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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Chen, Zihao Huang, Jiangli Liu, Yiting Yang, Fan Shang, Li Zhou, Dian Zeng, Xuan State Key Laboratory of Integrated Chips and Systems School of Microelectronics Fudan University Shanghai China China and Shanghai Key Laboratory of Data Science School of Computer Science Fudan University Shanghai China Department of Electrical Engineering University of Texas at Dallas RichardsonTX United States

ISBN: (纸本)9798400706011

This paper presents Artisan, an automated operational amplifier design framework using large language models (LLMs). We develop a bidirectional representation to align abstract circuit topologies with their structural and functional semantics. We further employ Tree-of-Thoughts and Chain-of-Thoughts approaches to model the design process as a hierarchical question-answer sequence, implemented by a mechanism of multi-agent interaction. A high-quality opamp dataset is developed to enhance the design proficiency of the Artisan-LLM. Experimental results demonstrate that Artisan outperforms state-of-the-art optimization-based methods and benchmark LLMs, in success rate, circuit performance metrics, and interpretability, while accelerating the design process by up to 50.1X. Artisan will be released for public access. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Semantics

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Machine Learning for Caching Placement in Edge computing Networks

Machine Learning for Caching Placement in Edge Computing Net...

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International Conference on computing, Networking and Communications (ICNC)

作者： Liang Zhang Bijan Jabbari Department of Electrical and Computer Engineering George Mason University Fairfax VA USA Department of Electrical and Computing Engineering Communications and Networks Laboratory George Mason University Fairfax VA USA

ISBN: (数字)9798350370997

ISBN: (纸本)9798350371000

Internet of Things devices (IoTDs) that deployed for various applications have limited size, power, storage, and computing capabilities, and many of them are used for low-latency applications. Mobile edge computing (MEC) can be leveraged to reduce the latency of IoTDs, and judicious caching placement can help further to improve the quality of service. In this paper, we study multi-content placement (MCP) in the MEC networks for IoTDs by considering the background data caching in the edge nodes and the data collection of IoTDs. The MCP problem is formulated by considering the caching, the IoTD assignment, and the communication and computing resources allocation to minimize the average latency of all IoTDs. As the MCP problem is NP-hard, we propose a deep reinforcement machine learning algorithm to obtain the caching placement and IoTD assignment jointly to solve the MCP problem. We use an optimal joint resource-scheduling algorithm to assign the resources. Our results demonstrate that considerable latency improvement can be achieved through the proposed deep reinforcement machine learning algorithm as compared to baseline algorithms.

关键词： Machine learning algorithms Multi-access edge computing Scheduling algorithms Simulation Quality of service Data collection Deep reinforcement learning

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Electric Vehicle Performance Enhancement Utilizing Hybrid Energy Storage systems

Electric Vehicle Performance Enhancement Utilizing Hybrid En...

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Hossam M. Hussein SM Sajjad Hossain Rafin Mahmoud S. Abdelrahman Ibtissam Kharchouf Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami Fl USA

ISBN: (数字)9798331541606

ISBN: (纸本)9798331541613

Energy storage systems (ESSs) are vital in various applications, including electric vehicles (EVs) and microgrids. In comparison, lithium-ion batteries (LIBs) are widely used in ESSs, and challenges such as power density, thermal management, and cell voltage balance prompt the exploration of alternative solutions. Integrating supercapacitors (SCs) alongside batteries in hybrid energy storage systems (HESS) presents a promising solution. SCs can provide high bursts of power, extending battery lifespan and improving efficiency, especially during high-demand scenarios like acceleration and braking. Optimizing energy management strategies (EMS) is crucial to minimize operational costs and ensure practical battery usage within HESS. Different driving cycles, such as the New European Driving Cycle (NEDC) and World Harmonized Light Vehicles Test Procedure (WLTP), provide insights into real-world driving conditions. HESS configurations and operational modes, including traction and regenerative braking, are essential for efficient EV operation. This study uses simulation models to investigate EVs' performance with HESS under various driving conditions, highlighting the system's stability and adaptability.

关键词： Lithium-ion batteries Power system measurements Supercapacitors Propulsion Power system stability Thermal management Stability analysis Energy management Thermal stability Strain

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Customer-Level Photovoltaic Disaggregation With Customer-Specific Exemplars

Customer-Level Photovoltaic Disaggregation With Customer-Spe...

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IEEE Industry Applications Society Annual Meeting (IAS)

作者： Anne Stratman Wei Qiao Liyan Qu Department of Electrical and Computer Engineering Power and Energy Systems Laboratory University of Nebraska-Lincoln Lincoln NE USA

ISBN: (数字)9798350372717

ISBN: (纸本)9798350372724

Residential photovoltaic (PV) systems, which have become widely integrated into distribution systems, are typically installed behind-the-meter (BTM). However, accurate estimates of the BTM PV generation are necessary for load forecasting, network control, and demand response, so the measured net load data must be disaggregated into separate measurements of PV generation and pure load. This paper proposes a dictionary learning-based, customer-level PV disaggregation framework based on constructing customer-specific dictionary atoms. First, the observable data of a reference home is used to disaggregate the data of another fully observable home. The disaggregation is formulated as dictionary learning problem and solved via lasso regression. Then, synthetic dictionary atoms are constructed as a weighted linear combination of the PV generation and pure load profiles of the reference home, and the estimated profiles of the second observable home. The weights are optimized to minimize the disaggregation error of the known profiles of the second observable home. Finally, the data of the target home is disaggregated initially. Then, the optimized weights are used to construct synthetic exemplars using the reference home's data and the initial disaggregation estimates of the target home. The proposed method is compared to the case where synthetic exemplars are not used and is tested under a variety of weather conditions. Case study results show that the proposed framework reduces the disaggregation error by $3.27-81.01 \%$ , with a mean reduction of $\mathbf{2 0. 2 4 \%}$ across all test days.

关键词： Photovoltaic systems Dictionaries Accuracy Load forecasting Machine learning Solar energy Atoms Demand response Weighted sum model Testing

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Data Fusion-based Hybrid Framework for Cyber-physical Security of the Smart Grid

Data Fusion-based Hybrid Framework for Cyber-physical Securi...

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Resilience Week (RWS)

作者： Sharon A. Boamah Reynold Mathieu Victor Faillace Dennis Agnew Janise McNair Arturo Bretas Department of Electrical and Computer Engineering University of Florida Gainesville FL Distributed Systems Group Sandia National Laboratory

ISBN: (数字)9798350388985

ISBN: (纸本)9798350388992

The integration of information communication technology with the power grid exposes it to cyber threats. The network state estimation process provides stability to the smart grid. The communication network plays a major role in ensuring the successful transmission of state information. However, these network measurements are vulnerable to malicious attacks. This subsequently affects the network measurement such as associated high transmission delays and packet losses affecting the reliability of the smart grid. In this work, we propose a hybrid physics-based data-driven model that uses data fusion from the state-of-the-art physics-based Network State Estimation model and a data-driven model to detect false data injection attacks in the communication network layer of the smart grid. The performance of the data fusion method is evaluated and the simulation results show that the proposed model outperforms the standalone approaches in the detection of bad data. This shows that the proposed scheme is able to improve the cyber-physical security of the communication network layer of the smart grid.

关键词： Simulation Data integration Data models Stability analysis Smart grids Communication networks Security Reliability State estimation Resilience

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Fractional Order Linear Active Disturbance Rejection Control for Linear Flexible Joint System

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computers, Materials & Continua 2022年第3期70卷 5133-5142页

作者： Ibrahim M.Mehedi Rachid Mansouri Ubaid M.Al-Saggaf Ahmed I.M.Iskanderani Maamar Bettayeb Abdulah Jeza Aljohani Thangam Palaniswamy Shaikh Abdul Latif Abdul Latif Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia L2CSP Laboratory Mouloud Mammeri UniversityTizi OuzouAlgeria Electrical&Computer Engineering Department University of SharjahUnited Arab Emirates Department of Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics King Abdulaziz UniversityJeddah21589Saudi Arabia

A linear flexible joint system using fractional order linear active disturbance rejection control is studied in this *** this control scheme,the performance against disturbances,uncertainties,and attenuation is *** active disturbance rejection control(LADRC)is mainly based on an extended state observer(ESO)technology.A fractional integral(FOI)action is combined with the LADRC technique which proposes a hybrid control scheme like *** this FOI action improves the robustness of the standard *** set-point tracking of the proposed FO-LADRC scheme is designed by Bode’s ideal transfer function(BITF)based robust closed-loop concept,an appropriate pole placement *** effectiveness of the proposed FO-LADRC scheme is illustrated through experimental results on the linear flexible joint system(LFJS).The results show the enhancement of the robustness with disturbance ***,a comparative analysis is presented with the results obtained using the integer-order LADRC and FO-LADRC scheme.

关键词： Active disturbance rejection fractional calculus ADRC pole placement linear flexible joint system robust control

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Container-based Platform for Edge-computing in Energy System Applications

Container-based Platform for Edge-Computing in Energy System...

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IEEE General Meeting Power& Energy Society

作者： Mahmoud S. Abdelrahman Hossam Hussein Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami Fl USA

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

The design of power systems is growing more complex due to the large-scale building of microgrids and the ongoing advancement of renewable energy technologies. Several management approaches are applied to overcome these issues using cloud computing and the Internet of Things (IoT). However, the security and time delay for long-distance transferring to cloud communication are crucial concerns. Edge computing is a promising technology to address these challenges. Emerging smart energy systems are frequently deployed at the Edge of the power grid to meet the needs of smart grid users and achieve secure, efficient, and low-latency data processing. This paper proposes a container-based platform for Edge computing emulation based on a co-simulation model to implement, test, and validate Edge computing-based energy system applications. In addition, the feasibility of the proposed model is demonstrated by a case study of a consensus control technique based on an Edge computing framework for multi-microgrids.

关键词： Cloud computing Computational modeling Emulation Microgrids Containers Consensus control Smart grids Internet of Things Security Edge computing

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Communication Networks-Based Control of Cyber-Physical Microgrids

Communication Networks-Based Control of Cyber-Physical Micro...

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IEEE Industry Applications Society Annual Meeting (IAS)

作者： Ola Ali Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

ISBN: (数字)9798350372717

ISBN: (纸本)9798350372724

This paper surveys the communication networksbased control of cyber-physical microgrids (MGs), including the different architectures of MGs, the control system, and the communication networks within the MGs. The proposed work introduces an overview of the AC, DC, and hybrid AC/DC architectures, highlighting the challenges in the control systems used for each architecture. Focusing on the hierarchical control structure of MGs, we demonstrate the vital role of communication infrastructure in the resilient control of MGs to coordinate between the primary, secondary, and tertiary layers for achieving the control objective. The requirements for communication networks and their influence on MGs' reliable and secure operation are also presented. We have investigated the impact of communication delays, failures, and packet loss on the control system's performance. This survey offers insights into the effects of communication infrastructure on efficient and robust control of cyber-physical MGs in dynamic energy environments.

关键词： Surveys Robust control System performance Packet loss Microgrids Control systems Delays Communication networks Reliability Resilience

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Graph Models of Electric Power Transmission Networks Using Synchrophasor Data

Graph Models of Electric Power Transmission Networks Using S...

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IEEE Southeastcon

作者： Ganesh K. Venayagamoorthy Dulip Madurasinghe Rajan Ratnakumar Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory Clemson University SC USA

The electric power transmission network (EPTN) is a connected, geographically distributed network, which can be represented with a graph model with nodes and edges. The graph represents the physical connectivity of the EPTN. Deriving the graph model of the EPTN solely based on continually measured data is important for reliable power system operational situation awareness and decreasing uncertainties driven by weather, electrification, and interconnections. In this paper, an exhaustive search algorithm is presented to derive the EPTN graph model (TNGM) solely based on synchrophasor measurements retrieved from the substations without prior knowledge of the connectivity. Furthermore, an evaluation metric for any data-driven TNGM is introduced. The transmission network of the two-area, four-machine power system is used as the test system, and typical TNGMs for different power plant operating conditions are presented. Typical graphs obtained for network impedance and power flows are shown to be accurate, on average within 2% error margin.

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Coordinated EMS for Stability Enhancement of NMGs During Disturbance and Fault Conditions

Coordinated EMS for Stability Enhancement of NMGs During Dis...

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Annual Conference of Industrial Electronics Society

作者： Hossam M. Hussein Mahmoud S. Abdelrahman Ibtissam Kharchouf S M Sajjad Hossain Rafin Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami Fl USA

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Power systems are evolving from centralized power grid structures to networks of intelligent microgrids (MGs) that can share power more independently. The interconnection between these MGs, forming the networked MGs (NMGs), will increase the power system’s stability and expand its capabilities. However, a critical concern that necessitates sophisticated management strategies for voltage stabilization across the microgrids is the optimal and effective power sharing between renewable resources and energy storage devices. Effective power sharing between AC and DC sides is critical, necessitating robust control mechanisms for interlink converters (ILC). This paper presents a coordinated energy management strategy for hybrid networked MGs (NMGs) to enhance stability during contingencies and fault instances. The proposed Energy Management System (EMS) operates in two distinct modes: grid-connected and islanded. The system takes specific actions to maintain stability depending on the current mode. In grid-connected mode, the grid supplies the load demand while one of the microgrids (MGs) serves as a backup to ensure system stability. Several scenarios were created using MATLAB/Simulink to test and validate the EMS. These scenarios included varying load demands, pulsed power loads, uncertainties in photovoltaic (PV) system generation, disconnection from the AC side, and fault conditions. The proposed EMS has proven its efficiency while maintaining the system stability within the standard limits and fulfilling the load demands.

关键词： Robust control Renewable energy sources Contingency management Microgrids Power system stability Stability analysis MATLAB Energy management systems Thermal stability Energy storage

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