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Stochastic Unit Commitment: Model Reduction via Learning

Current Sustainable/Renewable Energy Reports 2023年第2期10卷 36-44页

作者： Liu, Xuan Conejo, Antonio J. Constante Flores, Gonzalo E. Department of Electrical and Computer Engineering The Ohio State University ColumbusOH43210 United States Department of Integrated Systems Engineering The Ohio State University ColumbusOH43210 United States Davidson School of Chemical Engineering Purdue University West LafayetteIN47907 United States

Purpose of Review: As weather-dependent renewable generation increases its share in the generation mix of most electric energy systems, a stochastic unit commitment becomes the natural day-ahead scheduling tool. However, such a tool is generally computationally intractable if a detailed uncertainty description is considered. Taking this into account, we proposed a learning method to make the stochastic unit commitment problem tractable. Recent Findings: Recent advances in statistical learning and machine learning to address optimization problems can be advantageously applied to the rather intractable stochastic unit commitment problem. Considering these advances, we explore simple learning techniques to drastically reduce the size of a stochastic unit commitment problem without significantly altering its optimal solution. Summary: The considered stochastic unit commitment problem is formulated as a two-stage stochastic programming problem. The first stage represents commitment decisions, while the second one represents the operation conditions under different scenarios. Taking into account historical solved instances (or proxies for them), we reduce the size (measured by numbers of constraints and variables) of the stochastic unit commitment problem by (i) fixing unchanged binary variables and by (ii) eliminating inactive inequality constraints. Our numerical results show that the reduced problem generally requires significantly less time to solve while obtaining high-quality solutions, which are very close to or indistinguishable from the one obtained by solving the original problem. We use an Illinois 200-bus system to illustrate and characterize the performance of the proposed problem-reduction method. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Stochastic programming

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State Estimation for Integrated Energy systems: Motivations, Advances, and Future Work

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IEEE Transactions on Power systems 2024年第4期40卷 3057-3073页

作者： Zhao, Junbo Srivastava, Ankur Guo, Ye Cetenovic, Dragan Lin, Yuzhang Levi, Victor Yin, Guanxiong Huang, Manyun Zhang, Tingting Li, Zhigang Chen, Yanbo Exposito, Antonio G. Zhang, Wen Zheng, Weiye Chakrabarti, Saikat Li, Yang Sharma, Ankush Kamwa, Innocent Guo, Qinglai Terzija, Vladimir Mili, Lamine University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States Tsinghua University Tsinghua-Berkeley Shenzhen Institute Shenzhen518055 China The University of Manchester Department of Eee ManchesterM13 9PL United Kingdom University of Kragujevac Faculty of Technical Sciences Čačak Čačak32000 Serbia New York University Department of Electrical and Computer Engineering NY11201 United States Tsinghua University Department of Electrical Engineering Beijing100084 China Hohai University College of Energy and Electrical Engineering Nanjing210098 China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan250061 China The Chinese University of Hong Kong-Shenzhen School of Science and Engineering Shenzhen518172 China North China Electric Power University School of Electrical and Electronic Engineering Beijing102206 China University of Sevilla Spain Sevilla41092 Spain South China University of Technology School of Electrical Power Engineering Guangzhou510641 China Indian Institute of Technology Kanpur Department of Electrical Engineering Kanpur208016 India Northeast Electric Power University School of Electrical Engineering Jilin132012 China Laval University Department of Electrical and Computer Engineering QuebecQCG1V 0A6 Canada Tsinghua University State Key Laboratory of Power Systems Department of Electrical Engineering Beijing100084 China Newcastle University School of Engineering Newcastle upon TyneNE1 7RU United Kingdom Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering Falls ChurchVA22043 United States

This paper summarizes the technical activities of a three-year-long IEEE Task Force (TF) on State Estimation (SE) for Integrated Energy systems (IES). It presents the formal definition and characteristics of IES, along with the comprehensive discussion on Electric Power systems (EPS) model, and static and dynamic models associated with heating and natural gas systems. The paper also identifies the barriers of SE for IES, such as estimation modeling, observability analysis, and measurement requirements, together with addressing multi-scale dynamics. An extensive comparative analysis between Integrated Energy systems-State Estimation (IES-SE) and more established Electric Power System-State Estimation (EPS-SE) is presented. The paper also provides future research needs and directions related to IES-SE. © 1969-2012 IEEE.

关键词： Power system analysis

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An Overview and Experimental Study of Learning-Based Optimization Algorithms for the Vehicle Routing Problem

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1115-1138页

作者： Bingjie Li Guohua Wu Yongming He Mingfeng Fan Witold Pedrycz School of Traffic and Transportation Engineering Central South UniversityChangsha 410075China College of Systems Engineering National University of Defense TechnologyChangsha 410073China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6G 2V4Canada the Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia the Systems Research Institute Polish Academy of SciencesWarsaw 01447Poland IEEE

The vehicle routing problem(VRP)is a typical discrete combinatorial optimization problem,and many models and algorithms have been proposed to solve the VRP and its *** existing approaches have contributed significantly to the development of this field,these approaches either are limited in problem size or need manual intervention in choosing *** solve these difficulties,many studies have considered learning-based optimization(LBO)algorithms to solve the *** paper reviews recent advances in this field and divides relevant approaches into end-to-end approaches and step-by-step *** performed a statistical analysis of the reviewed articles from various aspects and designed three experiments to evaluate the performance of four representative LBO ***,we conclude the applicable types of problems for different LBO algorithms and suggest directions in which researchers can improve LBO algorithms.

关键词： End-to-end approaches learning-based optimization(LBO)algorithms reinforcement learning step-by-step approaches vehicle routing problem(VRP)

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Comprehensive Overview of Multi-agent systems for Controlling Smart Grids

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CSEE Journal of Power and Energy systems 2022年第1期8卷 115-131页

作者： Om Prakash Mahela Mahdi Khosravy Neeraj Gupta Baseem Khan Hassan Haes Alhelou Rajendra Mahla Nilesh Patel Pierluigi Siano Power System Planning Division Rajasthan Rajya Vidyut Prasaran Nigam Ltd.Jaipur-302005India Media Integrated Communication Laboratory Graduate School of EngineeringOsaka UniversityOsakaJapan Computer Science and Engineering Department Oakland UniversityRochesterUSA Department of Electrical and Computer Engineering Hawassa UniversityHawassa 1530Ethiopia Faculty of Mechanical and Electrical Engineering Tishreen UniversityLattakiaSyria Department of Electrical Engineering National Institute of Technology Kurukshetra Department of Management&Innovation Systems University of Salerno84084 SalernoItaly

Agents are intelligent entities that act flexibly and autonomously and make wise decisions based on their intelligence and experience.A multi-agent system(MAS)contains multiple,intelligent,and interconnected collaborating agents for solving a problem beyond the ability of a single agent.A smart grid(SG)combines advanced intelligent systems,control techniques,and sensing methods with an existing utility power *** controlling smart grids,various control systems with different architectures have already been ***-based control of power system operations has been shown to overcome the limitations of time required for analysis,relaying,and protection;transmission switching;communication protocols;and management of plant *** systems provide an alternative for fast and accurate power network *** paper provides a comprehensive overview of MASs used for the control of smart *** paper provides a wide-spectrum view of the status of smart grids,MAS-based control techniques and their implementation for the control of smart *** of MASs in the control of various aspects of smart grids-including the management of energy,marketing energy,pricing,scheduling energy,reliability,network security,fault handling capability,communication between agents,SG-electrical vehicles,SG-building energy systems,and soft grids—have been critically *** than a hundred publications on the topic of MAS-based control of smart grids have been critically examined,classified,and arranged for fast reference.

关键词： Coordinated control multi-agent systems renewable energy sources smart energy infrastructure smart grid

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Optimal Load Forecasting Model for Peer-to-Peer Energy Trading in Smart Grids

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computers, Materials & Continua 2022年第1期70卷 1053-1067页

作者： Lijo Jacob Varghese K.Dhayalini Suma Sira Jacob Ihsan Ali Abdelzahir Abdelmaboud Taiseer Abdalla Elfadil Eisa Department of Electrical and Electronics Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Electrical and Electronics Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science and Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala LumpurMalaysia Department of Information Systems King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia

Peer-to-Peer(P2P)electricity trading is a significant research area that offers maximum fulfilment for both prosumer and *** also decreases the quantity of line loss incurred in Smart Grid(SG).But,uncertainities in demand and supply of the electricity might lead to instability in P2P market for both prosumer and *** recent times,numerous Machine Learning(ML)-enabled load predictive techniques have been developed,while most of the existing studies did not consider its implicit features,optimal parameter selection,and prediction *** order to overcome fulfill this research gap,the current research paper presents a new Multi-Objective Grasshopper Optimisation Algorithm(MOGOA)with Deep Extreme Learning Machine(DELM)-based short-term load predictive technique i.e.,MOGOA-DELM model for P2P Energy Trading(ET)in *** proposed MOGOA-DELM model involves four distinct stages of operations namely,data cleaning,Feature Selection(FS),prediction,and parameter *** addition,MOGOA-based FS technique is utilized in the selection of optimum subset of ***,DELM-based predictive model is also applied in forecasting the load *** proposed MOGOA model is also applied in FS and the selection of optimalDELM parameters to improve the predictive *** inspect the effectual outcome of the proposed MOGOA-DELM model,a series of simulations was performed using UK Smart Meter *** the experimentation procedure,the proposed model achieved the highest accuracy of 85.80%and the results established the superiority of the proposed model in predicting the testing data.

关键词： Peer to Peer energy trade smart grid load forecasting machine learning feature selection

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Decentralized Droop-based Finite-Control-Set Model Predictive Control of Inverter-based Resources in Islanded AC Microgrid

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IFAC-PapersOnLine 2024年第28期58卷 384-389页

作者： Ayobami Olajube Koto Omiloli Satish Vedula Olugbenga M. Anubi Department of Electrical and Computer Engineering the Center for Advanced Power Systems Florida State University

This paper presents an improved droop control method to ensure effective power sharing, voltage regulation, and frequency stabilization of inverter-based resources (IBRs) connected in parallel in an islanded AC microgrid. In the contemporary droop control algorithm, the distance between connected inverters affects the effectiveness of the active power-frequency and the reactive power-voltage droop characteristics which results in poor power sharing at the primary level of the microgrid. That is, high impedance emanating from long transmission lines results in instability, poor voltage tracking, and ineffective frequency regulation. Hence, in this work, we use a finite-control-set model predictive controller (FCS-MPC) in the inner loop, which gives efficient voltage tracking, good frequency regulation, and faster performance response. FCS-MPC is easy to implement in fast switching converters and does not suffer from computational burden unlike the continuous-set MPC and is also devoid of issues of multiple-loop, parameter variation, and slow response associated with conventional droop control methods. We derived the condition for bounded stability for the FCS-MPC and the proposed method is tested via a numerical simulation on three IBRs. The results show effective power sharing, capacitor voltage tracking, and efficient frequency regulation with reduced oscillations to changes in load.

关键词： Droop control finite-control-set model predictive control active power sharing reactive power sharing voltage regulation inverter-based resources islanded microgrid

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Multidimensional Voronoi Constellations vs. Short Blocklength Probabilistic Shaping: A Comparison for Multilevel Coding Approach

Multidimensional Voronoi Constellations vs. Short Blocklengt...

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2024 Asia Communications and Photonics Conference, ACP 2024 and International Conference on Information Photonics and Optical Communications, IPOC 2024

作者： Sheng, Yajie Chen, Bin Lei, Yi Deng, Jingxin Xu, Jiwei Fu, Mengfan Zhuge, Qunbi Li, Shen Department of Computer Science and Information Engineering Hefei University of Technology Hefei China State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China Department of Electrical and Computer Engineering Université Laval Québec Canada

Performance of concatenated multilevel coding with probabilistic shaping (PS) and Voronoi constellations (VCs) is analysed over AWGN channel. Numerical results show that VCs provide up to 1.3 dB SNR gains over PS-QAM ... 详细信息

ISBN: (纸本)9798350379266

关键词： Probability distributions

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BioPoint: Enhancing Human-computer Interaction through Single-Site, Multi-Sensor Gesture Recognition 46

BioPoint: Enhancing Human-Computer Interaction through Singl...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Isabel, Xavier Campbell, Evan Olivier, Loïc Gagné, Gabriel Scheme, Erik Côté-Allard, Ulysse Gagnon-Turcotte, Gabriel Laval University Dept. of Electrical and Computer Engineering QC Canada University of New Brunswick Department of Electrical and Computer Engineering FrederictonNBE3B 5A3 Canada University of Oslo Dept. of Technology Systems Oslo Norway

ISBN: (纸本)9798350371499

Advancements in human-computer interaction (HCI) and machine learning are seen as key avenues to help individuals living with upper limb disabilities in accomplishing their activities of daily living. Multi-channel myoelectric systems are a promising approach for HCI due to their intuitive and accurate capture of user intent through muscle activity. However, such systems are still bulky compared to widely accepted smartwatches-like devices and as such pose a challenge for seamless integration into daily life. Consequently, this work presents the first single-site EMG-IMU-PPG system for multi-gesture recognition from the wrist. Overall, when evaluated on eight able-bodied participant, the system achieves an average accuracy of 65.28%±10.45% on 17 finger and wrist gestures and 90.98%±5.65% on eight hand gestures. This study also introduces "Myo Hero", an online environment inspired by "Guitar Hero."Myo Hero provides a dynamic method for testing multi-gesture recognition systems, improving the evaluation process's appeal. Online evaluation of the multimodal system substantially outperformed random play, signifying EMG-IMU-PPG's potential for human-computer interaction. © 2024 IEEE.

关键词： Electromyography

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Self-excitation of Terahertz Plasmons in Graphene FETs Enabled by Transit-time Negative Dynamic Conductance 2

Self-excitation of Terahertz Plasmons in Graphene FETs Enabl...

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2nd International Conference for Advancement in Technology, ICONAT 2023

作者： Ryzhii, Maxim Ryzhii, Victor Otsuji, Taiichi Mitin, Vladimir Shur, Michael S. University of Aizu Department of Computer Science and Engineering Aizu-Wakamatsu Japan Research Institute of Electrical Communication Tohoku University Sendai Japan University at Buffalo Department of Electrical Engineering SUNY BuffaloNY United States Rensselaer Polytechnic Institute Department of Electrical Computer and Systems Engineering TroyNY United States

ISBN: (纸本)9781665475174

The interband Zener-Klein interband tunneling in the field-effect transistors (FETs) with the graphene channels consisting of the reverse-biased p-i-n junctions enables the negative dynamic conductance associated with the electrons and hole propagation delays. This can lead to the self-excitation of plasmons in the gated p- and n-regions. For the submicrometer gate lengths, the frequency of these plasmons is in the terahertz (THz) range. The plasmon self-excitation in this regime can be used for the generation of THz radiation. © 2023 IEEE.

关键词： Plasmons

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Secured Framework for Vehicle Management Using Blockchain

Secured Framework for Vehicle Management Using Blockchain

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2024 International Conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Poonguzhali, N. Amarabalan, N. School of Computer and Systems Sciences Jawaharlal Nehru University New Delhi India Manakula Vinayagar Institute of Technology Department of Electrical and Electronics Engineering Puducherry India

ISBN: (纸本)9798331510022

For many years, there were many different ways to arrange a vehicle's information using just the license plate. The number on a vehicle's license plate is the primary symbol used to identify it. The industries used to reciprocate the number plates in order to further uphold their basic standards. Anonymization through encryption is the preferred privacy setting for a license plate. We will have access to all the services required for faultless data maintenance through the Vehicle Management system. The entire system depends on the data, which is technologically encrypted and decrypted. However, data stored on a chip will be more secure than image recognition. It reduces the likelihood of mistakes and misunderstandings of the required information. Vehicle-related data is stored in a decentralized system. The suggested system either retrieves data from the smart number plate or uses an image processing technique to determine the license plate number through edge detection. The required data can be seen with this number. In order to ensure security, these data are encrypted using the SHA-256 algorithm and stored in a decentralized system using the Hyperledger Sawtooth framework, which also employs the PoET and BFT algorithms. © 2024 IEEE.

关键词： Blockchain

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