Pub Date : 2012-11-01DOI: 10.1109/INDUSCON.2012.6453399
H. Voltolini, M. H. Granza, J. Ivanqui, R. Carlson
This paper presents a Wind Turbine Emulator (WTE) with induction motor driven by scalar torque control inverter. Additionally, the closed loop torque and rotor flux was implemented so that the induction motor emulates the real behavior of the wind turbine. The wind turbine model is developed considering its aerodynamics characteristic. This model will define the torque level in the electrical generator shaft. The induction motor control system implemented is capable to regulate the electromagnetic torque and rotor flux independently. The simulated results demonstrate the effectiveness of the induction motor system control. The strategy control was implemented in simulation using Matlab/Simulink/SimpowerSystems.
{"title":"Modeling and simulation of the Wind Turbine Emulator using induction motor driven by torque control inverter","authors":"H. Voltolini, M. H. Granza, J. Ivanqui, R. Carlson","doi":"10.1109/INDUSCON.2012.6453399","DOIUrl":"https://doi.org/10.1109/INDUSCON.2012.6453399","url":null,"abstract":"This paper presents a Wind Turbine Emulator (WTE) with induction motor driven by scalar torque control inverter. Additionally, the closed loop torque and rotor flux was implemented so that the induction motor emulates the real behavior of the wind turbine. The wind turbine model is developed considering its aerodynamics characteristic. This model will define the torque level in the electrical generator shaft. The induction motor control system implemented is capable to regulate the electromagnetic torque and rotor flux independently. The simulated results demonstrate the effectiveness of the induction motor system control. The strategy control was implemented in simulation using Matlab/Simulink/SimpowerSystems.","PeriodicalId":442317,"journal":{"name":"2012 10th IEEE/IAS International Conference on Industry Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128335503","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}
Pub Date : 2012-11-01DOI: 10.1109/INDUSCON.2012.6451397
M. F. Medeiros, C. B. M. Oliveira, M. Filho
Distributed generation is already a reality in almost all countries in the world. Wind farms, cogeneration systems and SHP (small hydropower) are already common elements that can be connected to medium voltage systems (up to 15kV). Additionally, with the development of tecnologies and reduced costs, it is expected that the number of generations connected through the network increases, whether coming from solar collectors, biomass, SHP, wind turbine, or any other popular kind of generation in the future. Based on this premise, a new problem arises, what are the level of real power injection and best place for each connection to the network. The work proposed here aims to develop a method to determines the best connection point for each generation to the network and search the constraint of real power injection of each producer by which the greatest possible reduction of active power flow in its sections, ie, there is a reduction of the maximum load in each line.
{"title":"Method for definition of the real power limits and designation of distributed generation","authors":"M. F. Medeiros, C. B. M. Oliveira, M. Filho","doi":"10.1109/INDUSCON.2012.6451397","DOIUrl":"https://doi.org/10.1109/INDUSCON.2012.6451397","url":null,"abstract":"Distributed generation is already a reality in almost all countries in the world. Wind farms, cogeneration systems and SHP (small hydropower) are already common elements that can be connected to medium voltage systems (up to 15kV). Additionally, with the development of tecnologies and reduced costs, it is expected that the number of generations connected through the network increases, whether coming from solar collectors, biomass, SHP, wind turbine, or any other popular kind of generation in the future. Based on this premise, a new problem arises, what are the level of real power injection and best place for each connection to the network. The work proposed here aims to develop a method to determines the best connection point for each generation to the network and search the constraint of real power injection of each producer by which the greatest possible reduction of active power flow in its sections, ie, there is a reduction of the maximum load in each line.","PeriodicalId":442317,"journal":{"name":"2012 10th IEEE/IAS International Conference on Industry Applications","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127317340","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}
Pub Date : 2012-11-01DOI: 10.1109/INDUSCON.2012.6451415
W. A. Gaspar, E. D. de Oliveira, P. Garcia, M. B. do Amaral
This paper discusses the use of a hybrid system in the field of Computational Intelligence in order to refine the measurement dataset used for determination of the parameters for static load models in Electric Power Systems (EPS). The objective is reducing the effects of natural fluctuation observed in measurement dataset resulting from random loading aggregation and disaggregation on the system under study. Specifically, it is used a fuzzy logic system for processing the filtering of measurement data obtained in the field. It is also important to note that the used approach makes the adjustment of the membership functions of a fuzzy linguistic variables using a meta heuristic called differential evolution. As a result, it is possible to get parameters both for ZIP and Exponential models with mean errors lower than those obtained with raw measurement dataset. The validation of this proposal uses measures that have been made at a CEMIG utility substation in Minas Gerais state, Brazil.
{"title":"Static load model adjustment using fuzzy logic and differential evolution","authors":"W. A. Gaspar, E. D. de Oliveira, P. Garcia, M. B. do Amaral","doi":"10.1109/INDUSCON.2012.6451415","DOIUrl":"https://doi.org/10.1109/INDUSCON.2012.6451415","url":null,"abstract":"This paper discusses the use of a hybrid system in the field of Computational Intelligence in order to refine the measurement dataset used for determination of the parameters for static load models in Electric Power Systems (EPS). The objective is reducing the effects of natural fluctuation observed in measurement dataset resulting from random loading aggregation and disaggregation on the system under study. Specifically, it is used a fuzzy logic system for processing the filtering of measurement data obtained in the field. It is also important to note that the used approach makes the adjustment of the membership functions of a fuzzy linguistic variables using a meta heuristic called differential evolution. As a result, it is possible to get parameters both for ZIP and Exponential models with mean errors lower than those obtained with raw measurement dataset. The validation of this proposal uses measures that have been made at a CEMIG utility substation in Minas Gerais state, Brazil.","PeriodicalId":442317,"journal":{"name":"2012 10th IEEE/IAS International Conference on Industry Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114915985","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}
Pub Date : 2012-11-01DOI: 10.1109/INDUSCON.2012.6451382
M. J. da Cunha, V. L. Belini, G. Caurin
The growing demand for higher productivity in the sugar-alcohol sector has required higher levels of automation in new and existing production plants. However, with increasing the number of sensors and equipment emerges a correspondent growth in the amount of data generated. Although the industry stores most of these data in dedicated data warehouse they are rarely used in future analysis due to the inherent technological challenge to properly cope with the large amount of data. This paper proposes the usage of a Knowledge Discovery in Database (KDD) process as a powerful tool to assist one in obtaining relevant industrial behavior from the stored data with the purpose of allowing quality and efficiency analysis. The experiments conducted with data collected in an industrial sugarcane plant successfully demonstrate that it is possible to apply the KDD to predict the ethanol concentration of future harvests.
糖酒精部门对提高生产率的需求日益增长，要求新的和现有的生产工厂实现更高水平的自动化。然而，随着传感器和设备数量的增加，产生的数据量也相应增长。尽管业界将大部分这些数据存储在专用数据仓库中，但由于正确处理大量数据所固有的技术挑战，它们很少用于未来的分析。本文提出使用数据库中的知识发现(Knowledge Discovery in Database, KDD)过程作为一种强大的工具，帮助人们从存储的数据中获得相关的行业行为，从而实现质量和效率分析。用在工业甘蔗厂收集的数据进行的实验成功地证明，可以应用KDD来预测未来收获的乙醇浓度。
{"title":"Predicting ethanol concentration behavior of future harvests using Knowledge Discovery in Database","authors":"M. J. da Cunha, V. L. Belini, G. Caurin","doi":"10.1109/INDUSCON.2012.6451382","DOIUrl":"https://doi.org/10.1109/INDUSCON.2012.6451382","url":null,"abstract":"The growing demand for higher productivity in the sugar-alcohol sector has required higher levels of automation in new and existing production plants. However, with increasing the number of sensors and equipment emerges a correspondent growth in the amount of data generated. Although the industry stores most of these data in dedicated data warehouse they are rarely used in future analysis due to the inherent technological challenge to properly cope with the large amount of data. This paper proposes the usage of a Knowledge Discovery in Database (KDD) process as a powerful tool to assist one in obtaining relevant industrial behavior from the stored data with the purpose of allowing quality and efficiency analysis. The experiments conducted with data collected in an industrial sugarcane plant successfully demonstrate that it is possible to apply the KDD to predict the ethanol concentration of future harvests.","PeriodicalId":442317,"journal":{"name":"2012 10th IEEE/IAS International Conference on Industry Applications","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133001362","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：