2023 5th Global Power, Energy and Communication Conference (GPECOM)最新文献

Virtual power plant challenges, opportunities and targets analysis in the current electricity markets 当前电力市场中虚拟电厂的挑战、机遇和目标分析

2023 5th Global Power, Energy and Communication Conference (GPECOM) Pub Date : 2023-06-14 DOI: 10.1109/GPECOM58364.2023.10175677

Zahid Ullah, Arshad, Azam Nikahi

{"title":"Virtual power plant challenges, opportunities and targets analysis in the current electricity markets","authors":"Zahid Ullah, Arshad, Azam Nikahi","doi":"10.1109/GPECOM58364.2023.10175677","DOIUrl":"https://doi.org/10.1109/GPECOM58364.2023.10175677","url":null,"abstract":"Virtual power plants (VPPs) are becoming more popular worldwide due to their diversified characteristics, the potential to provide energy flexibility, durability, and smarter electrical grid system, as well as economic benefits. Despite its significance, VPP currently has a very limited presence in the energy markets. A lack of systematic assessment of the multiple factors has been identified as the main reason for VPP’s limited admittance into the energy markets. This necessitates research initiatives that consider superior approaches and frameworks for the sustainable future of VPPs. A novel multi-aspect framework (MAF) is proposed in this study to examine objectively multi-dimensional aspects. A STEEP (social, technological, environmental, economic, and political) analysis tool is used to assess the challenges, opportunities, and benefits of VPP in the energy market. The approach outlines the essential factors and actions needed to address the challenges of VPP admittance in the energy markets. This study demonstrated that there is still more work to be done to support the fast and wide-scale adoption of sustainable VPP applications. For this reason, a more favourable policy and regulatory framework based on social, technological, economic, environmental, and policy considerations are necessary to realize the genuine contributions of a VPP.","PeriodicalId":288300,"journal":{"name":"2023 5th Global Power, Energy and Communication Conference (GPECOM)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124948024","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

High Resolution DoA Estimation Using LWA for MIMO OFDM Millimeter-Wave Systems 基于LWA的MIMO OFDM毫米波系统高分辨率DoA估计

2023 5th Global Power, Energy and Communication Conference (GPECOM) Pub Date : 2023-06-14 DOI: 10.1109/GPECOM58364.2023.10175692

R. S. Zakariyya, Jae-Neung Lee, M. U. F. Qaisar, Umar J. Mohammed, Qingfeng Zhang

引用次数: 0

The Intelligent Mechanism for Data Collection and Data Mining in the Vehicular Ad-Hoc Networks (VANETs) Based on Big-Data-Driven 基于大数据驱动的车载自组网数据采集与挖掘智能机制

2023 5th Global Power, Energy and Communication Conference (GPECOM) Pub Date : 2023-06-14 DOI: 10.1109/GPECOM58364.2023.10175794

Mahshad Mahmoudian, S. M. Zanjani, Hossein Shahinzadeh, Y. Kabalci, E. Kabalci, Farshad Ebrahimi

{"title":"The Intelligent Mechanism for Data Collection and Data Mining in the Vehicular Ad-Hoc Networks (VANETs) Based on Big-Data-Driven","authors":"Mahshad Mahmoudian, S. M. Zanjani, Hossein Shahinzadeh, Y. Kabalci, E. Kabalci, Farshad Ebrahimi","doi":"10.1109/GPECOM58364.2023.10175794","DOIUrl":"https://doi.org/10.1109/GPECOM58364.2023.10175794","url":null,"abstract":"Big data technology has attracted the main attention of researchers in almost all sciences. The Vehicular Ad-Hoc Network (VANET) enables information exchange between vehicles, other devices, and public networks, playing a key role in road safety and intelligent transportation systems. With the proliferation of connected vehicles and the development of novel mobile apps and technologies, VANETs will generate vast quantities of data that need to be transmitted quickly and reliably. Furthermore, analyzing a wide range of data types can enhance VANET’s performance. By utilizing big data technologies, the Ad-Hoc Vehicular Network can extract valuable insights from a large amount of operational data, thus improving traffic management processes, including planning, engineering, and operations. VANETs have access to big data during real-time operations. This paper presents VANET features as big data features in the literature, followed by a discussion of methods for utilizing big data to study VANET features. Combining automotive ad networks and big data facilitates the easy management of a large number of driving factors, as the data mining process in big data enables quick decision-making based on statistical analysis or graphical representations of data.","PeriodicalId":288300,"journal":{"name":"2023 5th Global Power, Energy and Communication Conference (GPECOM)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114497955","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

Didactic Integration For The Monitoring Of Electric Power Systems Using Power Monitoring Expert With Modbus TCP/IP And IEC 61850 Communication 基于Modbus、TCP/IP和IEC 61850通信的电力监控专家在电力系统监控中的教学集成

2023 5th Global Power, Energy and Communication Conference (GPECOM) Pub Date : 2023-06-14 DOI: 10.1109/GPECOM58364.2023.10175740

Danny F. Cisneros Solórzano, Jefferson A. Gutama Chuñir, F. Q. Palomeque

引用次数: 0

Automatic Docking Method for Charging Connector of Electric Vehicle Based on Hybrid Force-position Compliance Control 基于混合力-位置顺应控制的电动汽车充电连接器自动对接方法

2023 5th Global Power, Energy and Communication Conference (GPECOM) Pub Date : 2023-06-14 DOI: 10.1109/GPECOM58364.2023.10175802

Lianming Hun, Heng Song, Xize Jiao, Shanjun Xu, Junlong Guo, Zhifeng Liu

{"title":"Automatic Docking Method for Charging Connector of Electric Vehicle Based on Hybrid Force-position Compliance Control","authors":"Lianming Hun, Heng Song, Xize Jiao, Shanjun Xu, Junlong Guo, Zhifeng Liu","doi":"10.1109/GPECOM58364.2023.10175802","DOIUrl":"https://doi.org/10.1109/GPECOM58364.2023.10175802","url":null,"abstract":"Aiming to solve the docking problems of an electric vehicle’s DC charging connector, including small fitting tolerance, large model difference, and uncertain position and pose, this paper proposes a flexible docking method for an automatic charging robot based on hybrid force-position control. In the proposed method, the automatic docking operation of a charging connector is divided into four stages. The contact stage includes single-and two-point contacts, and in this stage, a mechanical model of a charging connector is established. In addition, considering the requirements of practical applications, a hybrid force-position control model and a flexible docking method of a self-adaptive position are developed in the contact stage, and a complete control strategy is designed according to typical application requirements for the automatic docking of a charging connector. A test system is constructed to test the proposed hybrid compliance control method and compare it with the existing docking method without compliance control. The test results show that the proposed hybrid force-position compliance control method can stably comply with external constraints in the process of automatic docking of an electric vehicle’s charging connector and complete the docking. The maximum docking force in the Z-direction is reduced by 52.8%.","PeriodicalId":288300,"journal":{"name":"2023 5th Global Power, Energy and Communication Conference (GPECOM)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128520296","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

Weighting Factor-Free Model Predictive Control for Three-Level Buck Converters 三电平降压变换器的加权无因子模型预测控制

2023 5th Global Power, Energy and Communication Conference (GPECOM) Pub Date : 2023-06-14 DOI: 10.1109/GPECOM58364.2023.10175673

Hamza Makhamreh, Amer Dyab

引用次数: 0

Evaluating LMP Forecasting with LSTM Networks: A Deep Learning Approach to Analyzing Electricity Prices During Unpredictable Events 用LSTM网络评估LMP预测:在不可预测事件中分析电价的深度学习方法

2023 5th Global Power, Energy and Communication Conference (GPECOM) Pub Date : 2023-06-14 DOI: 10.1109/GPECOM58364.2023.10175743

Basak Ersoz Yildirim, Sevval Yıldız, A. S. Turkoglu, O. Erdinç, A. R. Boynuegri

{"title":"Evaluating LMP Forecasting with LSTM Networks: A Deep Learning Approach to Analyzing Electricity Prices During Unpredictable Events","authors":"Basak Ersoz Yildirim, Sevval Yıldız, A. S. Turkoglu, O. Erdinç, A. R. Boynuegri","doi":"10.1109/GPECOM58364.2023.10175743","DOIUrl":"https://doi.org/10.1109/GPECOM58364.2023.10175743","url":null,"abstract":"The unpredictable events can significantly impact energy demand and supply in the electricity market, leading to price volatility. This study aims to evaluate the effectiveness of Long Short Term Memory (LSTM) approach in analyzing real-time data on Locational Marginal Prices (LMPs) during periods before, during, and after the COVID19 pandemic. Open data from the Midcontinent Independent System Operator (MISO) are utilized to obtain the LMP data. To evaluate the accuracy of the model predictions, three performance metrics were utilized, namely Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and coefficient of determination (R2). Additionally, the study assesses the ability of LSTM to forecast LMP, considering yearly fluctuations. Graphical visualizations are created to depict the trends and patterns of LMP changes and forecasts over time. The results demonstrate the promising potential of LSTM in forecasting LMP even in unpredictable situations like pandemic. Despite the challenges of accurately estimating extreme energy demands during the pandemic, the LSTM model generates reliable forecasts, as evidenced by the performance metrics. The graphical visualizations also illustrate the effectiveness of LSTM in capturing the underlying trends and patterns of LMP changes over time.","PeriodicalId":288300,"journal":{"name":"2023 5th Global Power, Energy and Communication Conference (GPECOM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130347070","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

Revisiting Network Reconfiguration in the Era of Unpredictable EV Charger Integration 在不可预测的电动汽车充电器集成时代重新审视网络重构

2023 5th Global Power, Energy and Communication Conference (GPECOM) Pub Date : 2023-06-14 DOI: 10.1109/GPECOM58364.2023.10175829

Eren Tekeler, Gokturk Poyrazoglu

{"title":"Revisiting Network Reconfiguration in the Era of Unpredictable EV Charger Integration","authors":"Eren Tekeler, Gokturk Poyrazoglu","doi":"10.1109/GPECOM58364.2023.10175829","DOIUrl":"https://doi.org/10.1109/GPECOM58364.2023.10175829","url":null,"abstract":"An expanded network of electric vehicle (EV) chargers is required due to the rapid uptake of EVs. The voltage profile may be disturbed by the unanticipated integration of these chargers into distribution networks, potentially resulting in system instability. There is currently no study that offers a methodology for evaluating the voltage responsiveness of various network configurations in relation to EV chargers, even though prior research has sought to improve network parameters in the face of distributed generation and network reconfiguration (NR). The problem of choosing the best network configuration remains unsolved due to this gap. In order to address this, our study analyzes a distribution network in all of its possible configurations, taking into account the possible effects of electric vehicle chargers placed in all possible locations, in the Python programming language using the Pandapower network analysis library. The results of this study will give system administrators useful information for choosing the most reliable network configuration in advance of the unpredictable integration of EV chargers into their distribution networks.","PeriodicalId":288300,"journal":{"name":"2023 5th Global Power, Energy and Communication Conference (GPECOM)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126892143","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

Diagnostic and Prognostic Health Management of Electric Vehicle Powertrains: An Empirical Methodology for Induction Motor Analysis 电动汽车动力系统的诊断和预后健康管理:感应电机分析的经验方法

2023 5th Global Power, Energy and Communication Conference (GPECOM) Pub Date : 2023-06-14 DOI: 10.1109/GPECOM58364.2023.10175674

Hicham El Hadraoui, Oussama Laayati, Adila El Maghraoui, Erroumayssae Sabani, M. Zegrari, Ahmed Chebak

{"title":"Diagnostic and Prognostic Health Management of Electric Vehicle Powertrains: An Empirical Methodology for Induction Motor Analysis","authors":"Hicham El Hadraoui, Oussama Laayati, Adila El Maghraoui, Erroumayssae Sabani, M. Zegrari, Ahmed Chebak","doi":"10.1109/GPECOM58364.2023.10175674","DOIUrl":"https://doi.org/10.1109/GPECOM58364.2023.10175674","url":null,"abstract":"The growing interest in electric vehicles has led to an increased focus on the development of efficient and reliable electric motors. To ensure reliable operation, it is essential to incorporate on-board diagnostic and prognostic tools that can detect and predict potential failures. This paper proposes an approach to diagnose and predict the health condition of induction motors used in electric vehicle powertrain applications using machine learning techniques. The proposed approach utilizes vibration signals collected from accelerometers attached to the motor and employs decision forest and decision tree algorithms to classify the health condition of the motor. The study aims to identify the most significant features of the vibration signals and evaluate the effectiveness of the proposed approach in diagnosing and predicting the health of the motor. The models are trained on full extracted features and selected features using Principal Component Analysis (PCA) and Correlation Analysis (CA) to improve the classification performance. The experimental results demonstrate that the combination of selected features using PCA with the Decision Forest (DF) algorithm achieves the best classification performance for the simulated motor fault conditions. This suggests that machine learning techniques can be effective in diagnosing and predicting the health of induction motors used in electric vehicle powertrain applications.","PeriodicalId":288300,"journal":{"name":"2023 5th Global Power, Energy and Communication Conference (GPECOM)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124133582","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

FPGA-Based Hysteresis Current Control for Induction Motor fed by a Voltage-Source Inverter 基于fpga的电压源逆变器异步电机磁滞电流控制

2023 5th Global Power, Energy and Communication Conference (GPECOM) Pub Date : 2023-06-14 DOI: 10.1109/GPECOM58364.2023.10175749

Ozan Gulbudak, M. Gokdag

引用次数: 0