Yaochu Jin Kun Kuang Mengze Li Cewu Lu Jiaxu Miao Yongwei Wang Ying Wei Fan Wu Junchi Yan Hongxia Yang Yi Yang Shengyu Zhang Zhou Zhao Yueting Zhuang Yunhe Pan College of Computer Science and Technology Zhejiang UniversityHangzhou 310027China Leiden Institute of Advanced Computer Science Leiden UniversityLeiden 2333 CCNetherlands College of Electrical Engineering Zhejiang UniversityHangzhou 310027China School of Engineering Westlake UniversityHangzhou 310024China Department of Computer Science and Engineering Hong Kong University of Science and TechnologyHong Kong 999077China Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China School of Cyber Science and Technology Sun Yat-Sen UniversityShenzhen 518107China Department of Computing The Hong Kong Polytechnic UniversityHong Kong 999077China

Large language models(LLMs)have significantly advanced artificial intelligence(AI)by excelling in tasks such as understanding,generation,and reasoning across multiple *** these achieve-ments,LLMs have inherent limitations including outdated information,hallucinations,inefficiency,lack of interpretability,and challenges in domain-specific *** address these issues,this survey explores three promising directions in the post-LLM era:knowledge empowerment,model collaboration,and model ***,we examine methods of integrating external knowledge into LLMs to enhance factual accuracy,reasoning capabilities,and interpretability,including incorporating knowledge into training objectives,instruction tuning,retrieval-augmented inference,and knowledge ***,we discuss model collaboration strategies that leverage the complementary strengths of LLMs and smaller models to improve efficiency and domain-specific performance through techniques such as model merging,functional model collaboration,and knowledge ***,we delve into model co-evolution,in which multiple models collaboratively evolve by sharing knowledge,parameters,and learning strategies to adapt to dynamic environments and tasks,thereby enhancing their adaptability and continual *** illustrate how the integration of these techniques advances AI capabilities in science,engineering,and society—particularly in hypothesis development,problem formulation,problem-solving,and interpretability across various *** conclude by outlining future pathways for further advancement and applications.

关键词： Artificial intelligence Large language models Knowledge empowerment Model collaboration Model co-evolution

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Reversible data hiding scheme using prediction neural network and adaptive modulation mapping

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Multimedia Tools and Applications 2025年第9期84卷 6665-6686页

作者： Chen, Si-Sheng Chang, Chin-Chen Horng, Ji-Hwei School of Big Data and Artificial Intelligence Fujian Polytechnic Normal University Fujian Fuzhou35030 China Department of Information Engineering and Computer Science Feng Chia University Taichung40724 Taiwan Department of Electrical Engineering National Quemoy University Kinmen89250 Taiwan

Prediction error expansion (PEE) is an attractive approach for reversible data hiding (RDH). The key issue for PEE-based RDH is to improve the prediction accuracy and design a better modulation mapping. This paper proposes a novel prediction error modulation (PEM) scheme, which comprises a prediction neural network and a modulation mapping rule generation algorithm. We use the multi-scale feature extraction (MSFE) module and the residual dense networks (RDN) to construct the prediction neural network. In the proposed RDH scheme, the cover image is divided into two parts, the reference pixel set and the cover pixel set, based on the chessboard pattern. The prediction network serves to predict the values of the cover pixel set using the reference pixel set. An optimization model is set up to adaptively determine the optimal modulation mapping for data hiding based on the specific prediction-error histogram and payload constraint. Experimental results show the superiority of the proposed prediction neural network and the optimized modulation mapping compared with related works. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Mapping

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Enhancing Track Management Systems with Vehicle-To-Vehicle Enabled Sensor Fusion 100

Enhancing Track Management Systems with Vehicle-To-Vehicle E...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Billington, Thomas Gwash, Ansh Kothari, Aadi Izquierdo, Lucas Talty, Timothy Virginia Polytechnic Institute and State University Department of Computer Science BlacksburgVA United States Virginia Polytechnic Institute and State University Department of Electrical and Computer Engineering BlacksburgVA United States

ISBN: (纸本)9798331517786

In the rapidly advancing landscape of connected and automated vehicles (CAV), the integration of Vehicle-to-Everything (V2X) communication in traditional fusion systems presents a promising avenue for enhancing vehicle perception. Addressing current limitations with vehicle sensing, this paper proposes a novel Vehicle-to-Vehicle (V2V) enabled track management system that leverages the synergy between V2V signals and detections from radar and camera sensors. The core innovation lies in the creation of independent priority track lists, consisting of fused detections validated through V2V communication. This approach enables more flexible and resilient thresholds for track management, particularly in scenarios with numerous occlusions where the tracked objects move outside the field of view of the perception sensors. The proposed system considers the implications of falsification of V2X signals which is combated through an initial vehicle identification process using detection from perception sensors. Presented are the fusion algorithm, simulated environments, and validation mechanisms. Experimental results demonstrate the improved accuracy and robustness of the proposed system in common driving scenarios, highlighting its potential to advance the reliability and efficiency of autonomous vehicles. © 2024 IEEE.

关键词： Magnetic levitation vehicles

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Nonlinear Sub-Optimal Control of SIR Infectious Disease Model 3

Nonlinear Sub-Optimal Control of SIR Infectious Disease Mode...

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3rd IEEE International Conference on Distributed Computing and electrical Circuits and Electronics, ICDCECE 2024

作者： Islam, Samiul Paul, Sudipta Pramanik, Md. Abu Hanif Bhattacharjee, Srijita Naidu, D. Subbaram Rajshahi University Of Eng. & Tech. Electrical & Computer Engineering Rajshahi Bangladesh Rensselaer Polytechnic Institute Electrical Engineering New York United States University Of Minnesota Duluth Electrical Engineering Duluth United States

ISBN: (纸本)9798350318609

The Susceptible-Infectious-Recovered (SIR) disease model is a basic epidemiological framework for analyzing the spread of infectious diseases using various control theories. It plays a vital role in assessing disease control strategies and minimizing the impact of an infectious disease. This paper employs a nonlinear closed-loop infinite-horizon optimal tracking control via state-dependent Riccati equation (IH-SDRE) to the nonlinear SIR model with vaccination, aiming to reduce the number of infected individuals within a desired timeframe. This method, by transforming the nonlinear SIR model into a state-dependent coefficient form, solves the Riccati equation and the vector equation at every time step to determine the control law. The results obtained via MATLAB/Simulink demonstrate that the IH-SDRE minimizes the number of infected populations, reducing it to nearly zero within 30 days of the desired timeframe with an effective vaccination strategy. The findings show the effectiveness of the IH-SDRE as a robust method in the control and mitigation of infectious diseases. © 2024 IEEE.

关键词： Riccati equations

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Protection of Inverter-Based Resources under Open-Circuit Breaker Malfunction

Protection of Inverter-Based Resources under Open-Circuit Br...

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2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Alexander, Brady Mehrizi-Sani, Ali Mohammadhassani, Ardavan Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering BlacksburgVA24061 United States

ISBN: (纸本)9798350313604

Power system protection ensures the safe and reliable delivery of electric power to customers. The increasing number of inverter-based resources (IBR) creates challenges for conventional power system protection as IBRs respond differently to faults than synchronous generators (SG). This means that protection schemes need to be modified to ensure proper power system protection. Currently, most of the proposed IBR protection schemes focus on short-circuit (SC) faults. However, open-circuit (OC) faults also occur in the power system and cause unbalanced currents, overvoltages, and degraded power quality. This paper proposes an OC fault protection scheme for an IBR connected in a transmission system. The IBR control system is studied first. The response of an IBR to an OC fault is studied next. Finally, a protection logic is proposed to detect and clear OC faults. The performance of the proposed scheme is evaluated under time-domain simulation case studies using PSCAD/EMTDC software package. © 2024 IEEE.

关键词： Power quality

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