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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Milos Stanojevic Gordana Ostojic Tamara Skoric Natasa Popovic Srdjan Lale Nikola Kukric Department of Industrial Engineering and Management Faculty of Technical Sciences Center for Identification Technologies Novi Sad Serbia Department of Power Electronic and Telecommunication Engineering Faculty of Technical Sciences Novi Sad Serbia Department of Automation and Robotics Faculty of Electrical Engineering University of East Sarajevo East Sarajevo Bosnia and Herzegovina Department of Electronics and Electonic Systems Faculty of Electrical Engineering University of East Sarajevo East Sarajevo Bosnia and Herzegovina

ISBN: (数字)9798331515799

ISBN: (纸本)9798331515805

The development of pervasive healthcare systems in the automotive industry is enabled by unobtrusive acquisition systems for recording vital parameters of drivers and developed ML algorithms for driver health services. The paper proposes a pervasive system based on the acquisition of the cECG signal recorded through clothing during driving, the transmission of the cECG to the local device for processing cECG and extraction of cECG parameters, and the extracted parameters transmission via vehicle-to-infrastructure (V2I) communication channel to the cloud. The potential of cyber security risk in implementing the proposed system is identified.

关键词： Industries Vehicle-to-infrastructure Clothing Medical services Communication channels Recording Computer crime Vehicles Automotive engineering

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Investigation of Transformer Oil Properties with advanced Multidimensional Methods 13

Investigation of Transformer Oil Properties with advanced Mu...

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13th IEEE International Conference on the Properties and Applications of Dielectric Materials, ICPADM 2021

作者： Schreiter, Sebastian Lohmeyer, Holger Werle, Peter Leipzig University of Applied Science Faculty of Electrical Engineering Institute for Electrical Power Systems Leipzig Germany Hitachi Abb Power Grids Engineering Solutions Department Halle Germany Schering-Institute Leipniz University Hannover Institute of Electric Power Systems Division of High Voltage Engineering and Asset Management Hannover Germany

ISBN: (纸本)9781728182384

power Transformers are basic elements in electric power systems. In case of an unplanned outage due to failure at the transformer not only to the costs reflected to the repair costs but also the costs related to interrupted power supply or the stop of production will occur. Therefore, it is necessary to assess the condition of power transformers and to identify risks early. For this, different diagnostic techniques were developed. In this context oil test, such as the measurement of the oil properties and the DGA, are well established and easy to perform *** the help of the insulation oil properties, possible aging of the oil can be identified and the remaining capability withstand dielectric stresses can be investigated. Because some parameters indicate the same properties (such as ageing state) it could be possible that there are pairs or groups of parameters, which give redundant results. Therefore, in this contribution it is investigated if a correlation between different insulation oil properties can be found. Furthermore, it was investigated if relationships between insulation oil properties and DGA results can be *** investigations were based on a huge number of oil test results of real transformers of different voltage levels, applications, age, and manufacturers. © 2021 IEEE.

关键词： power transformers

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An overview of PMU-based electrical power systems modelling for power Quality enhancement

An overview of PMU-based Electrical Power Systems modelling ...

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International Universities power engineering Conference (UPEC)

作者： Nicolae Anton Constantin Bulac Mihai Sănduleac Eda-Elif Gemil Bogdan Dobrin Vlăduț-Andrei Ion Electrical Power Systems Dept University POLITEHNICA of Bucharest Bucharest Romania Department of Electrical Power Systems Faculty of Energy Engineering University Politehnica of Bucharest Bucharest Romania

ISBN: (数字)9781665455053

ISBN: (纸本)9781665455060

The increasingly important use of renewable energy resources within the electricity networks has changed the paradigm of electrical power system operation. This shift is enforced by the ever-present power electronic devices, which are used both at generation side, as well as on the consumption side, cluttering the normal operation, and issuing new threats from power quality point of view. However, the new technology involved in the advanced metering systems, such as Phasor Measurement Units (PMUs), is helping both transmission and distribution operators to efficiently manage the electrical system, by correctly identify the upcoming threats for a priori calculations, as well as the causes which may have led to faults, for a posteriori evaluation. This paper deals with the widespread use of PMU-based advanced metering systems.

关键词： Fault diagnosis Renewable energy sources power engineering power measurement power quality Phasor measurement units power electronics

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Collective Citizen Energy Investment Models for Solar power: Case Study Croatia

Collective Citizen Energy Investment Models for Solar Power:...

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Future Energy Solutions (FES), International Conference on

作者： Lin Herenčić Tomislav Capuder Mislav Kirac Goran Čačić Department of Energy and Power Systems University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia Green Energy Cooperative (ZEZ) Zagreb Croatia

Cost-competitiveness of decentralized renewable energy sources (RESs) has opened opportunities for citizens’ ownership of RES and for the development of new business models. Citizen energy investment models based on cooperative principles have gained increased attention lately due to promises to support local economic welfare, boost local economy, increase social cohesion, help in grid optimization, and increase citizens’ support for new RES projects. In this paper, we provide an overview of collective citizen energy investment concepts and describe the six types of models being developed in Croatia. We provide an overview of the initiatives together with the challenges, threats, and opportunities found when concepts are faced with the real-life practice in Croatia. We show that even though citizens’ ownership of RES (mainly individual solar PV systems) is strongly increasing, the current developments of collective (group) citizen energy investment models are predominantly related to sporadic research projects and enthusiasts’ initiatives, meaning still no wider-scope investments in RES have been conducted this way. Following the findings, we provide recommendations for removing the barriers and speeding up the development of such projects in the future.

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Analysis of the Magneto-Mechanical Characteristic of Double Three-phase PMSM 3

Analysis of the Magneto-Mechanical Characteristic of Double ...

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3rd IEEE Ukraine Conference on electrical and Computer engineering, UKRCON 2021

作者： Makarchuk, Oleksandr Kharchyshyn, Bohdan Kasha, Lidiia Institute of Power Engineering and Control Systems Lviv Polytechnic National University Lviv Ukraine Faculty of Electrical Engineering Czestochowa Universityof Technology Czestochowa Poland

ISBN: (纸本)9781665400947

The article studies the performance of a multiphase brushless synchronous motor with excitation from permanent magnets (PMSM). The motor has two sets of independent and unconnected three-phase windings on the stator, which resulting magneto-move forces are shifted by 30 electrical degrees. These windings are supplied with two independent three-phase current systems. The study is based on the analysis of the so-called magnetic mechanical characteristic (MMC) as a multidimensional dependence of the flux linkages of the phase windings and the machine electromagnetic torque from all phase currents and the angle of the rotor position. The analysis is based of the FEM calculation of the 2D machine magnetic field. The mutual influence of dependent and independent MMC variables have been researched with changes in the magnitude of load currents, the initial phases of these currents and the angle of the rotor position. The obtained calculation results are analyzed with regard to the expansion of the machine speed range in the constant power mode at field-oriented control (FOC). © 2021 IEEE.

关键词： Flux linkage

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Impact of High Photovoltaic Penetration on the Voltage Stability of Vietnam's power System

Impact of High Photovoltaic Penetration on the Voltage Stabi...

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International Youth Conference on Radio Electronics, electrical and power engineering (REEPE)

作者： Nam H. Pham Oleg N. Kuzetsov Canh T. Doan Electrical Power Systems Department National Research University “MPEI” Moscow Russian Federation Department of Electrical and Electronic Engineering Technology Institute of Engineering and Technology Vinh University Viet Nam Department of Relay Protection and Automation of Energy Systems National Research University “MPEI” Moscow Russian Federation Faculty of Engineering and Technology Hong Duc University Vietnam

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

Photovoltaics (PV) play an essential role in energy networks by promoting clean, sustainable energy and reducing reliance on fossil fuels. However, their operational characteristics introduce new challenges, particularly concerning grid reliability and voltage stability. In this paper, the impact of solar photovoltaic plant (SPP) penetration on voltage behavior in the central region of Vietnam is examined using dynamic models at different integration levels, ranging from 0% to 40%. The results reveal that while low SPP penetration has minimal effects, high penetration levels (30% and 40%) significantly reduce reactive power support, exacerbating voltage collapse risks. These findings underscore the necessity for advanced voltage and reactive power control strategies to ensure grid stability in high-SPP scenarios.

关键词： Photovoltaic systems Reactive power Reactive power control power system dynamics power system stability Stability analysis Threshold voltage Synchronous generators Reliability Voltage control

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A PID-incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis

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IEEE/CAA Journal of Automatica Sinica 2022年第3期9卷 533-546页

作者： Hao Wu Xin Luo MengChu Zhou Muhyaddin J.Rawa Khaled Sedraoui Aiiad Albeshri Chongqing Institute of Green and Intelligent Technology Chinese Academy of SciencesChongqing 400714and also with the University of Chinese Academy of SciencesBeijing 100049China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA IEEE Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of Engineeringand K.A.CARE Energy Research and Innovation CenterKing Abdulaziz UniversityJeddah 21589Saudi Arabia College of Engineering King Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Computer Science King Abdulaziz UniversityJeddah 21481Saudi Arabia

A large-scale dynamically weighted directed network(DWDN)involving numerous entities and massive dynamic interaction is an essential data source in many big-data-related applications,like in a terminal interaction pattern analysis system(TIPAS).It can be represented by a high-dimensional and incomplete(HDI)tensor whose entries are mostly *** such an HDI tensor contains a wealth knowledge regarding various desired patterns like potential links in a DWDN.A latent factorization-of-tensors(LFT)model proves to be highly efficient in extracting such knowledge from an HDI tensor,which is commonly achieved via a stochastic gradient descent(SGD)***,an SGD-based LFT model suffers from slow convergence that impairs its efficiency on large-scale *** address this issue,this work proposes a proportional-integralderivative(PID)-incorporated LFT *** constructs an adjusted instance error based on the PID control principle,and then substitutes it into an SGD solver to improve the convergence *** studies on two DWDNs generated by a real TIPAS show that compared with state-of-the-art models,the proposed model achieves significant efficiency gain as well as highly competitive prediction accuracy when handling the task of missing link prediction for a given DWDN.

关键词： Big data high dimensional and incomplete(HDI)tensor latent factorization-of-tensors(LFT) machine learning missing data optimization proportional-integral-derivative(PID)controller

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TSO-DSO Coordinated Operational Planning in the Presence of Shared Resources $i,m,o,t$

TSO-DSO Coordinated Operational Planning in the Presence of ...

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power Tech Conference

作者： Micael Simoes Andre G. Madureira Filipe Soares Joao Pecas Lopes Center for Power and Energy Systems INESC TEC Porto Portugal Intelligent Clean Energy Systems LIST Belvaux Luxembourg Department of Electrical and Computer Engineering Faculty of Engineering of University of Porto Porto Portugal

Electric power systems are currently experiencing a profound change, as increasing amounts of Renewable Energy Sources (RESs) displace conventional forms of generation. This development has gone hand-in-hand with an increasing share of distributed power generation being connected directly to the Distribution Network (DN), and the widespread of other types of Distributed Energy Resources (DERs), such as Energy Storage Sytems (ESSs), Electric Vehicles (EVs), and active (flexible) consumers. As these trends are expected to continue, this will require a profound revision of the way Transmission System Operators (TSOs) and Distribution System Operators (DSOs) interact with each other to fully benefit from the growing flexibility that is available at the DN level. In this work we propose a new tool for the coordinated operational planning of transmission and distribution systems, considering the existence of shared resources that can be simultaneously used by TSO and DSOs for the optimal operation of their networks. The tool uses advanced distributed optimization techniques, namely the Alternating Direction Method of Multipliers (ADMM) in order to maintain data privacy of the several agents involved in the optimization problem, and keep the tractability of the problem. The proposed tool is applied to modified IEEE test systems, and the results obtained highlight the benefits of the proposed coordination mechanism to solve problems occurring simultaneously at the transmission and DN-levels.

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Machine learning-based forecast of secondary distribution network losses calculated from the smart meters data

Machine learning-based forecast of secondary distribution ne...

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International Multidisciplinary Conference on Computer and Energy Science (SpliTech)

作者： Terezija Matijaš ević Tomislav Antić Tomislav Capuder Department of Energy and Power Systems University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (纸本)9781665488280

With greater integration of smart meters, an opportunity to increase the observability of the traditionally unobservable low-voltage distribution networks is created. The purpose of such meters is mainly to collect and store data on end-user consumption for billing purposes, and it is these large data flows that open up a wide range of analyses to Distribution System Operators. Leading in this is the prediction of end-user consumption, which finds its application especially in determining network losses for more efficient planning and operation of distribution networks. Due to the complicated features of the collected load series data, the application of synthetic curves for the consumption forecasting problem is abandoned and energy utilities are turning to more complex solutions, most often based on machine learning algorithms. Therefore, this paper presents a machine learning-based model for forecasting losses in a low-voltage distribution network. power flow simulation tools are frequently used to estimate and predict active power losses but are applied only in the case of available network topology and elements data. Hence, in this paper, special emphasis is placed on a model that does not rely on network data, but only on historical measurements collected from smart meters. The model is tested on a real-world distribution network with more than 150 end-users. The results show the effectiveness of the model in forecasting active power losses of the observed network, but also highlight the sensitivity of the model to errors, which is a good basis for the implementation of additional algorithms and variables as a means to enabling near real-time operation planning of distribution networks.

关键词： Low voltage Substations Machine learning algorithms Network topology Distribution networks Predictive models Smart meters

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