2022 Global Energy Conference (GEC)最新文献_第6页

Advanced Measurement Systems with Smart Grid in Turkey: Roadmap 2032 土耳其智能电网的先进测量系统:2032年路线图

2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9986630

T. Akinci, A. Martinez-Morales, M. Yilmaz, Idris Demir

{"title":"Advanced Measurement Systems with Smart Grid in Turkey: Roadmap 2032","authors":"T. Akinci, A. Martinez-Morales, M. Yilmaz, Idris Demir","doi":"10.1109/GEC55014.2022.9986630","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9986630","url":null,"abstract":"There have been strategic and important developments in the field of energy in Turkey in recent years. Considering the current energy policy framework, smart grids are an important paving stone for Turkey to reach the determined targets. In the development of smart networks, the most important part is smart meters and their communication. Smart energy meters, together with their communications, power and control infrastructure, constitute a system associated with electrical networks of worldwide interest. The massive implementation of these technologies requires not only the corresponding conceptual management but also the formulation of policies and regulatory frameworks, the analysis of the benefits that they entail and the barriers that arise for their use. This study presents a scheme that integrates the actors, processes and functionalities associated with advanced measurement systems through an appropriate hardware and software infrastructure. Successful cases of massive use of smart meters are compared, and the benefits and barriers are analyzed to propose possible future scenarios in Turkey and present some applicable use cases. In this study, a prepay or supply-demand balanced solution proposal was presented for Turkey with communication infrastructure smart meters.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123813286","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

Implementation of Sliding Mode Control Method for Switched-Inductor Quasi-Z-Source Inverter 开关电感准z源逆变器滑模控制方法的实现

2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9986995

Özkan Özkara, Zafer Ortatepe, A. Karaarslan

引用次数: 0

Modeling of STATCOM Connected System to Microgrid STATCOM连接系统与微电网的建模

2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9986624

Aysenur Oymak, M. Tür, Eklas Hossain

{"title":"Modeling of STATCOM Connected System to Microgrid","authors":"Aysenur Oymak, M. Tür, Eklas Hossain","doi":"10.1109/GEC55014.2022.9986624","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9986624","url":null,"abstract":"The use of renewable energy systems has enhanced in recent years due to reduce in fossil fuel resources and the damaging impacts of fossil resources on the environment. The most widely used renewable energy types are wind, solar, hydroelectric and geothermal energy systems. A micro grid is a small grid with its own energy sources, generation and loads. With the widespread use of micro-grids and the increase in the installed power of renewable energy sources, their negative effects on the grid are increasing. Due to the intermittent nature of renewable energy sources, it will not be able to meet the ever-changing load demand. For this, it was deemed necessary to create a hybrid system to increase voltage stability, reactive power compensation and power quality. In this study, a micro grid connected to a solar power plant and a STATCOM element in a grid was created in a Matlab simulink environment. Voltage regulation and reactive power variation in the distribution line are investigated. It has been seen that optimization of the PI controller should be done in STATCOM control. It is thought that particle swarm optimization will give more results for the optimization.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134104480","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

Multi-node Communication Solution for Synchronous Control of Distributed Power Electronic Devices 分布式电力电子设备同步控制的多节点通信解决方案

2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9987196

Marcin Firla, Wiktor Feliniak, Bartłomiej Flak, Daniel Lewandowski, P. Rajda, Krzvsztof Zietara

{"title":"Multi-node Communication Solution for Synchronous Control of Distributed Power Electronic Devices","authors":"Marcin Firla, Wiktor Feliniak, Bartłomiej Flak, Daniel Lewandowski, P. Rajda, Krzvsztof Zietara","doi":"10.1109/GEC55014.2022.9987196","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9987196","url":null,"abstract":"The development of power electronic devices and advances in control engineering made the application of sophisticated control algorithms possible. The state of the art solution assumes that each device has an integrated controller that closes a local control loop. Remote control is achieved by receiving commands and reference values from the central unit through the same communication channel. The update rate is usually a few times slower than the computational step of the algorithm implemented locally. However, this approach brings some problems to synchronization of switching times of low level power electronics components. Such problem arises for applications using larger number of switches or when parallel operation of converters is a requirement. This article presents a solution to synchronize common clock over multiple nodes connected in a daisy-chain topology. Thus, it gives an opportunity to synchronize transmitted data to the respect of a single bit. In the end it is possible to achieve nanosecond resolution of the switching times for a multi-node network that could be highly distributed.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132036259","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

Transaction And Operation Control Algorithm For An Energy Bank 能源银行的交易与运行控制算法

2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9986712

M. Giraneza, K. Abo-Al-Ez

引用次数: 0

A novel day ahead charging scheme for electric vehicles with time of use-based prioritization supported by genetic algorithm 基于遗传算法的电动汽车日前充电优化方案

2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9987156

Syed Abdullah-Al-Nahid, T. Aziz

引用次数: 0

Measurement-based Parameter Estimation for Dynamic Load Modeling 基于测量的动态负荷建模参数估计

2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9986572

Selçuk Emiroğlu, Talha Enes Gümüş

引用次数: 0

Preface - Welcome Message From the Conference General Chair 前言-大会主席致欢迎辞

2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/gec55014.2022.9987224

引用次数: 0

Artificial Intelligence Based Regression Models for Prediction of Smart Grid Stability 基于人工智能的智能电网稳定性预测回归模型

2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9986814

Abdurrahman Gönenç, Emrullah Acar, Idris Demir, M. Yilmaz

{"title":"Artificial Intelligence Based Regression Models for Prediction of Smart Grid Stability","authors":"Abdurrahman Gönenç, Emrullah Acar, Idris Demir, M. Yilmaz","doi":"10.1109/GEC55014.2022.9986814","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9986814","url":null,"abstract":"In parallel with the rapid increase in the world population and the rapid development of technology day by day, the need for electrical energy is increasing to this extent. However, today, due to the limited energy resources, electrical energy must be utilized efficiently and reach the users. Today, electrical smart grids play an important role in ensuring electrical grid stability. Artificial intelligence (AI) applications are used to ensure electricity grid stability. In this study, artificial intelligence based regression models (Gaussian Process Regression, Support Vector Machine Regression, Generalized Regression of Neural Network, Linear Regression and Decision Tree Regression) were employed to predict electricity grid stability. The coefficient of determination (R2) and error parameters Mean squared error (MSE), Mean Absolute Error (MAE) resulting from these models were analyzed. Finally, good results have been obtained to the proposed approach. The results show that with the proposed models, the energy demand-response balance can be department from these estimations, and the load and pricing can be made more effectively in the smart grid system. Also, for the Smart grid, a small estimation difference eliminates billions of dollars in investment and operating costs. Strong global growth in grid-integrated renewable energy deployment was supported by a variety of policies addressing energy security, local pollution issues and climate goals.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133623579","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

Short-term Load Forecasting using the Combined Method of Wavelet Transform and Neural Networks Tuned by the Gray Wolf Optimization Algorithm 基于小波变换和灰狼优化算法的神经网络联合预测短期负荷

2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9986711

S. M. Zanjani, Hossein Shahinzadeh, Jalal Moradi, Mohammad-hossein Fayaz-dastgerdi, W. Yaïci, Mohamed Benbouzid

{"title":"Short-term Load Forecasting using the Combined Method of Wavelet Transform and Neural Networks Tuned by the Gray Wolf Optimization Algorithm","authors":"S. M. Zanjani, Hossein Shahinzadeh, Jalal Moradi, Mohammad-hossein Fayaz-dastgerdi, W. Yaïci, Mohamed Benbouzid","doi":"10.1109/GEC55014.2022.9986711","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9986711","url":null,"abstract":"Daily load forecasting in distribution companies, which is to present to the network management company and adopt the appropriate load management method, is considered an inseparable matter in distribution networks. Accurate load forecasting will reduce the price of electricity generation in the power network. In the discussion of exploitation and capability, The reliability of the power network is effective and necessary. Therefore, it is difficult to accurately predict the load due to the influence of load patterns on various factors such as weather, economic, and social factors. For this reason, they have addressed load forecasting problems in recent years using different methods. In this article, the goal is to achieve a combination of Neural Network-Wavelet Transform that can accurately predict the load of distribution networks. The data used in this model is electric charge. Wavelet Transform has been used for multimodal forecasting, filter type, window length (the number of past data used in forecasting), and the number of hidden layers for each neural network has been optimized by the gray wolf algorithm to minimize the forecasting error. Also, the data used in the analysis, evaluation, and short-term forecasting is based on the actual load data of the electricity distribution network of Isfahan province.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134056060","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: 2