Pub Date : 2010-11-18DOI: 10.1109/ICCCT.2010.5640486
D. Mishra, Raman Bhati, Sarika Jain, Dinesh Bhati
In this paper we propose a new approach to find the optimum learning rate that increases the recognition rate and reduces the training time of the back propagation neural network as well as single layer feed forward Neural Network. We give a comparative analysis of performance of back propagation neural network and single layer feed forward neural network. In our approach we use variable learning rate and demonstrate its superiority over constant learning rate. We use different inner epochs for different input patterns according to their difficulty of recognition. We also show the effect of optimum numbers of inner epochs, best variable learning rate and numbers of hidden neurons on training time and recognition accuracy. We run our algorithm for face recognition application using Principal Component Analysis and neural network and demonstrate the effect of number of hidden neurons and size of feature vector on training time and recognition accuracy for given numbers of input patterns. We use ORL database for all the experiments.
{"title":"A Comparative Analysis of Different Neural Networks for Face Recognition Using Principal Component Analysis and Efficient Variable Learning Rate","authors":"D. Mishra, Raman Bhati, Sarika Jain, Dinesh Bhati","doi":"10.1109/ICCCT.2010.5640486","DOIUrl":"https://doi.org/10.1109/ICCCT.2010.5640486","url":null,"abstract":"In this paper we propose a new approach to find the optimum learning rate that increases the recognition rate and reduces the training time of the back propagation neural network as well as single layer feed forward Neural Network. We give a comparative analysis of performance of back propagation neural network and single layer feed forward neural network. In our approach we use variable learning rate and demonstrate its superiority over constant learning rate. We use different inner epochs for different input patterns according to their difficulty of recognition. We also show the effect of optimum numbers of inner epochs, best variable learning rate and numbers of hidden neurons on training time and recognition accuracy. We run our algorithm for face recognition application using Principal Component Analysis and neural network and demonstrate the effect of number of hidden neurons and size of feature vector on training time and recognition accuracy for given numbers of input patterns. We use ORL database for all the experiments.","PeriodicalId":437153,"journal":{"name":"2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129790198","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}
Changes in housing prices concern both individuals and government since they have substantial influence on the socio-economic conditions. Valuations of housing are necessary in order to assess the benefit and liabilities in housing section. The housing price in Iran is based on eight economic indices. The study of trends in housing price has been made by considering the related seasonal data from 16 years ago and using the techniques of Artificial Neural Network Back propagation (ANN-Back propagation) and Fuzzy regression. The results of our experiments indicate that the estimation error (Mean Absolute Percentage Error, “MAPE”) in the ANN-Back propagation technique is less than that in Fuzzy regression. It can be shown, by comparing the estimated housing prices by applying the ANN technique with the observed ones, that the ANN technique has favorably estimated the trends in the changes of housing prices.
{"title":"Estimation of Housing Prices by Fuzzy Regression and Artificial Neural Network","authors":"R. Ghodsi, A. Boostani, F. Faghihi","doi":"10.1109/AMS.2010.29","DOIUrl":"https://doi.org/10.1109/AMS.2010.29","url":null,"abstract":"Changes in housing prices concern both individuals and government since they have substantial influence on the socio-economic conditions. Valuations of housing are necessary in order to assess the benefit and liabilities in housing section. The housing price in Iran is based on eight economic indices. The study of trends in housing price has been made by considering the related seasonal data from 16 years ago and using the techniques of Artificial Neural Network Back propagation (ANN-Back propagation) and Fuzzy regression. The results of our experiments indicate that the estimation error (Mean Absolute Percentage Error, “MAPE”) in the ANN-Back propagation technique is less than that in Fuzzy regression. It can be shown, by comparing the estimated housing prices by applying the ANN technique with the observed ones, that the ANN technique has favorably estimated the trends in the changes of housing prices.","PeriodicalId":437153,"journal":{"name":"2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122082354","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}
Dielectric Barrier Discharge (DBD) is a discharge phenomenon where a high voltage is applied on at least two electrodes separated by an insulating dielectric material. Dielectric Barrier Discharge plasma actuator has been studied widely in this last decade but mostly the study is focusing on experimental research rather than mathematical modeling. The limitation with studying DBD plasma actuator experimentally is that it does not obtain direct information on the physics of the plasma flow, which is important in determining its efficiency. In this paper, we model the steady fluid model DBD plasma actuator mathematically. The preliminary result of the model are presented and discussed. To initiate the modeling process, the stream-function and vorticity are defined so that the Navier-Stokes momentum equation could be transformed into vorticity equation. The resulting two governing equations, which are vorticity and stream-function equations are solved numerically to obtain the vorticity of the flow in x and y directions. Finite difference method was adopted to discretize both equations and the system of equations is solved by the Gauss-Seidel method. Our numerical solutions show that the applied voltage plays an important role in the model. We found that as the applied voltage increases, the vorticity of the plasma flow also increases.
{"title":"Numerical Modeling of the Dielectric Barrier Discharges Plasma Flow","authors":"A. Ahmadi, J. Labadin, P. Piau, A. Rigit","doi":"10.1109/AMS.2010.88","DOIUrl":"https://doi.org/10.1109/AMS.2010.88","url":null,"abstract":"Dielectric Barrier Discharge (DBD) is a discharge phenomenon where a high voltage is applied on at least two electrodes separated by an insulating dielectric material. Dielectric Barrier Discharge plasma actuator has been studied widely in this last decade but mostly the study is focusing on experimental research rather than mathematical modeling. The limitation with studying DBD plasma actuator experimentally is that it does not obtain direct information on the physics of the plasma flow, which is important in determining its efficiency. In this paper, we model the steady fluid model DBD plasma actuator mathematically. The preliminary result of the model are presented and discussed. To initiate the modeling process, the stream-function and vorticity are defined so that the Navier-Stokes momentum equation could be transformed into vorticity equation. The resulting two governing equations, which are vorticity and stream-function equations are solved numerically to obtain the vorticity of the flow in x and y directions. Finite difference method was adopted to discretize both equations and the system of equations is solved by the Gauss-Seidel method. Our numerical solutions show that the applied voltage plays an important role in the model. We found that as the applied voltage increases, the vorticity of the plasma flow also increases.","PeriodicalId":437153,"journal":{"name":"2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128745021","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}
In this paper a model that locates Compressed Natural Gas (CNG) refueling stations to cover the full volume of vehicle flows is developed and applied. The model inputs consist of a road network include nodes and arcs, the volume of vehicle flows between each pairs of origin and destination nodes, also some assumptions are considered as follows, refueling stations locating hierarchy, road network arcs hierarchy, crisp demand based on the volume of arc demands, road network arc flows, the potential location for refueling stations are limited and the refueling stations are capacitated. This paper extends Arc Demand Coverage Problem (ADCP) to determine locations for constructing CNG refueling stations at the considered potential locations such that the flow demands are fully met and the cost function is minimized. The cost function is positive and non-decreasing function of the located facility number. A heuristic algorithm is applied to solve ADCP.
{"title":"Optimal Location of Compressed Natural Gas (CNG) Refueling Station Using the Arc Demand Coverage Model","authors":"A. Boostani, R. Ghodsi, Ali Kamali Miab","doi":"10.1109/AMS.2010.49","DOIUrl":"https://doi.org/10.1109/AMS.2010.49","url":null,"abstract":"In this paper a model that locates Compressed Natural Gas (CNG) refueling stations to cover the full volume of vehicle flows is developed and applied. The model inputs consist of a road network include nodes and arcs, the volume of vehicle flows between each pairs of origin and destination nodes, also some assumptions are considered as follows, refueling stations locating hierarchy, road network arcs hierarchy, crisp demand based on the volume of arc demands, road network arc flows, the potential location for refueling stations are limited and the refueling stations are capacitated. This paper extends Arc Demand Coverage Problem (ADCP) to determine locations for constructing CNG refueling stations at the considered potential locations such that the flow demands are fully met and the cost function is minimized. The cost function is positive and non-decreasing function of the located facility number. A heuristic algorithm is applied to solve ADCP.","PeriodicalId":437153,"journal":{"name":"2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128967790","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}
Z. Oplatková, R. Šenkeřík, I. Zelinka, Jiri Holoska
The paper deals with a synthesis of control law for discrete chaotic logistic equation system by means of analytic programming. This is a preliminary study in which the aim is to show that tool for symbolic regression – analytic programming - is possible to use for such kind of problems. The paper consists of description of analytic programming as well as chaotic logistic equation system. This article contents only 12 successful simulations out of 12 in the result section and will be extended within future tests in this field. For experiments in this case SOMA (Self-Organizing Migrating Algorithm) with analytic programming was used.
{"title":"Synthesis of Control Law for Chaotic Logistic Equation - Preliminary Study","authors":"Z. Oplatková, R. Šenkeřík, I. Zelinka, Jiri Holoska","doi":"10.1109/AMS.2010.26","DOIUrl":"https://doi.org/10.1109/AMS.2010.26","url":null,"abstract":"The paper deals with a synthesis of control law for discrete chaotic logistic equation system by means of analytic programming. This is a preliminary study in which the aim is to show that tool for symbolic regression – analytic programming - is possible to use for such kind of problems. The paper consists of description of analytic programming as well as chaotic logistic equation system. This article contents only 12 successful simulations out of 12 in the result section and will be extended within future tests in this field. For experiments in this case SOMA (Self-Organizing Migrating Algorithm) with analytic programming was used.","PeriodicalId":437153,"journal":{"name":"2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114860813","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}
This paper presents a novel Electric Energy Management compensator based on Multi Objective Particle Swarm Optimization search technique MOPSO for use in hydrogen and island electricity generation. It combines a fuel cell power source and a micro hydro water turbine. The novel control strategy is designed to achieve the high-efficiency coordinated operation of the two individual power sources and to regulate current and voltage for maximum utilization, without compromising the power quality and performance of the overall system. To achieve these conflicting objectives, a novel dual action Modulated Power Filter and Compensator at the AC bus (MPFC) and Green Power Filter GPF scheme at the DC bus using real time self regulating error tracking scheme for voltage stability, energy conservation, loss reduction, power factor correction, and power quality enhancement for hybrid multi source energy utilization systems. A tri-loop error driven dynamic controller is used to adjust the Pulse Width Modulation PWM switching of the DFC - Dynamic filter compensator on the AC side and green power filter on the DC side. Power factor correction and power quality enhancement is validated by simulation under different operating conditions, including sudden load disturbances and wind velocity excursions. Multi Objective Optimization MOPSO technique is used to find the optimal control gain settings that dynamically minimize the global dynamic error.
{"title":"A Smart Dynamic Electric Energy Conservation VSC-Self Regulating Controller for Micro Hydro-Fuel Cell Green Scheme","authors":"A. Sharaf, A. El-Gammal","doi":"10.1109/AMS.2010.89","DOIUrl":"https://doi.org/10.1109/AMS.2010.89","url":null,"abstract":"This paper presents a novel Electric Energy Management compensator based on Multi Objective Particle Swarm Optimization search technique MOPSO for use in hydrogen and island electricity generation. It combines a fuel cell power source and a micro hydro water turbine. The novel control strategy is designed to achieve the high-efficiency coordinated operation of the two individual power sources and to regulate current and voltage for maximum utilization, without compromising the power quality and performance of the overall system. To achieve these conflicting objectives, a novel dual action Modulated Power Filter and Compensator at the AC bus (MPFC) and Green Power Filter GPF scheme at the DC bus using real time self regulating error tracking scheme for voltage stability, energy conservation, loss reduction, power factor correction, and power quality enhancement for hybrid multi source energy utilization systems. A tri-loop error driven dynamic controller is used to adjust the Pulse Width Modulation PWM switching of the DFC - Dynamic filter compensator on the AC side and green power filter on the DC side. Power factor correction and power quality enhancement is validated by simulation under different operating conditions, including sudden load disturbances and wind velocity excursions. Multi Objective Optimization MOPSO technique is used to find the optimal control gain settings that dynamically minimize the global dynamic error.","PeriodicalId":437153,"journal":{"name":"2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134242814","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}
N. Bolong, A. Ismail, M. Salim, D. Rana, T. Matsuura
Hollow fiber membranes using Polyethersulfone (PES) were fabricated in-house using phase inversion technique by modification with synthesized charged-surface modifying macromolecules (cSMM). The cSMM comprise with end-group component of Hydroxybenzene sulfonate or Hydroxybenzene carboxylate. The electrical properties of the membranes were modeled by utilizing the combination of irreversible thermodynamic model, Steric-Hindrance Pore (SHP) model and Teorell-Meyer-Sievers (TMS) model. The negatively-charged of the modified hollow fiber membranes was calculated based on sodium chloride rejection performance. The analysis of the modeling results revealed that sulfonate induce negative 1.61 electrical properties compared to carboxylate that is negative 1.49 for the modified PES membranes.
{"title":"Modeling the Rejection Performance of Hollow Fiber Nanofiltration Membranes Modified by Negatively Charged-Modifying Macromolecule","authors":"N. Bolong, A. Ismail, M. Salim, D. Rana, T. Matsuura","doi":"10.1109/AMS.2010.83","DOIUrl":"https://doi.org/10.1109/AMS.2010.83","url":null,"abstract":"Hollow fiber membranes using Polyethersulfone (PES) were fabricated in-house using phase inversion technique by modification with synthesized charged-surface modifying macromolecules (cSMM). The cSMM comprise with end-group component of Hydroxybenzene sulfonate or Hydroxybenzene carboxylate. The electrical properties of the membranes were modeled by utilizing the combination of irreversible thermodynamic model, Steric-Hindrance Pore (SHP) model and Teorell-Meyer-Sievers (TMS) model. The negatively-charged of the modified hollow fiber membranes was calculated based on sodium chloride rejection performance. The analysis of the modeling results revealed that sulfonate induce negative 1.61 electrical properties compared to carboxylate that is negative 1.49 for the modified PES membranes.","PeriodicalId":437153,"journal":{"name":"2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131854239","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}
Although search engines are quite useful for obtaining information from the World Wide Web, users still have problems obtaining the most relevant information when processing their web queries. Different methods exist for query expansion with various levels of success. A major point in query expansion techniques is to consider the relations existing between the query terms as a means for retrieving more relevant web pages. Therefore, the more comprehensible these relations are observed, the more relevance can be expected for the retrieved web pages. Taking this point into account, in this paper, a framework is represented for query expansion based on viewpoint- oriented manipulation of the related query terms. Comparison between the relevant retrieved documents, on proposed queries with Google results, illustrate how more relevant results are obtained in the situations where the very viewpoints type relations existing between the query terms are clearly detectable and in the meantime no semantic relation may at the first look exists between the query terms. In this paper, we have made use of two approaches to retrieval issue, out of which one is based on information fusion while the other is grounded on collaboration of the results in a selective way.
{"title":"A Framework for Query Expansion Based on Viewpoint-Oriented Manipulation of the Related Concepts","authors":"K. Badie, M. Mahmoudi, Mohammad Ali Ghaderi","doi":"10.1109/AMS.2010.35","DOIUrl":"https://doi.org/10.1109/AMS.2010.35","url":null,"abstract":"Although search engines are quite useful for obtaining information from the World Wide Web, users still have problems obtaining the most relevant information when processing their web queries. Different methods exist for query expansion with various levels of success. A major point in query expansion techniques is to consider the relations existing between the query terms as a means for retrieving more relevant web pages. Therefore, the more comprehensible these relations are observed, the more relevance can be expected for the retrieved web pages. Taking this point into account, in this paper, a framework is represented for query expansion based on viewpoint- oriented manipulation of the related query terms. Comparison between the relevant retrieved documents, on proposed queries with Google results, illustrate how more relevant results are obtained in the situations where the very viewpoints type relations existing between the query terms are clearly detectable and in the meantime no semantic relation may at the first look exists between the query terms. In this paper, we have made use of two approaches to retrieval issue, out of which one is based on information fusion while the other is grounded on collaboration of the results in a selective way.","PeriodicalId":437153,"journal":{"name":"2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130794234","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}
In electromagnetic dosimetry, anatomical human models are commonly obtained by segmentation of magnetic resonance imaging (MRI) or computed tomography (CT) scans. In this paper, a human head model extracted from thermal IR images is examined in terms of its applicability to specific absorption rate (SAR) calculations. Since thermal scans are two-dimensional (2-D) representation of surface temperature, this allows researchers to overcome the extensive computational demand associated with three-dimensional (3-D) simulation. The numerical calculations are performed using the finite difference time domain (FDTD) method with mesh sizes of 2 mm at 900 MHz plane wave irradiation. The power density of the incident plane wave is assumed to be 10 W/m2. Computations were compared with a realistic anatomical head model. The results show that although there were marked differences in the local SAR distribution in the various tissues in the two models, the 1g peak SAR values are approximately similar in the two models.
{"title":"SAR Calculations in Human Head Model Extracted from Thermal Infrared Images","authors":"A. Gasmelseed, J. Yunus","doi":"10.1109/AMS.2010.58","DOIUrl":"https://doi.org/10.1109/AMS.2010.58","url":null,"abstract":"In electromagnetic dosimetry, anatomical human models are commonly obtained by segmentation of magnetic resonance imaging (MRI) or computed tomography (CT) scans. In this paper, a human head model extracted from thermal IR images is examined in terms of its applicability to specific absorption rate (SAR) calculations. Since thermal scans are two-dimensional (2-D) representation of surface temperature, this allows researchers to overcome the extensive computational demand associated with three-dimensional (3-D) simulation. The numerical calculations are performed using the finite difference time domain (FDTD) method with mesh sizes of 2 mm at 900 MHz plane wave irradiation. The power density of the incident plane wave is assumed to be 10 W/m2. Computations were compared with a realistic anatomical head model. The results show that although there were marked differences in the local SAR distribution in the various tissues in the two models, the 1g peak SAR values are approximately similar in the two models.","PeriodicalId":437153,"journal":{"name":"2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114585992","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}
The paper presents the dynamic modeling and coordinated control strategy for an integrated micro grid scheme using Photo Voltaic PV, Fuel Cell FC, and backup Diesel generation with additional battery backup system. The integrated scheme is fully stabilized using a novel FACTS based green filter compensators that ensures stabilized DC bus voltage, minimal inrush current conditions, and load excursions while ensuring that the diesel generator set is only utilized when the demand energy exceeds the PV, FC and battery sources capacity within a specified operational levels to ensure highest efficient operation of the integrated renewable energy sources with the diesel engine. The paper presents a novel application of Multi Objective Genetic search Algorithms MOGA to control the 6-pulse controlled rectifier converter, dynamic filter/capacitor compensation DFC and the Green Power Filter GPF AC and DC schemes using real time dynamic self regulating error tracking.
{"title":"A Novel Coordinated Efficient GA-Self Regulating PID Controller for Hybrid PV-FC-Diesel-Battery Renewable Energy Scheme for Household Electricity Utilization","authors":"A. Sharaf, A. El-Gammal","doi":"10.1109/AMS.2010.94","DOIUrl":"https://doi.org/10.1109/AMS.2010.94","url":null,"abstract":"The paper presents the dynamic modeling and coordinated control strategy for an integrated micro grid scheme using Photo Voltaic PV, Fuel Cell FC, and backup Diesel generation with additional battery backup system. The integrated scheme is fully stabilized using a novel FACTS based green filter compensators that ensures stabilized DC bus voltage, minimal inrush current conditions, and load excursions while ensuring that the diesel generator set is only utilized when the demand energy exceeds the PV, FC and battery sources capacity within a specified operational levels to ensure highest efficient operation of the integrated renewable energy sources with the diesel engine. The paper presents a novel application of Multi Objective Genetic search Algorithms MOGA to control the 6-pulse controlled rectifier converter, dynamic filter/capacitor compensation DFC and the Green Power Filter GPF AC and DC schemes using real time dynamic self regulating error tracking.","PeriodicalId":437153,"journal":{"name":"2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116998708","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：