2021 6th IEEE Workshop on the Electronic Grid (eGRID)最新文献_第4页

A Decentralized PCC Voltage Secondary Control Method Based on Small-AC-Signal Injection for Parallel Inverters in Islanded Microgrids 孤岛微电网并联逆变器小交流信号注入分散PCC电压二次控制方法

2021 6th IEEE Workshop on the Electronic Grid (eGRID) Pub Date : 2021-11-08 DOI: 10.1109/eGRID52793.2021.9662133

Yidong Shi, Zeng Liu, Jiazhi Wang, Jinjun Liu

引用次数: 2

Modeling and Stability Analysis of Converter-Dominated Grids with Dynamic Loads 带动负荷变流器控制电网的建模与稳定性分析

2021 6th IEEE Workshop on the Electronic Grid (eGRID) Pub Date : 2021-11-08 DOI: 10.1109/eGRID52793.2021.9662151

Huoming Yang, Malte Eggers, Peter Teske, S. Dieckerhoff

{"title":"Modeling and Stability Analysis of Converter-Dominated Grids with Dynamic Loads","authors":"Huoming Yang, Malte Eggers, Peter Teske, S. Dieckerhoff","doi":"10.1109/eGRID52793.2021.9662151","DOIUrl":"https://doi.org/10.1109/eGRID52793.2021.9662151","url":null,"abstract":"In recent years, continuous efforts have been made on the modeling and stability analysis of converter-dominated grids (CDGs) to guarantee efficient, stable and resilient operations. The literature has tried to reveal the mechanism behind abnormal instability and resonances caused by the interaction between multiple time-scale control loops within a single converter, different types of converters and power networks. It is commonly assumed that CDGs are three-phase balanced systems and supply only passive loads. In reality, CDGs can experience imbalance caused by asymmetric networks, loads or faults. Moreover, induction motor (IM) loads, which exhibit highly nonlinear couplings between dynamics of power, voltage and frequency, typically account for a large portion of electric loads. Ignoring the impact of imbalance and dynamic loads in the modeling and stability analysis of CDGs can lead to unrealistic stability assessment results. To fill the gap, this paper presents a general small-signal modeling framework for CDGs in the presence of IM loads. Linear time-periodic (LTP) eigenvalue analysis is performed to investigate the impact of the interaction between IM loads, grid-following (GFL) converters and virtual synchronous generator (VSG) converters on the system stability. The time-domain simulation and experimental results validate the theoretical analysis.","PeriodicalId":198321,"journal":{"name":"2021 6th IEEE Workshop on the Electronic Grid (eGRID)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126432010","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

Current Harmonic Compensation by Active Power Filter Using Neural Network-Based Recognition and Controller 基于神经网络识别与控制的有源电力滤波器电流谐波补偿

2021 6th IEEE Workshop on the Electronic Grid (eGRID) Pub Date : 2021-11-08 DOI: 10.1109/eGRID52793.2021.9662134

Sahand Liasi, R. Hadidi, Narges S. Ghiasi

{"title":"Current Harmonic Compensation by Active Power Filter Using Neural Network-Based Recognition and Controller","authors":"Sahand Liasi, R. Hadidi, Narges S. Ghiasi","doi":"10.1109/eGRID52793.2021.9662134","DOIUrl":"https://doi.org/10.1109/eGRID52793.2021.9662134","url":null,"abstract":"In recent decades, the increasing use of nonlinear loads has caused many problems in terms of power quality. These problems include low power factor, and voltage and current harmonics. The distorted voltage can result in increasing temperature of wires and cables, inappropriate performance of protective devices and disturbance in telecommunication lines. Therefore, it would be essential to install filters to omit or damp these distortions. Conventionally, passive filters were used to maintain harmonics under a sensible level. Nevertheless, this kind of filters has many problems such as large size and resonance issues. In recent years, by improvements in power electronics, passive filters have been replaced with active power filters (APF). Controlling APFs using PI, deadbeat, and predictive controllers have been discussed in different works. However, they all need an accurate model of the system or information about the converters. In this paper, we will provide two control strategies: first, an artificial neural network (ANN)-based control method which mimic conventional control methods; second, ANN-based recognition and control method, which does not require any information about the system model. This control method can be well suiting any system because it can control the whole system only based on the effects on the input on the output of the system. In this paper, ANN-based control methods have been discussed. Then, a control method based on ANN recognition and control will be introduced and developed. The simulation results will be brought, discussed, and compared to show the proficiency of the proposed method over the existent methods.","PeriodicalId":198321,"journal":{"name":"2021 6th IEEE Workshop on the Electronic Grid (eGRID)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133529956","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

Ransomware Attack Modeling and Artificial Intelligence-Based Ransomware Detection for Digital Substations 数字变电站勒索软件攻击建模及基于人工智能的勒索软件检测

2021 6th IEEE Workshop on the Electronic Grid (eGRID) Pub Date : 2021-11-08 DOI: 10.1109/eGRID52793.2021.9662158

Syed. R. B. Alvee, Bohyun Ahn, Taesic Kim, Ying Su, Y. Youn, Myung-Hyo Ryu

引用次数: 4

A Fault Detection Scheme for Islanded-Microgrid with Grid-Forming Inverters 一种带并网逆变器的孤岛微电网故障检测方案

2021 6th IEEE Workshop on the Electronic Grid (eGRID) Pub Date : 2021-11-08 DOI: 10.1109/eGRID52793.2021.9662140

S. F. Zarei, M. A. Ghasemi, S. Peyghami, F. Blaabjerg

引用次数: 1

SEPIC and Flyback Converters for Isolated Photovoltaic Battery Charging Application 隔离式光伏电池充电用SEPIC和反激变换器

2021 6th IEEE Workshop on the Electronic Grid (eGRID) Pub Date : 2021-11-08 DOI: 10.1109/eGRID52793.2021.9662142

N. Tan, Filippo Savi, G. Buticchi, Sulaiha Ahmad, C. Gerada

引用次数: 1

Artificial Neural Network-Based Voltage Control of DC/DC Converter for DC Microgrid Applications 基于人工神经网络的直流微电网DC/DC变换器电压控制

2021 6th IEEE Workshop on the Electronic Grid (eGRID) Pub Date : 2021-11-05 DOI: 10.1109/eGRID52793.2021.9662132

Hussain Sarwar Khan, Ihab S. Mohamed, K. Kauhaniemi, Lantao Liu

{"title":"Artificial Neural Network-Based Voltage Control of DC/DC Converter for DC Microgrid Applications","authors":"Hussain Sarwar Khan, Ihab S. Mohamed, K. Kauhaniemi, Lantao Liu","doi":"10.1109/eGRID52793.2021.9662132","DOIUrl":"https://doi.org/10.1109/eGRID52793.2021.9662132","url":null,"abstract":"The rapid growth of renewable energy technology enables the concept of microgrid (MG) to be widely accepted in the power systems. Due to the advantages of the DC distribution system such as easy integration of energy storage and less system loss, DC MG attracts significant attention nowadays. The linear controller such as PI or PID is matured and extensively used by the power electronics industry, but their performance is not optimal as system parameters are changed. In this study, an artificial neural network (ANN) based voltage control strategy is proposed for the DC-DC boost converter. In this paper, the model predictive control (MPC) is used as an expert, which provides the data to train the proposed ANN. As ANN is tuned finely, then it is utilized directly to control the step-up DC converter. The main advantage of the ANN is that the neural network system identification decreases the inaccuracy of the system model even with inaccurate parameters and has less computational burden compared to MPC due to its parallel structure. To validate the performance of the proposed ANN, extensive MATLAB/Simulink simulations are carried out. The simulation results show that the ANN-based control strategy has better performance under different loading conditions comparison to the PI controller. The accuracy of the trained ANN model is about 97%, which makes it suitable to be used for DC microgrid applications.","PeriodicalId":198321,"journal":{"name":"2021 6th IEEE Workshop on the Electronic Grid (eGRID)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122888527","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: 11