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An Information Theoretic Unified Global Theory For a Stable $M/G/1$ Queue With Potential Maximum Entropy Applications to Energy Works 具有最大熵势的稳定$M/G/1$队列的信息论统一全局理论
2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9986719
Ismail A. Mageed, Quichun Zhang
{"title":"An Information Theoretic Unified Global Theory For a Stable $M/G/1$ Queue With Potential Maximum Entropy Applications to Energy Works","authors":"Ismail A. Mageed, Quichun Zhang","doi":"10.1109/GEC55014.2022.9986719","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9986719","url":null,"abstract":"This paper establishes comprehensive description of the theory of maximum entropy global formalism to analyze a stable $boldsymbol{M/G/1}$ queue, novel state probability $boldsymbol{p_{q, UG}(n)},boldsymbol{n=0,1,}$ 2,… as inductive inference approach for systems. This revolutioanry approach is based on the provision of maximizing Ismail's entropy(IE), namely, $boldsymbol{H_{(q, UG)}}$, which is the ultimte generalization to all the entropy measures in the literature, subject to prescribed contraints. Numerical portraits are provided to capture the influential effect of the derived formalism, $boldsymbol{p_{q, UG}(n), n=} boldsymbol{0,1,2, ldots}$ on the stable $boldsymbol{M/GE_{q, UG}/1}$ queue with heavy tails. An expxposition to several potential applictaions of maximum entropy(ME) to energy works is undertaken. Conclusion with possible future research pathways are given.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"1 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":"129936303","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
State Estimation of Buck Converter by Using Kalman Filter 基于卡尔曼滤波的Buck变换器状态估计
2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9986519
Kadir Eker, Y. Cetinceviz, E. Şehirli, Faruk Erken
{"title":"State Estimation of Buck Converter by Using Kalman Filter","authors":"Kadir Eker, Y. Cetinceviz, E. Şehirli, Faruk Erken","doi":"10.1109/GEC55014.2022.9986519","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9986519","url":null,"abstract":"This study presents buck converter modeling and estimation of state variables in noisy and noiseless environments using Kalman Filter. Firstly, the linearized state space model of the buck converter is obtained and the simulation model is created. The output voltage of the buck converter, the state variables of inductor current and capacitor voltage are estimated using the Kalman state observer. The simulations are carried out in the MATLAB/Simulink software environment. Eventually the estimation of the state variables with the Kalman filter has been verified by comparing it with the model of the converter with maximum 7.10%%, minimum 0.0% error regarding to different scenarios.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"22 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":"122948188","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
Combining Regularization and Dropout Techniques for Deep Convolutional Neural Network 深度卷积神经网络正则化与Dropout技术的结合
2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9986657
Zari Farhadi, H. Bevrani, M. Feizi-Derakhshi
{"title":"Combining Regularization and Dropout Techniques for Deep Convolutional Neural Network","authors":"Zari Farhadi, H. Bevrani, M. Feizi-Derakhshi","doi":"10.1109/GEC55014.2022.9986657","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9986657","url":null,"abstract":"Deep learning techniques face the problem of overfitting due to their complex layer structure. Regularization methods are used to overcome this problem and improve the designed models. In this article, we use the combination of L1 regularization, L2 regularization, Elastic Net-regularization, and Dropout methods. The designed deep model using combination of these methods is considered with different rates. The deep network model using a combination of these methods is designed with different rates. Finally, the performance of all combination methods is compared with the Convolutional Neural Network model which does not use regularization methods. Experiments are performed using the Gold price per ounce data set and linear simulation model. The obtained results show that the performance of the combination model of Dropout and Elastic Net regularization is better than the other models.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"8 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":"115854745","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
Advanced Control Techniques for Doubly-Fed Induction Generators Based Wind Energy Conversion Systems 基于双馈感应发电机的风能转换系统的先进控制技术
2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9987088
Hamid Chojaa, A. Derouich, Seif Eddine Chehaidia, M. Taoussi, O. Zamzoum, M. I. Mosaad, H. Benbouhenni, Mourad Yessef
{"title":"Advanced Control Techniques for Doubly-Fed Induction Generators Based Wind Energy Conversion Systems","authors":"Hamid Chojaa, A. Derouich, Seif Eddine Chehaidia, M. Taoussi, O. Zamzoum, M. I. Mosaad, H. Benbouhenni, Mourad Yessef","doi":"10.1109/GEC55014.2022.9987088","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9987088","url":null,"abstract":"Due to their advantages especially the capability of operation at wide wind speed ranges, doubly-fed induction generators (DFIGs) are widely used in wind energy conversion systems (WECSs). This paper introduces a performance enhancement of WECS-DFIG by extracting the maximum power from WECS-DFIG in addition to active and reactive powers control. The maximum power point is extracted by capturing the optimal speed by an intelligent controller. While Integral Sliding Mode Controller (ISMC) and the Field Oriented Control (FOC_PI) are presented for active and reactive powers control. The proposed controllers were applied to control a 1.5 grid-connected DFIG. All simulations were done using Matlab Software.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"63 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":"130646424","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
Dual Side Control Design for a 600W LCC Compensated Wireless Power Transfer System 600W LCC补偿无线电力传输系统的双向控制设计
2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9987129
A. Pashaei, Emrullah Aydin, M. Aydemir
{"title":"Dual Side Control Design for a 600W LCC Compensated Wireless Power Transfer System","authors":"A. Pashaei, Emrullah Aydin, M. Aydemir","doi":"10.1109/GEC55014.2022.9987129","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9987129","url":null,"abstract":"The purpose of this paper is to design a dual side control for a 600 W LCC resonant WPT electrical bicycle with an 85 kHz resonant frequency. Primary side control use inverter voltage and current to determine mutual inductance and load value in coils misalignment case. The secondary side control uses a DC-DC converter that has two voltage and current feedback with a PI controller to achieve CC/CV charging in the battery. Additionally, with primary side control the high-frequency inverter operates in ZVS mode. Optimal design parameters are obtained and results and control method feasibility validated by simulations.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"28 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":"126782594","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
Performance Improvement for Interior Permanent Magnet Machines by Winding Reconfiguration 内部永磁电机绕组重构的性能改进
2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9987231
T. Gundogdu
{"title":"Performance Improvement for Interior Permanent Magnet Machines by Winding Reconfiguration","authors":"T. Gundogdu","doi":"10.1109/GEC55014.2022.9987231","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9987231","url":null,"abstract":"Interior permanent magnet (IPM) machines have been widely employed in traction applications because of their significant advantages in power density and efficiency. In traction applications, it is essential to achieve speeds above nominal speed and operate in the flux-weakening region. In this paper, the winding reconfiguration method is proposed to improve the flux-weakening performance characteristics of IPM machines. An IPM machine, having the 2010 Toyota Prius IPM Machine's specifications, is designed to have two separate winding sets as “main” and “auxiliary” windings. Hence, it has become feasible to switch between different winding characteristics using power switches. The turns-changing method is employed to decrease the winding inductance by reducing coil turns, and the parallel branch method is employed to reduce the winding resistance. In this way, a high-torque at constant power region or high efficiency at constant torque region can be achieved. The influence of different operation modes, obtained by arranging the switching between windings, on the flux-weakening characteristics, including torque/speed, power/speed, and efficiency maps, has been investigated. The flux-weakening performance characteristics of the IPM machine with reconfigurable windings are calculated using a hybrid calculation method that combines finite-element analysis (FEA) with MATLAB. The flux-weakening performance characteristics of the IPM machine have been significantly enhanced thanks to the proposed winding changeover approach.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"30 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":"116922757","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
ANN Based Prediction of Module Temperature in a Single Axis PV System 基于神经网络的单轴光伏系统组件温度预测
2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9986829
İsmail Kayri, H. Aydin
{"title":"ANN Based Prediction of Module Temperature in a Single Axis PV System","authors":"İsmail Kayri, H. Aydin","doi":"10.1109/GEC55014.2022.9986829","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9986829","url":null,"abstract":"Photovoltaic technology is one of the most effective and cleanest methods of obtaining energy from the sun. The efficiency of modules that is one of the most basic components of photovoltaic systems, is very sensitive to environmental variables. The air temperature and the electric current that passing through the panels cause the panels to heat up. Temperature negatively affects the efficiency of the panels. In photovoltaic systems, the panel temperature must be determined in order to know the rate of heat losses, which is one of the many types of losses. In this study, an artificial neural network model was developed that determines the temperature of a single axis tracking solar panel according to environmental variables. For the development of the model, 36699 data rows were used, which were measured and recorded with a data logger for one year. In this model, the module temperature is the dependent variable while the solar irradiance, ambient temperature, wind speed, relative humidity and panel power are selected as the independent variables. In the developed model, there is a 98.87% correlation between the actual values and the estimated values. The developed model predicts the module temperature very well according to the actual values with 1.45 MAE, 4.27 MAE, 6.37% MAPE and 2.24% RSE performance criteria. By knowing the module temperature, the amount of heat losses that will occur in photovoltaic systems can be calculated. In addition, estimating the panel temperature value can be used as an important parameter in the organization of cooling processes to increase efficiency.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"33 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":"124354968","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
Comparison of Energy Storage Technologies in Smart Grids, Implementation Challenges of Vanadium Technique 智能电网中储能技术的比较，钒技术的实现挑战
2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9987133
Mehmet Necat Tur, Ö. F. Ertugrul, Mehmet Rida Tur
{"title":"Comparison of Energy Storage Technologies in Smart Grids, Implementation Challenges of Vanadium Technique","authors":"Mehmet Necat Tur, Ö. F. Ertugrul, Mehmet Rida Tur","doi":"10.1109/GEC55014.2022.9987133","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9987133","url":null,"abstract":"In general, one of the most important goals of smart grids; the establishment of networks that allow for more distributed generation and energy storage at the end-user side. Energy storage technology; It has great potential to improve electric power systems, increase renewable electricity generation and offer alternatives to petroleum-derived fuels in the transportation sector. This study sheds light on the advantages offered by energy storage technologies, which play an active role in solving the problems encountered during the grid integration of renewable energy sources in smart grid applications. In addition, different solutions offered by different energy storage technologies such as Vanadium are also evaluated in this study. In this study, an energy storage unit with high energy and high power density was designed with the Hybrid Energy Storage System (V-HEES) consisting of vanadium and ultra-capacitor. In addition, the results of the hybrid energy storage system consisting of vanadium and ultra-capacitors and the application areas of these technologies in smart grids are also included.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"1 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":"129912324","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
Resilience-Oriented Optimal Planning of Gas-Fired DGs in Electrical Distribution Networks Considering Damage of Natural Gas Network 考虑天然气网络损坏的配电网燃气dg弹性优化规划
2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9987000
Yasin Gilasi, S. H. Hosseini, Hossein Ranjbar
{"title":"Resilience-Oriented Optimal Planning of Gas-Fired DGs in Electrical Distribution Networks Considering Damage of Natural Gas Network","authors":"Yasin Gilasi, S. H. Hosseini, Hossein Ranjbar","doi":"10.1109/GEC55014.2022.9987000","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9987000","url":null,"abstract":"Natural hazards such as earthquakes are of the main causes of destruction in important infrastructures such as electricity and natural gas networks. Planning of distributed generations is a compelling method for increasing the resilience of energy infrastructures against such events. This paper presents a resilience-oriented planning framework for gas-fired distributed generations (GFDGs) in distribution networks, considering the outages of electric-gas network components, dispatching the electric repair crews, and proper utilization of installed GFDGs. The proposed framework is formulated as a mixed-integer linear programming (MILP) optimization problem. The results of applying this MILP model on the IEEE 33-bus distribution system supplied by the 14-bus natural gas network show that considering operational actions such as dispatching repair crews or possible damages to network components can have a significant impact on achieving more optimal expansion plans.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"178 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":"130199981","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
A Machine Learning Approach to Transformer Oil Temperature Monitoring Using Load Analysis 基于负载分析的变压器油温监测的机器学习方法
2022 Global Energy Conference (GEC) Pub Date : 2022-10-26 DOI: 10.1109/GEC55014.2022.9986623
I. Sheikh, A. Vedant, A. Sheikh
{"title":"A Machine Learning Approach to Transformer Oil Temperature Monitoring Using Load Analysis","authors":"I. Sheikh, A. Vedant, A. Sheikh","doi":"10.1109/GEC55014.2022.9986623","DOIUrl":"https://doi.org/10.1109/GEC55014.2022.9986623","url":null,"abstract":"Transformers are the vital components of the electrical power network, and they must be adequately monitored and examined to avoid irreversible damage. The transformers coolant, which is oil, maintain its dielectric properties for a certain temperature ranges and hence it is essential to monitor it effectively for increasing the life shell of transformer. In view of this the paper proposes a transformer monitoring system which is based on machine learning technique. For monitoring oil temperature whether low or high, various machine learning classifier like random forest, support vector machine (SVM), k-nearest neighbors (kNN), and logistic regression are evaluated in this paper. The impact of different load condition on the oil temperature is also highlighted. The performance of various classifier is validated by calculating the evaluation metrics and it can be seen from the results that kNN outperforms the random forest, SVM, and logistic regression.","PeriodicalId":280565,"journal":{"name":"2022 Global Energy Conference (GEC)","volume":"22 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":"125416999","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
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