智能电网与可再生能源(英文)最新文献_第3页

Disturbance Observer-Based Feedback Linearization Control for Three-Phase Power Inverters in Autonomous Mode of Operation 基于扰动观测器的三相功率逆变器自主运行反馈线性化控制

智能电网与可再生能源(英文) Pub Date : 2022-03-20 DOI: 10.1109/SGRE53517.2022.9774117

Samantha Stephen, H. Shareef, R. Errouissi, K. Phani Kiranmai

引用次数: 0

Reserve Formulations for Power-Based Unit Commitment with N-1 Security N-1安全下基于功率的机组承诺储备公式

智能电网与可再生能源(英文) Pub Date : 2022-03-20 DOI: 10.1109/SGRE53517.2022.9774206

Elis Nycander, G. Morales-España, L. Söder

引用次数: 0

Efficient Deep Learning Based Detector for Electricity Theft Generation System Attacks in Smart Grid 基于深度学习的智能电网窃电发电系统攻击检测器

智能电网与可再生能源(英文) Pub Date : 2022-03-20 DOI: 10.1109/SGRE53517.2022.9774050

Maymouna Ezeddin, A. Albaseer, M. Abdallah, S. Bayhan, M. Qaraqe, S. Al-Kuwari

{"title":"Efficient Deep Learning Based Detector for Electricity Theft Generation System Attacks in Smart Grid","authors":"Maymouna Ezeddin, A. Albaseer, M. Abdallah, S. Bayhan, M. Qaraqe, S. Al-Kuwari","doi":"10.1109/SGRE53517.2022.9774050","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774050","url":null,"abstract":"This paper investigates the problem of electricity theft attacks in the generation domain. In this attack, the adversaries aim to manipulate readings to claim higher energy injected into the grid for overcharging utility companies by hacking smart meters monitoring renewable-based distributed generation. In prior research, deep learning (DL) based detectors were developed to detect such behavior, though they relied on different data sources and overlooked the critical impact of small perturbations which an attacker could integrate into its reported energy. This paper takes advantage of addressing this gap by proposing an efficient DL-based detector that can offer much higher accuracy and detection rate using only a single source of data by adding two features to enhance the performance. Subsequently, the proposed detector is further extended to cope with the small perturbations that attackers can add. We carry out extensive simulation using realistic data sets, and the results show that the proposed models detect the adversaries with higher rate detection even with small perturbations.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"114 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88122842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Multi-objective Optimization of a DC Microgrid with a Back-up Diesel Generator 带备用柴油发电机的直流微电网多目标优化

智能电网与可再生能源(英文) Pub Date : 2022-03-20 DOI: 10.1109/SGRE53517.2022.9774128

Elie Hleihel, M. Fadel, H. Kanaan

{"title":"Multi-objective Optimization of a DC Microgrid with a Back-up Diesel Generator","authors":"Elie Hleihel, M. Fadel, H. Kanaan","doi":"10.1109/SGRE53517.2022.9774128","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774128","url":null,"abstract":"Nowadays, microgrid applications are proliferate all around the world. Owing to many grounds, such the ease of control, the high efficiency and reliability, the improvement of power electronics devices, the rise of DC type loads and sources, etc. researchers’ interest was diverted from AC to DC microgrids. Yet, on a global control and management level, several challenges are confronted. A variety of objectives can be achieved by controlling the power flow of each of the distributed energy sources. By means of this, an optimization problem is formulated and solved using heuristic methods such the genetic algorithm (GA), the particle swarm optimization (PSO), the pattern search (PS), etc. However, other techniques were exploited in the literature such the dynamic programming (DP) which is a stepby-step optimization algorithm. In this paper, a (DP) technique is applied to solve a multi-objective optimization problem. Two objectives are set: DC microgrid operation cost minimization, and pollutant gas emissions reduction. A sole cost function is established, and weights are assigned to each of the predefined goals. Besides, each objective function is detailed apart, and several constrains are set. Two simulations tests are performed to prove the convergence, and the viability of the applied (DP) technique. Finally, different weights are selected in each of simulation tests to validate the effectiveness, and robustness of the (DP) in solving such problems.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"43 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88418371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Formal Verification of a Dynamic Multi-factor Secure Communication Protocol 动态多因素安全通信协议的形式化验证

智能电网与可再生能源(英文) Pub Date : 2022-03-20 DOI: 10.1109/SGRE53517.2022.9774119

K. Scott, S. Khatri, A. Ghrayeb

{"title":"Formal Verification of a Dynamic Multi-factor Secure Communication Protocol","authors":"K. Scott, S. Khatri, A. Ghrayeb","doi":"10.1109/SGRE53517.2022.9774119","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774119","url":null,"abstract":"In a smart grid, there is much sensitive data that must be transmitted continually. This requires secure communication protocols that are well-suited for use in a smart grid context. A typical smart grid is composed of many agents - like smart meters and control centers - and hence it is necessary that its communication protocols not only are cryptographically secure, but also fast and lightweight. In this paper, we perform formal verification on a novel secure communication protocol to be used in a smart grid. In each protocol iteration, the two parties that wish to communicate will exchange authentication tokens to establish trust and generate session keys. The authentication tokens have three key features: (1) each token is constructed using multiple factors, preventing a single point of failure, (2) the factors are updated dynamically during every protocol iteration, ensuring that authentication keys potentially snooped by an attacker are never reused, and (3) factor updates utilize a True Random Number Generator (TRNG), and therefore cannot be deterministically or algorithmically predicted. This paper describes the protocol as implemented between two arbitrary agents in a smart grid. We realize the protocol in software, and formally verify the protocol using ProVerif. Our results demonstrate that our protocol is a secure and lightweight communication protocol that would be suitable for use in a smart grid.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"4 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75862089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detection and Classification of Defects in XLPE Power Cable Insulation via Machine Learning Algorithms 基于机器学习算法的XLPE电力电缆绝缘缺陷检测与分类

智能电网与可再生能源(英文) Pub Date : 2022-03-20 DOI: 10.1109/SGRE53517.2022.9774113

M. Saleh, S. Refaat, S. Khatri, A. Ghrayeb

{"title":"Detection and Classification of Defects in XLPE Power Cable Insulation via Machine Learning Algorithms","authors":"M. Saleh, S. Refaat, S. Khatri, A. Ghrayeb","doi":"10.1109/SGRE53517.2022.9774113","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774113","url":null,"abstract":"Due to high electric stresses in power equipment, insulation degradation has been prevalent as a result of increased PD exposure. In this paper, we study different machine learning (ML) methods for the detection and classification of partial discharges (PDs) for assessing the reliability of insulation systems. We introduce and examine a set of features using selected machine learning-based algorithms. The aim is to detect and classify PDs transpiring within insulation systems. Therefore, this paper presents tools to detect defects using suitable PD sensors and Machine Learning algorithms to facilitate diagnostics and enhance isolation system design. Experiments are being conducted on several voids in the insulator with varying shapes and sizes. A PD sensor is used for detecting the PDs taking place. Due to the presence of noise and other external interferences, appropriate filters and denoising methods are implemented. After that, the relevant PD features, such as the PD magnitude, PD repetition rate, statistical features, wavelet features, etc., are extracted. This study attempts to emphasize the importance of classifying the type of defect, as this will allow engineers to determine the severity of the fault taking place, and take the proper countermeasures.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"56 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79258542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Vulnerabilities and Strategies of Cybersecurity in Smart Grid - Evaluation and Review 智能电网中的网络安全漏洞与策略——评估与回顾

智能电网与可再生能源(英文) Pub Date : 2022-03-20 DOI: 10.1109/SGRE53517.2022.9774038

Amira Mohammed, Gibin George

引用次数: 4

ANN based Auto-Tuned Optimized FCS-MPC for Grid-Connected CSC Inverter 基于神经网络的并网CSC逆变器自调谐优化FCS-MPC

智能电网与可再生能源(英文) Pub Date : 2022-03-20 DOI: 10.1109/SGRE53517.2022.9774145

A. N. Alquennah, M. Trabelsi, A. Krama, H. Vahedi, Mostefa Mohamed-Seghir

{"title":"ANN based Auto-Tuned Optimized FCS-MPC for Grid-Connected CSC Inverter","authors":"A. N. Alquennah, M. Trabelsi, A. Krama, H. Vahedi, Mostefa Mohamed-Seghir","doi":"10.1109/SGRE53517.2022.9774145","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774145","url":null,"abstract":"This paper proposes an auto-tuned finite control set-model predictive control (FCS-MPC) for a grid-tied singlephase crossover switches cell (CSC) inverter. The multilevel inverter (MLI) under study generates 9 voltage levels. The FCSMPCobjective is to minimize the total harmonic distortion (THD) of the current fed to the grid with unity power factor while regulating the capacitor voltage at its reference value to maintain the 9 voltage levels. The switching losses are reduced by managing the redundant switching states selection. Artificial Neural Network (ANN) based on the Bayesian regularized feedforward learning technique is applied to predict the optimal weighting factor of the FCS-MPC with respect to the measured reference current value. The effect of using a dynamic weighting factor on the current THD for different reference current peak values (ranging from 2A to 8A) is studied through MATLAB/Simulink simulation. The presented simulation is intended to show that the application of a dynamic weighting factor can significantly enhance the current THD compared to the use of a fixed weighting factor.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"16 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76556595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Performance Enhancement of SMC Based Buck Converter under Variable Conditions by Particle Swarm Optimization Algorithm 基于粒子群优化算法的变条件下SMC降压变换器性能增强

智能电网与可再生能源(英文) Pub Date : 2022-03-20 DOI: 10.1109/SGRE53517.2022.9774271

S. Vadi, R. Bayindir

引用次数: 0

Sensorless Backstepping Control of Multiphase Induction Machines Under Fault Conditions 故障条件下多相感应电机的无传感器反步控制

智能电网与可再生能源(英文) Pub Date : 2022-03-20 DOI: 10.1109/SGRE53517.2022.9774112

A. Kouzou, M. Morawiec, F. Wilczyński

引用次数: 0